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All Journal JOIN (Jurnal Online Informatika) JURNAL INSTEK (Informatika Sains dan Teknologi) ILKOM Jurnal Ilmiah Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming JURNAL TEKNOLOGI INFORMASI Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Digital Transformation Technology (Digitech) Murabbi: Pendidikan Guru Madrasah Ibtidaiyah Masile:Jurnal Studi Ilmu Keislaman
Mulyana, Jajang
Unknown Affiliation
Religion Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health

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PENGAMANAN FILE DOKUMEN MENGGUNAKAN KOMBINASI METODE SUBTITUSI DAN VIGENERE CIPHER Budi, Sarwo; Purba, Arif Budimansyah; Mulyana, Jajang
ILKOM Jurnal Ilmiah Vol 11, No 3 (2019)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i3.477.222-230

Abstract

Cryptography is a method of securing data using algorithms that have been developed continuously until now. Cryptography offers security in the form of data confidentiality, for example the confidentiality of data generated through encryption algorithms that scrambles personal information so that it cannot be read or solved by unauthorized parties. One of them is the substitution algorithm and the vigenere cipher is a classic method used for data security. The combination of these algorithm methods becomes a solution for double security as file protection. By using a cryptographic application for data security, the combination of the two method algorithms produces a data file that provides more security to the text file so that it is not easy and difficult to solve.
Sistem Pendukung Keputusan Penerimaan Beasiswa Menggunakan Metode Bayesian Probability Untuk Meningkatkan Akurasi Seleksi Wahyudi; Mulyana, Jajang
Techno Xplore: Journal of Computer Science and Information Technology Vol. 11 No. 1 (2026): Techno Xplore: Jurnal Ilmu Komputer dan Teknologi Informasi
Publisher : Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/pr4y8n46

Abstract

Scholarship selection processes in higher education institutions commonly involve multiple evaluation criteria, making manual assessment time-consuming, inconsistent, and prone to subjective bias. This study proposes a web-based Decision Support System (DSS) for scholarship recipient selection, built upon Bayesian Probability inference integrated with Laplace Smoothing to address the zero-probability limitation inherent in conventional Naive Bayes classification. The system processes five standardized selection criteria — cumulative GPA, parental income, residential status, active semester, and non-academic achievement — and produces real-time eligibility recommendations alongside normalized posterior probability visualizations to enhance decision transparency. A dataset of 150 historical scholarship application records from a university in Karawang, covering two academic years (2022/2023 and 2023/2024), was used to train and evaluate the model. Performance assessment was conducted through 5-fold cross-validation, yielding a mean accuracy of 91.67%, precision of 90.00%, recall of 93.33%, and F1-score of 91.61%. Comparative analysis against conventional Naive Bayes, TOPSIS, and Bayesian-AHP hybrid methods demonstrated consistent superiority across all evaluation metrics. The 13.67% accuracy improvement over conventional Naive Bayes was primarily attributed to the elimination of zero-probability events through Laplace Smoothing with α = 1, as well as structured posterior normalization. User acceptance testing confirmed that the probability distribution visualization feature significantly improved operator comprehension of the system's reasoning. These findings establish Bayesian Probability with Laplace Smoothing as a technically sound and practically effective foundation for automated, transparent, and auditable scholarship decision support systems.
Co-Authors Aftoni, Falikul Isbah Ahmad Rifai Budi, Sarwo Budimansyah Purba, Arif Fairuzia, Fazat Hidayatullah, Agus Noor HUSEIN, MUHAMAD SADDAM Lailiyah, Nisful Lenggana, U Tresna Mohamad Yudiyanto Mustolih, Riyanto Nabila, Tahsya Noviyanti, Nabila Dwi Nurishlah, Lesti Peri Ramdani Purba, Arif Budimansyah Sahrilah, Ahmad Samadi, Mochammad Ramdan Sanjaya , Herno Aji Setiawan, Miko Sihombing, J. Rolles Herwin Supriyadi Supriyadi Suryani, Indri WAHYUDI