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All Journal JURNAL ILMIAH INFORMATIKA INTECOMS: Journal of Information Technology and Computer Science
Muhammad Diki Hendriyanto
Universitas Singaperbangsa Karawang
Computer Science & IT

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Analisis Sentimen Ulasan Aplikasi Mola Pada Google Play Store Menggunakan Algoritma Support Vector Machine Muhammad Diki Hendriyanto; Azhari Ali Ridha; Ultach Enri
INTECOMS: Journal of Information Technology and Computer Science Vol 5 No 1 (2022): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v5i1.3708

Abstract

MOLA is one of the video streaming platform applications on the google play store. The mola application has been downloaded 5 million times but only has a 3.2 rating. On the Google Play Store app rating is followed by user reviews of the app. There are quite a lot of reviews that are unstructured and contain opinions from users about their satisfaction with the application so that it is often taken into consideration by potential users to choose the application used. Based on this, sentiment analysis was carried out using the Support Vector Machine algorithm to find out how the sentiments of users towards the MOLA application on the google play store were carried out. This study uses the Knowledge Discovery in Database (KDD) method. The data used is a review of the MOLA application with as many 520 data consisting of 312 positive reviews and 208 negative reviews. The best results are obtained in scenario 1 (90:10) using the RBF (Radial Basis Function) kernel which produces 92.31% accuracy, 96.3% precision, 89.66% recall, and 92.86% f1-score. Keywords: Sentiment Analysis, Support Vector Machine, MOLA
PENERAPAN ALGORITMA K-NEAREST NEIGHBOR DALAM KLASIFIKASI JUDUL BERITA HOAX Muhammad Diki Hendriyanto; Betha Nurina Sari
JURNAL ILMIAH INFORMATIKA Vol 10 No 02 (2022): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v10i02.5477

Abstract

With the rapid development of information technology, especially in Indonesia, information is more easily obtained through online media. Therefore, the dissemination of information in online media becomes uncontrollable and a lot of information is not in accordance with the facts or can be said to be a hoax. Readers should be more careful when reading news headlines to avoid hoaxes. The purpose of this research is to find out how to apply the K-Nearest Neighbor (KNN) algorithm in classifying news including hoaxes or not hoaxes. In the process, the classification of hoaxes or non-hoaxes uses the KDD method in text mining and goes through several stages, namely preprocessing, word weighting with TF-IDF and classification using the KNN algorithm. There are 3 scenarios in the data split process, namely 90:10, 80:20, and 70:30. Evaluation is done by using a confusion matrix. The results of this study obtained the highest accuracy of 93.33% with a k value of 3 in the 90:10 scenario. So, the K-Nearest Neighbor algorithm is suitable for classifying hoax news titles.
Co-Authors Azhari Ali Ridha Betha Nurina Sari Ultach Enri