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p-Index From 2021 - 2026
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All Journal Jurnal Manajemen Informatika dan Bisnis Digital Smart International Management Journal (SIMJ)
Muhammad Damas Fatih
Universitas Jambi
Computer Science & IT Decision Sciences, Operations Research & Management

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Digital Economy Acceleration and the Reconfiguration of Labor Wage Structures within the Indonesian Service Sector Radna Nurmalina; Muhammad Damas Fatih
Smart International Management Journal Vol 3 No 2 (2026): June 2026
Publisher : CV. HEI PUBLISHING INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70076/simj.v3i2.186

Abstract

The rapid acceleration of the digital economy in Indonesia has substantially transformed the service sector landscape, particularly in shaping labor wage structures. This study aims to examine how digital economy acceleration influences the reconfiguration of wage structures within Indonesia's service sector. A quantitative approach was employed using secondary data obtained from Statistics Indonesia (BPS), the World Bank, and national digital economy reports covering the period 2018–2024. The findings indicate that digitalization has increased the demand for high-skilled labor, leading to higher wage premiums for this group, while low-skilled workers tend to experience wage stagnation. Furthermore, the expansion of the platform-based economy (gig economy) has enhanced labor flexibility but also introduced income instability. Wage disparities across service subsectors, including app-based transportation and digital financial services, have become more pronounced. The study concludes that the acceleration of the digital economy not only improves economic efficiency but also fundamentally reshapes wage structures, potentially widening inequality if not accompanied by effective policies in skill development and adaptive social protection systems.
Systematic Literature Review: Integrasi Explainable AI dalam Decision Support System untuk Manajemen Risiko dan Krisis Muhammad Damas Fatih; Hamzah Alghifari; Pariyadi Pariyadi; Mohammad Alfiza Rayesa
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 5 No. 1 (2026): Mei 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v5i1.8113

Abstract

The growing complexity of risks and crisis situations across various sectors has encouraged the development of Artificial Intelligence-based Decision Support Systems (DSS) to support more accurate, responsive, and data-driven decision-making. These systems are considered valuable because they can help decision-makers analyze uncertainty, recognize potential threats, predict possible impacts, and determine appropriate actions in complex conditions. However, the use of black-box AI models creates serious challenges, particularly regarding transparency, accountability, interpretability, and user trust. Therefore, this study focuses on examining the trend of Explainable Artificial Intelligence (XAI) integration in DSS for risk and crisis management, identifying the XAI methods commonly applied, and revealing research gaps that still need further attention. The study applies a Systematic Literature Review (SLR) method using the PRISMA approach, involving 47 selected articles obtained from Scopus, IEEE Xplore, ScienceDirect, and Google Scholar databases, published between 2020 and 2025. The findings show that XAI plays an important role in improving transparency, interpretability, and trust in AI-based DSS, with SHAP and LIME being the most frequently used methods. Nevertheless, gaps remain, especially limited XAI implementation in real-time crisis scenarios and insufficient human-centered design approaches. This study contributes a conceptual framework integrating DSS, XAI, and risk management.
Co-Authors Alghifari, Hamzah Mohammad Alfiza Rayesa Nurmalina, Radna Pariyadi Pariyadi