Sentiment Analysis of the 2024 General Election Commission in Indonesia through Twitter using the Support Vector Machine (SVM) Algorithm - Maulana, Mhd.Rizki; Putri, Raissa Amanda (Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer, 2024)
Indonesia can be a country of justice based on Pancasila and the 1945 Constitution. Everything related to government has been regulated in the Law. Indonesia itself has gone through three phases of government since proclaiming Independence on August 17, 1945. These three phases, specifically, the old order, the new order, and the reformation, still have an impact today. This is different from the previous two phases, where all choices were centered on the government. In this study, the method used in classifying the 2024 general election commission is Support Vector Machine (SVM). The SVM method is one of the advantages that can be implemented relatively easily, because the process of determining the support vector can be formulated in the confusion matrix. Sentiment analysis and opinion mining are fields of study that analyze a person's opinion, a person's sentiment, a person's evaluation, but in its implementation there are many things that are considered by voters that this election is not in accordance with existing rules. Starting from the aroma of fraud voiced by netizens, the non-neutrality of law enforcers against one of the candidates for the presidential and vice presidential pairs, and the implementation that is not JURDIL or Honest and Fair. Everything is widely voiced through social media, one of which is twitter. It is known that of the 2084 data obtained from tweets about the KPU, 29.5% are positive sentiments and 70.5% are negative sentiments. The results of sentiment classification about KPU using the Support Vector Machine algorithm that matches the actual data amounted to 307 data out of a total of 418 test data The accuracy value of the sentiment classification about KPU using the Support Vector Machine (SVM) algorithm obtained is 73%.