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This Author published in this journals
All Journal Jurnal Ilmiah Manajemen Kesatuan Journal of Comprehensive Science Journal Research of Social Science, Economics, and Management
Mohammad Riza Sutjipto
Universitas Telkom, Indonesia
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Technology, Organization, Environment, and Digital Transformation for Sustainability Siti Annisa; Mohammad Riza Sutjipto
Jurnal Ilmiah Manajemen Kesatuan Vol. 13 No. 4 (2025): JIMKES Edisi Juli 2025
Publisher : LPPM Institut Bisnis dan Informatika Kesatuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37641/jimkes.v13i4.3497

Abstract

The demands of digital transformation and intense competition are affecting Indonesia's insurance industry. PT Jasaraharja Putera needs to adopt digital technology to enhance productivity and competitiveness. This research utilizes digital transformation as a mediating variable to analyze the impact of organizational, environmental, and technological elements on sustainable advantage through the Technology-Organization-Environment (TOE) framework. The quantitative approach used is Structural Equation Modeling-Partial Least Squares (SEM-PLS) analysis. The Slovin formula analyzed data gathered from 227 participants. The results indicated that organizational (t=8.364; p=0.000) and technological (t=2.432; p=0.015) factors considerably influenced digital transformation. Environmental factors significantly influence outcomes (t=3.871; p=0.000). Digital transformation is crucial for enhancing sustainable excellence (t=3.773; p=0.000). Moreover, the indirect influence of the three TOE factors on sustainable advantage via digital transformation is also noteworthy (e.g., X2 → Z → Y, t=3.152; p=0.002). This study adds to the theoretical understanding by validating the significance of the TOE framework within the insurance sector and offers actionable insights for PT Jasaraharja Putera’s management to enhance organizational preparedness for technology adoption, foster HR capabilities, and bolster technology integration in customer service to maintain competitiveness. This study focuses on a single company, so applying the findings more broadly should be approached carefully. It is suggested that upcoming studies include a wider range of subjects from various sectors and locations.
Analysis of Random Forest Machine Learning Integration in Enterprise Resource Planning (ERP) Systems to Improve Operational Efficiency in Supply Chain Management: A Case Study at PT Sentosa Laju Sejahtera Putri Hardiyanti; Mohammad Riza Sutjipto; Edi Witjara
Journal of Comprehensive Science Vol. 5 No. 6 (2026): Journal of Comprehensive Science
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v5i6.4189

Abstract

The rapid advancement of digital technologies and volatile market dynamics have challenged mining companies to optimize supply chain management (SCM) processes. PT Sentosa Laju Sejahtera (SLS) experiences inefficiencies in procurement and inventory, causing decision latency and increased operational costs. This study aims to explore how integrating Machine Learning, specifically the Random Forest algorithm, into the company’s Enterprise Resource Planning (ERP) system can enhance predictive capabilities, reduce costs, and strengthen operational resilience. A qualitative case study approach was employed, combining in-depth interviews with key managerial stakeholders, participatory observations of operational workflows, and analysis of 63,818 historical Purchase Order documents. Triangulation techniques ensured data credibility and reliability. Findings reveal that Random Forest integration transforms decision-making from reactive to data-driven, reducing procurement cycle times from seven days to 2–3 days and lowering Total Cost of Ownership by 15% through fewer emergency orders. Feature Importance metrics enabled management to identify key inefficiency drivers, improving strategic interventions. Organizational readiness and data governance were identified as critical factors for successful implementation. In conclusion, the integration of predictive analytics into ERP systems provides significant operational and strategic benefits, enhancing efficiency, agility, and competitiveness. The study contributes both empirically to the literature on digital business transformation and practically as a model for multi-site mining enterprises seeking data-driven SCM optimization.
Analysis of Digital Service Business Development at Pln Using Swot Analysis and Business Model Canvas (BMC) (Case Study of PT PLN (Persero) UIW Nusa Tenggara Timur) Ni Wayan Asri Vitaloka; Mohammad Riza Sutjipto
Journal Research of Social Science, Economics, and Management Vol. 5 No. 4 (2025): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i4.1183

Abstract

PLN’s digital transformation has advanced significantly through the implementation of digital services as a one-stop platform aimed at improving customer satisfaction and increasing company revenue. These services offer various conveniences, including bill payments, electricity token purchases, product requests, and access to a marketplace. Understanding PLN’s digital service business model is essential to support business development and service enhancement. This study analyzes PLN Mobile’s business model across customer segments based on tariff classifications using SWOT analysis and the Business Model Canvas (BMC). Additionally, external business factors are examined through PESTEL and Porter’s Five Forces frameworks to identify opportunities and threats. The research adopts a qualitative and descriptive approach, utilizing both primary and secondary data. Primary data are collected through in-depth interviews with internal and external PLN sources, while secondary data include the number of users, token purchases, complaint transactions, and PLN product requests obtained from PLN UIW NTT’s internal reports. The findings reveal that PLN’s digital services strengthen customer engagement and operational efficiency but also face challenges from technological, regulatory, and competitive dynamics. The analysis identifies 18 new strategic recommendations within a revised BMC framework, focusing on expanding customer segments, diversifying revenue streams, supporting green energy initiatives, and optimizing digital infrastructure and resources. These strategies are expected to enhance PLN’s digital service performance, improve customer experience, and contribute to sustainable growth in the national electricity sector.
Co-Authors Edi Witjara Ni Wayan Asri Vitaloka Putri Hardiyanti Siti Annisa