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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal of Applied Mathematics and Computing.
Muhammad Derry Oktaviandi
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics

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Perancangan UI/UX untuk Optimalisasi Booking Online dalam meningkatkan Potensi Wisata Daerah Leuwi Asih Humam Mu'asyir; Tundo; Husain Rahmani; Muhammad Derry Oktaviandi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3794

Abstract

UI/ UX Design for development of online booking technology and digital tour guides in the Leuwi Asih tourist area aims to increase regional tourism potential through web-based services. This system is designed to make it easy for tourists to make reservations and get information related to tourist destinations efficiently. This research uses a qualitative method by collecting data through direct interviews with local residents and local tourism business owners. The result of this research is a website that functions as a platform to facilitate the management of tourist reservations and provide digital tourist information. Thus, this system is able to support the development of local tourism and improve the tourist experience significantly.
Analisis Sentimen Publik terhadap Hashtag #kaburajadulu Menggunakan Kombinasi Algoritma Support Vector Machine (SVM) dan Random Forest Yuma Akbar; Frencis Matheos Sarimolle; Dwi Swasono Rachmad; Muhammad Derry Oktaviandi
International Journal of Applied Mathematics and Computing Vol. 2 No. 3 (2025): July : 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.v2i3.129

Abstract

This study aims to analyze public sentiment toward the hashtag #KaburAjaDulu, which has circulated widely on the social media platform X (formerly Twitter). The hashtag reflects the growing anxiety among the public, especially younger generations, regarding socio-political issues in Indonesia. The data were collected using web scraping techniques, focusing on user-generated tweets that contain the hashtag. A comprehensive text preprocessing phase was conducted to clean the raw data by removing irrelevant elements such as URLs, emojis, numbers, and punctuation. The research applies a hybrid classification approach using a combination of Support Vector Machine (SVM) and Random Forest algorithms to categorize sentiment into three classes: positive, negative, and neutral. The performance of the model was evaluated using metrics such as accuracy, precision, recall, and F1-score to determine the effectiveness of the classification. The study aims to demonstrate that combining algorithms can improve classification performance compared to using a single algorithm. This research contributes to the field of sentiment analysis and provides valuable insights for researchers, policymakers, and social observers in understanding public opinion trends in digital media.
Co-Authors Akbar, Yuma Dwi Swasono Rachmad Frencis Matheos Sarimolle Humam Mu'asyir Husain Rahmani Tundo, Tundo