Pengembangan Model Supply Chain Resilience Untuk Bencana Alam Banjir Di Unit Layanan Pelanggan (ULP) PLN

Bakti, Ahmad Darmawan Andhika (2026) Pengembangan Model Supply Chain Resilience Untuk Bencana Alam Banjir Di Unit Layanan Pelanggan (ULP) PLN. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Banjir dapat menyebabkan disrupsi pada sistem distribusi tenaga listrik, khususnya di wilayah kerja Unit Layanan Pelanggan (ULP) PLN, baik itu disrupsi operasional maupun disrupsi terkait pelayanan pelanggan. Untuk itu diperlukan suatu model yang mampu mengidentifikasi disrupsi-disrupsi yang mungkin terjadi serta kapabilitas apa yang dimiliki suatu perusahaan agar dapat meningkatkan strategi resiliensinya. Penelitian ini bertujuan untuk mengembangkan model Supply Chain Resilience (SCRes) terhadap disrupsi akibat banjir yang dapat menyebabkan padam meluas pada ULP PLN. Penelitian dilakukan pada wilayah kerja PT PLN (Persero) Unit Induk Distribusi Sumatera Selatan, Jambi, dan Bengkulu. Bayesian Network adalah metode yang digunakan untuk menganalisis hubungan antar disruption events. Setelah itu, hasil prioritas disrupsi yang berupa expected value akan dipetakan terhadap SCRes capabilities untuk menentukan kapabilitas mana saja yang paling memberikan kontribusi dalam mengurangi disrupsi yang ada. Dari hasil penelitian yang dilakukan, menunjukkan terdapat 13 disrupsi yang dinyatakan relevan. Disrupsi prioritas paling tinggi berkaitan dengan peningkatan pengaduan pelanggan, terhambatnya operasi dan pemeliharaan jaringan, terdampaknya gardu/jaringan distribusi, keterbatasan mobilitas tim teknik, serta durasi padam yang lebih lama. Sedangkan untuk hasil pemetaan SCRes capabilities menunjukkan bahwa Learning and Improvement Capability, koordinasi ULP–UP3–UID saat gangguan, dan Operational Flexibility menjadi kapabilitas dengan kontribusi tertinggi. Penelitian ini juga menunjukkan adanya capability gap pada beberapa disrupsi yang belum dapat direduksi secara optimal oleh kapabilitas yang dimiliki oleh ULP PLN saat ini.
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Floods can disrupt electricity distribution systems, particularly within the PLN Customer Service Unit (ULP) operational area, affecting both operational performance and customer service delivery. Consequently, there is a need for a model capable of identifying potential disruptions and assessing the capabilities a company possesses to enhance its resilience strategy. This study aims to develop a Supply Chain Resilience (SCRes) model for flood-induced disruptions that can cause widespread outages within PLN’s ULP. The research was conducted in the service area of PT PLN (Persero), Distribution Main Unit for South Sumatra, Jambi, and Bengkulu. Bayesian Networks were employed to analyze the relationships among disruption events. Subsequently, the prioritized disruptions, expressed as expected values, were mapped onto SCRes capabilities to determine which capabilities most effectively mitigate existing disruptions. The findings indicate 13 disruptions deemed relevant. The highest-priority disruptions relate to increased customer complaints, impeded network operation and maintenance, affected substations/distribution networks, limited mobility of technical teams, and prolonged outage durations. Regarding SCRes capabilities, the most contributive elements are Learning and Improvement Capability, coordination among ULP–UP3–UID during disturbances, and Operational Flexibility. The study also identifies capability gaps for several disruptions that are not optimally mitigated by the current capabilities of PLN’s ULP.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Supply Chain Resilience, Bayesian Network, Disrupsi, SCRes Capabilities, Banjir, Supply Chain Resilience, Bayesian Network, Disruption Events, SCRes Capabilities, Floods
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD38.5 Business logistics--Cost effectiveness. Supply chain management. ERP
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User:	Ahmad Darmawan Andhika Bakti
Date Deposited:	01 Jul 2026 03:26
Last Modified:	01 Jul 2026 03:26
URI:	http://repository.its.ac.id/id/eprint/134157

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