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All Journal JURNAL ELEKTRO
Egipta Pranadjaya
Program Studi Teknik Mesin, Fakultas Teknik, Universitas Katolik Indonesia Atma Jaya, Jakarta 12930, Indonesia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Perbandingan Algoritma Machine Learning menggunakan Orange Data Mining untuk Klasifikasi Jenis Kendaraan pada Sistem Tilang Digital Egipta Pranadjaya; Evan Sudira Pangestu; Catherine Olivia Sereati; Sandra Octaviani; Marten Darmawan
Jurnal Elektro Vol 17 No 1 (2024): Jurnal Elektro: April 2024
Publisher : Program Studi Teknik Elektro, Fakultas Biosains, Teknologi, dan Inovasi, Universitas Katolik Indonesia Atma Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v17i1.5429

Abstract

This paper discusses the application of the Orange Data Mining application to compare several machine learning algorithms for classifying vehicle types in digital ticket systems. This research compares and analyzes the logistic regression algorithm, Support Vector Machine (SVM) and Neural Network (NN) to solve vehicle classification problems in digital traffic tickets. The research results show that in the training process and based on the dataset used, the algorithms that have the highest level of accuracy are Logistic Regression, Neural Network and Support Vector Machine. Meanwhile, during the testing process, all algorithms in the model were able to carry out classification with 100% accuracy
Co-Authors Catherine Olivia Sereati Evan Sudira Pangestu Marten Darmawan Sandra Octaviani