Analysis of Technical Efficiency of Electricity Distribution at PT. PLN UP3 Parepare for 2019-2024: Stochastic Frontier Analysis (SFA) Approach

Endah Suryaning Wulandari; Dyah Wulan Sari

doi:10.59261/inkubis.v8i3.408

Authors

Endah Suryaning Wulandari Universitas Airlangga
Dyah Wulan Sari Universitas Airlangga

DOI:

https://doi.org/10.59261/inkubis.v8i3.408

Keywords:

Education Level, Electricity Distribution, SAIDI-SAIFI, Stochastic Frontier Analysis (SFA), Technical Efficiency

Abstract

Background: Electricity distribution efficiency is essential for maintaining service quality, operational performance, and system reliability. Despite Indonesia’s high electrification rate, efficiency at the service-unit level remains underexplored, particularly regarding network reliability and human resource quality.

Objective: This study aims to analyze the level of technical efficiency in electricity distribution and the factors influencing inefficiency at PT PLN (Persero) UP3 Parepare during the 2019–2024 period.

Methods: The research uses monthly panel data from seven Customer Service Units (ULP) and applies a Stochastic Frontier Analysis (SFA) approach with a translog production function. Output variables include the number of customers, electricity energy sold, and energy losses, while input variables consist of labor, distribution networks, the number of transformers, and transformer capacity. The inefficiency factors analyzed are System Average Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), employee education level, and the COVID-19 pandemic.

Results: Technical efficiency was high, averaging above 0.97, with ULP Mattirotasi recording the highest efficiency score (0.986). Distribution networks and transformer capacity contributed positively to output. SAIDI was positively associated with inefficiency at the 10% significance level but was not statistically significant at the 5% level, while higher employee education levels were associated with reduced inefficiency.

Conclusion: These findings indicate that improving electricity distribution efficiency requires optimizing distribution assets, enhancing network reliability, and strengthening human resource competencies.

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