PERAMALAN TINGKAT KEANDALAN SISTEM DISTRIBUSI TENAGA LISTRIK DI PT.PLN (PERSERO) UP3 BULUNGAN BERDASARKAN SAIDI DAN SAIFI

Sinaga, Dea Angelia Br and Hajar, Ibnu (2024) PERAMALAN TINGKAT KEANDALAN SISTEM DISTRIBUSI TENAGA LISTRIK DI PT.PLN (PERSERO) UP3 BULUNGAN BERDASARKAN SAIDI DAN SAIFI. Diploma thesis, ITPLN.

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Abstract

Peramalan merupakan kegiatan memperkirakan atau memprediksi apa yang akan terjadi pada masa yang akan datang, sedangkan ramalan adalah suatu kondisi yang diperkirakan akan terjadi pada masa yang akan datang. Dalam penelitian ini dilakukan peramalan untuk indeks keandalan jaringan distribusi yaitu SAIDI dan SAIFI, dengan melakukan peramalan total pelanggan menggunakan metode regresi linear dan melakukan peramalan durasi padam dan pelanggan padam menggunakan metode ARIMA. Tujuan penelitian ini adalah untuk menganalisa nilai SAIDI dan SAIFI pada seluruh pelanggan untuk April 2024 hingga desember 2025, membandingkan indeks keandalan SAIDI dan SAIFI dari hasil peramalan, dan mengetahui upaya yang dapat diterapkan guna menjaga keandalan jaringan distribusi. SAIDI dan SAIFI tahun 2024 hingga 2025, dengan hasil SAIDI SAIFI tahun 2024 yaitu 0,329 dan 0,265 dan hasil SAIDI dan SAIFI tahun 2025 yaitu 0,302 dan 0,245. Berdasarkan SPLN 68-2 1986, untuk indeks keandalan jaringan distribusi SAIDI dan SAIFI di UP3 Bulungan masih andal karena SAIDI ≤ 12,842 pemadaman/ pelanggan/ tahun dan SAIFI ≤ 2,406 jam/ pelanggan/ tahun.Hasil penelitian ini dapat dijadikan referensi untuk meramalkan keandalan sistem distribusi di PT. PLN (Persero) UP3 Bulungan untuk 3 tahun kedepan. Dapat menjadi suatu acuan dalam upaya meminimalisir permasalahan atau kegagalan dalam jaringan distribusi pada tahun-tahun berikutnya.

Forecasting is the activity of estimating or predicting what will happen in the future, while forecasting is a condition that is expected to occur in the future. is a condition that is expected to occur in the future. In this research, forecasting is carried out for distribution network reliability indices, namely SAIDI and SAIFI, by forecasting total customers. distribution network reliability indices, namely SAIDI and SAIFI, by forecasting total customers using the linear regression method and forecasting total customers using the linear regression method. using the linear regression method and forecasting the duration of outages and customer outages using the ARIMA method. outage customers using the ARIMA method. The purpose of this research is to know how to analyse the SAIDI and SAIFI values of all customers for April 2024 to December 2025. 2024 to December 2025, compare the SAIDI and SAIFI reliability indices from the forecasting results, and find out the efforts to improve the reliability of SAIDI and SAIFI. forecasting results and find out the efforts that can be applied to maintain the reliability of the distribution network. reliability of the distribution network. SAIDI and SAIFI for the years 2024 to 2025, with SAIDI and SAIFI results in 2024 are 0.329 and 0.265 and the results of SAIDI and SAIFI in 2025 are 0.302. in 2025, namely 0.302 and 0.245. Based on SPLN 68-2 1986, for distribution network reliability index’s reliability index of the distribution network SAIDI and SAIFI in UP3 Bulungan are still reliable because SAIDI ≤ 12.842 outages / customer / year and SAIFI ≤ 2.406 hours / customer / year. The results of this study can be used as a reference to forecast the reliability of the distribution system in PT PLN Bulungan. reliability of the distribution system at PT PLN (Persero) UP3 Bulungan for the next 3 years. in the future. Can be a reference in an effort to minimise problems or failures in the distribution network in the following years. failure in the distribution network in the following years

Item Type: Thesis (Diploma)
Uncontrolled Keywords: Peramalan, ARIMA, SAIDI, SAIFI Forecasting, ARIMA, SAIDI, SAIFI
Subjects: Skripsi
Bidang Keilmuan > Teknik Elektro
Divisions: Fakultas Ketenagalistrikan dan Energi Terbarukan > S1 Teknik Elektro
Depositing User: Sudarman
Date Deposited: 03 Nov 2025 04:07
Last Modified: 03 Nov 2025 04:07
URI: https://repository.itpln.ac.id/id/eprint/3273

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