Article Per Year (5 Year)
p-Index From 2021 - 2026
1.971
P-Index
This Author published in this journals
All Journal Teknosains: Media Informasi Sains dan Teknologi JUSIFO : Jurnal Sistem Informasi Sistemasi: Jurnal Sistem Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Riset Informatika Jurnal Informatika Global Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Software Engineering and Computational Intelligence Journal of Intelligent Networks and IoT Global
Muhammad Haviz Irfani
Universitas Indo Global Mandiri
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Physics

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Software Engineering and Computational Intelligence

 1 
Penjadwalan Mata Pelajaran Menggunakan Algoritma Particle Swarm Optimization (PSO) Pada SMPIT Mufidatul Ilmi Muhammad Muhardeny; Muhammad Haviz Irfani; Juhaini Alie
Jurnal Software Engineering and Computational Intelligence Vol 1 No 1 (2023)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v1i1.3047

Abstract

Scheduling has a division of time based on a work sequence arrangement plan in the form of a list or table of activities or an activity plan with a detailed division of implementation time which is very necessary in carrying out institutional/company business processes. It is important to note the complexity of the process in scheduling appropriate subjects from various perspectives, both teachers, students and classrooms. Provision of teacher teaching schedules based on abilities in the field of subjects, suitable time each semester is very important to consider for very complex schedule arrangements, the number of classrooms that can be used in teaching activities is relatively small, and preventing teacher teaching conflicts so that the need for optimization of eye scheduling lesson to be made. Furthermore, at the stage of application development using the Waterfall method. The purpose of this research is to build a lesson scheduling application at SMPIT Mufidatul Ilmi by applying the particle swarm optimization (PSO) algorithm to compile lesson schedules. Particle Swarm Optimization is a population-based algorithm that exploits individuals in search. In PSO the population is called a swarm and individuals are called particles. Each particle moves at a speed adapted from the search area and stores it as the best position ever achieved. Design analysis includes Use Case Diagrams, Activity Diagrams, Class Diagrams, Sequence Diagrams, Entity Relationship Diagrams (ERD). The results of this study provide several primary data (service) features, especially features to provide scheduling results from processing with the PSO algorithm
Pengaruh Deteksi Tepi Citra Urat Daun Pada Pengenalan Jenis Bibit Jeruk Menggunakan Metode Pengenalan JST-PB dan GLCM Dimas Apriandi; Gasim; Muhammad Haviz Irfani; Muhammad Ikhwan Jambak
Jurnal Software Engineering and Computational Intelligence Vol 3 No 02 (2025)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v3i02.6219

Abstract

Identifikasi awal jenis bibit jeruk sangat penting untuk menjamin kualitas bibit dan meningkatkan produktivitas pertanian. Identifikasi secara manual membutuhkan keahlian khusus dan rentan terhadap kesalahan. Penelitian ini bertujuan untuk menganalisis pengaruh metode deteksi tepi terhadap akurasi klasifikasi bibit jeruk menggunakan Jaringan Syaraf Tiruan Propagasi Balik (JST-PB) dan fitur tekstur yang diekstraksi dengan Gray Level Co-occurrence Matrix (GLCM). Tiga metode deteksi tepi yaitu Canny, Laplacian of Gaussian (LoG), dan Roberts yang diterapkan pada citra daun jeruk dari empat varietas antara lain: Kunci, Nipis, Purut, dan Sambal. Fitur tekstur berupa contrast, correlation, homogeneity, dan entropy digunakan sebagai masukan dalam pelatihan JST-PB. Hasil penelitian menunjukkan bahwa metode Roberts dengan 30 neuron tersembunyi memberikan kinerja terbaik dengan precision rata-rata 75,56%, recall 75,00%, dan F1-score 74,97%. Hal ini menunjukkan bahwa pemilihan metode deteksi tepi berpengaruh signifikan terhadap akurasi klasifikasi. Kombinasi metode deteksi tepi Roberts, ekstraksi fitur GLCM, dan JST-PB terbukti efektif untuk pengenalan otomatis jenis bibit jeruk berbasis citra digital.    
Co-Authors Andika Afrianto Anna Nurlita Daniel Udjulawa DEWI SARTIKA Dimas Apriandi Gasim gasim, Gasim Imelda Saluza, Imelda Juhaini Alie Maharani, Aiga Rizki Muhammad Ikhwan Jambak Muhammad Muhardeny Nazori Suhandi Ramadhani, Kiki Rendra Gustriansyah Sartika, Dewi Siska Anggraini Sri Rahayu