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Asesmen Risiko Gangguan Saluran Kabel Tegangan Menengah 20 kV Menggunakan Metode Bow Tie pada PT X Syaiful Azhari Siregar; Suparno Suparno
G-Tech: Jurnal Teknologi Terapan Vol 8 No 3 (2024): G-Tech, Vol. 8 No. 3 Juli 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i3.4420

As one of the operational units of PT PLN (Persero) operated in the distribution and customer service processes, the reliability of the distribution network is a critical concern for PT X. This study conducts a three-stage assessment of the risks associated with disturbances in the 20 kV medium voltage cable network at PT X. In the first stage, a bow-tie diagram comprising 10 threats, 4 consequences, and 18 risk control activities, is developed. In the second stage, the risk level is determined, beginning with assessing likelihood, impact level, and risk control effectiveness. By mapping these results on the risk matrix, it was concluded that the risk level was in the “High” category. In the final stage, the effectiveness of risk controls is ranked to determine the priority for improving risk control activities. 7 activities are identified as requiring immediate attention due to their current ineffective implementation.

Selection Of Coal Terminal Port Spare Parts Suppliers Using The AHP-Topsis Method Rizky Ramadhani; Suparno Suparno
Journal Research of Social Science, Economics, and Management Vol. 4 No. 11 (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.v4i11.864

In the coal mining industry, the conveyor system is a vital component in ensuring the smooth distribution of coal from the stockpile to barges at the terminal port. PT X, one of the leading coal mining companies in Indonesia, faces challenges regarding the sustainability of conveyor operations, particularly in spare part procurement. Dependence on specific suppliers without continuous evaluation can pose risks such as delivery delays, price fluctuations, and operational downtime, which affect the company’s productivity. This study aims to develop a supplier selection model for spare parts at the Coal Terminal Port of PT X using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. AHP is employed to determine the priority weights of criteria based on expert assessments through pairwise comparisons, while TOPSIS is used to rank suppliers based on their relative closeness to the ideal solution. The AHP results indicate that the highest weighted criteria are Quality (35,59%), Services (29.59%), Delivery (15,93%), Cost (12,98%), and Profile (5,91%), while the top sub-criteria are Specification (19,30%), Certification (16,28%), followed by After-Sales Service (15,63%) and Warranty (13,97%) with a consistency ratio < 0,1. Supplier S1 ranks the highest with a preference value of 0,8837. Furthermore, to ensure the robustness of the TOPSIS ranking results, a sensitivity analysis was conducted by increasing or decreasing weights by 1%, and the top-ranked supplier remained unchanged. Thus, the TOPSIS method in this study is proven to be robust.

Increasing Coal Crushing Production at PT. XYZ Using Lean Six Sigma Approach Ahmad Fauzi; Suparno Suparno
Jurnal Indonesia Sosial Teknologi Vol. 6 No. 1 (2025): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v6i1.8925

Coal is a primary energy source in Indonesia, particularly for steam power plants (PLTU). The coal crushing process at PT. XYZ is a critical stage in coal mining operations; however, the company faces operational challenges that hinder the achievement of production targets. This study aims to identify the main issues, analyze factors affecting productivity, and design effective improvement solutions. The methodology used is DMAIC (Define, Measure, Analyze, Improve, Control). In the Define phase, process mapping and waste identification were conducted. The Measure phase utilized a Pareto diagram to determine key issues. Root cause analysis using the 5 Why's method was performed in the Analyze phase. In the Improve phase, solutions were designed through Future State Mapping, while in the Control phase a Kanban Board for monitoring. The results show that Year-to-Date coal crushing production as of October 2024 reached 9.9 million MT, or 94% of the 10.56 million MT target, representing a 139% increase compared to October 2023, which only reached 7.2 million MT.

Control of Main Distribution Material Inventory (MDU) at Pt PLN UP3 Mempawah with Fsn-Xyz and Risk Analysis Arrahmad Ihsan; Suparno Suparno
Jurnal Impresi Indonesia Vol. 4 No. 6 (2025): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v4i6.6658

Main Distribution Materials (MDU) have a vital role in supporting the operational activities of PT PLN UP3 Mempawah, especially in meeting the needs of electricity services for new installations and power changes. The management of MDU inventory that is not optimal often causes problems such as shortage or excess stock due to not taking into account demand uncertainty. This study aims to optimize the inventory management and distribution of MDUs by combining the FSN-XYZ analysis method with the FMEA and FMECA risk assessment approaches. The FSN-XYZ method is used to classify materials based on the frequency of movement and demand variability, while FMEA and FMECA are used to identify potential failures and assess their criticality. The data used in this study came from primary and secondary data, including inventory history and company policies. The results show that most MDU items are classified as Z which has high demand but is unstable, so there is a risk of causing operational disruptions. By implementing an integrated risk-based classification strategy, PLN can prioritize critical items, reduce operational disruptions, and improve cost efficiency. The study also recommends strategies tailored to each category of inventory, such as Just-In-Time for stable materials and a consignment or bundling system for slow-moving materials. The implications of this study emphasize the importance of data-driven adaptive inventory policies in the electricity infrastructure industry that requires high reliability.

Determination Of Marketing Area Priority Scale To Enhance Financial Transactions Through Pln Mobile Using Ahp-Topsis Method At Pln Up3 Palembang Henry Nugroho; Suparno Suparno
Jurnal Impresi Indonesia Vol. 5 No. 2 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i2.7498

Adoption disparities are influenced by technological infrastructure quality, financial resource availability, and socio-economic readiness (facilitating conditions). To address these challenges, a multi-criteria decision-making approach is required to identify marketing areas with the highest potential for increasing financial transactions through PLN Mobile. This study aims to determine the priority scale of marketing areas that are most effective in improving PLN Mobile’s financial transaction performance by applying the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method is employed to determine the relative importance weights among criteria, while TOPSIS is used to rank alternative areas based on their proximity to the ideal solution. The criteria applied include market potential, technological factors, human resource-related aspects, economic conditions, and quality of services. The results are expected to produce an objective and quantifiable model for determining marketing area priorities. Through this approach, PLN UP3 Palembang can optimize marketing resource allocation and expand digital service adoption among customers across South Sumatra.

Selection Of Coal Terminal Port Spare Parts Suppliers Using The AHP-Topsis Method Rizky Ramadhani; Suparno Suparno
Journal Research of Social Science, Economics, and Management Vol. 4 No. 11 (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.v4i11.864

In the coal mining industry, the conveyor system is a vital component in ensuring the smooth distribution of coal from the stockpile to barges at the terminal port. PT X, one of the leading coal mining companies in Indonesia, faces challenges regarding the sustainability of conveyor operations, particularly in spare part procurement. Dependence on specific suppliers without continuous evaluation can pose risks such as delivery delays, price fluctuations, and operational downtime, which affect the company’s productivity. This study aims to develop a supplier selection model for spare parts at the Coal Terminal Port of PT X using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. AHP is employed to determine the priority weights of criteria based on expert assessments through pairwise comparisons, while TOPSIS is used to rank suppliers based on their relative closeness to the ideal solution. The AHP results indicate that the highest weighted criteria are Quality (35,59%), Services (29.59%), Delivery (15,93%), Cost (12,98%), and Profile (5,91%), while the top sub-criteria are Specification (19,30%), Certification (16,28%), followed by After-Sales Service (15,63%) and Warranty (13,97%) with a consistency ratio < 0,1. Supplier S1 ranks the highest with a preference value of 0,8837. Furthermore, to ensure the robustness of the TOPSIS ranking results, a sensitivity analysis was conducted by increasing or decreasing weights by 1%, and the top-ranked supplier remained unchanged. Thus, the TOPSIS method in this study is proven to be robust.

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