Article Per Year (5 Year)
p-Index From 2021 - 2026
1.8
P-Index
This Author published in this journals
All Journal Seminar Nasional Informatika (SEMNASIF) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Mobile and Forensics Jurnal Abdi Insani Budimas : Jurnal Pengabdian Masyarakat JITU : Journal Informatic Technology And Communication Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Komputer, Informasi dan Teknologi Data Sciences Indonesia (DSI)
Muhammad Abdul Aziz
Program Studi Teknik Informatika, Universitas Ahmad Dahlan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Nursing Physics Social Sciences Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : JITU : Journal Informatic Technology And Communication

 1 
Deteksi Pola Kejadian Bencana Menggunakan Algoritma Naïve Bayes di Kabupaten Boyolali Prasetyo, Miranto Sri Agus; Wahyono, Ari; Aziz, Muhammad Abdul
JITU Vol 8 No 1 (2024)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Boyolali Regency, which is geographically located between Mount Merbabu and the still active Mount Merapi, does have high potential as a disaster-prone area. According to data from the Boyolali Regional Disaster Management Agency, during the period from 2022 to 2023, 936 disaster events were recorded in the region. These disasters have a devastating impact on ecosystems and the environment, causing significant material losses, causing psychological disorders, and even threatening human safety. In this context, detecting patterns of disaster events is an important step in disaster mitigation and management efforts. This research was conducted with the aim of understanding patterns of disaster events based on data collected by BPBD Boyolali. The method used is the Naive Bayes algorithm, which has proven to be a powerful tool in data analysis. The results of this research show a high level of accuracy of 92.52%, precision of 92.68%, and recall of 91.64% using the Naive Bayes algorithm. This indicates that the algorithm is effective in recognizing and classifying patterns of disaster events based on existing data. Thus, the results of this research can provide a valuable contribution to the development of an early disaster detection system, as well as assist the authorities in designing more effective mitigation strategies to protect the community and environment in Boyolali Regency.
Pengelompokkan Daerah Rawan Bencana di Kabupaten Boyolali Menggunakan Algoritma K-Means Abdul Aziz , Muhammad; Sanjaya, Wisnu; Rama Pratama Zulkifli Putra
JITU Vol 8 No 2 (2024)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v8i2.1726

Abstract

The country of Indonesia, which is located in the Southeast Asia region, faces a high challenge of disasters due to demographic, geological and geographical factors that influence the occurrence of disasters, both those caused by natural, non-natural and human factors. In the Province of Central Java, especially Boyolali, disasters pose a significant threat, especially when the weather is uncertain. However, to identify priority areas for the lowest and highest levels of natural disasters in Boyolali, it is necessary to improve using data mining methods, therefore to facilitate analysis and grouping of data in identifying disaster-prone areas in Boyolali, the K-Means clustering algorithm is used. The method used in this research is qualitative and the data is analyzed using the Rapidminer Studio Ver application. 9.10. Based on the results of the analysis, there is a division of disaster-prone areas into 3 clusters in Boyolali Regency, namely very high vulnerability, medium vulnerability, and low vulnerability. The results of calculations with Rapidminer show that there are 3 sub-districts in cluster 2, 2 sub-districts in cluster 1, and 17 sub-districts in cluster 0. It should be noted that manual calculations can produce differences because the cluster center point or centroid is taken randomly for each calculation method. It is hoped that this grouping of areas can be used as a support for the Boyolali regional BPBD to focus on anticipatory steps to reduce the impact of disasters on society that may occur in the future.
Implementasi Front-End Responsif Sistem Bantuan Sosial Berbasis Bootstrap di Dinsos Boyolali Wahit Fitriyanto; Muhammad Abdul Aziz; Amelia; Dhefi Intan Lukmana
JITU Vol 9 No 1 (2025)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v9i1.1828

Abstract

Dinas Sosial Kabupaten Boyolali memiliki tanggung jawab besar dalam mengelola dan mendistribusikan bantuan sosial kepada masyarakat yang membutuhkan. Namun, proses pencatatan barang masuk dan keluar yang masih dilakukan secara manual menimbulkan berbagai kendala seperti ketidakefisienan dan risiko kesalahan data. Penelitian ini bertujuan untuk mengembangkan tampilan user interface yang user-friendly menggunakan framework Bootstrap berbasis web untuk memudahkan pengelolaan barang bantuan sosial. Metode yang digunakan adalah prototype dengan tahapan analisis kebutuhan, desain, implementasi, evaluasi, perbaikan, dan pemeliharaan. Pengembangan sistem memanfaatkan framework Laravel, Bootstrap, dan database MySQL. Sistem yang dikembangkan mencakup dua modul utama yaitu modul pendataan barang persediaan bantuan sosial dan modul pelaporan barang ke Kementerian. Hasil pengujian menggunakan blackbox testing menunjukkan tingkat kemudahan penggunaan sistem dengan persentase sangat mudah sebesar 22% dan mudah 78%. Implementasi sistem ini telah memungkinkan Dinas Sosial Kabupaten Boyolali mengelola barang masuk dan keluar dengan lebih baik, membuat pencatatan menjadi lebih efisien, dan mempercepat proses pembuatan laporan dari harian hingga tahunan. Sistem ini juga menyediakan keamanan data yang terlindungi dari akses yang tidak sah.
Co-Authors Ahmad Yani Amelia Ammar Fauzan ardiyanto, joko Ari Wahyono Arifin Arifin Aryo Putro, Fanny Hendro Asmedy Asmedy Chumaeson, Wahyuning Dhefi Intan Lukmana Donna Setiawati FADILA, NUR Fathirma'ruf Hertini, Etty Sri Imam Riadi Imam Riadi Lestari, Istiqomah Dwi Lestari, Jihan Lukmana, Dhefi Intan Nurjayanti, Alfilla Prasetyo, Aris Budi Prasetyo, Miranto Sri Agus prayudi, Andi Putro, Fanny Hendro Aryo R, Yusuf Rama Pratama Zulkifli Putra Rochani, Muhammad Rohmadi, Yusuf Eko Rusydi Umar Sanjaya, Wisnu Setiawan, Topan Sigit Muryanto, Sigit Supriyaddin Supriyaddin W, Yunanri Wahit Fitriyanto