Article Per Year (5 Year)
p-Index From 2021 - 2026
2.567
P-Index
This Author published in this journals
All Journal Natural Science: Journal of Science and Technology Jurnal Ecosolum Jurnal Nalar Pendidikan Medula Sistemasi: Jurnal Sistem Informasi Dinamika Ilmu JOURNAL OF APPLIED INFORMATICS AND COMPUTING AKURASI: Jurnal Riset Akuntansi dan Keuangan Jurnal Abdi Insani Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Pariwisata DINAMIKA ILMU: Jurnal Pendidikan International Journal of Economics (IJEC) Jurnal Agrosilvopasture-Tech Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications Akurasi JPM (Jurnal Pengabdian Masyarakat) Ruwa Jurai
Muhammad Yusran
Department of Ophthalmology, Faculty of Medicine, Universitas Lampung
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

Published : 23 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Evaluating Fasttext and Glove Embeddings for Sentiment Analysis of AI-Generated Ghibli-Style Images Sentana Putra, I Gusti Ngurah; Yusran, Muhammad; Sari, Jefita Resti; Suhaeni, Cici; Sartono, Bagus; Dito, Gerry Alfa
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10600

Abstract

The development of text-to-image generation technology based on artificial intelligence has triggered mixed public reactions, especially when applied to iconic visual styles such as Studio Ghibli. This research aims to evaluate public sentiment towards the phenomenon of Ghibli-style AI images by comparing two static word embedding methods, namely FastText and GloVe, on three classification algorithms: Logistic Regression, Random Forest, and Convolutional Neural Network (CNN). Data in the form of Indonesian tweets were collected from Twitter using hashtags such as #ghibli, #ghiblistyle, and #hayaomiyazaki during the period 25 March to 25 April 2025. Each tweet was manually labelled with positive or negative sentiment, then preprocessed and represented using pre-trained FastText and GloVe embeddings. Evaluation was conducted using accuracy, precision, recall, and F1-score metrics, both macro and weighted. Results showed that FastText consistently performed the best on most models, especially in terms of precision and overall accuracy, thanks to its ability to handle sub-word information and spelling variations in social media texts. The combination of CNN with FastText yielded the highest performance with a macro F1-score of 76.56% and accuracy of 84.69%. However, GloVe still showed competitive performance in recall on the Logistic Regression model, making it relevant for contexts that prioritise sentiment detection coverage. This study emphasizes the importance of selecting embeddings and models that are appropriate to the characteristics of the data and the purpose of the analysis in informal social media-based sentiment classification.
Household Clustering in West Java Based on Stunting Risk Factors Using K-Modes and K-Prototypes Algorithms Yusran, Muhammad; Nuradilla, Siti; Putri, Mega Ramatika; Fitrianto, Anwar; Yudhianto, Rachmat Bintang
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11508

Abstract

Stunting remains one of Indonesia’s most persistent public health challenges, with West Java contributing the highest number of cases due to its large population and regional disparities in household welfare. Identifying household groups vulnerable to stunting is essential for designing targeted interventions that integrate nutrition, sanitation, and socio-economic development. This study introduces a data-driven clustering framework using the K-Modes and K-Prototypes algorithms to classify 22,161 households in West Java based on 26 indicators from the March 2024 National Socioeconomic Survey (SUSENAS), encompassing food security, sanitation, drinking water access, economic conditions, social assistance, and demographics. The K-Modes algorithm was applied to categorical data, while K-Prototypes integrated numerical and categorical variables, with parameter optimization performed using a grid search and the Elbow method. Clustering performance was evaluated through the Silhouette Score, Calinski–Harabasz Index, and Davies–Bouldin Index, followed by a bootstrapped stability analysis employing the Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Results show that K-Prototypes outperformed K-Modes, yielding a higher Silhouette Score (0.6681 compared to 0.2922), higher CH Index (13,890.6 compared to 3,976.1), and lower DBI (0.4607 compared to 1.5274), indicating superior compactness and separation. Stability testing confirmed strong robustness, with mean ARI = 0.959 and mean NMI = 0.932 across 50 bootstrap replications. The optimal five-cluster structure identified distinct socioeconomic groups, with the highest stunting risk found among households with low income, limited housing space, inadequate sanitation, and more children under five. The findings highlight the effectiveness of K-Prototypes in modeling mixed-type data and support the design of evidence-based, regionally adaptive stunting reduction strategies aligned with Presidential Regulation No. 72/2021 on the Acceleration of Stunting Reduction.
Co-Authors Ab., Ahmad AGUS Agus Mohamad Soleh Agustyas Tjiptaningrum Ahmad Khumaidi Alfa Dito, Gerry Alfred Trisakti Amirullah, Sufyan Amos, Erpianto Andi Hasbi Anna Islamiyati Bagus Sartono Bahrul Ulum Ilham, Bahrul Ulum Betta Kurniawan, Betta Dalillah, Fathian Nur Damanik, Inta P N Dito, Gerry Alfa Dwi Indria Anggraini Erwin Erwin Ety Apriliana Fahira, Fani Fauzi Ahmad Muda Fitria Saftarina Fitrianto, Anwar Hamdan Hamdan Hanna Mutiara, Hanna Hendra Tarigan Sibero Hijrah Amaliah Azis Ilyas, Herlina Intanri Kurniati Jhons Fatriyadi Suwandi JUMARDI Kamila, Sabrina Adnin Kartika, Juspeni Kusman Sadik Mahyuddin Barni, Mahyuddin Maryana, Dwi Muhammad Sulaiman Zubair Mukhlis Imanto, Mukhlis Munawir Mustam, Mariaulfa NURADILLA, SITI Nurlina Ibrahim Oktafany, Oktafany Poke, Andi Alif Rahmatullah Putri, Mega Ramatika Rahmayani, Fidha Ramdani, Nurfika Ramdanil Ramdanil Rengganis Wardani, Dyah Wulan Sumekar Rika Lisiswanti Rodiani, Rodiani Rufaida, Erty Rospyana S Siswanto Safira, Dela Sahusilawane, Aphrodite M Sari, Jefita Resti Sentana Putra, I Gusti Ngurah Sitti Hadijah, Sitti Sri Amalia Edy Suhaeni, Cici Syariful Anam Tri Umiana Soleha Wahab, Nurhikmah Yudhianto, Rachmat Bintang Zaman , Nur