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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Teknologi dan Manajemen Informatika Prosiding SNATIKA Vol 01 (2011) Record and Library Journal Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Journal of Research and Technology Indonesian Journal of Artificial Intelligence and Data Mining JKTP: Jurnal Kajian Teknologi Pendidikan Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika JUSIM (Jurnal Sistem Informasi Musirawas) SPIRIT Building of Informatics, Technology and Science Journal of Information Systems and Informatics Buletin Ilmiah Sarjana Teknik Elektro Zonasi: Jurnal Sistem Informasi JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Advanced in Information and Industrial Technology (JAIIT) SKANIKA: Sistem Komputer dan Teknik Informatika Teknika KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Data Science, Engineering, and Analytics (IJDASEA) Decode: Jurnal Pendidikan Teknologi Informasi JITSI : Jurnal Ilmiah Teknologi Sistem Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Informatics, Electrical and Electronics Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science The Indonesian Journal of Computer Science INOVTEK Polbeng - Seri Informatika JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Anik Vega Vitianingsih
UNITOMO, Surabaya
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Sentiment Analysis E-Wallet Application Services Using the Support Vector Machine and Long Short-Term Memory Methods Arya Darmansyah, Mochammad Dzikri; Vitianingsih, Anik Vega; Lidya Maukar, Anastasia; Yuliani, SY.; Fitri Ana Wati, Seftin
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/apedaz75

Abstract

The rapid growth of financial technology services in Indonesia has increased the volume of user reviews, yet their utilization for sentiment-based insights remains limited in the e-wallet sector. This study compares the effectiveness of Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) in classifying the sentiment of 3,185 DANA e-wallet reviews collected from the Google Play Store and Instagram. The research process includes text preprocessing, lexicon-based labeling, and feature extraction using TF-IDF for SVM and word embeddings for LSTM. Model evaluation is conducted using a confusion matrix based on accuracy, precision, and recall, without inferential statistical testing. The results show that LSTM outperforms SVM, achieving an accuracy of 86.66%, a recall of 81.86%, and a precision of 82.09%, while the best SVM variant with an RBF kernel attains an accuracy of 84.93%. This study contributes by identifying key service-related factors influencing user satisfaction and dissatisfaction and by providing practical, sentiment-based insights to support service quality improvement. The novelty lies in the multi-platform analysis of Indonesian e-wallet reviews and the direct comparison of classical machine learning and deep learning approaches without statistical hypothesis testing. These findings confirm the effectiveness of deep learning for sentiment analysis of unstructured Indonesian text.
Sentiment Analysis of the Matahari Application to Provide User Experience Insights using Support Vector Machine Rizal, Moch Arif Samsul; Vitianingsih, Anik Vega; Zangana, Hewa Majeed; Maukar, Anastasia Lidya; Marisa, Fitri
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8811

Abstract

The expansion of Indonesia's digital commerce ecosystem has pushed retail companies to strengthen the quality of their online services to remain competitive. Matahari, one of the country's leading retail brands, launched its mobile app as a platform for shopping, promotions, and customer interaction. However, user feedback on the Google Play Store indicates persistent problems with system responsiveness, ease of use, and the consistency of promotional information. This study examines sentiment patterns in 2,500 user reviews and classifies them using a Support Vector Machine (SVM) based model that incorporates three kernel types: Linear, RBF, and Polynomial. Before modelling, the text corpus underwent several pre-processing steps—such as tokenization, stopword filtering, and stemming represented numerically using TF-IDF weighting. Among all tested configurations, the Linear kernel produced the strongest results, achieving an accuracy rate of 88%. Despite a moderate distribution across categories (1030 negative, 886 neutral, and 584 positive), the model achieved consistent performance across all classes. Evaluation using Precision, Recall, and F1-Score confirmed the validity of the 88% accuracy without the need for additional sampling techniques. From a scholarly standpoint, this research adds insight into sentiment analysis for retail applications within the Indonesian context by applying a machine-learning approach. In practice, the outcomes highlight areas for improvement, particularly technical stability, the intuitiveness of user flows, and promotional clarity to support a better overall user experience.
Sentiment Analysis of User Reviews for the PLN Mobile Application Using Naïve Bayes and Long Short-Term Memory Ayomi, Jose Mario; Vitianingsih, Anik Vega; Kristyawan, Yudi; Maukar, Anastasia Lidya; Widiartin, Tjatursari
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1342

Abstract

This study explores large-scale sentiment analysis of user reviews for the PLN Mobile application to better understand public perception and provide quantitative insights for improving digital electricity services in Indonesia. Addressing the lack of benchmarks for Indonesian public-service apps—where prior studies rely on smaller datasets and traditional machine learning—this research positions sentiment analysis as a tool for continuous user experience monitoring. A total of 50,000 Indonesian-language reviews from Google Play were collected and pre-processed using cleaning, case folding, tokenization, stopword removal, normalization, and stemming. Sentiments (positive, neutral, negative) were assigned using a domain-specific Indonesian sentiment lexicon, yielding approximately 40% positive, 35% neutral, and 25% negative labels. Two models were applied: Multinomial Naïve Bayes using TF-IDF features and a Long Short-Term Memory (LSTM) model with 100-dimensional word embeddings and a 128-unit LSTM layer. Naïve Bayes achieved 70.89% accuracy (F1-score: 0.6964), while LSTM outperformed it with 98.02% accuracy (F1-score: 0.9800). These results highlight the superiority of deep learning in sentiment monitoring and offer a scalable framework to help PLN and policymakers enhance digital public service delivery.
Co-Authors Abdul Rezha Efrat Najaf Achmad Choiron Ade Susianti, Febrina Adharani, Salza Kartika Agustinus Noertjahyana Ahmad, Sharifah Sakinah Syed Al-Karaki, Jamal N. Ana Wati, Seftin Fitri Anastasia Lidya Maukar ANGGI FIRMANSYAH Arumsari, Andini Dwi Arya Darmansyah, Mochammad Dzikri Ayomi, Jose Mario Aziiza, Arizia Aulia Azzahra, Morra Fatya Gisna Nourielda Badrussalam, Nanda Budi Suprio, Yoyon Arie Cahyono, Cahyono Kaelan Damayanti, Erika DWI CAHYONO Dwi Indrawan, Dwi Dwi Prasetyo, Septian Fardhan Maulana, Abelardi Fauzan, Rizky Fauzi, Ariq Ammar Fawaidul Badri Febrian Rusdi, Jack Firmansyah, Deden Fitri Ana Wati, Seftin Fitri, Anindo Saka Ghibran Jhi S, Moch Hamidan, Rusdi Hengki Suhartoyo, Hengki Hermansyah, David Hikmawati, Nina Kurnia Jazaudhi’fi, Ahmad Khusnaini, Geovandi Gamma Krismantoro, Putu Gede Ari KRISTIAWAN KRISTIAWAN Li, Shuai Lidya Maukar, Anastasia MARIFANI FITRI ARISA Maukar, Anastasia L Maukar, Anastasya Lidya Maulidiana, Putri Dwi Rahayu Miftakhul Wijayanti Akhmad, Miftakhul Wijayanti Minggow, Lingua Franca Septha Mudinillah, Adam Mustafa, Zulfikar Amirul Muzaki, Mochammad Rizki Nabil, Muh Niken Titi Pratitis Oktafamero, Yomara Omar, Marwan Ongko, Bagus Kustiono Pamudi Pamudi, Pamudi Pangestu, Resza Adistya Pradana, Dwifa Yuda Pramisela, Intan Yosa Pramudita, Atanasia Pramudita, Krisna Eka Pujiono, Halim Puspitarini, Erri Wahyu Putra Selian, Rasyid Ihsan Putri, Jessica Ananda Putri, Natasya Kurnia Rahmansyah, Ragada Ramadhan, Prayudi Wahyu Ramadhani, Illham Ratna Nur Tiara Shanty, Ratna Nur Tiara Rijal, Khaidar Ahsanur Riza , M. Syaiful Rizal, Moch Arif Samsul Rusdi Hamidan Rusdi, Jack Febrian Salmanarrizqie, Ageng Sari, Dita Prawita Seftin Fitri Ana Wati Slamet . Slamet Kacung, Slamet Slamet Riyadi, Slamet Riyadi Slamet Winardi Sufianto, Dani Suyanto Suyanto Suyanto Tiara Shanty, Ratna Nur Titus Kristanto Tjatursari Widiartin Tri Adhi Wijaya, Tri Adhi Umam, Azizul Voni Anggraeni Suwito Putri Warsito Sujatmiko, Achmad Wati , Seftin Fitri Ana Wati, Seftin Fiti Ana Wati, Seftin Fitri Ana Wijiono, Aditya Kusuma Wikaningrum, Anggit Wikanningrum , Anggit Yasin, Verdi Yoyon Arie Budi Suprio Yudi Kristyawan, Yudi Yuliani, SY. Yunior, Kevin Heryadi Zandroto, Yosefin Yuniati Zangana, Hewa Majeed