Penerapan Framework Flask Pada Machine Learning Dalam Memprediksi Umur Transformer
Abstract
Based on data from the Ministry of Energy and Mineral Resources (ESDM) shows that there has been an increase in electricity consumption of 5.46% since the pandemic hit Indonesia in early 2020. Disruption to the supply of electricity to customers can have a hugely detrimental effect in various sectors. The transformer is a static device to distribute electrical energy to customers. So that we can conclude that this device plays a vital role in measuring stability. This study aims to implement the flask framework and Machine Learning in predicting the life of transformers. The dataset uses measurement results using temperature, current, and voltage sensors. The results of this study indicate a prediction accuracy of 70% when using Multilayer Perceptron Method.
Keywords: Flask, Machine Learning, Prediction.
ABSTRAK
Berdasarkan data Kementerian Energi dan Sumber Daya Mineral (ESDM) pada awal tahun 2020 menunjukkan adanya peningkatan konsumsi listrik sebesar 5,46%. Terganggunya pasokan listrik pada pelanggan dapat menimbulkan efek kerugian yang besar diberbagai sektor. Trafo merupakan sebuah perangkat statis yang berfungsi dalam menyalurkan energi listrik kepada pelanggan. Sehingga bisa dikatakan perangkat ini memegang peranan vital yang kondisinya harus dipastikan kestabilannya. Penelitian ini bertujuan untuk mengimplementasikan framework Flask dan Machine Learning dalam memprediksi umur dari trafo. Adapun dataset yang digunakan menggunakan dataset hasil pengukuran menggunakan sensor suhu, arus dan tegangan. Hasil dari penelitian ini menunjukkan keakurasian prediksi sebesar 70% pada saat menerapkan Machine Learning dengan menggunakan Multilayer Perceptron.
Kata Kunci: Flask, Machine Learning, Prediksi Trafo.
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