Developing a Reference for Smart Rural Communities: An Enterprise Architecture Perspective for Smart Governance

The digital transformation of rural governance is critical to achieving Sustainable Development Goals (SDGs) and fostering community self-reliance. This study develops a comprehensive Enterprise Architecture (EA) framework tailored for smart rural communities using the TOGAF 9.2 methodology. The framework integrates business, data, application, and technology architectures to address inefficiencies, enhance transparency, and optimize governance processes in rural Indonesia. The research adopts the Design Science Research Methodology (DSRM) to ensure systematic artifact development and alignment with strategic goals. Key outcomes include improved administrative services, asset management, and community engagement, demonstrated through case studies involving systems such as SIMIDES, SISMANDES, and OpenSID. The proposed EA framework directly contributes to enhancing Village Development Index (IDM) scores, supporting SDGs like poverty alleviation, quality education, and reduced regional disparities. While the framework presents a scalable model for rural governance, challenges such as IT infrastructure limitations and stakeholder readiness remain. Future research should explore the integration of emerging technologies like IoT and AI to further enhance the model’s adaptability.

Authors

Institutions

Publication Details

Journal
JUSIFO (JURNAL SISTEM INFORMASI)
Published
2024-12-31
DOI
https://doi.org/10.19109/jusifo.v10i2.24294
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Developing a Reference for Smart Rural Communities: An Enterprise Architecture Perspective for Smart Governance

Asti Amalia Nur Fajrillah, Iqbal Yulizar Mukti, Intania Fadya Safitri
JUSIFO (JURNAL SISTEM INFORMASI)
Smart Cities and Technologies
article

Developing a Reference for Smart Rural Communities: An Enterprise Architecture Perspective for Smart Governance

Asti Amalia Nur Fajrillah, Iqbal Yulizar Mukti, Intania Fadya Safitri
article en

Abstract

The digital transformation of rural governance is critical to achieving Sustainable Development Goals (SDGs) and fostering community self-reliance. This study develops a comprehensive Enterprise Architecture (EA) framework tailored for smart rural communities using the TOGAF 9.2 methodology. The framework integrates business, data, application, and technology architectures to address inefficiencies, enhance transparency, and optimize governance processes in rural Indonesia. The research adopts the Design Science Research Methodology (DSRM) to ensure systematic artifact development and alignment with strategic goals. Key outcomes include improved administrative services, asset management, and community engagement, demonstrated through case studies involving systems such as SIMIDES, SISMANDES, and OpenSID. The proposed EA framework directly contributes to enhancing Village Development Index (IDM) scores, supporting SDGs like poverty alleviation, quality education, and reduced regional disparities. While the framework presents a scalable model for rural governance, challenges such as IT infrastructure limitations and stakeholder readiness remain. Future research should explore the integration of emerging technologies like IoT and AI to further enhance the model’s adaptability.

JUSIFO (JURNAL SISTEM INFORMASI)Vol. 10(2)
Telkom University (ID)
Universitas Telkom
Openalex Percentile: Top 62%
Smart Cities and Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.