Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of Computer Science and Informatics Engineering Indonesian Journal of Multidisciplinary on Social and Technology
Khaerul Ma'mur
Universitas Pamulang
Computer Science & IT Economics, Econometrics & Finance Engineering Social Sciences

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Implementasi Metode Electre pada Sistem Penunjang Keputusan Penentuan Starting line-up Pemain Sepak Bola Berbasis Web Muhammad Andika Frasetya; Khaerul Ma'mur
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 4 No. 3 (2026): Juli - Oktober
Publisher : PT Ilmu Data Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijmst.v4i3.12393

Abstract

Penentuan starting line-up dalam pertandingan sepak bola memerlukan pertimbangan berbagai kriteria sehingga dibutuhkan suatu sistem yang dapat membantu pelatih dalam mengambil keputusan secara lebih objektif. Penelitian ini bertujuan membangun Sistem Penunjang Keputusan berbasis web menggunakan metode Elimination and Choice Translating Reality (ELECTRE) untuk menentukan starting line-up pemain sepak bola pada SSB Metro Kukusan Depok. Metode penelitian yang digunakan adalah Waterfall, sedangkan metode pengambilan keputusan menggunakan ELECTRE. Sistem dikembangkan menggunakan React.js, Node.js, Express.js, dan PostgreSQL. Penilaian pemain dilakukan berdasarkan kriteria sesuai posisi bermain, kemudian diproses menggunakan tahapan metode ELECTRE untuk menghasilkan peringkat alternatif. Hasil penelitian menunjukkan bahwa sistem mampu menghasilkan rekomendasi starting line-up sesuai formasi yang dipilih berdasarkan nilai dan bobot kriteria setiap pemain. Pengujian menggunakan Black Box Testing menunjukkan bahwa seluruh fungsi sistem berjalan sesuai dengan kebutuhan. Dengan demikian, sistem yang dibangun dapat membantu pelatih dalam menentukan starting line-up secara lebih objektif, efektif, dan terstruktur.  
Implementation of Reverse Engineering Techniques for Malware Risk Level Categorization Using Simple Additive Weighting Muhammad Firdaus Aldiansyah; Khaerul Ma'mur
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1520

Abstract

The rapid growth of Android devices has been accompanied by an increasing number of malware threats, particularly spyware that can steal sensitive user information. This study aims to classify the risk level of Android spyware using reverse engineering techniques, VirusTotal API integration, and the Simple Additive Weighting (SAW) method. Reverse engineering is performed to extract internal malware attributes such as the number of permissions and the category of dangerous permissions from APK files. In addition, external attributes are obtained through VirusTotal API integration, including the number of antivirus engines detecting the malware and the threat category. These attributes are then processed using the SAW method to generate preference values used for classifying spyware risk levels into low, medium, and high categories. The malware sample used in this study is AhMyth, which represents Android spyware. The results indicate that the developed system is capable of providing systematic spyware risk classification and presenting more informative risk information to users. This research is expected to improve user awareness of spyware threats and support the development of more informative malware detection systems
Co-Authors Muhammad Andika Frasetya Muhammad Firdaus Aldiansyah