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Ramadana, Rica
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Other

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PENERAPAN METODE BACKPROPAGATION DALAM PERAMALAN BEBAN TRAFO DAYA HARIAN GARDU INDUK PADA PTPLN (PERSERO) UP3 PEMATANG SIANTAR Ramadana, Rica; Suhendro, Dedi
INTEKNA Jurnal Informasi Teknik dan Niaga Vol 23 No 2 (2023): Jurnal INTEKNA, Volume 23, No. 2, Nov 2023
Publisher : P3M Politeknik Negeri Banjarmasin

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Abstract

PT PLN (Persero) merupakan salah satu penyedia jasa ketenagalistrikan yang selalu terhubung erat dengan masyarakat, karena merupakan produk yang selalu dibutuhkan masyarakat untuk kebutuhan sehari-hari. Perkembangan saat ini, terkait dengan pertumbuhan jumlah penduduk, kemajuan teknologi dan informasi, mengharuskan PLN untuk meningkatkan jumlah kebutuhan energi. Oleh karena itu, diperlukan langkah-langkah strategis untuk memprediksi beban lebih trafo. Penelitian ini membahas prediksi beban transformator harian berdasarkan data yang tersedia pada laporan real-time UP2D di Sumatera Utara pada bulan Juni 2023. Algoritma yang digunakan untuk prediksi adalah jaringan syaraf tiruan membuat propagasi balik. Algoritma backpropagation ini menggunakan lima model arsitektur diantaranya 29-15-1, 29-30-1, 29-40-1, 29-50-1 dan 29-65-1. Diantara kelima model arsitektur yang digunakan, dipilih arsitektur terbaik yaitu 29-50-1 yang mempunyai akurasi sebesar 87.50%, MSE 0.000996722 dan MSE yang digunakan sebesar 0.002 - 0.29. Oleh karena itu, model arsitektur ini cukup efektif untuk beban transformator berdasarkan data beban penyulang.
Analisis Backpropagation Dalam Menentukan Jumlah Perusahaan Industri Besar Dan Sedang (IBS) Di Indonesia Pramesti, Adinda Frizy; Ramadana, Rica; Beauti, Intan; Febiola, Adinda; Windarto, Agus Perdana
Journal of Informatics Management and Information Technology Vol. 4 No. 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v4i4.414

Abstract

Companies are economic actors whose main function is to produce goods and services needed by the community. However, in 2020, the COVID-19 pandemic had an impact on various economic activities, causing many workers to lose their jobs and the unavailability of new jobs, which led to an increase in unemployment in Indonesia. Therefore, strategic steps are needed to prevent an increase in the number of unemployed. One of them is to forecast the number of IBS companies for the next few years. Implementing early prevention as a step to identify new job opportunities in the industry. The forecast data is the number of IBS companies (large and medium industrial companies) collected by BPS for the period 2015-2022. The algorithm used for prediction is a backpropagation artificial neural network. This algorithm is able to remember what existed before and make generalizations from it. This backpropagation algorithm uses five architectural models including 6-10-1, 6-20-1, 6-35-1, 6-45-1, and 6-60-1. Of the five architectural models used, the best architecture was chosen, namely 6-35-1 which has an accuracy of 88%, MSE of 0.003821515 and the error rate used is 0.001-0.07. So this architectural model is good enough to predict the number of IBS companies.
Co-Authors Agus Perdana Windarto Beauti, Intan Febiola, Adinda Pramesti, Adinda Frizy Suhendro, Dedi