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All Journal SMARTICS Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Global JSAI (Journal Scientific and Applied Informatics) Jurnal Abdimas Mandiri Jurnal Informasi dan Teknologi Reswara: Jurnal Pengabdian Kepada Masyarakat J-ENSITEC (Journal of Engineering and Sustainable Technology)
Evi Purnamasari
Universitas Indo Global Mandiri
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Journal : smartics journal

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Benchmarking Kinerja Sistem Operasi Linux dan Windows dalam Pengelolaan Proses dan Memori Dwi Asa Verano; Evi Purnamasari
SMARTICS Journal Vol 11 No 2 (2025): Journal SMARTICS (Oktober 2025)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v11i2.13850

Abstract

The operating system plays an important role in managing computer resources, especially in the aspect of process and memory management. Currently, many do not know the level of operating system performance between Linux and Windows in managing processes and memory. This study aims to analyze and compare the performance of Linux and Windows operating systems in the context of multitasking process management and the efficiency of physical and virtual memory usage. The method used is a comparative experiment with direct testing using identical hardware and specifications. The parameters tested include CPU efficiency, context switching speed, idle memory usage, swap activation, and system response time when given a high load. The results of the study show that Linux has advantages in process load distribution, memory efficiency, and system stability when handling heavy loads. Windows, on the other hand, excels in application compatibility and ease of system monitoring through a graphical interface. Both systems have different characteristics that are suitable for different usage contexts. Recommendations are given based on the findings that Linux is more optimal for server environments and heavy computing, while Windows is more suitable for general desktop users with high graphics needs, with this the user can choose which operating system suits their needs.
Prediksi Tingkat Keamanan Terhadap Pencurian Menggunakan Naive Bayes di Wilayah Sektor Kepolisian Merapi Barat Sutria Rahmi; Indah Permatasari; Evi Purnamasari
SMARTICS Journal Vol 12 No 1 (2026): Journal SMARTICS (April 2026)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v12i1.13919

Abstract

Theft remains one of the most prevalent forms of criminal activity in the jurisdiction of the West Merapi Police Sector, significantly impacting public safety and community security. Historically, the handling and securing of this region has been reactive in nature, lacking a predictive system capable of estimating theft risks preventively. This study aims to develop a predictive model for regional security levels related to theft cases using a machine learning approach. The data utilized in this research comprises secondary data obtained from 459 theft case reports documented by the West Merapi Police Sector from 2021 to 2024. Ten relevant variables were selected as features, while three security level categories (Low, Medium, and High) served as target classes. Data preprocessing included data cleaning, variable transformation, and label encoding. The Naive Bayes algorithm was employed with a 70% training data and 30% testing data split. The results demonstrated that the Naive Bayes method achieved an accuracy of 76.09% in predicting regional security levels. The model exhibited optimal performance for the High security level class, while the Low class showed lower performance due to imbalanced data distribution. This research demonstrates that police case report data can be effectively utilized to support data-driven risk analysis and has the potential to serve as a decision-making tool for preventive measures by law enforcement agencies.
Co-Authors Agustina Heryati Doly Nofiansyah Dona Marcelina Dwi Asa Verano Endang Sri Lestari Endang Sri Lestari Hafiz Hidayatullah Husni Mubarat Indah Permatasari K. Ghazali K. Ghazali Leksi Saputra Lesi Hertati Muhammad Adli Dary Hanif Nazori Suhandi Nuraini Nuraini Peny Meliaty Hutabarat Saputra, Tedy Setiawan Sutria Rahmi Terttiaavini, Terttiaavini