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All Journal Applied Information Technology and Computer Science (AICOMS)
Jaysen Stephanus
Universitas Multi Data Palembang
Computer Science & IT

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Analisis Sentimen Masyarakat terhadap Kenaikan Harga BBM Non-Subsidi Akibat Penutupan Selat Hormuz Menggunakan IndoBERT Jaysen Stephanus; Jonathan Tanujaya; Muhammad Rizky Pribadi
Applied Information Technology and Computer Science (AICOMS) Vol 5 No 1 (2026): AICOMS
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/kx4xgz78

Abstract

Public discussions regarding the potential increase in non-subsidized fuel prices resulting from the closure of the Strait of Hormuz on the X platform between January 1, 2026, and May 17, 2026, were highly intensive and generated diverse public responses to the global economic impacts triggered by the geopolitical conflict between Iran and Israel. The primary issue addressed in this study is the growing public concern over the possibility of rising non-subsidized fuel prices, which may affect transportation costs, logistics distribution, and daily living expenses. This study aims to analyze public sentiment toward this issue using the IndoBERT deep learning model to obtain a more accurate understanding of public opinion trends. Data were collected through a scraping process on the X platform using keywords related to non-subsidized fuel and the Strait of Hormuz. The collected data were then processed through several preprocessing stages, including case folding, noise removal, tokenization, stopword removal, and stemming, before being classified into positive, neutral, and negative sentiment categories. Out of 412 analyzed tweets, negative sentiment emerged as the dominant category at 49.8%, followed by neutral sentiment at 48.5%, while positive sentiment accounted for only 1.7%. The findings indicate that the majority of the public expressed concern regarding the potential increase in non-subsidized fuel prices and its impact on economic conditions and household expenditures.
Penerapan Metode Branch and Bound untuk Optimalisasi Rute Wisata Terdekat di Kota Palembang Jaysen Stephanus; Felix Gunawan; Yohannes Yohannes
Applied Information Technology and Computer Science (AICOMS) Vol 5 No 1 (2026): AICOMS
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/eqadem96

Abstract

This study discusses the application of the Branch and Bound method to optimize the nearest tourist route in Palembang City using the Traveling Salesman Problem (TSP) approach. The problem raised is how to determine the most efficient tourist route from several tourist destinations with minimum travel distance. The study utilizes geographic coordinate data of tourist destinations obtained through OpenStreetMap, then the distance between locations is calculated using the Haversine Formula to obtain an accurate distance estimate based on latitude and longitude. Furthermore, the Branch and Bound Algorithm is used to find the optimal route solution through the process of branching, bounding, and pruning so that the solution search becomes more efficient than the brute force method. The results show that the system successfully produces an optimal circular tourist route with a total minimum distance of 40.47 km and an execution time of 12.84 seconds. The integration of the Haversine Formula and Branch and Bound is proven to be able to provide efficient, accurate, and adaptive tourist route recommendations to help tourists save travel time and transportation costs in Palembang City.
Co-Authors Felix Gunawan Jonathan Tanujaya Muhammad Rizky Pribadi Yohannes, Yohannes