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All Journal Jurnal Teknik Industri Reaktor IPTEK Journal of Proceedings Series JURNAL DINAMIKA VOKASIONAL TEKNIK MESIN Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal STT Yuppentek International Journal of Economics, Business and Accounting Research (IJEBAR) BIP'S : Jurnal Bisnis Perspektif Jurnal Sains dan Aplikasi Keilmuan Teknik Industri JESCEE- Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Integrasi: Jurnal Ilmiah Teknik Industri
Gembong Baskoro
Swiss German University, Tangerang
Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation

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Risk Mitigation of Inventory Discrepancies in Spare Parts Warehouse Using RCA–FMEA–QFD Approach: A Case Study at PT XYZ Ferdira, Novri Oekma; Santoso, Filiana; Baskoro, Gembong
Integrasi: Jurnal Ilmiah Teknik Industri Vol 10 No 2 (2025): Integrasi : Jurnal Ilmiah Teknik Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/integrasi.v10i2.1142

Abstract

This study addressed the issue of inventory discrepancies in the spare parts warehouse of PT XYZ, which previously recorded a discrepancy rate of 0.94% in 2024. The objective was to design and evaluate a mitigation strategy to reduce the discrepancy rate to 0.5%. An integrated approach combining Root Cause Analysis (RCA), Failure Mode and Effect Analysis (FMEA), and Quality Function Deployment (QFD) was applied. RCA identified human error, inaccurate recording, and weak monitoring as the dominant causes of discrepancies. FMEA results showed that stock visibility, accuracy of receiving, and shipping errors were the most critical risks. QFD analysis further revealed that three technical requirements—real-time stock visibility, 100% receiving accuracy, and the penalty system—contributed most significantly to discrepancy reduction. The implementation of these requirements reduced the discrepancy rate from 0.94% to 0.5% between January 2024 and May 2025. Pearson correlation analysis confirmed that these factors had strong positive relationships with customer requirements and discrepancy reduction, with correlation coefficients above 0.7. These findings demonstrated that the integrated RCA–FMEA–QFD approach not only reduced discrepancies but also improved process reliability and operational performance in warehouse management.
Real-Time Temperature Monitoring VHMS Dashboard Development to Reduce Component Unscheduled Breakdown Nur, M. Hidayatullah; Hendriana, Dena; Baskoro, Gembong
BIP's JURNAL BISNIS PERSPEKTIF Vol. 17 No. 1 (2025): Januari
Publisher : Universitas Katolik Darma Cendika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37477/bip.v17i1.697

Abstract

The coal mining industry relies on heavy equipment such as excavators and bulldozers and their efficiencies are critical for the productivity. This paper addresses the issue of unscheduled breakdowns due to high operational temperatures which impacts productivity, equipment availability and maintenance costs. The existing Vehicle Health Monitoring System (VHMS) from Komatsu Original Manufacturing lacks of real-time data for coolant temperature. The data recording is only every 20 hours and data reporting to the monitoring system is transferred daily. This lack of data is leading to unable for identifying the causes of problems. This study proposes a real-time temperature monitoring dashboard for the VHMS to track and manage Komatsu equipment temperature limits and to upgrade the existing system to record temperature data in every second instead of every 20 hours. This fine data collection provides enough information for a comprehensive analysis of machine conditions. This allows for quick identification of abnormal temperature trends, leading to timely maintenance and failures prevention. The new dashboard system provides immediate access to detailed temperature data, facilitating prompt decision-making in maintenance process. It also involves setting new temperature limits to prevent overheating and reduce unscheduled component breakdown from 25% in 2019 to 0% in 2023 and 2024. Implementing a real-time temperature monitoring dashboard is expected to improve equipment availability, reduce breakdowns, optimize maintenance schedules and lower operational costs in the coal mining industry.
PRESCRIPTIVE MAINTENANCE OF KOMATSU DUMP TRUCK HD785-7 USING NAÏVE BAYES CLASSIFIER UNDER FULL MAINTENANCE CONTRACT Paimin; Baskoro, Gembong; Sahputra, Iwan
Jurnal Dinamika Vokasional Teknik Mesin Vol. 10 No. 2 (2025)
Publisher : Department of Mechanical Engineering Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/dinamika.v10i2.89737

Abstract

This study proposes a Prescriptive Maintenance (RxM) framework aimed at improving the Physical Availability (PA) of Komatsu Dump Trucks HD785-7 operated under a Full Maintenance Contract (FMC) at PT ABC Site Sangkulirang. The research integrates the DMAIC methodology with the Knowledge Discovery in Databases (KDD) process to systematically analyze operational failures. Historical breakdown data were preprocessed and modeled using a Naïve Bayes (NB) classifier, selected for its robustness in handling categorical features common in maintenance records. The model demonstrated high predictive performance with 97.93% accuracy, 100% precision, 94.12% recall, and an AUC of 0.995, indicating strong reliability in distinguishing high-risk conditions. The RxM framework was embedded into daily maintenance planning and Standard Operating Procedures (SOPs), supported by a monitoring dashboard for continuous feedback and retraining. As a result, the proportion of Breakdown Unscheduled (BUS) events decreased from 45% in 2024 to 26% in mid-2025, while fleet PA consistently exceeded the contractual target of 92%, reaching 95.5%. These findings confirm that embedding prescriptive analytics into maintenance workflows not only reduces unplanned downtime but also enhances resource allocation and decision-making. The case study highlights the practical value of combining statistical learning with structured process improvement to drive digital transformation in mining operations.
Improvement of Forecating and Inventory Control For Optimizing Inventory at PT United Tractors Site Muara Tiga Besar Fabio, Muhammad Ridho; T. Pratama, Aditya; Baskoro, Gembong
Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Vol 4 No 1 (2025): Journal of Emerging Supply Chain, Clean Energy, and Process Engineering
Publisher : Universitas Pertamina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57102/jescee.v4i1.105

Abstract

PT United Tractors, Muara Tiga Besar site, is one of the company’s sites in Indonesia, responsible for accurately meeting customer demands in terms of timeliness, quantity, and quality. Ineffective and inefficient inventory management leads to idle capital and increased inventory costs, such as storage expenses and other inventory-related risks. Currently, PT United Tractors Muara Tiga Besar site has not yet optimized its inventory management, as evidenced by the Days of Inventory (DOI) performance in 2024 showing an upward trend, with the performance in May 2024 reaching 81.9 days. Therefore, this study aims to improve the DOI performance to meet the established targets. The root cause of the problem was identified using the 5 Why Analysis method, followed by generating ideas and solutions for improvement. The chosen solutions include forecasting using the Simple Moving Average method and inventory control through the Periodic Review and Continuous Review Systems. The research results indicate that forecasting with this purpose method effectively reduces DOI performance to 72 days, while inventory control using the Continuous Review System significantly reduces storage costs by 49%, achieving a more efficient outcome. Keywords — DMAIC, 5 Why Analysis, Forecasting, Simple Moving Average, Periodic Review System, Continuous Review System
Innovation to Improve Critical Thinking Skills in the Generation Z using Peeragogy as a Learning Approach and Artificial Intelligence (AI) as a Tool Baskoro, Gembong; Mariza, Ita; Sutapa, I Nyoman
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 25 No. 2 (2023): December 2023
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.25.2.121-130

Abstract

The current generation, known as generation Z (Gen Z), is a generation that lives and is familiar with information technology in everyday life, including but not limited to learning purposes. Gen Z is characterized by teamwork in cyberspace and solving problems. Gen Z can also adopt artificial intelligence (AI) technology as their learning tool. Meanwhile, Gen Z faces the challenge of acquiring 21st-century skills requiring higher-order thinking (HOTS). This paper will focus on learning skills, especially critical thinking (CT). For this reason, it is essential to improve the competency of CT skills in Gen Z by using a model that combines the 7E learning cycle with peeragogy learning approach and adopting the latest AI applications as a tool. This model will contribute to the theoretical and practical use of AI apps for education, particularly the role of correct utilization of AI. Additionally, it can be misused to improve learning skills, especially CT skills. The results carried out in class show AI's effectiveness in improving CT skills for Gen Z, especially the role of AI in the back-end learning process, namely to verify and validate understanding. This paper suggests that AI apps should be controlled if used in the front-end learning process, especially at the exploration stage, to improve CT skills. Without controlling the AI apps, they can reduce learners' ability to explore a topic according to their creativity and criticality.
Strategic Ambidexterity and Organizational Performance of Manufacturing Companies in Jakarta, Indonesia Mariza, Ita; Baskoro, Gembong
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 26 No. 2 (2024): December 2024
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.26.2.181-192

Abstract

This study identifies factors that improve competitive strategies in manufacturing companies, known as strategic ambidexterity (SA), and their impact on organizational performance to improve production systems as a source of competitive advantage. This survey study was conducted through employee perceptions of SA, by exploiting and exploring firm capacity and capability. Data were collected through a survey directly to the respondents involving 200 employees of manufacturing companies in Jakarta, Indonesia. The method used was a field survey, and the data were analyzed using Structural Equation Modeling (SEM) with Linear Structural Relations (LISREL 9.2). The findings are exploiting organizational capacity has significant effect on SA, exploring organizational capability has a significant effect on SA, and SA has a significant effect on organizational performance. The limitations of this research are it is characterized by cross-sectional and perceptual analysis. The location of all companies involved is only in Jakarta. The managerial implications are that optimal firm performance can be achieved by implementing SA through exploiting organizational capacity to maximize competitiveness in existing markets by optimizing the service quality to customer, improving processes to respond to market feedback, and understanding market needs, and exploring capability to take opportunities in new markets through product innovation, discovering and integrating new technologies, maintaining customers relationships, being flexible and adaptive to the market needs.
Co-Authors Agus Hari Hadi Dena Hendriana Fabio, Muhammad Ridho Ferdira, Novri Oekma Filiana Santoso Hendriana, Dena Henry Nasution I Nyoman Sutapa Mariza, Ita Mochamad Hamdan Aziz Muhamad Lutfi Rachmat Nur, M. Hidayatullah PAIMIN Sahputra, Iwan Sarwono, Edhie Subekti, Galih Akup T. Pratama, Aditya Yohanes Acep Nanang Kardana