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All Journal Jurnal Optimasi Sistem Industri Jurnal Pengabdian Masyarakat dan aplikasi Teknologi
Retno Wulan Damayanti
Universitas Sebelas Maret
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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Perancangan Perangkat Pembelajaran Internet of Things (IoT) dan Pengenalan Robotika Kepada Siswa Sekolah Menengah di Surakarta Sekitarnya Pringgo Widyo Laksono; Retno Wulan Damayanti; Cucuk Nur Rosyidi; Eko Pujiyanto; Wakhid Ahmad Jauhari; Anindya Rachma Dwicahyani
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi (Adipati) Vol 2, No 2 (2023)
Publisher : Institut Teknologi Adhi Tama Surabaya

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Abstract

Pemahaman dan keterampilan pada siswa sekolah menengah mengenai Internet of Things (IoT) dan teknologi robotika adalah hal yang penting untuk menjawab tantangan global. Melalui pengenalan IoT dan robotika, siswa mendapatkan kesempatan untuk merancang, membangun, dan memprogram perangkat IoT dan robot secara langsung. Tujuan program ini adalah untuk memperkenalkan siswa pada konsep dan penerapan teknologi serta membantu mereka mengembangkan keterampilan yang relevan untuk dunia kerja abad ke-21. Siswa diharapkan dapat meningkatkan pemahaman mereka tentang IoT dan robotika, sehingga mereka lebih siap menghadapi tuntutan dunia kerja yang semakin berkembang di era revolusi industri 4.0. Selain itu, mitra industri yang terlibat dalam program ini, CV Enuma Technology, akan mendapatkan manfaat dalam mengembangkan produk media pembelajaran yang dapat dikomersilikilkan di pasar secara lebih luas. Melalui program ini, mitra industri dapat meningkatkan kualitas produk yang dibutuhkan oleh konsumen serta meningkatkan daya saing di pasar teknologi yang terus berkembang.
Towards Safer Workplace: A Survey-Based Study on Developing a Safety Climate Model for the Indonesian Paper Industry Nana Rahdiana; Bambang Suhardi; Retno Wulan Damayanti; Novie Susanto; Jafri Mohd Rohani
Jurnal Optimasi Sistem Industri Vol. 23 No. 2 (2024): Published in January 2025 (published late, please read our note)
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v23.n2.p130-148.2024

Abstract

A reliable safety climate model is essential for evaluating safety behavior and predicting risks such as accidents or injuries, yet no research has specifically addressed the safety climate in the paper industry, either globally or in Indonesia. Recognized as high-risk due to its reliance on large machinery and hazardous chemicals, the paper industry has been understudied in this context. This research addresses the gap by developing a safety climate model tailored to the Indonesian paper industry, following a rigorous methodology that included a literature review, model design, validation processes, and Goodness-of-Fit testing. The study identified nine dimensions and 36 initial indicators, with strong content validity confirmed through Aiken’s V index, and refined through a survey of 313 employees—including managers, supervisors, and operators—at a paper factory in West Java, Indonesia. Confirmatory factor analysis (CFA) led to the final model, comprising nine dimensions and 32 validated indicators, achieving excellent fit across key criteria. These dimensions include management commitment, safety environment, safety communication, safety involvement, safety rules and procedures, safety training, safety competence, work pressure, and local wisdom. The validated model offers valuable insights into safety practices, providing a practical framework for improving safety performance in the Indonesian paper industry. By fostering a proactive safety culture and addressing sector-specific risks, this model has the potential to significantly reduce workplace accidents and improve overall safety performance, marking an important advancement in industry-specific safety research.
A Framework for Sustainable Supplier Selection Integrating Grey Forecasting and F-MCDM Methods: A Case Study Enty Nur Hayati; Wakhid Ahmad Jauhari; Retno Wulan Damayanti; Cucuk Nur Rosyidi; Muhammad Hafidz Fazli Bin Md Fauadi
Jurnal Optimasi Sistem Industri Vol. 24 No. 1 (2025): Published in June 2025
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v24.n1.p63-83.2025

Abstract

Selecting appropriate suppliers is critical for healthcare organizations to ensure high-quality, reliable, and sustainable patient care services. In an increasingly competitive environment, hospitals must optimize supplier selection not only based on economic factors but also by integrating environmental and social sustainability considerations. This study aims to create a strong system for choosing sustainable suppliers in healthcare by combining fuzzy-based multi-criteria decision-making (MCDM) methods with Grey Forecasting GM(1,1) to handle uncertainty and changes in performance over time. The proposed framework applies the Fuzzy Best-Worst Method (F-BWM) to determine the relative importance of sustainability criteria, while the Fuzzy Additive Ratio Assessment (F-ARAS) method is used to rank suppliers based on these weighted criteria. Grey Forecasting GM(1,1) is employed to predict supplier performance for future periods, with forecasting accuracy evaluated through Mean Absolute Percentage Error (MAPE). All supplier forecasts achieved MAPE values below 5%, indicating very high prediction reliability. Empirical results from a case study at a general hospital in Indonesia confirm that social aspects, such as patient safety and reputation, are prioritized over economic and environmental considerations. Practically, the proposed framework enables healthcare institutions to holistically evaluate suppliers, specifically reducing risks related to supply disruptions and quality inconsistencies. The model performs best under conditions of limited or uncertain data availability, where supplier historical performance trends can be leveraged to forecast future reliability and sustainability outcomes. The prioritization of sustainability criteria yields social criteria (weight = 0.3703) as the most important, followed by economic (0.3609) and environmental (0.2688) criteria.
Co-Authors Anindya Rachma Dwicahyani Bambang Suhardi Cucuk Nur Rosyidi Eko Pujiyanto Enty Nur Hayati Jafri Mohd Rohani Muhammad Hafidz Fazli Bin Md Fauadi Nana Rahdiana Novie Susanto Pringgo Widyo Laksono Wakhid Ahmad Jauhari