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All Journal Techno.Com: Jurnal Teknologi Informasi Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Jurnal Begawe Teknologi Informasi Journal of Information Technology and Cyber Security
Hamidi, Mohammad Zaenuddin
Informatics Engineering Dept., Faculty Of Engineering, University Of Mataram
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Journal : Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA )

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PENDEKATAN SENTIMEN BERBASIS ASPEK PADA ULASAN SIRKUIT MANDALIKA MENGGUNAKAN CNN DAN REPRESENTASI FASTTEXT Manuaba, Ida Bagus Ryand Wirayana; Dwiyansaputra, Ramaditia; Hamidi, Mohammad Zaenuddin
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 7 No 1 (2025): Maret 2025
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v7i1.460

Abstract

Reviews are texts that contain an assessment or comment on something and can be used to provide more in-depth information. This research aims to analyze community reviews of the Mandalika Circuit using the aspect-based sentiment analysis technique CNN method. The CNN model is trained using two types of word embedding, namely Keras and FastText, and supported by the Multilabel Stratified K-Fold Cross Validation method to ensure an even distribution of data on each label and produce a stable accuracy evaluation. The results show that CNN with FastText word embedding has a higher average accuracy than CNN with Keras word embedding for both aspect and sentiment classification tasks. However, the model had difficulty in classifying the positive class in the sentiment label, which was due to the smaller amount of review data with positive sentiment than neutral and negative. Therefore, for future research, it is recommended to use data augmentation techniques on the imbalanced classes to improve the accuracy of the model.
Co-Authors Akhyar, Halil Ario Yudo Husodo, Ario Yudo Daniel Oranova Siahaan Darmawan, Riski Diana Purwitasari Dwiyansaputra, Ramaditia Fitri Bimantoro I Gede Pasek Suta Wijaya I Wayan Agus Arimbawa Karimi, Muhammad Ihsan Manuaba, Ida Bagus Ryand Wirayana Maulana, Sutan Fajri Mitaremyana, I Nyoman Jovi Nugraha, Gibran Satya Putra, Ida Ayu Ravikan Varapanna Rassy, Regania Pasca Ratih Nur Esti Anggraini, Ratih Nur Esti Reza Fauzan Rizka Wakhidatus Sholikah Safitri, Winda Ayu Sri Endang Anjarwani Susi Rahayu