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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Journal of Progressive Information, Security, Computer and Embedded System
Sam, Muh. Hadal Ali
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Computer Science & IT Engineering

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Sistem Pengambilan Keputusan Untuk Menentukan Tingkat Kecanduan Game Online Menggunakan Metode Weighted Product Sam, Muh. Hadal Ali; Farid, Muhammad Miftah; Surianto, Dewi Fatmawati
Progressive Information, Security, Computer, and Embedded System Vol. 3, No. 1 Maret (2025)
Publisher : Sakura Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/pisces.v3i1.700

Abstract

Playing online games is one of the activities that many people do to entertain themselves in the midst of their busy daily lives. The existence of several genres in online games certainly makes the game more exciting and entertaining. However, excessive and unlimited use as a means of entertainment can have a negative impact, such as online game addiction. In addition, not everyone realizes that they have developed this type of addictive behavior towards the game. As a result, a person who experiences online game addiction tends to be less interested in other activities, feels restless when not playing online games, decreased academic achievement, social relationships and health. For this reason, the utilization of a decision-making system with the weighted product method is very necessary to determine the level of online game addiction. Therefore, the purpose of this research is to develop a decision-making system to determine the level of online game addiction using the weighted product (WP) method. This research consists of several assessment criteria, namely playing time, frequency of play, level of satisfaction playing games, financial expenses, social interactions and physical problems. in this study, manual calculations were carried out with excel and also used a system to determine the level of online game addiction from several alternatives.
Sentiment Analysis of Data Security in Indonesia Using Naive Bayes Sam, Muh. Hadal Ali
JATISI Vol 12 No 3 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i3.12899

Abstract

Keamanan data sangat penting untuk mencegah berbagai tindakan yang bisa merugikan serta melindungi informasi pribadi maupun publik. Namun, pada kenyataannya sistem keamanan data di Indonesia masih memiliki banyak celah. Dampak dari permasalahan ini mempengaruhi kepercayaan publik terhadap kemampuan pemerintah dalam menjaga data dan infrastruktur digital. Hal ini memicu berbagai tanggapan dari masyarakat yang menjadi perbincangan hangat di media sosial. Penelitian ini bertujuan untuk mengetahui sentimen keamanan data di Indonesia pada platform media sosial X menggunakan Naïve Bayes Classifier serta mengetahui akurasi metode tersebut. Subjek dalam penelitian ini adalah sentimen publik terhadap keamanan data di Indonesia yang menggunakan media sosial X sebagai sumber data dengan 1.500 tweet berbahasa Indonesia. Data diperoleh melalui proses crawling, lalu dianalisis menggunakan algoritma Naïve Bayes Classifier. Analisis dimulai dengan tahap preprocessing meliputi cleaning, case folding, normalization, stopword removal, tokenization, stemming, dan translate. Setelah itu, pelabelan sentimen dilakukan menggunakan metode Vader untuk mengkategorikan tweet ke dalam tiga kelas: positif, negatif, dan netral. Pengujian dilakukan dengan empat skenario berdasarkan jumlah data per kelas. Hasil terbaik diperoleh pada skenario keempat dengan akurasi 79%. Kata kunci—Sentimen, Keamanan Data, Naïve Bayes
Co-Authors Farid, Muhammad Miftah Surianto, Dewi Fatmawati