CLASSIFICATION OF RELIABILITY OF ELECTRIC POWER DISTRIBUTION SYSTEMS AT PT. PLN (PERSERO) UP3 SOUTH SURABAYA USING THE SINGLE PERCEPTRON METHOD

Giovanni Dimas Prenata

Abstract

The reliability of the electricity distribution system is very important for PLN. With a high level of reliability, PLN can ensure that electrical energy is distributed properly to customers. A high level of reliability is a guarantee for customers to get electrical energy. Some researchers measure reliability using the SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) values. Apart from that, there are also those who use the FMEA (Failure Modes and Effects Analysis) method. In this study, researchers carried out reliability classification based on the SPLN 59-1985 standard using the artificial neuron network single perceptron method. Researchers used 3 neurons as input, namely the SAIDI value, SAIFI value and bias. The training data used is SAIDI value data and SAIFI value data for 10 months in 2021. The single perceptron neuron network application was created using C++ language with a learning rate of 0.1, and a sigmoid signal as the activation. So the weighting values obtained for 3 neurons, namely -3.95772 (W[0]), 1.15408 (W[1]) and 1.45799 (W[2]) in 6 training times to classify the level of reliability.

Keywords

SAIDI, SAIFI dan artificial neuron network single perceptron.

Full Text:

PDF

References

J. D. Haryantho and H. H. Tumbelaka, “Analisa Keandalan Sistem Kelistrikan Di Daerah Pelayanan P.T. PLN (Persero) Area Timika Berbasis SAIDI SAIFI,” J. Tek. Elektro, vol. 10, no. 2, pp. 71–74, 2017, doi: 10.9744/jte.10.2.71-74.

D. Wahyudi, “Evaluasi Keandalan Sistem Distribusi Tenaga Listrik Berdasarkan SAIDI Dan SAIFI Pada PT. PLN (Persero) Rayon Kakap,” J. Tek. Elektro, vol. 1, no. 8, pp. 1–7, 2016.

A. Fatoni, “Analisa Keandalan Sistem Distribusi 20 kV PT.PLN Rayon Lumajang dengan Metode FMEA (Failure Modes and Effects Analysis),” J. Tek. ITS, vol. 5, no. 2, pp. 462–467, 2017, doi: 10.12962/j23373539.v5i2.16150.

D. L. Rura, L. S. Patras, and S. Silimang, “Evaluasi Keandalan Sistem Distribusi Menggunakan Indeks Saifi Dan Saidi Pada Pt.Pln (Persero) Area Bitung,” 2014.

J. Husna and Z. Pelawi, “Menentukan Indeks Saidi Dan Saifi Pada Saluran Udara Tegangan Menengah Di PT. PLN Wilayah Nad Cabang Langsa,” Bul. Utama Tek., vol. 14, no. 1, pp. 13–17, 2018, [Online]. Available: http://123dok.com

D. Agung Riansa, Widodo, and B. Prasetya Adhi, “Pengenalan Tanda Tangan Menggunakan Algoritma Single Layer Perceptron,” PINTER J. Pendidik. Tek. Inform. dan Komput., vol. 3, no. 1, pp. 1–6, 2019, doi: 10.21009/pinter.3.1.1.

Y. Pangaribuan and M. Sagala, “Menerapkan Jaringan Saraf Tiruan untuk Mengenali Pola Huruf Menggunakan Metode Perceptron,” J. Tek. Inform. UNIKA St. Thomas, vol. 2, no. 479, pp. 53–59, 2017, [Online]. Available: http://103.76.21.184/index.php/JTIUST/article/view/191

Y. U. Budiman, “Identifikasi Kata Benda dan Bukan Kata Benda Menggunakan,” vol. 1, no. 5, pp. 759–768, 2022.

M. Y. Pratama and R. Chrisnanto, Y H Ilyas, “Prediksi Penjualan dan Bahan Baku Produksi Menggunakan Single Perceptron di PT. Gorila Indonesia Muda,” Pros. Semin. Rekayasa Teknol. Inf., no. November, pp. 219–221, 2018.

Shedriko, “Single Layer Perceptron Dengan Backpropagation Dalam Memprediksi Kelulusan Mahasiswa Pada Mata Kuliah PTI Di Universitas XYZ,” Semin. Nas. Ris. dan Inov. Teknol. (SEMNAS RISTEK), pp. 821–826, 2021.

U. L. Negara, “SPLN 59 : 1985 Keandalan Sistem Distribusi,” 1985.

DOI: https://doi.org/10.1593/jreec.v3i2.5091