Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Al-Mau'izhoh: Jurnal Pendidikan Agama Islam CSRID
Abdullah, Iqbal
Unknown Affiliation
Religion Humanities Computer Science & IT Education Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Peran Sosialisasi Sekolah Demi Menciptakan Pembelajaran Kooperatif, Inovatif dan Selektif Toyyibah, Niswatun; Ikrom, Bonafid; Abdullah, Iqbal; Maulana El-Yunusi, M. Yusron
Al-Mau'izhoh: Jurnal Pendidikan Agama Islam Vol. 6 No. 1 (2024): Juni 2024
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/am.v6i1.9442

Abstract

This research aims to determine socialization in schools using a cooperative learning model, using a qualitative research approach involving Tunas Buana Middle School Surabaya, that cooperative learning can involve students in learning collaboratively, exchanging ideas and being confident in expressing opinions. The results of this research were collected through interviews and observations, so it can be concluded that by using cooperative learning, students can develop thinking patterns and increase creativity in socializing, as well as having an impact on every lesson. So that students can develop their potential through innovative and selective learning.
Sistem Pakar Diagnosa Penyakit Busuk Kuncup Pada Tanaman Sawit Menggunakan Trend Moment Siddik, Muhammad; Abdullah, Iqbal; Samsir, Samsir; Sirait, Azrai
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 3 (2025): Oktober 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.3.2025.408-420

Abstract

Bud rot disease in oil palm is one of the most serious threats that can significantly reduce productivity and even cause plant death if not detected early. To support a faster and more accurate diagnosis process, this study developed a web-based expert system that applies the Trend Moment method. The system is built on a knowledge base containing the main symptoms of the disease, including wilted and rotting young leaves (G001), foul odor from the bud (G002), easily detached young leaves due to decay (G003), and rotting crown with brown mucus (G004). The system is able to identify three types of diseases, namely bud rot, Phytophthora palmivora, and Erwinia spp.. The diagnosis process is carried out by calculating the weight of symptoms selected by the user and determining the most probable disease based on the highest Trend Moment value. Experimental results on 20 test cases showed that the system achieved an accuracy rate of 100% when compared with expert diagnoses. These findings indicate that the developed expert system has strong potential to be an effective tool for farmers and field extension workers in detecting and managing oil palm diseases at an early stage.
Co-Authors Azrai Sirait Ikrom, Bonafid Maulana El-Yunusi, M. Yusron Samsir Samsir, Samsir Siddik, Muhammad Toyyibah, Niswatun