SENTIMEN ANALISIS TERHADAP IMPLEMENTASI PROGRAM KAMPUS MERDEKA DENGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) DAN NAÏVE BAYES

Handira Leo Putra Sinaga Sinaga; Winsy Christo Deilan Weku; Charles Efraim Mongi

doi:10.35799/ijids.v1i1.50031

Authors

Handira Leo Putra Sinaga Sinaga Universitas Sam Ratulangi
Winsy Christo Deilan Weku Universitas Sam Ratulangi
Charles Efraim Mongi Universitas Sam Ratulangi

DOI:

https://doi.org/10.35799/ijids.v1i1.50031

Keywords:

Analisis sentimen, svm , naive bayes, mbkm

Abstract

The Kampus Merdeka Program is a government program to improve the quality of higher education in Indonesia. For its implementation, this program has raised various responses and feelings from the public, including from students and alumni of universities. Therefore, it is important to analyze these feelings and opinions to understand how the implementation of this program is received by the public using sentiment analysis. Data will be taken from Twitter tweets using #kampusmerdeka. In this study, sentiment analysis will be carried out on Twitter tweet text data containing responses related to the implementation of the Kampus Merdeka program. The Support Vector Machine (SVM) and Naive Bayes algorithms will be used as methods to conduct this sentiment analysis. By using an 80:20 data division for training data and test data. The accuracy for SVM was 98%, and Naive Bayes was 85%. Both showed good ability to predict overall sentiment in the dataset used.

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