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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Valianda Farradillah Hakim
Universitas Nusa Mandiri
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Pengkategorian Komentar Instagram Terhadap Layanan Akademik dan Non-Akademik Universitas Terbuka Rhini Fatmasari; Alda Zevana Putri Widodo; Valianda Farradillah Hakim; Windu Gata; Dedi Dwi Saputra
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 1 (2023): JANUARY-MARCH 2023
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i1.669

Abstract

Instagram is one of the social media that has many users in Indonesia, where users are free to comment on whatever is going on, including being a form of online communication between campuses and their students. The number of topics and comments on an official Instagram account can be used as evaluation or learning material. The Open University is one of the campuses that has an official Instagram account with thousands of followers. In order to get an evaluation of academic and non-academic services, in this study a categorization analysis was carried out with 10,000 comment data taken from the official @univterbuka Instagram account. The data is categorized into 7 categories, then processed using 4 algorithms, namely SVM, Naïve Bayes, Random Forest and KNN. The highest accuracy in the category of teachers with the KNN method is 98.97% and the highest AUC is in the module category with the SVM method of 94.60%.
Sentimen Analisis Masyarakat Indonesia Terhadap Presiden Rusia Pada Komentar Media Berita Online Ihud Hafid; Windu Gata; Khairunisa Hilyati; Valianda Farradillah Hakim; Sri Rahayu
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 1 (2023): JANUARY-MARCH 2023
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i1.698

Abstract

Russia's invasion of Ukraine was criticized by various parties, including from Indonesia. The attitude shown by the Indonesian government is not the same as the response of the Indonesian people based on various comments on online news media pages. Comments by online news readers are used as an assessment of the Russian President who is involved in the conflict between Russia and Ukraine in the form of sentiment analysis. This study succeeded in obtaining data as many as 352 comments from one of the online news media, the data had previously gone through the cleansing stage to eliminate duplication. To get basic information on comments, Text mining and Text Pre-Processing become an important part of the process. The algorithm used in this research is the Naive Bayes (NB) and Support Vector Machine (SVM) classification algorithm which is optimized using Particle Swarm Optimization (PSO). The two algorithms were tested and gave the result that PSO-based SVM got the best accuracy, which was 79.90% and AUC 0.901.
Co-Authors Alda Zevana Putri Widodo Dedi Dwi Saputra Ihud Hafid Khairunisa Hilyati Rhini Fatmasari Sri Rahayu Windu Gata