Perbandingan Algoritma Machine Learning menggunakan Orange Data Mining untuk Klasifikasi Jenis Kendaraan pada Sistem Tilang Digital

Pranadjaya, Egipta
Pangestu, Evan Sudira
Octaviani, Sandra
Darmawan, Marten
Sereati, Catherine Olivia

JURNAL ELEKTRO
Vol 17 No 1 (2024): Jurnal Elektro: April 2024

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