IT Service Management Intelligence Model to Support the Implementation of Electronic Government System (EGS) in Indonesia

Heru Nugroho, - Aradea, Kridanto Surendro

Abstract


Government institutions operate in a diverse environment that includes a wide range of issues such as social, economic, political, cultural, and other related issues. This fact eventually leads to various challenges and problems related to public services. The state of the existing resources and the management mechanisms affect the quality of services. These conditions require a comprehensive approach to the government's system. Electronic Government System (EGS) architecture is developed to provide guidelines in synchronizing and integrating applications employed by central or regional government agencies. The purpose of EGS service management is to guarantee sustainability and improve the quality of EGS Services to EGS users. The development of smart and holistic service applications can be a starting point in achieving a quality service system, including the government system, a system of service management that involves various elements holistically. This research aims to propose an Information Technology Services Management Intelligence model to support the implementation of EGS. This model approach is based on a holistic view of an environment in delivering public information technology services. It is also based on ITSM and Intelligent Systems, including architecture, alignment, and adaptability. The proposed model assists developers in defining conceptual needs of information technology services based on business perspectives to create intelligent systems that can dynamically predict and meet their needs.

Keywords


Electronic government system; ITSM; model; intelligent systems.

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References


ITU-T, “An overview of smart sustainable cities and the role of information and communication technologies,†2014.

Kementerian Pendayagunaan Aparatur Negara dan Reformasi Birokrasi (PANRB), “Babak Baru Sistem Pemerintahan Berbasis Elektronik,†2019. [Online]. Available: https://www.menpan.go.id/site/berita-terkini/babak-baru-sistem-pemerintahan-berbasis-elektronik.

Kementerian Pendayagunaan Aparatur Negara dan Reformasi Birokrasi (PANRB), “Dua Tahun Perpres SPBE, Setiap Instansi Harus Gunakan Aplikasi Umum,†2018. [Online]. Available: https://www.menpan.go.id/site/berita-terkini/dua-tahun-perpres-spbe-setiap-instansi-harus-gunakan-aplikasi-umum.

Kementerian Sekretariat Negara Republik Indonesia, Peraturan Presiden Republik Indonesia Nomor 95 tahun 2018 tentang Sistem Pemerintahan Berbasis Elektronik (SPBE). 2018.

“Making Indonesia 4.0,†2019.

H. T. Sukmana, L. K. Wardhani, R. Argantone, and K. Lee, “The Evaluation of ITSM Open-Source Software for Small Medium Organizations Based on ITIL v.3 Criteria using AHP Method,†Int. J. Control Autom., 2017.

J. Serrano, J. Faustino, D. Adriano, R. Pereira, and M. M. da Silva, “An it service management literature review: Challenges, benefits, opportunities and implementation practices,†Information (Switzerland). 2021.

T. J. Winkler and J. Wulf, “Effectiveness of IT Service Management Capability: Value Co-Creation and Value Facilitation Mechanisms,†J. Manag. Inf. Syst., 2019.

A. Keller, “Challenges and Directions in Service Management Automation,†J. Netw. Syst. Manag., vol. 25, no. 4, pp. 884–901, 2017.

M. Jäntti, T. Rout, L. Wen, S. Heikkinen, and A. Cater-Steel, “Exploring the Impact of IT Service Management Process Improvement Initiatives: A Case Study Approach,†Commun. Comput. Inf. Sci., vol. 349 CCIS, pp. 176–187, 2013.

E. Orta and M. Ruiz, “Met4ITIL: A process management and simulation-based method for implementing ITIL,†Comput. Stand. Interfaces, 2019.

P. Kubiak and S. Rass, “An Overview of Data-Driven Techniques for IT-Service-Management,†IEEE Access, 2018.

B. Barafort, A. L. Mesquida, and A. Mas, “Integrating risk management in IT settings from ISO standards and management systems perspectives,†Comput. Stand. Interfaces, 2017.

O. S. Al-Mushayt, “Automating E-Government Services with Artificial Intelligence,†IEEE Access, 2019.

G. D. Uniyal and A. Sethi, “Service Experience Transformation with Servicenow AI,†2018.

J. L. Mohr, “ITIL® 4 And Artificial Intelligence,†2019.

M. Engine ServiceDesk Plus, “The AI advantage Use cases and scenarios on how AI will redefine the way IT service desks work.,†2018.

S. J. Mikhaylov, M. Esteve, and A. Campion, “Artificial intelligence for the public sector: Opportunities and challenges of cross-sector collaboration,†Philos. Trans. R. Soc. A Math. Phys. Eng. Sci., 2018.

D. Valle-Cruz, R. Sandoval-Almazan, E. A. Ruvalcaba-Gomez, and J. Ignacio Criado, “A review of artificial intelligence in government and its potential from a public policy perspective,†in ACM International Conference Proceeding Series, 2019.

D. A. D. Putra et al., “Tactical steps for e-government development,†Int. J. Pure Appl. Math., 2018.

A. Zuiderwijk, Y. C. Chen, and F. Salem, “Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda,†Gov. Inf. Q., 2021.

B. W. Wirtz, J. C. Weyerer, and C. Geyer, “Artificial Intelligence and the Public Sector—Applications and Challenges,†Int. J. Public Adm., 2019.

M. Kuziemski and G. Misuraca, “AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings,†Telecomm. Policy, 2020.

S. Fatima, K. C. Desouza, and G. S. Dawson, “National strategic artificial intelligence plans: A multi-dimensional analysis,†Econ. Anal. Policy, 2020.

W. G. de Sousa, E. R. P. de Melo, P. H. D. S. Bermejo, R. A. S. Farias, and A. O. Gomes, “How and where is artificial intelligence in the public sector going? A literature review and research agenda,†Government Information Quarterly. 2019.

B. W. Wirtz and W. M. Müller, “An integrated artificial intelligence framework for public management,†Public Manag. Rev., 2019.

Y. K. Dwivedi et al., “Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,†Int. J. Inf. Manage., 2021.

M. Janssen, P. Brous, E. Estevez, L. S. Barbosa, and T. Janowski, “Data governance: Organizing data for trustworthy Artificial Intelligence,†Gov. Inf. Q., 2020.

D. Zuev, A. Kalistratov, and A. Zuev, “Machine Learning in IT Service Management,†Procedia Comput. Sci., vol. 145, pp. 675–679, 2018.

F. Al-Hawari and H. Barham, “A machine learning based help desk system for IT service management,†J. King Saud Univ. - Comput. Inf. Sci., 2019.

L. Cui, S. Yang, F. Chen, Z. Ming, N. Lu, and J. Qin, “A survey on application of machine learning for Internet of Things,†Int. J. Mach. Learn. Cybern., 2018.

H. Nandedkar, “Service Management with IoT,†Fusion Global Business Solution, 2019. [Online]. Available: https://www.fusiongbs.com/service-management-with-iot/.

Forbes, “Delivering Value to Today’s Digital Enterprise,†2017.

A. I. A. Ahmed et al., “Service management for iot: Requirements, taxonomy, recent advances and open research challenges,†IEEE Access, 2019.

S. N. Han and N. Crespi, “Semantic service provisioning for smart objects: Integrating IoT applications into the web,†Futur. Gener. Comput. Syst., 2017.

Z. Khan, Z. Pervez, and A. G. Abbasi, “Towards a secure service provisioning framework in a Smart city environment,†Futur. Gener. Comput. Syst., 2017.

A. Viejo and D. Sánchez, “Secure and privacy-preserving orchestration and delivery of fog-enabled IoT services,†Ad Hoc Networks, 2019.

J. Wang, H. Qi, K. Li, and X. Zhou, “PRSFC-IoT: A performance and resource aware orchestration system of service function chaining for internet of things,†IEEE Internet Things J., 2018.

S. Moro, P. Cortez, and P. Rita, “A framework for increasing the value of predictive data-driven models by enriching problem domain characterization with novel features,†Nat. Comput. Appl., vol. 28, pp. 1515–1523, 2017.

X. Min, X. Xu, Z. Liu, D. Chu, and Z. Wang, “An Approach to Resource and QoS-Aware Services Optimal Composition in the Big Service and Internet of Things,†IEEE Access, 2018.

O. Alsaryrah, I. Mashal, and T. Y. Chung, “Bi-Objective Optimization for Energy Aware Internet of Things Service Composition,†IEEE Access, 2018.

Z. Huang, K. J. Lin, B. L. Tsai, S. Yan, and C. S. Shih, “Building edge intelligence for online activity recognition in service-oriented IoT systems,†Futur. Gener. Comput. Syst., 2018.

M. Mohammadi, A. Al-Fuqaha, M. Guizani, and J. S. Oh, “Semisupervised Deep Reinforcement Learning in Support of IoT and Smart City Services,†IEEE Internet Things J., 2018.

M. Sun, Z. Shi, S. Chen, Z. Zhou, and Y. Duan, “Energy-Efficient Composition of Configurable Internet of Things Services,†IEEE Access, 2017.

T. D. Lee, B. M. Lee, and W. Noh, “Hierarchical Cloud Computing Architecture for Context-Aware IoT Services,†IEEE Trans. Consum. Electron., 2018.

O. Hahm, E. Baccelli, H. Petersen, and N. Tsiftes, “Operating Systems for Low-End Devices in the Internet of Things: A Survey,†IEEE Internet Things J., 2016.

M. Ganzha, M. Paprzycki, W. Pawłowski, P. Szmeja, and K. Wasielewska, “Semantic interoperability in the Internet of Things: An overview from the INTER-IoT perspective,†J. Netw. Comput. Appl., 2017.

I. Yaqoob et al., “Internet of Things Architecture: Recent Advances, Taxonomy, Requirements, and Open Challenges,†IEEE Wirel. Commun., 2017.

X. Zhu and Y. Badr, “Identity Management Systems for the Internet of Things: A Survey Towards Blockchain Solutions,†Sensors (Basel)., 2018.

M. Ammar, G. Russello, and B. Crispo, “Internet of Things: A survey on the security of IoT frameworks,†J. Inf. Secur. Appl., 2018.

M. Marjani et al., “Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges,†IEEE Access, 2017.

R. A. Ariyaluran Habeeb, F. Nasaruddin, A. Gani, I. A. Targio Hashem, E. Ahmed, and M. Imran, “Real-time big data processing for anomaly detection: A Survey,†International Journal of Information Management. 2019.

B. W. Wirtz, J. C. Weyerer, and F. T. Schichtel, “An integrative public IoT framework for smart government,†Gov. Inf. Q., 2019.

J. G. Harris and T. H. Davenport, “Competing on Analytics, Updated, with a New Introduction: The New Science of Winning.,†Harvard Bus. Sch. Press Books, 2017.

E. S. Kim, Y. Choi, and J. Byun, “Big data analytics in government: Improving decision making for R&D investment in Korean SMEs,†sustainability, vol. 12, no. 1, 2020.

Aradea, I. Supriana, K. Surendro, and H. Mubarok, “Self-adaptation modeling for service evolution on the Internet of Things (IoT),†IOP Conf. Ser. Mater. Sci. Eng., vol. 550, no. 1, 2019.

A. Aradea, I. Supriana, and K. Surendro, “Self-adaptive model based on goal-oriented requirements engineering for handling service variability,†J. Inf. Common. Technol., 2020.

Aradea, I. Supriana, and K. Surendro, “Self-adaptive software modeling based on contextual requirements,†Telkomnika (Telecommunication Comput. Electron. Control., 2018.

K. Surendro, Aradea, and I. Supriana, “Requirements engineering for cloud computing adaptive model,†J. Inf. Commun. Technol., 2016.




DOI: http://dx.doi.org/10.18517/ijaseit.12.2.13789

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