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All Journal Jurnal Teknoin Journal of Engineering and Management in Industrial System JMPM (Jurnal Material dan Proses Manufaktur) International Journal of Artificial Intelligence Research Jurnal Sistem dan Manajemen Industri PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Angkasa: Jurnal Ilmiah Bidang Teknologi Jurnal Migasian Akamigas Balongan Indramayu Journal of Applied Data Sciences Journal of Industrial Engineering and Halal Industries INJURITY: Journal of Interdisciplinary Studies Science and Technology (SciTech) Jurnal Migasian
Imam Djati Widodo
Magister Teknik Industri, Fakultas Teknologi Industri, Universitas Islam Indonesia
Religion Arts Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Transportation

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Utilizing PLS-SEM and NCA for Understanding Workforce Performance Dicky Suryapranatha; Agus Mansur; Imam Djati Widodo
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 18, No 2 (2026): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v18i2.4007

Abstract

This study explores workforce performance in AI-driven environments where individuals operate under dual-role conditions. Existing studies emphasize technological factors while neglecting human behavioral constraints and the distinction between sufficient and necessary conditions. This study addresses this gap by integrating Partial Least Squares Structural Equation Modeling and Necessary Condition Analysis to identify both enabling and limiting factors. Data were collected from 200 manufacturing workers in Indonesia. The results show that engagement level is the main driver of performance (β = 0.519), while self-regulation capability has a strong effect (β = 0.345). NCA revealed that self-regulation capability is the key necessary condition and main bottleneck (d = 0.189), indicating that high performance cannot be achieved without a minimum threshold. AI system support acts as an enabling factor (d = 0.166), while digital capability shows a weak effect (d = 0.065). These findings highlight that performance is not only driven by engagement but is constrained by self-regulatory capabilities. Future research should extend this model using longitudinal data, multi-sector analysis, and additional variables such as organizational support and system complexity to improve model generalizability and robustness
Co-Authors A. Parkhan Adrian Indarti Adrian Indarti Affan Rifai Agus Mansur, Agus Ali Parkhan Arifa, Dhinar Elma Cahyo, Winda Nur Dicky Suryapranatha E. Fausa Eritrina Rizki Chairani Erlangga Fausa Fausa, Erlangga Hanistia Pahlavi, Banggas Hari Purnomo HARI PURNOMO Hari Purnomo Harwati - Indarti, Adrian Istiqomah, Khairunnisa Nurul Lientje Setyawati Maurits Mufid, Nisrina Faiza Muhammad Ridwan Andi Purnomo Qurtubi Qurtubi Qurtubi Qurtubi, Qurtubi Rahma Fariza Ridho Dimas Sofwan S. Wirayudha Saputra, Bisma Rahmad Yunita Primasanti Zainudin Zukhri