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Journal : Computer Science (CO-SCIENCE)

Rancang Bangun Aplikasi Berbasis Android Untuk Pembelajaran Linux Centos Rusady Rusady; Sari Dewi; Rian Septian Anwar
Computer Science (CO-SCIENCE) Vol. 1 No. 2 (2021): Juli 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v1i2.439

Abstract

Centos is a Linux based framework commonly used by network supervisors. Given the educational plan of learning in the current PC innovation study program, students are familiar with this framework. In today's all-mechanical era, there are lots of learning media such as android applications. This application was created to offer a different convenience to the Java programming language. In addition, this application is also developed using the SDLC model. There are still some uses that can help with learning exercises, especially those related to the Centos linux framework, the basic explanation of application makers to create applications that can later help learn about Centos linux. Although not as popular as Windows and iOS frameworks, there are still many who use the Centos Linux framework, especially for framework needs with this application making it easier for users to learn because it is mobile based so that we can learn Centos anywhere and anytime.
Perancangan Sistem Informasi Dengan PHP Dan MYSQL Untuk Pendaftaran Sekolah Di Masa Pandemi Mugi Raharjo; Musriatun Napiah; Rian Septian Anwar
Computer Science (CO-SCIENCE) Vol. 2 No. 1 (2022): Januari 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v2i1.689

Abstract

During the current Covid-19 pandemic, a platform such as a website is needed to facilitate the process and activities of new student admissions in the field of education, the activity in question is holding a selection of new student admissions in schools. In the process of admitting new students, there are still a lot of schools that still use the system manually or face to face in the admissions process, so that the level of efficiency and security in order to maintain health protocols can be met. In this design, the author conducted a case study in one of the kindergartens in Jakarta which still applies a manual system so that in this pandemic era it is very effective. Students don't need to be bothered to come to school during this pandemic. In terms of education on the website, we provide guidance to parents on how to use the website via whatsapp video call or Zoom Meeting to make it easier. For that we tried to make the website, which is an information system that is used for new student admissions based on the website to make it easier for parents to register for school for their children. And the selection of the website platform was chosen to make it easier for parents to open this service without having to install applications that would normally take up memory on smartphone devices, we created this website with Php and My Sql. The results of this study indicate that this system is able to manage the process of accepting new students for this school.
Klasifikasi Perilaku Pemain Game Online Menggunakan Naïve Bayes Berbasis Particle Swarm Optimization Heristian, Sujiliani; Anwar, Rian Septian; Kautsar, Hanggoro Aji Al
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.
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.