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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Sistemasi: Jurnal Sistem Informasi Jiko (Jurnal Informatika dan komputer) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Dinasti International Journal of Education Management and Social Science Jurnal Locus Penelitian dan Pengabdian Eduvest - Journal of Universal Studies The Indonesian Journal of Computer Science TONJI
Santoso, Aris Budi
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Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Social Sciences

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Improving Sentiment Analysis and Topic Extraction in Indonesian Travel App Reviews Through BERT Fine-Tuning Irmawan, Oky Ade; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.77028

Abstract

Abstract The increasing use of the internet in Indonesia has an influence on the presence of Online Travel Agents (OTA). Through the OTA application, users can book transportation and accommodation tickets more easily and quickly. The increasingly rigorous competition is causing companies like PT XYZ to be able to provide solutions to the needs and problems of their customers in the field of online ticket booking. Many customers submit reviews of the use of the PT XYZ application through Playstore and Appstore, and it needs a technique to group thousands of reviews and detect the topics discussed by customers automatically. In this study, we classified reviews from Android and iOS applications using BERT that had been adjusted through fine-tuning with IndoBERT, as well as modeling topics using LDA to evaluate the coherence score of each sentiment. The result of the comparison of hyperparameter models for the most optimal classification is epoch 4 with a learning rate of 5e-5. The accuracy obtained is 0.91, with an f1-score of 0.74. In addition, testing was carried out to compare BERT with other traditional machine learning. The best performing algorithm was Logistic Regression using TF-IDF word embeddings, achieving an accuracy of 0.890 and an F1-score of 0.865. Therefore, it can be inferred that the accuracy achieved by the fine-tuned classification model of IndoBert is sufficiently high for application in the PT XYZ review classification. Using a coherence score, we found 29 positive topics, 6 neutral topics, and 3 negative topics that were considered the most optimal. This finding can be used as evaluation material for PT XYZ to provide the best service to customers.
Measuring mobile banking service quality using Topic Modeling and Term Ranking: A case study of an Indonesian digital bank Anggraini, Veny; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4517

Abstract

The rapid expansion of digital transactions in Indonesia is driving the transformation of both traditional and digital banks. Since digital banks operate without physical branches, all banking services are via mobile banking apps. This study examines mobile banking service quality using text mining techniques like topic modeling and term ranking to analyze 11,815 user reviews from app stores and assess customer satisfaction through ratings. The research involves extracting and preprocessing reviews, identifying key topics, and linking them to satisfaction levels. Seven service dimensions were found: customers were satisfied with Enjoyment, Debit Card Delivery, and Feature-Free Transactions but dissatisfied with Accessibility, Data Privacy, Loan Services, and Touchless Customer Support. Debit Card Delivery and Feature-Free Transactions were highlighted as significant factors in Indonesia's digital banking market. With limitations in analyzing user reviews in Bahasa Indonesia, the findings are specific to the Indonesian digital banking context and may not be applicable elsewhere.
Sentiment Analysis and Topic Modeling of Public Opinion on Indonesia New Capital City Development Policies Angelo, Michael David; Harwenda, Reyhan Widyatna; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Eduvest - Journal of Universal Studies Vol. 5 No. 5 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i5.51234

Abstract

This study investigates public sentiment dynamics and dominant thematic concerns related to Indonesia’s new capital city development project (Ibu Kota Nusantara–IKN), particularly in the context of the political leadership transition from President Joko Widodo to President-elect Prabowo Subianto. Utilizing a dataset comprising 9,451 tweets collected from 2017 to 2025, sentiment analysis and topic modeling were applied to classify sentiment polarity and identify prevailing public discourse themes. Various traditional machine learning models—including Naïve Bayes, Support Vector Machine (SVM), AdaBoost, XGBoost, and LightGBM—were systematically compared with transformer-based deep learning models, specifically IndoBERT, to determine their effectiveness in sentiment classification. Results demonstrated that the IndoBERT model outperformed all traditional classifiers, achieving the highest accuracy, precision, recall, and F1 score, highlighting its superior capability in capturing nuanced linguistic patterns within informal social media texts. Independent samples t-tests revealed statistically significant sentiment shifts between the two political phases, emphasizing the impact of leadership transitions on public sentiment. Topic modeling further identified critical themes such as environmental sustainability, socio-economic implications, transparency, governance, and infrastructure development as central concerns driving public discussions. These findings provide actionable insights for policymakers and stakeholders, underscoring the importance of strategic communication and responsiveness to public sentiment in large-scale government initiatives.
The Role of Social Media in Shaping Social Movements: A Case Study of #Daruratreformasi In Indonesia Using Text Mining and Network Analytics Dekatama, Alifdaffa Nurfahmi; Prayogo, Devin; Budi, Indra; Putra, Prabu Kresna; Santoso, Aris Budi
Eduvest - Journal of Universal Studies Vol. 5 No. 7 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i7.51376

Abstract

The social movement #DaruratReformasi emerging in Indonesia since July 2024 has attracted widespread attention both nationally and internationally. This study aims to analyze the communication dynamics and interaction patterns within the social media network of the movement using text mining and network analytics approaches. Topic modeling identifies the dominant key issues in public discourse, while social network analysis reveals the main actors and influencers involved in information dissemination and public opinion formation. A modularity approach is employed to detect naturally formed discussion communities within the network, and temporal analysis illustrates the phases of the movement’s development from initiation to its peak in November 2024. The results indicate that social media serves as a strategic platform for social mobilization and political advocacy, with key actors distributed across interconnected communities. Additionally, the involvement of government institutions as central actors highlights the two-way communication dynamics within the digital public sphere. These findings underscore the urgency of understanding social network structures in the context of modern digital social movements and provide implications for public communication management and mass mobilization strategies in the digital era.
Sentiment Analysis on Government Public Policies: A Systematic Literature Review Harwenda, Reyhan Widyatna; Angelo, Michael David; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 5 (2025): Dinasti International Journal of Education Management and Social Science (June
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i5.4699

Abstract

In the digital era, public discourse on government policies has shifted significantly to online platforms. This presents valuable opportunities for governments to assess real-time public sentiment. However, prior studies on sentiment analysis in public policy remain fragmented, often lacking methodological consistency and domain-wide synthesis. This study conducts a Systematic Literature Review (SLR) to consolidate insights on the techniques, datasets, and trends involved in sentiment analysis applied to government development policies. The review identifies SVM, BERT, and Naive Bayes as the most frequently used and effective methods, with SVM excelling in structured data and simpler tasks, and BERT demonstrating superior performance in handling nuanced textual data. Lexicon based tools such as VADER are also used for quick sentiment classification. Social media platforms, particularly Twitter, emerge as the dominant data sources due to their high volume and real-time nature, while evaluation metrics such as precision, recall, F1-score, and confusion matrix are commonly applied to assess model performance. The findings also reveal evolving research interests from early focus on health policies to recent interest in infrastructure, environmental, and technology-related policies. Public sentiment across these areas varies, with health and environmental policies often eliciting negative responses, while technology policies show more neutral to positive sentiment. By synthesizing methods, datasets, evaluation strategies, and policy domains, this review provides a structured foundation to future research and supports policymakers in designing strategies.
Uncovering the Reasons Behind Abstain Voters' Stances in the 2024 Indonesian Presidential Election: Social Media X Study Cases Putri, Irzanes; Insani, Faiz Nur Fitrah; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4126

Abstract

The Indonesian Government expects the participation of all Indonesian people in holding General Elections. However, according to the 2019 Political Statistics by BPS, there were 34.75 million people who did not exercise their right to vote or were abstain voters (golput) in the 2019 Election. This research aims to analyze individual attitudes towards abstaining voters using stance analysis and topic modelling. From 9,045 collected tweets, subsequent manual annotation revealed 2,566 pro stances, 5,264 neutral stances, and 1,215 contra stances. The classification models utilized are Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Gradient Boosting. The classification outcomes will be analyzed by comparing the accuracy, precision, recall, and F1-score results based on their algorithms and n-grams. The results obtained from the stance analysis show that Random Forest achieved the highest accuracy and precision scores, with values of 84% and 83%, respectively. The discussion topic among those supporting golput due to low trust in the presidential and vice-presidential candidates. Other topics mentioned public feels dissatisfied with the pairs of candidates.
User Review Analysis of the BNI Wondr Mobile Banking Application: Systematic Literature Review Mubina, Basma Fathan; Halim, Dicky; Budi, Indra; Ramadiah, Amanah; Putra, Prabu Kresna; santoso, Aris budi
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 8 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i8.4541

Abstract

In the digital age, mobile banking has become essential for facilitating efficient financial transactions, with the Wondr mobile banking application from Bank Negara Indonesia (BNI) emerging as a significant innovation in this sector. Designed to provide a secure and user-friendly experience, Wondr aims to meet the diverse needs of its customers. However, to enhance its service and ensure user satisfaction, BNI must actively engage with customer feedback. This study leverages user reviews from platforms like Google Play Store to gain insights into the strengths and weaknesses of the Wondr application. Employing text analysis techniques, we utilise topic modeling through Latent Dirichlet Allocation (LDA) to extract relevant themes from these reviews to identify key areas for improvement and generate targeted recommendations. The findings of this research are intended to inform the ongoing development of the Wondr application, ultimately enhancing user experience and reinforcing BNI’s position within the digital banking landscape.
Sentiment Analysis of Air Pollution on Social Media: Systematic Literature Review Permana, Yandi Dwi; Gofur, Abdul; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.3679

Abstract

The need for a healthy and pollution-free environment is the basis of the problem that this study examines. Social media has become an integral aspect of daily existence for the majority engaged in the digital realm. It enables individuals from various backgrounds to utilize these platforms to stay updated on the latest information, such as the current state of pollution in Jakarta. This research explores the attitudes of social media users regarding their perspectives on air pollution in Jakarta. The method used includes conducting a Systematic Literature Review of academic papers released from 2020 to 2023. The results of this research can unveil the types of social media platforms utilized, the quantity of datasets, the procedures for data collection, data preprocessing techniques, and the commonly employed methods in sentiment analysis studies concerning the subject of air pollution.
TEORI DAN REALITAS ANTARA PENDIDIKAN SMK DAN SEKOLAH VOKASI BAGI PENINGKATAN DAYA SAING GENERASI MUDA DALAM MENDAPATKAN KESEMPATAN KERJA andika, andika; Santoso, Aris Budi; Kesuma, Husni Wira; Tobing, Rahel Nathalia Br
The Officium Nobile Journal Vol. 1 No. 2 (2024): December 2024
Publisher : The Officium Nobile Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70656/tonji.v1i2.259

Abstract

Pendidikan merupakan sebuah proses atau rangkaian kegiatan yang terencana, tersusun dan sistematis untuk mengembangkan kecerdasan dan karakter generasi penerus bangsa. Dengan adanya pendidikan tersebut, maka perlu generasi yang siap menghadapi perkembangan masa depan yang bayak dengan perubahan dan kompleksitas, masyarakat dapat memperoleh pengetahuan dan keterampilan yang dibutuhkan untuk menghadapi berbagai kebutuhan dan tantangan dalam kehidupan. Apalagi di masa yang cepat seperti di dalam penelitian ini, metode yang digunakan adalah metode kualitatif dengan pendekatan deskriptif dan studi pustaka. Metode Kualitatif digunakan untuk dapat memberikan informasi yang komprehensif, orisinal, dan ilmiah tentang subjek studi. Pendekatan deskriptif akan menekankan pada tujuan untuk dapat menguraikan dan menggambarkan fakta dengan mendeskripsi secara detail mengenai teori dan realitas mengenai Pendidikan SMK dan sekolah vokasi dalam menghadapi dunia kerja. Pendidikan vokasi atau disebut juga disebut pendidikan kejuruan, ialah jenis pendidikan yang berfokus pada menciptakan siswa yang siap untuk bekerja. Program ini berfokus pada pembangunan keterampilan kerja yang sesuai dengan kemajuan teknologi dan ilmu pengetahuan pekerjaan. Untuk mewujudkan masyarakat yang sejahtera dan kompetitif, pendidikan vokasi atau kejuruan memerlukan rumusan ketentuan pendidikan yang terjadi saat dengan keperluan yang akan datang. Tujuan utama dari pendidikan vokasi atau kejuruan adalah untuk meningkatkan relevansi pendidikan kejuruan terhadap kebutuhan dunia kerja. Pendidikan SMK dan sekolah Vokasi merupakan sarana pendidikan bagi generasi muda untuk memainkan peran dalam meningkatkan kemampuan kejuruan yang akan menciptakan generasi muda dan SDM yang berkualitas yang siap bekerja, adanya Revolusi Industri 4.0 yang saat ini tengah terjadi merupakan peluang serta tantangan yang harus dihadapi oleh sekolah Vokasi dan kejuruan, Lulusan sekolah tersebut tidak hanya harus mampu menguasai teori dan skil dalam dunia kerja namun juga perlu mempunyai kemampuan mandiri mengolah big-data.
Exploring the influence of soft information from economic news on exchange rate and gold price movements Prastowo, Rahardito Dio; Budi, Indra; Ramadiah, Amanah; Santoso, Aris Budi; Putra, Prabu Kresna
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i6.pp5231-5239

Abstract

Information on business conditions is an important concern for market players and regulators. Hard information relates to easily validated characteristics such as production levels and employment conditions. In contrast, soft information such as consumer and public perceptions—is subjective and difficult to verify. Although previous studies on hard and soft information mainly focus on microeconomics and banking, current developments in big data and machine learning enable broader applications in financial market analysis. This study combined VADER sentiment analysis and support vector machine (SVM) classification (accuracy=85%) to analyze economic news, followed by Granger causality and multiple linear regression to examine causal effects and predictive relationships. The findings reveal that negative news sentiment and the Indonesian Rupiah (IDR) exchange rate influence each other, while positive sentiment has no causal impact on the exchange rate. Both negative and positive sentiments affect gold prices, whereas gold price movements do not influence sentiment. Regression analysis shows that negative sentiment has a stronger effect in decreasing the IDR exchange rate than positive sentiment, with the model explaining approximately 20% of the variance. Integrating sentiment and exchange rate data enhances the predictive model for gold price forecasting and highlights the asymmetric roles of positive and negative news in financial dynamics.
Co-Authors Abdul Gofur Ananda, Dimas Andika Andika Angelo, Michael David Anggraini, Veny Budi, Indra Dekatama, Alifdaffa Nurfahmi Halim, Dicky Harwenda, Reyhan Widyatna Insani, Faiz Nur Fitrah Irmawan, Oky Ade Kesuma, Husni Wira Mubina, Basma Fathan Permana, Yandi Dwi Prabu Kresna Putra, Prabu Kresna Prastowo, Rahardito Dio Prayogo, Devin Putri, Irzanes Qureshi, Ali Adil Ramadiah, Amanah Tobing, Rahel Nathalia Br