Smart Governance System’s Design to Monitor the Commitments of Bio-Business Licensing in Indonesia

Abstract

Some business license commitments in online single submission (OSS) application currently only consist of an independent statement from the business actor, and there is no time limit for fulfilling the license, especially for low-risk bio-business licenses. Therefore, a system design is needed to monitor the fulfillment of business license commitments and to provide confidence to the public regarding the business provided. The system design started with discussing the importance of smart governance systems, defining the requirements for monitoring the commitment of bio-business licenses, selecting documents, determining important words and document types, and proposing a design. This research produces a prototype of a business license monitoring system. This smart governance system checks the validity of business license documents. This study provides new insights into how smart governance system can be implemented in bio-business licensing. This study also considers the thousands of government applications that currently exist and the desire to provide one solution that contains many functions that can fulfill the many needs of business actors for simple and transparent business licenses.

1. Introduction

Every Indonesian agency has several electronic services that the public can use. Several similar services have been consolidated into one one-stop-shop service to provide convenience and speed. One example of a one-stop-shop service is a business licensing service using an OSS application. Every business actor in Indonesia, whether micro, small, medium, or large, must have a business license applied via the OSS application. OSS as a one-stop-shop service is a service that integrates several services from government units or agencies (K/Ls); for all abbreviations related to government units or agencies, refer to

Table A1. Abbreviation and description.

Abbreviation	Description
BKPM	“Badan Koordinasi Penanaman Modal” or the Capital Investment Coordinating Board
BPJPH	“Badan Penyelenggara Jaminan Produk Halal” or the Halal Product Guarantee Organizing Agency
BPOM	“Badan Pengawas Obat dan Makanan” or the Food and Drug Supervisory Agency
BSN	“Badan Standardisasi Nasional” or the National Standardization Body
CPPOB	“Cara Produksi Pangan Olahan yang Baik” or the Good Processed Food Production Methods
KBLI	“Klasifikasi Baku Lapangan Usaha Indonesia” or the Indonesian Business Field Standard Classification
Kemendag	“Kementerian Perdagangan Republik Indonesia” or the Ministry of Trade of the Republic of Indonesia
Kemenperin	“Kementerian Perindustrian Republik Indonesia” or the Ministry of Industry of the Republic of Indonesia
Kementerian PUPR	“Kementerian Pekerjaan Umum dan Perumahan Rakyat Republik Indonesia” or the Ministry of Public Works and Public Housing of the Republic of Indonesia
Kominfo	“Kementerian Komunikasi dan Informatika Republik Indonesia” or the Ministry of Communication and Information Technology of the Republic of Indonesia
K3L	“Keselamatan, Keamanan, Kesehatan dan pelestarian lingkungan” or safety, security, health, and environmental preservation
K/L	“Kementrian/Lembaga” or ministry/agency functions
LPPOM	“Lembaga Pengkajian Pangan, Obat-obatan dan Kosmetika” or the Institute for the Study of Food, Drugs, and Cosmetics MUI
MUI	“Majelis Ulama Indonesia” or the Indonesian Council of Ulama
NIB	“Nomor Induk Berusaha” or the Business Identification Number
NIK	“Nomor Induk Kependudukan” or Identity Number
NPWP	“Nomor Pokok Wajib Pajak” or Tax Identity Number
PBG	“Persetujuan Bangunan Gedung” or building approvals
PB-UMKU	“Perizinan Berusaha Untuk Mendukung Kegiatan Usaha” or Business Licensing to Support Business Activities
SIINas	“Sistem Informasi Industri Nasional” or the National Industrial Information System
SLF	“Sertifikat Laik Fungsi” or the Functional Eligibility Certificate
SIMBG	“Sistem Informasi Manajemen Bangunan Gedung” or the Building Management Information System
SNI	“Standar Nasional Indonesia” or the Indonesian National Certificate
SPBE	“Sistem Pemerintahan Berbasis Elektronik” or e-government
SPJH	“Sistem Jaminan Produk Halal” or the Halal Product Guarantee System
UMK	“Usaha Mikro dan kecil” or micro and small enterprises
UMKM	“Usaha Mikro, Kecil dan Menengah” or micro, small, and medium enterprises

in the Appendix A. In its implementation, integration between systems sometimes requires a data validation process. This integration process is needed when applying for licenses and is used to monitor the fulfillment of the license requirements documents. In this case, it applies to bio-business licensing.

The successful implementation of one-stop-shop services hinges on meticulous planning and several key factors, including management commitment, mindset and culture, human resources, and infrastructure [1]. In light of the current capabilities of ICT infrastructure, there is a clear opportunity to develop a transparent business licensing system that can bolster public trust [2]. The commitment of government leaders and regional heads is pivotal in fostering a more efficient and effective business licensing service orientation [3]. This commitment is instrumental in determining the success of a license for this one-stop service. The simplification of licenses and the streamlining of the process for investors can potentially stimulate investment [4].

One example of bio-business licensing is palm oil licensing. Factors influencing licensing implementation’s success are socialization, information transformation, improving human resources, and clear procedures [5]. The regional government is committed to realizing environmentally friendly palm oil plantations by implementing legal and limited licensing aspects to the principles of Indonesian sustainable palm oil (ISPO) [6]. Implementing legal, licensing, and limited aspects will also overcome the problem of palm oil productivity in smallholder plantations [7]. Another example of bio-business licensing is chili farming, which has consistent supply and demand and requires commitment and collaboration from various stakeholders [8].

Based on the explanation above, fast fulfillment of business licenses needs to be balanced with the fulfillment of business license commitments so that the licenses granted can be accounted for even though they are included in the low- and medium-risk business permits category. With the support of adequate commitment, resources, and infrastructure, there is an opportunity to speed up the time to fulfill business license commitments. These requires a simple, transparent, and limited business licensing monitoring system. This solution can be used to fulfill licenses in central and regional government institutions, which still require commitment from management to adjust applicable regulations and are challenging to integrate. This research aims to design and develop a system that makes it possible to achieve the following:

• Monitor the fulfillment of bio-business business licenses.
• Monitor the status of the fulfillment of bio-business licenses.
• Support an easy and transparent licensing fulfillment process for actors or bio-business ventures.

The proposed smart governance system will overcome the complexity of the integration process for fulfilling business licenses from the Indonesian government units or agency systems with the OSS system.

2. Business License’s Implementation in Some Asian Countries

Business registration, company registration, and business license are required to register a business in a country. To obtain an overview of the implementation of business licensing in Indonesia and elsewhere, several Asian countries, such as China, India, the United Arab Emirates (UAE), and Southeast Asian countries, namely Malaysia and Singapore, were selected (see

Table 1. Number of business licenses in several Asian countries.

No	Country	Population	Income Per Capita	Business Category	Volume per Day (in Average)	Time Required (Maximum Days)
1	India	1439 Mio	USD 2239 1	44	474	1–30
2	China	1425 Mio	USD 2907 2	6	87,000	25–42
3	Indonesia	279.4 Mio	USD 5270	21	13,000	1–61
4	Malaysia	34.1 Mio	USD 13,310	12	1.020	30–360
5	UAE	9.9 Mio	USD 60,000	6	58	28–42
6	Singapore	5.9 Mio	USD 88,450	26	32	14–60

Note: ¹ = [9], ² = [10].

). Aside from potential, several things need to be looked at, such as population and per capita income and licensing implementation metrics, namely the number of business categories, licensing requests, and the time required to obtain a business license.

India has become the country with the largest population in the world since 2024, putting China in second place and Indonesia in fourth place [11]. Malaysia has a reasonably large population, namely 34 million people [12], while other countries, such as Singapore and the UAE, have small populations, namely 5.9 million people [13] and 2.9 million people, respectively [14]. This large population is inversely proportional to per capita income, where the more people there are, the lower it is. The last two countries have different conditions. Even though they have a small population, Singapore has the highest per capita income [15] than the United Arab Emirates [14].

The number of new businesses registered in India in 2022 was 173 [16]. Meanwhile, the number of business categories is very detailed, including criteria, license type, and annual fees. Business categories range from petty food business operators to head office/registered office [17]. The time required to obtain a license is 30 days for each license. Businesses in the small category only require a few individual licenses and registration, and the process is faster; it can be a one-day process [18].

Business licenses in China have explicitly been categorized into six types of companies [19]. These are wholly foreign-owned enterprises (WFOEs), joint ventures (JVs), representative offices (rep offices), state-owned enterprise (SOEs), non-state-owned enterprises (private enterprises), and small private companies (individually owned). The entire contents of the business license in China are written in Chinese, and the Unified Social Credit Code (USCC) is a unique, 18-digit national business registration. Other information includes company name, business scope, and registered address [20]. The number of registered enterprise companies in 2022 was 32.8 million.

Business licenses issued in Indonesia reached seven million by 2023 [21]. With the Indonesian Business Field Standard Classification (KBLI) 2020, obtaining a business license takes up to two months. Meanwhile, business licenses in Malaysia use 12 unique digits called the Business Registration Number (BRN). For foreigners, around 12 business categories can be submitted with minimum Bumiputera ownership, ranging from financial services to security and employment agencies. Obtaining a business license and employment pass takes around 1–6 months [22].

The last two countries, namely Singapore and the UAE, are rich. Statistics show that the number of companies registering business in Singapore was 600 thousand by the end of October 2024 [23]. There are 26 sectors for applying for business licenses, ranging from air transport to tourism [24]. It will take 2 weeks to 2 months to fully process business licenses [25]. Meanwhile, in the UAE, there are several more specific business license categories, such as commercial license, professional license, industrial license, tourism business license, freelance license, and agriculture license [26]. The number of active and registered business licenses was 665,246 as of July 2022 [27]. On average, it takes 1–2 weeks to obtain a license in the UAE for either a mainland business license or a free zone business license [28].

The assumption of a large population impacts the increasing number of requests for business licenses. It also results in the number of business categories becoming more numerous as well. China and Indonesia are countries with large populations and continue to strive to maintain business growth. Therefore, the number of business license applications for these two countries is enormous. Even though the number of requests is large, China can speed up its business licensing process to the same extent as the UAE. The time required for the business license process is from one month to a maximum of six months. At the same time, the average time is 2 months. Business licenses are granted more quickly, usually for micro and small or low-risk businesses. With this consideration in mind, Indonesia requires a strategy to increase the business issuance time to a maximum of a month, especially for requests for medium- and high-category business licenses.

3. The Importance of Smart Governance for Collaboration in Government Services

The components of intelligence, which have emerged as significant elements in the smart governance framework for bio-business licensing services [29], are of paramount importance. Previous research has underscored the crucial role of systems and technology in the implementation of business licenses, particularly for small and medium businesses [30]. Hence, it is imperative to delve into the components of intelligence that have been the focus of previous smart governance literature studies.

The intelligence concept, when implemented, has the power to transform several domains [31]. These include the following:

• Smart cities, by interconnecting elements within the city, such as government, society, and business, using sensor technology, computer networks, and decision-making. Governments use applications for planning and governance, energy regulation, population mobility, and government services. Generally, the technologies used are 5G, IoT, robotics, virtual and augmented reality (VR/AR), and AI.
• Smart homes implement network communications to connect and remotely control devices and services, such as air conditioning, air ventilation, lighting, household appliances, and security systems, via cellular telephone devices and tablets. The goal is to improve the quality of life with the help of smart systems, such as the IoT (Internet of Things).
• Smart industry/factories: In line with the implementation of Industry 4.0, how can the industry/factories personalize products and services according to customer needs? The technologies used include the cyber–physical system (CPS), Internet of Things (IoT), personalization of products and services, and the decentralization of decision-making.
• Smart service systems focus on searching for concepts through a literature review. Text mining from many scientific papers and articles uses machine learning algorithms.

Aspects of an intelligent system consist of technology, knowledge, learning, adaptation, sensing, and actuation. This smart system consists of several domains, such as smart service systems, smart cities, smart homes, and smart industries and factories. The smart city domain interconnects governments, entrepreneurs, society, and technology. One of the components of a smart city is smart governance. An overview of the components is shown in Figure 1. Literature studies regarding smart cities and governance are numerous, starting in 2016 [32]. Some common topics in smart governance literature studies concern how technology supports collaborative processes and transparency. Very few smart governance system support this collaborative process (see

Table A2. Smart governance literature review summary.

Year	References	Title	General Summary	Keywords	Components *
					1	2	3
2016	[83]	Smart Governance: Using a Literature Review and Empirical Analysis to Build a Research Model	Produced a model for research on implementation strategies (ideas and actions), smart governance arrangements (organization, technology and innovation), and smart governance outcomes (organizational change and urban improvement)	Organization, technology, Innovation	√	√	-
	[84]	Governing the smart city: a review of the literature on smart urban governance	Smart governance is not a technology issue: we must study smart governance as a complex process of institutional change and acknowledge the political nature of a compelling vision of socio-technical governance.	Socio-technical, technological	√	√	-
2018	[85]	Smart governance in the context of smart cities: A literature review	Provided a definition of ’smart city governance’ and contributed to developing a framework to build new smart governance models in addressing society’s digital challenges, collaborative governance, information sharing, citizen engagement, transparency and openness.	Model, collaborative, transparency	√	√	-
	[86]	The governance of smart cities: A systematic literature review	A systematic literature review showed that various definitions of smart city governance exist. Also, the study uncovered substantial variances in contextual factors, measurement techniques and outcomes among smart city governance concepts.	Contextual, metric, results	√	√	-
2019	[87]	Modelling the smart governance performance to support smart city program in Indonesia	The proposed model produced 29 indicators in 3 different domains (public services, bureaucracy, public policy) and 7 aspects of assessment (public administration services, basic needs facilities, service facilities, internal policies, bureaucratic governance, public aspirations, and open access). This model can serve as a reference for smart governance performance evaluation to support smart cities initiatives in Indonesia.	Bureaucracy, public service, public policy	√	√	√
	[88]	Smart Governance For Sustainable Cities: Findings from a Systematic Literature Review	Empirical evidence for expected sustainability benefits is scant. In addition, the picture that emerges is ambiguous because it reports negative positive impacts on the achievement of smart governance sustainability. This study identifies the contextual condition of smart governance as important. Our paper points to the need for more empirical research and developing an agenda to examine the relationship between smart governance and sustainability outcomes.	Contextual, sustainable results	√	√	√
2020	[89]	Smart City Governance in Developing Countries: A Systematic Literature Review	Tech-enabled smart cities in developing countries can only be realized when socioeconomic, human, legal, and regulatory reforms are instituted. The government needs to increase its efforts to meet people’s basic infrastructure needs, increase income, establish a clear regulatory framework to mitigate the technological risks involved, develop human capital, ensure digital inclusivity, and promote environmental sustainability.	Technology, people, regulation	√	-	√
	[32]	A Literature Review on Smart City and Smart Governance	Research on the themes of the smart city and smart governance and their implementation by the government is still very minimal in Asian countries and other countries outside Europe. Research on smart cities and smart governance was abundant in 2016 and beyond. It is very important to include urban communities in the urban planning process because they are the ones who will be the beneficiaries of its implementation.	Implementation, planning, community	√	-	√
2022	[90]	A Systematic Literature Review of Smart Governance	Smart governance is the ability or capacity to carry out smart activities, whether using technology that supports collaboration to produce efficient decision making. There are three main characteristics of smart governance, namely participation and partnership, collaboration, and transparency. The study also found that there are still few models, frameworks, or architectures for smart governance. Most research has created models, frameworks, or architectures for smart cities. With this in mind, research on the development of smart governance models, frameworks, or architectures is still open for further research.	Technology, transparency, participation, models/frameworks	√	√	√
2023	[91]	Smart Governance Toolbox: A Systematic Literature Review	Certain parts of the ’smart governance toolbox’ remain almost empty: there are very few tools to assess the context of smart collaborative governance, facilitating collaborative structures, addressing technology issues, and measuring the results of smart city practices.	Tools, collaborative, technology	√	√	-

Note: * 1 = public service, 2 = bureaucratic management, 3 = public policy.

in the Appendix A). Meanwhile, the most widely discussed smart governance components are related to public services and bureaucratic management, although some also discuss public policy. Therefore, this system of monitoring the implementation of business licensing will become a smart governance system that supports a collaborative bio-business licensing service process (involving many ministries and institutions) and transparency for both business actors and licensing providers.

The latest technology and the application of AI can also be considerations for future system development other than this monitoring system. For instance, Gartner released the latest technology hype cycle and AI applications in 2023; some of these applications, such as AI-powered anomaly detection for system security, or AI-driven predictive maintenance for system reliability, are mentioned below.

• Generative AI: using systems, like ChatGPT, for content creation and process automation to improve the customer experience.
• Cloud-native: utilization of cloud computing technology, including its ability to provide services, such as Data Lake SaaS and API-centric SaaS.
• Computer vision: technology for extracting contextual information by capturing and analyzing images and videos. OCR is used to recognize text in an image.

Some previously nonexistent technologies now exist, such as blockchain, which is widely used in the logistics sector for supply chains or tracking goods. For example, Walmart uses blockchain to track the origin of its food products. Another technology is drones, which are widely used for monitoring agricultural land. For instance, farmers use drones to monitor crop health. IoT (Internet of Things) technology is widely used for automation processes in households, such as controlling lights, doors, and air conditioning. AI technology is widely used in the transportation sector to reduce the number of accidents. And. most recently, generative AI, such as ChatGPT, which can provide complete information to users regarding the topics they want to know, has emerged. For example, OpenAI’s ChatGPT is used by various news organizations to generate news articles.

The seven categories of smart governance tools are context, stakeholders, structure, process, exchange settings, technology, and results [13]. The most innovative governance tools are those related to processes. Several new technologies and AI applications that support the business licensing process have been produced (see

Table 2. Potential smart system to support the business licensing process.

No	Process	Domain	Smart System Technologies
1	Validation	Authentication and authorization	Single sign-on/OAuth
2	Integration	Integration amd partnership	RESTful OPEN API 2.0
3	Licensing verification	Document verification	Blockchain
4	Data governance	Big data	Data Lake on SaaS
5	Data security	Data Protection	Homomorphic encryption
6	Licensing monitoring	Computer vision	Optical character recognition (OCR)
7	Complaint handling	Customer service support/chat/FAQ	Generative AI

). The focus is on developing the supervision process discussed in row number six of the table.

The development of this licensing supervision process is a form of prototype conceptual planning study towards a smart city that aims to improve prosperity by forming new businesses so that it can improve the quality of life and sustainable development [33]. The development of licensing supervision may differ because community-government interactions vary from one country to another. This process may become dynamic in the future [34]. Therefore, during implementation, a transition is needed for multilevel interaction between government institutions [35].

4. Methodology for the Development of a Monitoring System for the Commitments of Bio-Business Licensing

Government system services to support collaboration between ministries and government agencies need support from the smart system. The component of a smart city that supports this service is smart governance. Therefore, this research stage will focus more on developing the need to monitor the bio-business service license system. System development and testing will be the subject of further research. The development of a monitoring system for the commitments of bio-business licensing using the waterfall method involves identifying needs, planning by selecting documents and keywords, system analysis and development, and system testing [36].

• Identification. Identify the need for a bio-business license commitment monitoring system. While there are numerous potential solutions, we will focus on two specific approaches. The first solution is integrating the system between government agencies/ministries, while the second is uploading licensing documents. We will compare these two solutions from the perspective of integration requirements between systems.
• Selection. We selected documents as samples of bio-business business licenses. Based on the solution chosen, we will discuss what documents are prerequisites for the business license. Therefore, only two documents required for a business license were selected. Several halal certificates and BPOM licenses were taken from the Internet.
• Determination. We determined the keywords for each type of document. These critical words were chosen from several previously selected document examples. Later, these crucial words will determine the validity of the document.
• Development. We designed a smart governance system to monitor bio-business license commitments. This design discussed the user journey for accessing and uploading compliance with bio-business licensing documents. There are also detailed technical specifications for developing the solution. Developing smart governance system involved using the SDLC (software development life cycle) method: system design, system development, system testing, and evaluation.
• Testing. The requirement’s gathering process was carried out at points 1 and 4. The system testing method, which uses a black box approach, involves testing the main functions of the prototype system without considering its internal structure or implementation details. This approach ensures that the system is tested from a user’s perspective, providing a comprehensive evaluation of its functionality and usability.

5. Results

5.1. Identify the Need for a Commitment Monitoring System

The design of this business commitment monitoring system is part of the current OSS system (government regulation number 5/2021 concerning the implementation of risk-based business licensing). The OSS system comprises three sub-systems: information services, business licensing, and supervision (see Figure 2). The information service sub-system is a system that contains a library of information services, such as general explanations, guides, regulations, FAQs (frequently asked questions), and others. The business licensing sub-system is where business actors fill out business license applications. In this sub-system, there is a validation process for business actor information, such as identity number (NIK), tax identity number (NPWP), and reference data (such as business actor profile, basic requirements, SLA (service-level agreement), KBLI, and a risk matrix based on risk assessment, land area, buildings, and others).

The supervision sub-system, a vital component of the OSS, consists of several activities carried out regularly, such as routine, annual, and incidental supervision. This sub-system also includes a supervisory assignment letter, the supervision results, profiles of business actors, and the imposition of sanctions. The proposed commitment monitoring module for business actors will be seamlessly integrated into this sub-system, enabling real-time monitoring of these business actors’ commitments and enhancing the overall supervision process.

From the results of the above explanation, OSS has some integration and non-integration processes with systems from other K/Ls, as follows:

• Integration using a gateway (via API, file transfer, or others) to validate business actor data.
• Integration using a link to the application from the K/L system. Examples: Food and Drug Supervisory Agency (BPOM) distribution license, or the Indonesian National Certificate (SNI),
• There is no integration, and the business identification number (NIB) is the basis for the commitment process. The halal certificate (currently only an independent statement from MSME actors), SSO licensing, and the National Industrial Information System (SIINas) are examples.
• There is no integration because requirements are fulfilled already in OSS, e.g., building approvals (PBGs).

Therefore, the process of integrating systems in K/Ls into the OSS system is being carried out gradually, a systematic approach that should reassure the audience. However, not everything has become integrated into the OSS system. As a first step, several systems have used the NIB from the OSS system as unique data for business actors. The second step is to provide application link information for K/Ls that are targets for business actors to fulfill their commitments. These two steps are included in the low-effort steps because the process is easy to accomplish. Meanwhile, the other two steps, namely integration between systems by using a gateway system and adding function modules from the K/L system to the OSS system, are high-effort steps. This is because they require coordination and agreement between the two institutions, including integration costs.

Adding function modules from the K/L system to the OSS system also requires several considerations. The first is related to the costs invested so far in the solution. Based on the profits obtained (net book value = 0), the risk of the costs should be acceptable. The second consideration is related to adding complexity to the OSS system, which will be critical. Lastly, there will be additional infrastructure costs if it is needed for the new module. Therefore, the authors propose a solution with a system that uploads certification documents resulting from related ministries and agencies centrally in the OSS system. It is a form of monitoring the fulfillment of commitments from business actors, especially micro, small, and medium enterprises (UMKM) or those with low risk. The advantages (pros) and disadvantages (cons) of the proposed document upload system resulting from this commitment are visible in

Table 3. Pros and cons of bio-business licensing supervision prototype.

Approach	Pros and Cons
Bio-business licensing prototype by integrating system between government agencies/ministries	(+) Users do not need to upload documents (−) Integration fees (−) System development standards are required (−) Limited developers (resources)
2. Bio-business licensing prototype by uploading licensing documents to the system	(+) No integration fees (+) No system development standards are required (+) No need for many developers (−) There is user effort to upload compliance documents

.

With the OSS-RBA system, a testament to its success is the increase in the number of business and investment licenses, as has also happened in the region. This success story should inspire confidence in the proposed solution. However, there are also problems with its implementation, especially monitoring business licenses [37]. Other business licensing in other countries, such as the Philippines, include the e-BPLS (Electronic Business Licensing and Licensing System), which can speed up service responses that previously used manual processes [38]. Businesses that do not comply with regulations should have their business licenses rejected via appropriate systems, such as the Turkish BRSA (Banking Regulation and Supervision Agency), which is used against fintech companies that ignore regulations [39].

5.2. Select Documents as Samples for Fulfilling Business Licensing Documents

The selection of two document criteria as samples in this prototype is not arbitrary; they reflect the specifics of bio-business licensing (see

Table 4. Bio-business licensing certificate.

Bio-Business Licensing 2	Other Licensing	Ministries/Agencies
NIB	NIB	BKPM
Halal certificate	-	BPJPH
BPOM distribution license	-	BPOM
SNI	SNI	BSN
K3L	K3L	Kemendag
Comply to SIINas	Comply to SIINas	Kemenperin
PBG	PBG	Kementrian PUPR
-	IUP/IUPK	Local Government

² Business licensing obligations in the selected KBLI.

). This is a deliberate choice and a limitation of the system being developed, but one that is crucial to ensure its simplicity and focus. It is only implemented in two documents and only involves two K/Ls, but it is a starting point, and a foundation that can later be expanded to document fulfillment in other K/Ls. An example of a business license that is not included in bio-business is a mining business license or a special mining business license (IUP or IUPK).

As mentioned in previous research, bio-business includes biotechnology, human health technology, bioindustry, and agriculture biotechnology [40]. These are not just abstract concepts, but areas that require specific certificates for fulfilling business commitments. These certificates, issued by relevant ministries and institutions [41], are not mere formalities, but essential requirements for business licensing obligations in the selected [42].

• NIB is issued by the OSS system (oss.go.id) at the Capital Investment Coordinating Board (BKPM).
• Halal certification is issued by Halal Product Guarantee System (SPJH), which the Halal Product Guarantee Organizing Agency (BPJPH) organizes. For example, for MSEs that register their business through OSS, there is an independent statement that the business product is halal, and it must be registered as a halal product with no time limit [43]. Then, the business actor will process the halal certification of his product through Halal Product Guarantee System (halal.go.id) [44].
• The BPOM Distribution License is issued by the BPOM e-certification system (e-sertifikasi.pom.go.id). For example, to obtain Business Licensing to Support Business Activities (PB-UMKU)—Good Processed Food Production Methods (CPPOB), business actors apply for the license through OSS by selecting the appropriate KBLI, and the OSS system will direct them to the e-certification system [45].
• The National Standardization Body (BSN) issues SNI. For example, micro and small enterprises (UMK) with low risk will receive the SNI Bina-UMK mark after the user commits to fulfilling the SNI through the OSS application. After receiving the NIB, the perpetrator applies for SNI certification via binaumk.bsn.go.id by fulfilling the required requirements (such as photo and video evidence). Of the 145,936 UMKM who are entitled to free SNI-UMK coaching, 1100 UMKM receive SNI coaching [46].
• Security, health, and environmental preservation (K3L) certificate issued by the Ministry of Trade of the Republic of Indonesia (Kemendag). Issuance of registration of goods related to K3L can now be performed through the Ministry of Trade Licensing SSO Single Sign-On (SSO) application integrated with OSS [47]. Like the previous process, business actors can apply for registration of K3L-related goods via OSS by selecting the appropriate PB-UMKU and KBLI, and the OSS system will direct them to the simpktn.kemendag.go.id application [48]. After complying with all requirements, OSS will issue a digital signature and a printable goods registration [49].
• Industrial data are submitted to SIINas of the Ministry of Industry of the Republic of Indonesia (Kemenperin). Companies operating in the industrial sector must register at SIINas (siinas.kemenperin.go.id) and report their business periodically [50].
• PBG is issued by Building Management Information System (simbg.pu.go.id) from the Ministry of Public Works and Public Housing (Kementerian PUPR). As of February 2023, applications for PBGs and Functional Eligibility Certificates (SLFs) became available at OSS. Business actors must fill in building data correctly until the relevant parties contact them, and the license must be printable when it is issued [51].

In the 2020 KBLI, there are 21 categories, each with its own unique role in the bio-business landscape. Among these, those selected for bio-business are A (agriculture, forestry, and fishing), C (processing industry), and I (providing accommodation and providing food and drink). This diversity is not just a list of numbers, but a testament to the wide range of bio-business opportunities in Indonesia. Of the 21 categories, there are 1349 KBLI, and, for example, for the Department of Agriculture, there are 56 KBLI (See

Table 5. Categories in KBLI 2020.

KBLI 2020 (21 CATEGORIES) 3
A. Agriculture, forestry, and fisheries
B. Mining and quarrying
C. Processing industry
D. Procurement of electricity, gas, steam/hot Water, and cold air
E. Water treatment, wastewater treatment, waste material treatment and recovery, and remediation activities
F. Construction
G. Transportation and warehousing
H. Wholesale and retail trade; car and motorbike repair and maintenance
I. Provision of accommodation and provision of food and drink
J. Information and communication
K. Financial and insurance activities
L. Real estate
M. Professional, scientific, and technical activities
N. Rental and leasing activities without options, employment, travel agents, and other business support
O. Government administration, defense, and mandatory social security
P. Education
Q. Human health activities and social activities
R. Arts, entertainment, and recreation
S. Other service activities
T. Household activities as employers; activities that produce goods and services for households that are used to meet their own needs
U. Activities of international agencies and extra-international agencies

³ Refer to KBLI 2020.

).

5.3. Determine Keywords for Each Document

As previously mentioned, there are two checking activities in the data checking process: checking document types and keywords. This study had two critical documents as samples, namely a halal certificate and a BPOM license (a detailed explanation of why only two documents mentioned in Section 5.2). After checking the document type, the next step is checking the keywords for each document (see

Table 6. Bio-business licensing certificate data.

Document 4	Keywords	Supporting Data
1. Halal Certificate	Halal, MUI, LPPOM	Halal number Product type Product name Company name Company address Effective start date Effective end date
2. BPOM License	BPOM, distribution license	License number Name of food type Trade name Type of packaging Manufacturer’s name Manufacturer’s address Effective start date Effective end date

⁴ From 5–6 samples that available on the Internet.

). If these keywords match, then other data in the document will be retrieved to complete the information from the uploaded document. These supporting data include the certificate number, product information, and product identity, such as name, address, and validity date.

5.4. Design and Development of Monitoring System for Compliance with Business Licensing Documents

The meticulous design and development stages of this monitoring system are a testament to the precision and care we put into our work. It all starts with the design process, which includes a sequence diagram, database design, and document upload design. On the other hand, the development process involves setting up the environment, displaying the login form, registering, checking the status, uploading documents, validating documents, and testing the status (dashboard). The application development process, OCR, and E2E (end-to-end) process checks before testing are a continuation of the process. The testing process consists of scenario design, sample preparation, and test execution. The process of calculating research results and analyzing the results is part of the evaluation process.

In general, the programming structure of the monitoring system consists of four parts: filling in user data, uploading documents, submitting documents, and the checking of document suitability by the admin (see Figure 3). The expected user journey is as follows: (1) Users can access the business licensing document upload form. (2) The user uploads documents according to the type of document required. (3) The system determines the summary of the uploaded document. (4) The system records important words previously defined in the document. (5) The system assesses whether the document is valid; if it is not, it provides a notification or warning to the user. (6) If all documents are complete, the user can submit the document.

A use-case diagram provides an overview of the system’s interaction with its environment (see Figure 4). The system has two actors: the user/business actor and the admin/officer. Users or business actors can log in, register, upload documents to check their validity, and submit documents if they are valid. Valid documents will be checked by the administrator or officer using a random method (sampling).

In the prototype for monitoring business actors’ commitments, we have implemented stringent security measures in the authentication methods. There are two processes, namely the process of logging in to the monitoring form and the process of downloading the commitment documents. The login process can use the login process currently in the OSS application, but a link needs to be added to see the status of fulfilling the commitment documents. The login process begins with the user or business actor entering a username and password into the application. Authentication processes can be added to the system, such as 2FA (two-factor authentication) by adding a code in the application other than the username and password, or MFA (multi-factor authentication), which is a login process in which the user not only uses their username and password but also enters a code sent via email, answers secret questions, or uses biometric scans, such as fingerprint or face recognition. The next process is the document download process. The document download process will produce a user database and files (see Figure 5).

The next process is the document upload process. There are three processes when uploading documents: the process of entering data, the process of checking data, and the process of uploading data into the system. In the process of entering data, users can add more if they want to enter more than one document. Users can also delete or remove documents that are not needed. After confirming the number of documents to be downloaded, the user can select the documents to be uploaded from the files on his computer. Then, the user can upload the document until the process is successful. You can refer to the visual guide in Figure 6 for a better understanding of this process.

The following process is the data-checking process. If the file entered is incorrect, there will be a message or notification that the file is wrong. If the document is appropriate, a message will be successfully uploaded. Users can upload other documents, and if this is successful, then the users can submit the appropriate documents. The final process is uploading data into the system. If the data finish uploading, there will be a message indicating whether the process was successful (completed) or not (rejected) (see Figure 7).

The above process has several characteristics of a smart system, as follows:

• Keywords from each required document represent embedded knowledge in the system.
• There is a response if the document is valid or according to the stored knowledge.
• Communication between the user and the system is subject to the information received about whether the uploaded document is valid.

In conducting this research, it is necessary to first delve into several concepts of text recognition. In document classification processes, such as text mining, determining important words in documents is very necessary. Examples include determining plant genetic resources [52]. However, beyond this, the complexity of the task is further revealed in the need to summarize the document [53]. Text summarization, a process that can use soft computing methods (subject, predicate, and object rules) and fuzzy logic [54], or a word embedding approach [55], such as SummCoder or autoencoder, and sentence embedding [56], is a multifaceted challenge that requires careful consideration and understanding.

Another important element is the text classification process, which determines whether the text falls into a predetermined category [57]. Text classification can be knowledge-based, corpus-based, or learning-based [58]. Text classification can also use feature selection methods, like Hebb rules [59]. Other methods of text classification with a semantic approach are role labeling and explicit semantic analysis [60], taxonomy [61], the hidden Markov model (HMM) for opinion mining [62], and a new term-weighting approach using least information theory (LIT) for hierarchical classification [63]. The standard inverse moment of gravity formula is also used [64]. Another approach to categorizing documents is to use a feature projection method that selects the very first layer of fusion information [65] and a very deep convolutional neural network (CNN) [66]. These two methods are used to improve computational efficiency.

The development of this solution is at its initial stage but demonstrates its enhanced capabilities, namely supporting sustainable development. There is a close relationship between artificial intelligence (AI) and sustainable development targets, especially with the cultural shift towards digital processes [67]. The existence of AI is not just a trend but can also change business models and the global economy [68].

One use of AI in recognizing text is with OCR (optical character recognition). Text recognition using the OCR flask and Tesseract has shown their functionality, for example to extract the caption of the picture [69]. Therefore, it is widely used in record-management systems [70]. To increase the accuracy, document classification using OCR can also be combined with the naïve Bayes classifier [71] or other methods to obtain document classification automatically [72].

The system development process begins with setup, development, and testing environments. The specifications are as follows:

• OS: MS Windows Server;
• Server (VPS: https://my.idcloudhost.com (accessed on 26 March 2024));

  (1)

  CPU: 2 cores;

  (2)

  Memory: 8 GB;

  (3)

  Storage: 20 GB;

• OCR algorithm: Easyocr 1.7.1 Deep Learning using convolutional neural networks. Ref: https://pypi.org/project/easyocr/ (accessed on 9 April 2024);
• Application;

  (1)

  Frontend template: Bootstrap 5;

  (2)

  Apps: Python 3.12.2;

  (3)

  Framework: Flask;

  (4)

  API: Rest API;

  (5)

  Database: MySQL.

The results of the frontend and backend development are a login form (see Figure 8), a registration form (see Figure 9), a homepage (see Figure 10), and a dashboard page for uploading and sending documents (see Figure 11).

5.5. System Testing and Evaluation

Testing uses the black box method with several variables for developing business license prototypes. The test data consist of several halal certificates and BPOM licenses taken from the Internet, with two samples of valid halal certificates, seven samples of valid BPOM certificates, and two samples of invalid certificates. This test data are not yet available online and are still in the form of a hardcopy document (see

Table 7. Test scenarios.

No	Scenario	Success Criteria
1	User has successfully logged in	Pass
2	User failed to login	Fail
3	Users can upload valid halal certificate documents	Pass
4	Users can upload BPOM certificate documents—valid	Pass
5	User failed to upload certificate document—invalid	Fail
6	Users can submit valid halal certificate documents	Pass
7	The submitted data appears successfully	Pass
8	User has successfully logged out	Pass

).

A proposed solution for uploading documents to fulfill business license commitments has the following system assumptions:

(a).

The prototype is built to be more advanced, from a low-fidelity mock-up to a high-fidelity web prototype. An example of a high-fidelity prototype for online attendance during the pandemic is much needed [73]. Low- and high-fidelity prototypes both reveal usability problems [74].

(b).

The Tesseract OCR (Optical et al.) package or library to is used obtain text summaries from documents (images).

(c).

The text summary extraction results match the previously defined keywords.

(d).

Keywords are defined early, so the system has no modules or functions to add, subtract, or change them.

The system limitations are as follows:

(a).

The system is built as a stand-alone application; there is no integration process with the current system (OSS).

(b).

The system does not include email, SMS, or other notifications for users.

(c).

There is no feedback from the officer (admin) if there is an incorrect document.

The evaluation compares the number of successful scenarios with the total number of scenarios in the following Equation (1):

N = Number of successful scenarios ÷ Number of total scenarios × 100%

(1)

There is a note from the process that has been executed. The file size determines the length of the extraction process by OCR. A BPOM-valid marketing authorization file with a size of 2.6 MB can be processed by OCR within 35 s (see Figure 12). A halal-valid certificate file with a size of 382 kB can be processed by OCR within 25 s (see Figure 13), and an invalid document file with a size of 63 kB can be processed by OCR within 5 s (see Figure 14). The machine learning (ML) algorithm runs on a cloud’s virtual private server (VPS).

Therefore, an additional Graphics Processing Unit (GPU) is needed so that the processing of this ML algorithm can be faster. GPUs are different from high-performance computing (high-performance computing, or HPC for short), which can process large data sets quickly with parallel computing processes. The combination of GPU and HPC will likely quickly increase the processing capabilities of ML and AI algorithms that use big data.

Another solution is to use better ML algorithms. The easyOCR algorithm can be changed using the GPT4 OCR/image recognition algorithm developed by OpenAI. Of course, further research is required to confirm this, especially the implementation of OCR on the documents used in this research. If the expected time for document processing with OCR is within a specific time limit, limiting the maximum file size is necessary. For example, the maximum limit for the processed file is 100 kB with an expected processing time of 10 s.

6. Discussion

As an illustration, monitoring the bio-business license commitment only involves six institutions, especially for small and medium business licenses, considering that each K/L only has six applications apart from OSS. The government has more than 27 thousand applications planned to be simplified to focus on digital transactions, digital identity, and secure data exchange, which will become the basis for the e-government of Indonesia (SPBE) [75]. An example of an application that Kominfo has built is info.go.id [76], which is expected to unite news information from all K/Ls and may become one super application (a super app). Even now, with the increasing development of user needs, super apps not only function as one application but have become a new platform that can determine the adoption of a service based on the number of services provided [77]. Of course, this information service is available in a web form and as a mobile application, which will significantly impact public information access [78]. A monitoring system for business licenses will facilitate access (ease of access) for stakeholders from several ministries/institutions to see the fulfillment of business permits centrally without having to look at each application separately in each institution/ministry.

In general, there are three stages of the development of e-government from a public value perspective: the information stage, the transaction stage, and the engagement stage [79]. In this case, info.go.id is still at the information stage, focusing on disseminating public information as widely as possible to citizens. Of course, this requires developing the function of the application so that it can move to the next stage, namely the transaction stage, where citizens, business actors, and others can contact the government online at any time, reducing paper forms and the cost of visiting government offices, such as in the bio-business licensing process. The third stage is the engagement stage, where citizens and business actors also play an active role in consulting, collaborating, and participating in the government governance process, especially in forming public policy. This monitoring system for fulfilling business license commitments makes it easier for business actors (and more user-friendly) to see what documents are required and which have not been fulfilled. This convenience can improve the user experience in using government applications by continuously adapting to users’ needs.

Meanwhile, if compared with the maturity level of e-government of Indonesian service capabilities, which consist of levels of (1) information, (2) interaction, (3) transactions, (4) collaboration, and (5) optimum, this bio-business business licensing service is already at levels 4 (collaboration) and 5 (optimum) [80]. In this service, there is already collaboration and integration between the OSS system and other K/L systems, which needs to be continuously improved upon to adapt to the needs of users or business actors. In the future, the possibility of using machine learning methods to help monitor the whole process is due to the vast usage of this approach in many diverse applications, such as for predicting software defects [81,82]. The monitoring system for the fulfillment of business licenses prioritizes the functional aspect. Business actors can use this license granted based on their purpose. Meanwhile, non-functional elements, such as optimal system capacity and security, including protecting personal data from business actors, are crucial. This data protection will avoid the potential for data hacking by unauthorized parties.

7. Conclusions and Future Work

This business license’s commitment monitoring system is one of the best options currently, considering the complexity of the integration process of the OSS system with other K/L systems, especially for bio-business business services. Ideally, all government licensing services will become a single e-government application with public information and transactions (end-to-end), starting from the licensing fulfillment process to the payment process or super apps, and become a new platform. This system process will complement the existing OSS system in monitoring domain functions.

Another consideration is the large number of applications currently built by the government, where there may also be many applications in one ministry that still need to become one enterprise system due to gaps in different levels of e-government management maturity. Another factor to consider is that investment in e-government systems also needs time to provide benefits based on their development objectives by integrating their functions into the OSS system later. The costs of integrating and adding this new module become a consideration when implementing the bio-business license monitoring system using text summarization as a quick-win program.

The characteristics of the intelligent system in the business license monitoring system are communication capabilities, embedded knowledge, and control capabilities. Communication capabilities are demonstrated by exchanging data and information between elements (entrepreneurs, systems, and officers). Embedded knowledge is present in the form of keywords and information in documents that users must upload. The system has control capabilities that can determine whether the uploaded documents are valid. Other smart system characteristics can be added in subsequent developments, such as the ability to reason, learn, and perceive. This research focuses on smart governance processes; there is system development in this area but limited discussion (around 10–25%).

The process of monitoring business license commitments will complement existing functions in the OSS system monitoring domain. This smart governance system for fulfilling business licenses applies to the OSS system and fulfills documents for other government ministries and agencies. Considering the large number of existing KBLIs and applications, there are still many functions, modules, and capabilities of these applications that could be duplicated. Therefore, application development that begins with creating a framework will achieve the expected goals.

Developing a prototype system for summarizing the fulfillment of business licenses can also be improved in terms of its function by creating a module that does not stand alone, testing it directly with the current system, and carrying out testing and improvements by obtaining input from the business actors themselves. The text summarization algorithm can also be a research focus to increase the speed of recognizing business license documents. Returning to the initial goal, our intention is to create a simple and transparent system and to make it easier for business actors to immediately obtain business licenses to open up job opportunities, hopefully meet community needs, and reduce unemployment.