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MULTI-PARENT ORDER CROSSOVER MECHANISM OF GENETIC ALGORITHM FOR MINIMIZING VIOLATION OF SOFT CONSTRAINT ON COURSE TIMETABLING PROBLEM Fajrin, Ahmad Miftah; Fatichah, Chastine
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 6, No 1 (2020): January-June
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v6i1.1663

A crossover operator is one of the critical procedures in genetic algorithms. It creates a new chromosome from the mating result to an extensive search space. In the course timetabling problem, the quality of the solution is evaluated based on the hard and soft constraints. The hard constraints need to be satisfied without violation while the soft constraints allow violation. In this research, a multi-parent crossover mechanism is used to modify the classical crossover and minimize the violation of soft constraints, in order to produce the right solution. Multi-parent order crossover mechanism tends to produce better chromosome and also prevent the genetic algorithm from being trapped in a local optimum. The experiment with 21 datasets shows that the multi-parent order crossover mechanism provides a better performance and fitness value than the classical with a zero fitness value or no violation occurred. It is noteworthy that the proposed method is effective to produce available course timetabling.

Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem Fajrin, Ahmad Miftah; Fatichah, Chastine
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 6, No 1 (2020): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v6i1.1663

A crossover operator is one of the critical procedures in genetic algorithms. It creates a new chromosome from the mating result to an extensive search space. In the course timetabling problem, the quality of the solution is evaluated based on the hard and soft constraints. The hard constraints need to be satisfied without violation while the soft constraints allow violation. In this research, a multi-parent crossover mechanism is used to modify the classical crossover and minimize the violation of soft constraints, in order to produce the right solution. Multi-parent order crossover mechanism tends to produce better chromosome and also prevent the genetic algorithm from being trapped in a local optimum. The experiment with 21 datasets shows that the multi-parent order crossover mechanism provides a better performance and fitness value than the classical with a zero fitness value or no violation occurred. It is noteworthy that the proposed method is effective to produce available course timetabling.

Iterated Region for Interactive Image Segmentation on Dental Panoramic Radiograph Biandina Meidyani; Lailly S. Qolby; Ahmad Miftah Fajrin; Agus Zainal Arifin; Dini Adni Navastara
Jurnal Ilmu Komputer dan Informasi Vol 12, No 1 (2019): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Image Segmentation is a process to separate between foreground and background. Segmentation process in low contrast image such as dental panoramic radiograph image is not easily determined. Image segmentation accuracy determines the success or failure of the final analysis process. The process of segmentation can occur ambiguity. This ambiguity is due to an ambiguous area if it is not selected as a region so it may have occurred cluster errors. To solve this ambiguity, we proposed a new region merging by iterated region merging process on dental panoramic radiograph image. The proposed method starts from the user marking and works iteratively to label the surrounding regions. In each iteration, the minimal gray-levels value is merged so the unknown regions significantly reduced. This experiment shows that the proposed method is effective with an average of ME and RAE of 0.04% and 0.06%.

Pemberdayaan Karang Taruna Untuk Pengembangan Wisata Berbasis Potensi dan Kearifan Lokal di Desa Belik Kecamatan Trawas Mojokerto Asmawati, Endah; Lianto, Benny; Fajrin, Ahmad Miftah; Setyawan, Andhy; Mijiarto, Joko; Khosasih, Mikhael Ming
UN PENMAS (Jurnal Pengabdian Masyarakat untuk Negeri) Vol 4 No 2 (2024): UN PENMAS Vol 4 No 2
Publisher : LPPM Universitas Narotama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/un-penmas.v4i2.2969

Desa Belik merupakan salah satu desa wisata di Kecamatan Trawas Kabupaten Mojokerto. Potensi wisata di Desa Belik cukup besar, namun belum digunakan secara maksimal, salah satunya adalah hutan bambu. Karangtaruna sebagai salah satu organisasi pemuda yang aktif berkegiatan di desa Belik mempunyai peranan besar dalam pengembangan desa wisata. Oleh sebab itu pada pengabdian masyarakat ini, dilakukan pemberdayaan karangtaruna untuk mengembangkan wisata berbasis potensi dan kearifan lokal desa Belik. Kegiatan yang dilakukan antara lain pelatihan pengembangan wisata dan sapta pesona, pelatihan pelayanan prima, pembuatan konsep pengembangan hutan bambu, dan menampilkan budaya lokal pada acara desa yang sudah terjadwal. Tujuan program ini adalah memberdayakan karangtaruna Desa Belik dalam mengembangkan wisata sehingga dapat meningkatkan ekonomi masyarakat. Metode pelaksanaan adalah fasilitasi dan partisipasi melalui diskusi, pelatiham, dan pendampingan. Hasil dari pelaksanaan pengabdian masyarakat ini adalah karangtaruna memahami dan dapat menerapkan sapta pesona, dapat melayani pelanggan dengan prima. Selain itu juga terbentuk kelompok sadar wisata.

ANALISIS PERFORMA DARI ONE-POINT, MULTI-POINT DAN ORDER CROSSOVER DI ALGORITMA GENETIKA Fajrin, Ahmad Miftah
SemanTIK : Teknik Informasi Vol 7, No 2 (2021): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Algoritma Genetika (GA) adalah salah satu algoritma yang powerful untuk menyelesaikan masalah penjadwalan mata kuliah. Pada GA, terdapat operator crossover yang berperan aktif dalam pembuatan anak atau offspring. Crossover juga menjadi fondasi dalam menghasilkan solusi yang optimal. Kesalahan dalam pemilihan crossover membuat meningkatnya tingkat pelanggaran atau fitness terhadap constraint. Semakin tinggi nilai Fitness maka semakin buruk solusi yang dihasilkan. Pada penelitian ini, dilakukan analisis terdapat jenis crossover yang ada di GA yaitu One-Point Crossover, Multi-Point Crossover dan Order Crossover. Analisis yang dilakukan pada penelitian ini adalah dengan membandingkan nilai fitness dan waktu eksekusi antara jenis crossover tersebut. Hasil penelitian menunjukkan bahwa nilai fitness yang paling kecil dapat dihasilkan oleh One-Point Crossover pada 9 dataset. Untuk waktu eksekusi yang paling cepat dapat dihasilkan oleh Multi-Point Crossover pada 12 dataset.Kata kunci; Algoritma Genetika, Crossover, Penjadwalan, Pelanggaran

Analisis Performa dari Algoritma Kriptografi RSA dan ElGamal dalam Enkripsi dan Dekripsi Pesan Fajrin, Ahmad Miftah; Benedict, Jeremy Richard; Kusuma, Henri Jayanata
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 1 (2023): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i1.545

Cryptography is one of the most important things in computer science because it is related to data security or message security. Cryptographic algorithms are used to secure a message, the most popular of which are the Rivest-Shamir-Adleman (RSA) and ElGamal algorithms. ElGamal employs a prime number modulo while RSA employs the factorial of two large integer numbers. The workings of these two algorithms are distinct, and each has distinct advantages. Even though the two algorithms use different processes, they can both encrypt and decrypt a message. There are speed factors of execution time and peak memory when running the encryption and decryption process. One of these two factors is hardware, which determines the environment that will be used. According to the findings of this study, the RSA algorithm has a faster execution time than ElGamal. In terms of peak memory, both algorithms get the result similarly, with the same peak memory results shown..

Classification of Student Learning Styles Using Artificial Neural Networks on Imbalanced Data Baharuddin, Fikri; Fajrin, Ahmad Miftah; Handani, Felix
Teknika Vol. 13 No. 3 (2024): November 2024
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v13i3.1075

The transformation of learning activities towards digital form since the COVID-19 pandemic can affect students' learning process. One of the factors that can affect this learning process is the learning style owned by each student. Learning patterns that are not in line with students' learning styles can influence their learning process. This study aims to identify students' learning styles based on data extracted from the Moodle Learning Management System (LMS). The research methods applied in this study include data collection by extracting data from Moodle LMS logs and classifying student learning styles using the Artificial Neural Network (ANN) algorithm. This study uses 310 log extraction data on the Moodle platform. The Isolation Forest algorithm was applied to this study to detect anomalies or outliers in the dataset. The data used in this study also has an unbalanced distribution of data per class. To prevent the performance degradation of the classifier model caused by the imbalance of data distribution, this study uses the SMOTE algorithm which can generate new synthetic data on minority class. This study combines three algorithms consisting of the Isolation Forest Algorithm for dataset management, the SMOTE Algorithm to solve the problem of data imbalance, and the ANN Algorithm to build a classification model. The model evaluation is carried out by considering the values of accuracy, precision, recall, and F1-Score to identify the reliability level of the produced model. Based on the research, this study produced a classifying model with an accuracy of 96%. The model produced in this study can be used to identify students' learning styles and as a reference for improving the quality of the teaching and learning process.

Minimalist DevStack Deployment: An Analysis of Performance and Swap Utilization Kristyanto, Marco; Fajrin, Ahmad Miftah
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9792

Cloud technology offers significant advantages; however, its high implementation costs and high hardware requirements pose barriers to small-scale deployments and educational institutions. This study addresses these challenges by investigating the performance of OpenStack deployed via DevStack on a single-node server equipped with an Intel Core i7 processor, 16 GB of RAM, and a 500 GB solid-state drive (SSD) under resource-constrained conditions. We implemented a resource tuning approach by turning off non-essential services (including Cinder, Heat, and Tempest) and adjusting Nova's memory configurations to minimize overhead. Real-time system monitoring was performed using Prometheus and Grafana to examine trends in CPU, memory, and swap utilization across three configurations: default, optimized (RAM=1024 MB), and minimalist (RAM=512 MB). Our empirical results show that the optimized setup enhances system efficiency, decreasing CPU use and memory usage from 86% to 70.90% while maintaining the ability to run up to ten virtual machines with varying operating systems (e.g., CirrOS, Ubuntu 24.04 Server LTS). However, the minimalist configurations, which aim for aggressive swap utilization and reach 100% swap saturation when running 8 VMs under idle workloads, consequently compromise overall system responsiveness despite lower CPU usage. Efficiency in this context is defined as conserving RAM and CPU usage without degrading basic system responsiveness. This highlights a critical trade-off between RAM conservation and overall system responsiveness. This research provides practical insights into designing cost-effective and lightweight OpenStack environments. It establishes a crucial threshold for memory optimization, preventing performance degradation caused by excessive swap usage, particularly in resource-constrained research settings.

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