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p-Index From 2021 - 2026
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All Journal International Journal of Applied Mathematics and Computing. Journal of Engineering, Electrical and Informatics
Nova Dahliyanti
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics

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Application of TF-IDF and Xgboost Methods for Public Sentiment Analysis Towards Ozzaskin Skincare Brand on Social Media Mesra Betty Yel; Elviwani Elviwani; Nova Dahliyanti; Ahmad Syahran Zidane
Journal of Engineering, Electrical and Informatics Vol. 5 No. 1 (2025): Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i1.3676

Abstract

Ozzaskin is a local skincare brand founded by Ustadzah Oki Setiana Dewi that targets Muslim women and focuses on reducing dark spots and acne scars. Over time, this domestic brand has attracted considerable public attention on social media—particularly among mothers—garnering both praise for its product efficacy and criticism regarding price and texture. This study aims to analyze public sentiment toward the Ozzaskin brand by performing web scraping on Instagram and TikTok data, employing TF-IDF for textual feature extraction and XGBoost as the classification algorithm. The findings are expected to provide a comprehensive overview of consumer perceptions of Ozzaskin and to assist the marketing team and product developers in formulating communication strategies and improving product formulas that more effectively address user needs. The novelty of this research lies in the comprehensive application of the TF-IDF + XGBoost framework for brand-related sentiment analysis on Indonesian-language social media.
Design of a Financial Saving Challenge to Enhance Saving Interest Using the Reinforcement Learning Method Veri Arinal; Nandang Sutisna; Nova Dahliyanti; Dinda Raudhatul Jannah
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): January: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.247

Abstract

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.
Co-Authors Ahmad Syahran Zidane Arinal, Veri Betty Yel, Mesra Dinda Raudhatul Jannah Elviwani Elviwani Nandang Sutisna