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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Informatics and Software Engineering (ISE)
Atim, Sandi Badiwibowo
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Advanced Encryption Standard (AES) Cryptography Application Design Allwine, Allwine; Atim, Sandi Badiwibowo; Afdhaluddin, Muhammad
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22746

Abstract

As technology advances, the need for secure data transmission and storage increases. Encryption and decryption are essential processes to ensure data confidentiality and integrity. Encryption transforms original data into unreadable form during transmission, while decryption restores it to its original state for the recipient. This guarantees that unauthorized parties cannot access the data. Cryptosystems have evolved over time, and with the rapid growth of communication technologies, stronger standards are needed. AES (Advanced Encryption Standard), based on the Rijndael algorithm, has become the current standard for encryption. AES can encrypt and decrypt 128-bit data blocks with key lengths of 128, 192, or 256 bits, addressing the limitations of older algorithms and providing enhanced data security to protect confidentiality in modern cryptosystems.
Rule-Based Expert System Model with Backward Chaining Algorithm for Symptom-Based Skin Disease Diagnosis Atim, Sandi Badiwibowo; Ibrahim, M. Yhogha Ismail Ibn
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 1 (2025): Jurnal Teknologi dan Open Source, June 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i1.4416

Abstract

A rule-based expert system was a computational model designed to emulate expert decision-making using a knowledge base and inference algorithms. This research developed a rule-based expert system model with a backward chaining algorithm to diagnose skin diseases based on clinical symptoms. Backward chaining, a goal-driven inference method, started with a disease hypothesis (e.g., psoriasis) and verified related symptoms (e.g., kemerahan, sisik keperakan), enabling efficient differentiation of skin diseases with overlapping symptoms, such as dermatitis, psoriasis, and scabies. The model provided advantages in handling uncertainty, produced accurate diagnoses, and supporting interactive symptom verification. Developed using a knowledge base from credible sources like WHO and AAD, the model was intended to assist in clinical decision-making. The results showed that the backward chaining algorithm effectively improved the accuracy and efficiency of diagnosing skin diseases based on patient-reported symptoms
Tier-Aware Entropy-ARAS Approach to Select Microcontroller Boards for Education Sintaro, Sanriomi; Atim, Sandi Badiwibowo; Sabandar, Vederico Pitsalitz
Informatics and Software Engineering Vol. 3 No. 2 (2025): December
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v3i2.574

Abstract

This study develops a decision support system to recommend microcontroller and IoT learning devices for schools, universities, and training centers under realistic budget constraints while considering both technical capability and educational suitability. The alternatives are grouped into three budget tiers and evaluated using nine criteria covering price, CPU frequency, Flash, RAM/PSRAM, connectivity, usable GPIO, ease of learning, learning resources/community, and local availability/warranty. Objective criterion weights are computed using the Entropy method, and tier-wise rankings are produced using Additive Ratio Assessment (ARAS) through utility scores relative to an ideal alternative. Indicative local price and availability information are compiled from Tokopedia, while qualitative criteria are scored using consistent rubrics to support reproducibility. The results identify ESP32-CAM + baseboard as the top recommendation in Tier 1, LILYGO T-Display S3 in Tier 2, and M5StickC Plus2 in Tier 3; across tiers, Entropy assigns the largest weights to the most discriminative criteria, particularly RAM/PSRAM and, in higher tiers, Flash. The study is limited by market price volatility, approximations in usable GPIO values, and rubric-based qualitative scoring, and it also reflects the tendency of Entropy to concentrate weights on highly dispersed criteria, potentially amplifying outlier advantages. Overall, the proposed tier-aware Entropy–ARAS framework provides a transparent and actionable approach for educational institutions to justify device procurement and usage decisions based on budget, functionality, and learning readiness.
Rekomendasi Handheld Gaming PC Menggunakan MEREC untuk Pembobotan Objektif dan MARCOS untuk Pemeringkatan Sintaro, Sanriomi; Atim, Sandi Badiwibowo
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol. 11 No. 3 (2025): Desember 2025
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v11i3.19016

Abstract

This study proposes a decision support system to select a handheld gaming PC by integrating the MEREC weighting method with the MARCOS ranking method. Sixteen devices were evaluated using Tokopedia price data and technical specifications across nine criteria: price, SSD capacity, RAM capacity, battery capacity, device weight, screen size, refresh rate, total screen pixels, and a display-type score (OLED=3, IPS=2, LCD=1). MEREC indicates SSD capacity is the most influential criterion (wC2=0.2085), followed by total pixels (wC8=0.1497) and display score (wC9=0.1389). MARCOS ranks MSI CLAW 8 first with Si=0.7652 and f(Ki)=0.6776, followed by ROG Xbox Ally X Premium and ASUS ROG Ally X (both Si=0.7535; f(Ki)=0.6672). The results show that storage and display attributes dominate recommendations for the observed dataset, and the framework provides an explainable, data-driven ranking that can be updated when market prices change.
Co-Authors Afdhaluddin, Muhammad Allwine Ibrahim, M. Yhogha Ismail Ibn Sanriomi Sintaro Vederico Pitsalitz Sabandar