Article Per Year (5 Year)
p-Index From 2021 - 2026
3.127
P-Index
This Author published in this journals
All Journal Jurnal Mantik Penusa INTECOMS: Journal of Information Technology and Computer Science The IJICS (International Journal of Informatics and Computer Science) Jurnal Riset Informatika ComTech: Computer, Mathematics and Engineering Applications Jurnal Mantik bit-Tech Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bulletin of Information Technology (BIT) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Testing dan Implementasi Sistem Informasi Journal of Algorithmic Digital Engineering and Networks
Muhammad Iqbal
Universitas Pembangunan Panca Budi
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics

Published : 22 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 22 Documents
Search

 1   2   3 
Fungal Disease Detection Using CNN Deep Learning Method Dika Dika; Muhammad Iqbal
JADEN : Journal of Algorithmic Digital Engineering and Networks Vol. 1 No. 2 (2026): The Journal of Algorithmic Digital Engineering and Networks
Publisher : Cv. Data Sinergi Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65853/jaden.v1i2.120

Abstract

This study aims to detect mushroom diseases based on digital images using the Deep Learning Convolutional Neural Network (CNN) method. Fungal diseases are often the main cause of decreased quality and yield, so a fast and accurate detection method is needed. The dataset used consists of images of healthy mushrooms and diseased mushrooms obtained through direct image capture at the cultivation location. The research stages include image preprocessing, CNN model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results show that the CNN model is able to detect mushroom diseases with a high level of accuracy, so this method has the potential to be used as a decision support system in mushroom cultivation.
Analisis Tren Pendaftaran Siswa Menggunakan Big Data di Yayasan Pendidikan Raksana Medan Nadya Septiani Nadya; Muhammad Iqbal
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1744

Abstract

Yayasan Pendidikan Raksana Medan is an educational institution encompassing SMP, SMA, SMK-1, and SMK-2 levels. With an increasing number of students each year, analyzing student enrollment data has become crucial for strategic planning and decision-making. This study aims to analyze student enrollment trends using a Big Data approach to identify enrollment patterns, study program preferences, and factors influencing the number of applicants. The data used includes enrollment information from the past five years, such as demographic data, program choices, and enrollment timing. The analysis was conducted using data mining methods and data visualization to identify specific trends and patterns. The results of the study indicate a significant increase in applicants to vocational programs, with the majority of applicants coming from areas around Medan. These findings are expected to assist Yayasan Pendidikan Raksana Medan in improving marketing strategies and curriculum adjustments based on student and community demand
Co-Authors , Arpan Abdul Muin Nasution Ahkyar Khadafi Ardiansyah Ardiansyah Astri Aprilia Pratiwi Atja Ramadhan Boy Rizky Akbar Chairul Rizal Dika Dika DWI SURYANTO Efendi, Syahril Eko Hariyanto Firdaus Firdaus Hafizh Sallam Kairul Fahmi Khairunnisa Khairunnisa Kurnia Wira Syahputra Muhammad Adli Afdika Muhammad Eka Muhammad Israr Fathoni Muhammad Noor Hasan Siregar Nadya Septiani Nadya Niska, Debi Yandra Putra, Randi Rian Rindi Antika Sapna Indah Br Ginting Sartika Siburian Siti Hapsoh Lubis Sumarno Supiyandi Supiyandi Syaiful Asmi Hasibuan