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All Journal KONSELI: Jurnal Bimbingan dan Konseling (E-Journal) JUITA : Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan BAREKENG: Jurnal Ilmu Matematika dan Terapan Unisda Journal of Mathematics and Computer Science (UJMC) JRB-Jurnal Riset Bisnis Jurnal Penamas Adi Buana Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Jurnal Statistika dan Komputasi (STATKOM) UNP Journal of Statistics and Data Science Journal of Community Service and Society Empowerment
Hani Brilianti Rochmanto
Universitas PGRI Adi Buana Surabaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Klasifikasi Opini Publik terhadap Kenaikan PPN 12% di Platform X menggunakan Multinomial Naïve Bayes Hani Brilianti Rochmanto; Harun Al Azies
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 10 No 2 (2024): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Sciences and Technology Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v10i2.9120

Abstract

The increase in Value-Added Tax to 12% in 2025 has sparked diverse public opinions on the social media platform X (Twitter). This study aims to classify public sentiment toward the policy using Multinomial Naïve Bayes with a Term Frequency-Inverse Document Frequency (TF-IDF) approach. Multinomial Naïve Bayes is a probabilistic classification algorithm that assumes feature independence. Data were collected through web crawling using the keyword "ppn 12%" and underwent pre-processing, including text normalization, stopword removal, and stemming. To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. The best-performing model was obtained by tuning the alpha hyperparameter to 0.01, achieving an average accuracy of 83.37%, precision of 83.32%, recall of 83.38%, and an F1-score of 82.99% using 10-fold cross-validation. The findings indicate that Multinomial Naïve Bayes, combined with SMOTE and hyperparameter tuning, effectively classifies public sentiment and provides insights into public responses regarding the Value-Added Tax policy.
Geographically Weighted Machine Learning Model for Untangling Spatial Heterogeneity of Dengue Incidence in West Java Auralia Putri Astutiningsih; Gangga Anuraga; Hani Brilianti Rochmanto; Muhammad Athoillah
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 2, July 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v14i2.30181

Abstract

Dengue hemorrhagic fever continues to pose a significant public health challenge, particularly in West Java Province, Indonesia, which consistently reports the highest incidence rates in the country. This study examined the factors influencing dengue fever incidence using Random Forest Regression (RFR) and Geographically Weighted Random Forest (GWRF) methodologies. Utilizing secondary data from 2022 to 2024 across 27 districts/cities, the data from 2022 to 2023 served as training data, while the 2024 data were used for testing. The findings revealed that the optimal RFR model, with ntree = 1000 and mtry = 1, achieved an RMSE of 1796.409, a MAPE of 0.482, and an  of 0.685. Conversely, the GWRF model, which employed an adaptive kernel and an optimal bandwidth of 45 nearest neighbors, exhibited superior performance, with an RMSE of 1,756.713, MAPE of 0.466, and  of 0.700. This enhancement in the model performance suggests that spatial weighting improves the model's capacity to capture spatial heterogeneity. In addition, variations in local feature importance indicate spatial non-stationarity across regions. These results imply that the GWRF is more effective in modeling dengue fever outbreaks and can inform the development of region-specific public health interventions.
Monitoring The Quality of Getcontact Reviews Using Integration Sentiment Analysis and Statistical Process Control Maria Kristina Lusia Geong; Hani Brilianti Rochmanto; Fenny Fitriani; Gangga Anuraga
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/504

Abstract

The protection of digital communications becomes important as cybercrime rises. Getcontact, a digital communication app that offers services ranging from caller identification to spam detection, has garnered a range of opinions on Google Play Store, which serve as a basis for evaluating service quality. This study aims to monitor Getcontact’s service quality through integration of sentiment analysis and control charts based on reviews. The research data consists of reviews obtained through web scraping during the period from January 1, 2023, to September 30, 2025. The data was classified using SVM and then analyzed using p-control charts and Laney p-control charts. The results show that the negative category dominates the reviews data. SVM achieved excellent performance with accuracy 98%, precision 98%, specificity 98%, sensitivity 97%, and F1-score 97%. Control charts indicate that the process is not yet fully under control, with the Laney p chart being more representative. Pareto chart shows that complaints are dominated by issues in number identification accuracy. It is concluded that Getcontact’s service quality still needs improvement. Integration of sentiment analysis and control charts is effective for continuous quality monitoring, with the Laney p chart being more suitable.
Co-Authors Agustin, Risca Ahsan, Muhammad Alfisyahrina Hapsery Auralia Putri Astutiningsih Devi Putri Isnarwaty Dwi Cahya Julia Kartikasari Elvira Mustikawati Putri Hermanto Fawwaz Atha Rohmatullah Fitriani, Fenny Gangga Anuraga Harun Al Azies Idrus Syahzaqi Isnarwaty, Devi Putri Izequela De Jesus Madeira Maria Kristina Lusia Geong Muhammad Athoillah, Muhammad Niza Nurmalasari Pravesti, Cindy Asli Pretesya Septiliani Syukur Priyanto Priyanto Ratu Bunga Prawesti Arie Salim Rohmatullah, Fawwaz Atha Rokhmania, Nina Anggraini Junet Wae, Maria Yohana Vianey Wardani, Galuh Kusuma