SENTIMENT ANALYSIS ON ROUTE CHANGES OF JABODETABEK COMMUTER RAILROAD USING SUPPORT VECTOR MACHINE (SVM) ALGORITHM
Abstract
KRL Commuter Jabodetabek is one of the modes of public transportation that is an alternative choice for residents of the capital city of Jakarta and its surroundings to reduce congestion in the Jabodetabek area. However, since there was a change in the Jabodetabek Commuter KRL route on May 28, 2022, there have been pro and con opinions from among the public users of the Jabodetabek Commuter KRL public transportation mode. The data used in this research is tweet data from Twitter with the keyword 'krl route changes' with a time span between May 26, 2022 and February 28, 2023. This research uses the Knowledge Discovery in Database (KDD) method. The purpose of this study is to determine public sentiment towards changes in the Jabodetabek Commuter KRL route and to determine the performance evaluation value of Support Vector Machine (SVM) in analyzing public sentiment. This research compares 3 SVM kernels namely RBF kernel, Linear Kernel, and Polynomial Kernel with 3 dataset sharing scenarios (90:10, 80:20, and 70:30) and also compares the effect of using the Synthetic Minority Oversampling Technique (SMOTE) algorithm to handle data imbalance. This research resulted in positive labels totaling 17, neutral labels totaling 184, and negative labels totaling 140. And the best accuracy value was obtained by RBF kernel and Polynomial kernel in scenario 2 (80:20) with the same value of 88.2%.
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