Credit Risk Management Prediction Using the Support Vector Machine (SVM) Algorithm

Abstract

Information sharing throughout the globe or universe has become a characteristic of social media. There has been a lot of research into the classification of sentiments. In this study, Twitter has been mined for unstructured Gofood Reviews data. It has been preprocessed to analyze the reviews' sentiment with polarity analysis, feature extraction with TF-IDF, and supervised learning with random forest. From June 1, 2022 to June 30, 2022, a total of 28763 tweets with the keyword "Gofood" were retrieved from Twitter. The data is processed by the Python programming language utilizing NLTK, Sastrawi for the Indonesian language, Textblob, TF-IDF, Random Forest Classification, and other algorithms. Twitter is a nearly limitless source for classifying text. This algorithm takes roughly five minutes to computer.