Framework for Digital Transformation in Industry 4.0: Insights Data Driven Analysis in the Indonesia Manufacture Sector

This study presents a structured grey literature review to develop a digital transformation framework for Industry 4.0 in Indonesia’s manufacturing sector. The analysis draws from national policy documents such as Making Indonesia 4.0, the Indonesia Industry 4.0 Readiness Index (INDI), and the Perfo...

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Bibliographic Details
Published inJournal of Advances in Information and Industrial Technology Vol. 7; no. 1; pp. 45 - 60
Main Authors Fesa Kristianto, Ulfia, Yessi Nasia, Galih Prakoso
Format Journal Article
LanguageEnglish
Published 20.05.2025
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ISSN2716-1935
2716-1927
2716-1927
DOI10.52435/jaiit.v7i1.630

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Summary:This study presents a structured grey literature review to develop a digital transformation framework for Industry 4.0 in Indonesia’s manufacturing sector. The analysis draws from national policy documents such as Making Indonesia 4.0, the Indonesia Industry 4.0 Readiness Index (INDI), and the Performance Accountability Report (LAKIP), complemented by qualitative insights from Focus Group Discussions with stakeholders from Digital Industry 4.0 Center (PIDI 4.0) and Badan Standardisasi dan Kebijakan Jasa Industri (BKSJI). Using grounded theory techniques—open, axial, and selective coding—relevant themes were extracted from these non-academic sources and organized into four perspectives: Adaptation, Technologies for Transformation, Key Success Factors, and Implementation Steps. These were operationalized into 25 dimensions and four detailed activity tables. A gap analysis with PIDI 4.0 partner industries was conducted to validate the framework and reveal implementation challenges such as fragmented strategies, limited technical skills, and a lack of performance monitoring. The review method integrates institutional evidence and stakeholder knowledge into a practical model for digital transformation, offering transferability to other developing countries. This research highlights the methodological value of grey literature in constructing context-sensitive frameworks for complex industrial innovation.
ISSN:2716-1935
2716-1927
2716-1927
DOI:10.52435/jaiit.v7i1.630