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All Journal PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Kesmas dan Gizi (JKG) Computer Science (CO-SCIENCE)
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Klasifikasi Perilaku Pemain Game Online Menggunakan Naïve Bayes Berbasis Particle Swarm Optimization Heristian, Sujiliani; Anwar, Rian Septian; Kautsar, Hanggoro Aji Al; Sujiliani, Sujiliani Heristian; A
Computer Science (CO-SCIENCE) Vol. 4 No. 2 (2024): Juli 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i2.4433

Abstract

Much research has been conducted to understand player behavior as a result of the rapid growth of online gaming. In this research, we use the Naive Bayes method optimized using Particle Swarm Optimization (PSO) to analyze the behavior classification of online game players. The classification accuracy value of the baseline method is 75.09% and the Area Under the Curve (AUC) value is 0.798. We use PSO-based optimization on Naïve Bayes to improve model performance. The results showed that the combination of Naïve Bayes and PSO increased classification accuracy to 95.28% with an AUC value of 0.990. This is a major advance that shows that combining the PSO algorithm with Naive Bayes can enable better classification of online game player behavior. These findings will make a significant contribution to the process of making plans that can improve the gaming experience.
The Relationship Between Ultra-Processed Food Consumption Patterns and Nutritional Status Among Indonesian Adolescents: A Systematic Review Fitriani, Yessy; Apri Yulda; A; Farhan Firmansyah
JURNAL KESMAS DAN GIZI (JKG) Vol. 8 No. 1 (2025): Jurnal Kesmas dan Gizi (JKG)
Publisher : Fakultas Kesehatan Masyarakat Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/yxdhpt73

Abstract

Background: Nutritional problems among children and adolescents remain a major public health issue in Indonesia, with challenges including both undernutrition and overnutrition. One contributing factor is the increasing consumption of ultra-processed foods (UPF), especially among adolescents. UPFs are industrially processed foods that are high in energy, fat, sugar, and salt, but low in essential nutrients. Objective: To evaluate the relationship between UPF consumption and nutritional status among adolescents. Methodology: This study used an observational design based on data from a systematic review. Results and Discussion: A review of various national and international studies shows that most research found a positive association between high UPF consumption and excessive nutritional status, such as overweight and obesity. However, some studies did not show a significant relationship, which may be influenced by other factors such as physical activity, sedentary behavior, and socioeconomic conditions. Furthermore, the type of UPF consumed also affects its impact on nutritional status, with energy-dense foods showing a stronger correlation than beverages. Conclusion: High consumption of ultra-processed foods has the potential to be an independent risk factor for excessive nutritional status in adolescents, although individual characteristics and lifestyle variability should be considered as moderating factors in this relationship.
Pengaplikasian Kalman Filter sebagai Pengendali dalam Permainan The Open Racing Car Simulator (TORCS) Rendy Andrian; A; Victor
Jurnal PROCESSOR Vol 15 No 1 (2020): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2020.15.1.740

Abstract

The Open Racing Car Simulator (TORCS) works as both a playable game and a framework to develop artificial intelligence-based controllers. As a platform for researchers, TORCS has become a platform in controller development with various approaches in artificial intelligence using sensors and actuators provided by the SCR Server. In this research, the author develops a controller using the Kalman Filter, an algorithm to predict and measure states based on previous measurements to determine future trajectory.
Co-Authors Apri Yulda Farhan Firmansyah Fitriani, Yessy Hanggoro Aji Al Kautsar Rendy Andrian Rian Septian Anwar Sujiliani Heristian Victor