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All Journal PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science Jurnal Testing dan Implementasi Sistem Informasi
Jelita, Nur Futri Ayu
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Rancang Bangun Sistem Informasi Pemesanan Accessories Berbasis Online Dengan Metode Prototype Mahadewa, Bivandira Aurel; Rahman, Hafiz Aulia; Ryanda, Nayla Husna; Jelita, Nur Futri Ayu
Jurnal Testing dan Implementasi Sistem Informasi Vol. 2 No. 2 (2024): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v2i2.901

Abstract

Pandemi (COVID-19) telah berdampak pada perekonomian global dan meningkatkan popularitas e-commerce. Karena perekonomian bergantung pada e-commerce untuk bertahan selama pandemi. E-commerce memberikan peluang bagi siapa saja untuk dengan mudah memulai atau mengembangkan bisnis. Tujuan penelitian ini telah dimanfaatkan oleh pebisnis tokohitstore merupakan toko yang didirikan pada tanggal 28 Maret 2024 yang dimana pada tokohitstore ini menyediakan berbagai macam accessories. Penulis menggunakan metode prototyping dalam merancang sistem baru. Metode ini melibatkan lima tahapan, yang dimulai dengan pengumpulan data melalui kuesioner dan analisis kebutuhan. Hasil dari penelitian ini adalah pembangunan sistem informasi pemesanan aksesori berbasis online, yang memiliki modul pelanggan untuk mencari, melihat detail, dan memesan aksesori, modul admin untuk mengelola data aksesori, pelanggan, dan pesanan, serta modul laporan untuk memberikan informasi kepada pelanggan tentang aksesori yang tersedia.
Sentiment Analysis of Public Opinion on the Gaza Conflict Using Machine Learning Fadri, Agil Irman; Jelita, Nur Futri Ayu; Bagaskara, Diamond Dimas; Zahra, Raudiatul
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 3 No. 2: PREDATECS January 2026
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v3i2.2088

Abstract

The 2023 escalation of the Gaza conflict triggered widespread public discourse on the X platform, highlighting the importance of sentiment analysis for understanding public opinion on global geopolitical issues. While sentiment analysis has been widely applied to social media data, comparative evaluations of machine learning models on conflict-related datasets remain limited. This study analyzes public sentiment toward the Gaza conflict by comparing the performance of Multi-Layer Perceptron, XGBoost, and Logistic Regression models. A dataset of 2,175 tweets was processed using standard text preprocessing techniques and TF-IDF feature extraction. Model performance was evaluated using multiple train-test split scenarios. The results indicate that Logistic Regression consistently outperformed the other models, achieving the highest accuracy of 73.17% with an 80:20 data split. These findings suggest that simpler linear models may perform more robustly and efficiently than more complex approaches when applied to high-dimensional, noisy social media text data. This study provides practical insights into model selection for sentiment analysis of conflict-related discussions on social media platforms.
Co-Authors Bagaskara, Diamond Dimas Fadri, Agil Irman Mahadewa, Bivandira Aurel Rahman, Hafiz Aulia Ryanda, Nayla Husna Zahra, Raudiatul