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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Petir TIN: TERAPAN INFORMATIKA NUSANTARA Computer Science (CO-SCIENCE) Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Klik - Jurnal Ilmu Komputer Arcitech: Journal of Computer Science and Artificial Intelligence Prioritas : Jurnal Pengabdian Kepada Masyarakat Journal of Computer Engineering: Progress, Application and Technology MDP Student Conference Jurnal Sistem Informasi Komputer dan Teknologi Informasi Jurnal Teknik Indonesia (JU-TI) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Daniel Udjulawa
Universitas Multi Data Palembang
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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The Sentiment Analysis of Public Comments on “Program Makan Siang Gratis” Using KNN (K-Nearest Neighbor) and SMOTE Algorithm Vincent, Vincent; Irsansaputra, Vincentius Hansel; Udjulawa, Daniel
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 5 No 01 (2026): May 2026
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v3i02.7734

Abstract

This research analyzes public sentiment on “Program Makan Siang Gratis” using the KNN algorithm, enhanced with the SMOTE technique, to provide insights and recommendations for policymakers aiming to achieve “Indonesia Emas 2045”. The study employs Google Colab and Python for testing. KNN is used for sentiment analysis and classification, with SMOTE addressing data imbalance. Results from two scenarios without SMOTE and with SMOTE show that performance is more optimal without SMOTE, as SMOTE decreases performance by 34%. The k4 parameter yields the best results: 76% accuracy, 57% precision, 77% recall, and 65% F1-Score. Analysis of comments from the “tempodotco” YouTube channel reveals that public sentiment towards the program proposed by President Prabowo Subianto and Vice President Gibran Rakabuming Raka is predominantly negative
PELATIHAN BRANDING, DESAIN KEMASAN DAN PEMASARAN DIGITAL GUNA MENINGKATKAN DAYA SAING UMKM SANTAN KELAPA Kesuma, Dorie P.; Fransen, Lisa Amelia; Udjulawa, Daniel; Hartati, Ery
FORDICATE Vol 5 No 2 (2026): April 2026
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v5i2.15872

Abstract

The Erni Susilo coconut milk processing Micro, Small, and Medium Enterprise, located in Kemuning District, faces challenges regarding low competitiveness compared to similar products. This issue stems from ineffective brand identity management, simple packaging design, and suboptimal digital marketing. This community service project aims to improve the business quality of the owner through training in brand identity, packaging design, and digital marketing. The methodology employs a participatory approach, including focus group discussions, counseling, practical training, and mentoring. Results indicate an increase in the participant's understanding of the importance of brand identity, the ability to design more attractive packaging, and the skills to utilize social media for promotion. In conclusion, the training approach successfully improved the entrepreneur's knowledge and skills in utilizing technology to develop the business, thereby encouraging potential sales growth in the future.
Klasifikasi Penyakit Daun Kelapa Menggunakan Xception Pada Data Imbalanced Dengan Smote Muhammad Totti Alfarabi; Daniel Udjulawa
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17118

Abstract

The decline in coconut production due to Weligama Coconut Leaf Wilt Disease (WCLWD) and Coconut Caterpillar Infestation (CCI) can be detected using deep learning. However, previous studies have largely ignored extreme data imbalance ratios, leaving models vulnerable to pseudo-accuracy and failure in recognizing minority classes. Furthermore, no existing studies on coconut disease classification have specifically evaluated model robustness against visual anomalies and background bias. To fill this gap, this study not only integrates the Xception architecture with the SMOTE oversampling technique to overcome imbalanced data but also conducts comprehensive stress testing. Using 5,139 images distributed in a 70:15:15 ratio, SMOTE was specifically applied to the training data. The model was optimized using a 299x299 resolution, a learning rate of 0.00001, and a 0.5 Dropout layer. Testing demonstrated optimal results with an overall accuracy of 99%. The implementation of SMOTE successfully handled data imbalance without sacrificing the sensitivity of the minority class (healthy leaves), evidenced by a 0.95 Recall and 0.82 F1-Score. Moreover, as a novel evaluation, testing using anomalous Out-of-Distribution images revealed a background bias in the CCI class. Nevertheless, the low predictive confidence level (43.06%) confirms that the model's regularization effectively prevents overconfident predictions and optimally calibrates visual uncertainty.
Co-Authors Abdul Rahman Andreyas, Andreyas Anggoro Aryo P. Dafid Dafid Dafid Dafid Dandy, Dandy Darmawan, Dean Famerdi, Farhan Agung Fatchurrachman, Ahmad Fawzan, Muhammad Febbiola Febbiola Febbiola, Febbiola Hartati, Ery Irsansaputra, Vincentius Hansel Ja'far, Ja'far Kadafi, Aldo Kasanova, Sinyo Kesuma, Dorie P. Krisvyanti, Fanny Kurniawan, Marthin Hokita Lie, Jeason Lisa Amelia Fransen M Fajri Septian Dwi Cahyo Martin, Nicolas Marzali, Azizurrahman Muhammad Haviz Irfani Muhammad Totti Alfarabi Mulyati Mulyati Mulyati Mulyati Novan Wijaya Nyimas Artina Oktarina, Serly Pramudiya, Relin Ramadhan, Ahmad Wildan Rizky Regiza Giovanno Robert, Michael Roda Robert, Victoria Valensita Setiawan, Jerry Sewithto, Muhyi Haadi Shela, Shela Simanjuntak, Andreas Jeremy Obet Sutanto, Steven Yesua Timoteus Ivan Sariyo Vincent Vincent, Vincent William William Wiwik Handayani Yoannita, Yoannita Yohannes, Yohannes Zulnardi, Andre