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Journal : Building of Informatics, Technology and Science

Optimalisasi Penggunaan Image Stitching dan Seam Carving dalam Pengembangan Tur Virtual Responsif Buana, Pratama Angga; Putri, Astrid Novita; Adinugroho, Suryo
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5392

Abstract

Nglurah Village, Tawangmangu, still faces challenges in effective tourism promotion due to the use of conventional promotional methods. This study employs a mixed-method approach to identify the issues and expectations of tourism managers. The results indicate that 50% of managers struggle with tourism promotion, and 70% believe that the implementation of technology is crucial to promote the village's tourism potential in an attractive and interactive way. This research aims to combine image stitching and seam carving methods to enhance the quality and diversity of responsive virtual tour applications. Image stitching is the process of merging multiple 360° panoramic images into a single comprehensive image that accurately represents the actual scene. Meanwhile, seam carving is a technique for carefully cropping an image to remove less important parts while preserving important areas when the image is resized. The collaboration of these two methods is expected to produce virtual tour applications that can adapt to the shape and size of gadgets without losing important content. This virtual tour application is expected to enhance the user experience in virtual tourism and open up opportunities for technology-based tourism development in Tawangmangu Village. Additionally, this research can increase the attractiveness of Tawangmangu Village tourism and provide a foundation for further research in virtual tour development.
Penerapan Naïve Bayes Untuk Analisis Sentimen Pada Ulasan Aplikasi Mobile Legends Perkasa, Attila Elang; Putri, Astrid Novita
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6507

Abstract

Indonesia has become one of the potential markets for the gaming industry, continually increasing the number of gamers. One of the most popular mobile games in Indonesia is Mobile Legends. Mobile Legends is an online multiplayer battle arena (MOBA) video game developed by Moonton, a game development company based in China. The influence of reviews on the reputation of an app also affects potential new users, whether the reviews are positive or negative. Research has shown that the Naïve Bayes model provides good accuracy for sentiment analysis. This study is expected to help understand the perceptions and experiences of players of the game. The study uses the KDD (Knowledge Discovery in Data) method due to its advantages in identifying organized patterns from a complex dataset, making the data easier to understand. During the research process, 320,513 positive reviews, 185,777 negative reviews, and 20,210 neutral reviews were obtained. The accuracy value remained constant at 87% for the 80:20 data split scenario. Performance on the negative class showed high precision at 88%. The negative recall was 92%, indicating that the model could accurately capture truly negative reviews. A stable F1-Score of 82% signifies a good balance between precision and recall for the negative class. Performance on the positive class showed 87% precision and 83% recall. The F1-Score between the two was nearly balanced, indicating that the model performed similarly for both labels overall.