Fachreza, Rizqi
Universitas Stikubank Semarang

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Analisis Sentimen Masyarakat Terhadap Kinerja Trans Semarang Menggunakan Metode Random Forest Fachreza, Rizqi; Handoko, Widiyanto Tri
Progresif: Jurnal Ilmiah Komputer Vol 20, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v20i2.2093

Abstract

Opinion from the public on the performance of Trans Semarang transportation that has been widely discussed on social media X, resulting in many pros and cons. Sentiment analysis comes as a way to understand public opinion, examining the opinions and attitudes of individuals towards an object. individual attitudes towards an object. By using an algorithm methodology, namely Random Forest in classifying data to determine the accuracy of the data to determine the accuracy of the level of sentiment value of X users towards Trans Semarang performance. performance of Trans Semarang. This research uses a dataset taken with keyword "Trans Semarang". Random Forest algorithm is used to classify the data and then test it with various ratios, where the results of this algorithm can be used for the evaluation stage. The results of this algorithm can be used for the evaluation stage. This method produces a confusion matrix value with an accuracy of 81%, an average precission of 80%, average recall 80%, and average f-measure 80%.Keyword: Trans Semarang; Random Forest; Sentiment Analysis AbstrakOpini dari masyarakat terhadap kinerja transportasi Trans Semarang yang ramai dibicarakan di sosial media X, sehingga menimbulkan banyak pro dan kontra. Analisis sentimen hadir sebagai cara untuk memahami opini publik, meneliti pendapat dan sikap individu terhadap suatu objek. Dengan menggunakan metodologi algoritma yaitu Random Forest dalam pengklasifikasian data untuk mengetahui akurasi tingkat nilai sentimen pengguna X terhadap kinerja Trans Semarang. Penelitian ini menggunakan dataset yang diambil dengan kata kunci “Trans Semarang”. Algoritma Random Forest digunakan untuk mengklasifikasikan data dan kemudian mengujinya dengan berbagai rasio, dimana hasil algoritma ini dapat digunakan untuk tahap evaluasi. Metode ini menghasilkan nilai confusion matrix dengan accuracy 81%, precission rata-rata 80%, recall rata-rata 80%, dan f-measure rata-rata 80%.Kata kunci: Trans Semarang; Random Forest; Analisis Sentimen