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Journal : Jurnal Teknik Informatika (JUTIF)

SEMAR v1.0: An AI-driven Conceptual Model and Architecture for Smart Government in Indonesia Using a Mixed-Methods Approach Arief, Assaf; Muhammad, Miftah; Fuad, Achmad; Sensuse, Dana Indra
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4996

Abstract

Building smart cities represents a national priority for Indonesia to enhance global competitiveness, with artificial intelligence (AI) driven smart government as a key enabler. However, implementation faces significant challenges including unmeasured organizational maturity, lack of service innovation, fragmented governance, and minimal citizen engagement leading to government institutions' failure in achieving smart city vision. This study aims to develop a holistic conceptual model to identify critical success factors and evaluate processes that integrate public services, fostering AI-driven smart government innovation at strategic level. This research employs mixed-methods exploratory sequential design combining qualitative techniques (Systematic Literature Review, expert interviews) with quantitative validation (citizen survey, statistical analysis). The model was constructed using Factor Analysis, Thematic Analysis, TOGAF framework, and multidimensional view with validation through triangulation, expert judgment, Focus Group Discussions, and statistical analysis. Results show a comprehensive model consisting of 6 dimensions, 17 key components, and 5-layer organizational architecture with high reliability (Cronbach's Alpha 0.709-0.866) and expert consensus (86% agreement in Fuzzy Delphi Method analysis). This framework, referred to as SEMAR v1.0 (Smart Government Nusantara), serves as a benchmark for assessing the maturity and readiness of local government institutions in Indonesia. It offers the potential to improve SPBE scores through systematic evaluation, while also providing a theoretical foundation for smart government scholarship and a practical blueprint for policy implementation.
Development of a Smart Environment Maturity Model for Green Industry in North Maluku's Mining Villages, Indonesia Arief, Assaf; Apriyanto, Heri; Muhammad, Miftah; Harisun, Endah
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5107

Abstract

The smart environment maturity model for sustainable mining village areas in North Maluku Province has become a primary demand for the transformation towards sustainable green smart villages. North Maluku, one of Indonesia's largest mining industry provinces, includes the Halmahera and Obi archipelagos as sources of nickel, iron ore/sand, gold, and silver mines. This study aims to develop a maturity model that integrates Indonsian regulations to support green industry implementation in mining villages. The methodology employs Systematic Literature Review to identify Critical Success Factors (CSFs), validated through expert judgment using 5-point Likert scale assessment. The research results yield eight key dimensions, 25 sub-dimensions, and five maturity levels: underdeveloped, developing, self-reliant, advanced, and smart villages. Expert validation achieved an overall average score of 3.65/5.0, indicating moderate acceptance with improvement areas identified in local culture and technology dimensions. The developed framework provides a foundation for environmental informatics applications and decision support systems in rural development contexts. The model addresses national regulations concerning green industry while providing an adaptive framework for archipelago regions, serving as a reference for policy formulation and village fund allocation based on environmental indicators.