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All Journal Indonesian Journal of Electronics and Instrumentation Systems Jurnal Transformatika JUKI : Jurnal Komputer dan Informatika Journal of Innovation Information Technology and Application (JINITA) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pengabdian Kepada Masyarakat (JPKM) J-Icon : Jurnal Komputer dan Informatika Jurnal Sistem Informasi (JASISFO)
Derwin Rony Sina, Derwin
Universitas Nusa Cendana
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

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STREAM CIPHER ALGORITHM FOR ENCRYPTING TEXT USING LOGISTIC MAP, AUTO PARAMETERS LINEAR CONGRUENTIAL GENERATOR (APLCG), AND GRAY CODE Fanggidae, Adriana; Polly, Yulianto Triwahyuadi; Sina, Derwin Rony; Letelay, Kornelis; Nabuasa, Yelly Yosiana; Boru, Meiton; Ledoh, Juan Rizky Mannuel
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1535

Abstract

One aspect frequently posing a challenge in cryptography pertains to the length of the secret key that users must remember. Achieving the requisite key length for cryptographic algorithms necessitates key padding. However, it is crucial to note that key padding is susceptible to predictable patterns. Both the Linear Congruential Generator (LCG) and gray code are algorithms employed to generate sequences of padded key bits. Regrettably, LCG requires the determination of two pre-defined parameters, whereas the Auto Parameters Linear Congruential Generator (APLCG) automatically establishes these parameters. These parameters play a pivotal role in generating unique sequences of random integers. To fortify key security, the generation of new keys is performed using a modified logistic map, an enhancement of the standard logistic map that exhibits random behavior consistently. Stream cipher, an encryption algorithm, necessitates a continuous key stream matching the bit or byte length of the message. We conducted experiments on stream cipher algorithms employing key streams generated from APLCG, gray code, and modified logistic map. Twenty text documents were utilized as test samples. The outcomes indicate that stream ciphers employing APLCG, gray code, and modified logistic map demonstrate high-security performance based on the statistical analysis conducted.
CASE BASED REASONING UNTUK MENDIAGNOSA PENYAKIT ANAK MENGGUNAKAN METODE BLOCK CITY Mage, Marnon Yolinda Chrisma; Rony Sina, Derwin; Widiastuti, Tiwuk
Jurnal Sistem Informasi (JASISFO) Vol. 2 No. 2 (2021): September 2021
Publisher : Politeknik Negeri Sriwijaya

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Abstract

Metode Case Based Reasoning (CBR) adalah salah satu metode untuk membangun sebuah sistem yang bekerja dengan cara mendiagnosa kasus baru berdasarkan kasus lama yang pernah terjadi dan memberikan solusi pada kasus baru berdasarkan pada kasus lama yang memiliki nilai kemiripan tertinggi. Pada penelitian ini, penulis menerapkan CBR untuk mendiagnosis penyakit penyakit anak usia 1-12 tahun. Sumber pengetahuan sistem diperoleh dengan mengumpulkan berkas rekam medis pasien pada tahun 2014 dan 2015. Perhitungan nilai kemiripan menggunakan metode Block City fungsi Gower dengan nilai batas kewajaran adalah 70%. Sistem ini dapat mendiagnosis 10 penyakit berdasarkan 48 gejala yang ada. Keluaran sistem berupa penyakit yang dialami oleh pasien berdasarkan gejala yang diinputkan oleh tenaga medis non dokter, solusi penanganan dan presentasi kemiripan dengan kasus terdahulu untuk menunjukan tingkat kebenaran hasil diagnosis. Berdasarkan hasil pengujian menggunakan 83 kasus baru didapatkan keakuratan sistem sebesar 75,90%.
Comparative Analysis of C4.5 and Random Forest for Analyzing Factors Affecting Undergraduate Students’ Final Project Completion in Higher Education Nelci Dessy Rumlaklak; Derwin Rony Sina; Tifanny Sooai
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i2.2941

Abstract

This study analyzes factors influencing students’ final project completion status in a higher education context using six classification models: C4.5, Random Forest (RF), C4.5 with SMOTE, RF with SMOTE, Cost-Sensitive Random Forest (RF-CS), and Cost-Sensitive C4.5 (C4.5-CS). The dataset consists of 1,017 student records categorized into Ideal and Tidak Ideal, with a severe class imbalance where the minority class represents only 16.49% of the data.The results indicate that baseline models achieved high overall accuracy but showed limited effectiveness in identifying the minority Tidak Ideal class. SMOTE-based models improved minority-class recall but introduced a higher number of false positives, highlighting a trade-off between recall and precision. In contrast, cost-sensitive learning produced the most substantial improvement in minority-class detection. Among all evaluated models, Cost-Sensitive Random Forest demonstrated the most balanced performance by significantly reducing false-negative errors while maintaining reasonable overall accuracy.These findings confirm that algorithm-level cost-sensitive approaches are more effective than oversampling techniques for handling severe class imbalance in educational datasets. The proposed model provides a reliable basis for early identification of students at risk of delayed final project completion and supports data-driven academic decision-making
Co-Authors Abineno, Patrisius Adriana Fanggidae Agus Harjoko Alokamating, Abath Timothy Bloemhard, Putri E Boru, Meiton Clarissa Elfira Amos Pah Emerensye S. Y. Pandie Fanggidae, Adriana Farhan, Ahmad Z. Juan Rizky Mannuel Ledoh Kalvein Rantelobo Kornelis Letelay Koroh, Vladimir Ivan Mage, Marnon Yolinda Chrisma Manuel Luis Belo Marselina Elisabeth Soinbala Mauk, Imanuel Brian Calvin Meiton Boru Nabuasa, Yelly Yosiana Nalle, Olsen Junior Nelci Dessy Rumlaklak Nelci Dessy Rumlaklak NEUTRINO KUSRORONG SAE BELAUDIN KUSRORONG Polly, Yulianto Triwahyuadi Rumlaklak, Nelci Dessy Tagi Huma, Alexander William Tifanny Sooai Tiwuk Widiastuti Yelly Yosiana Nabuasa