Article Per Year (5 Year)
p-Index From 2021 - 2026
0.778
P-Index
This Author published in this journals
All Journal Kilat Progresif: Jurnal Ilmiah Komputer Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Bulletin of Computer Science Research Jurnal Informatika: Jurnal Pengembangan IT Teknologi Informasi dan Digital (TRIDI)
Muhammad Nur
Universitas Bani Saleh
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
SELF ADAPTIVE SOFTWARE DENGAN TEKNIK CASE-BASED REASONING UNTUK MENINGKATKAN PERFORMA APPLICATION SERVER Muhamad Nur; Domo Pranowo Kuswandono
KILAT Vol 7 No 2 (2018): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2560.561 KB) | DOI: 10.33322/kilat.v7i2.355

Abstract

Performance of application server is an important attribute that must be maintained quality and stability, because application server operated in dynamic environment with fluctuating user loads and resource levels, its potentially caused unpredictable errors. In order application server performance still optimal, it is need maintains configuration application parameters. But, do that process need deep observation each environment condition changed and of course the cost and time. The approach that can be used is self-adaptive (autonomic computing). Self-adaptive can configure application parameters automatically. Best combination application parameters configuration can be stored on a repository and used as reference when decide new decision for configuration of application server parameters when similar condition is occurred. Cased-based reasoning can do the process. Best approach will be used is self-adaptive with case-based reasoning. This research implements the approach on an experiment application that deployed on glassfish application server. The results show that self-adaptive with case-based reasoning can improve application server performance with significant improvement.
PROTOTIPE APLIKASI PENYIRAMAN TANAMAN MENGGUNAKAN SENSOR KELEMBABAN TANAH BERBASIS MICRO CONTOLLER ATMEGA 328 Rudi Budi Agung; Muhammad Nur; Didi Sukayadi
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 5 No 1 (2019): JOURNAL CERITA
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (549.362 KB) | DOI: 10.33050/cerita.v5i1.235

Abstract

The Indonesian country which is famous for its tropical climate has now experienced a shift in two seasons (dry season and rainy season). This has an impact on cropping and harvesting systems among farmers. In large scale this is very influential considering that farmers in Indonesia are stilldependent on rainfall which results in soil moisture. Some types of plants that are very dependent on soil moisture will greatly require rainfall or water for growth and development. Through this research, researchers tried to make a prototype application for watering plants using ATMEGA328 microcontroller based soil moisture sensor. Development of application systems using the prototype method as a simple method which is the first step and can be developed again for large scale. The working principle of this prototype is simply that when soil moisture reaches a certainthreshold (above 56%) then the system will work by activating the watering system, if it is below 56% the system does not work or in other words soil moisture is considered sufficient for certain plant needs.
Identifikasi Visual Cacat Produk Menggunakan Neural Network Model Backpropagation (Studi Kasus: PT. Panasonic Gobel Eco Solution) Muhammad Nur; Sjaeful Irwan; Danang Santosa
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 2-2 (2019): Special Issue on Seminar Nasional - Inovasi Dalam Teknologi Informasi & Teknol
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i2-2.1865

Abstract

Product defects are common in the production process. Visual identification of product defects is first carried out when the product is produced. Identification of vague defects in very small shapes with different sizes and positions is difficult to do with ordinary eye sight, so that often results in decisions about the status of the product that is not right. Product defects in visual form can be identified by patterns such as shape, size and position on the product image. In this study, we will apply a neural network with the backpropagation model as a classification of the pattern. Product images will be processed using image processing by converting the RGB pixel value of the image into a numeric value. Data in numerical form will be input for training values in the backpropagation model. Training results are used to identify identified product defects and produce product status decisions. The results show that the backpropagation neural network model is able to recognize product patterns with an accuracy of 99.24% and based on simulation test data with the final weight and bias of training results, able to identify product defects with success up to 91%.
IMPLEMENTASI METODE RAD DALAM PENGEMBANGAN APLIKASI BUKU INDUK SISWA BERBASIS WEB Indriani; Muhammad Nur; Widiyawati; Muhammad Dedi Suryadi; Zaenal Mutaqin Subekti
Jurnal Teknologi Informasi dan Digital Vol. 3 No. 2 (2025): Teknologi Informasi dan Digital
Publisher : LPPM Universitas Bani Saleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65624/tridi.v3i2.237

Abstract

Pengelolaan data siswa di SMK Teratai Putih Global 2 Bekasi masih dilakukan secara manual melalui buku besar, sehingga sering menimbulkan permasalahan seperti kesalahan pencatatan, duplikasi data, penyimpanan yang tidak efisien, serta keterlambatan dalam memperoleh informasi. Kondisi tersebut berdampak pada rendahnya efektivitas proses administrasi sekolah. Penelitian ini bertujuan merancang dan mengembangkan aplikasi Buku Induk Siswa berbasis web menggunakan metode Rapid Application Development (RAD). Metode RAD dipilih karena mampu mempercepat proses pengembangan dengan pendekatan iteratif, prototyping, serta keterlibatan pengguna secara intensif. Sistem yang dibangun menyediakan fitur pengelolaan identitas siswa, data kelas, mata pelajaran, kehadiran, dan nilai siswa. Implementasi aplikasi ini diharapkan mampu meningkatkan efisiensi pencatatan serta akurasi data jika dibandingkan dengan metode manual yang digunakan sebelumnya. Selain itu, sistem berbasis web ini memberikan kemudahan akses informasi bagi tata usaha, guru, serta tenaga pendidik lainnya. Hasil pengujian menunjukkan bahwa aplikasi Buku Induk Siswa berbasis web dapat meningkatkan efektivitas pengelolaan data, meminimalkan kesalahan administrasi, dan mempercepat proses pencarian informasi. Dengan demikian, digitalisasi melalui sistem informasi yang terintegrasi merupakan solusi yang tepat untuk mendukung peningkatan kualitas administrasi akademik di SMK Teratai Putih Global 2 Bekasi.
Penerapan Metode Particle Swarm Optimization (PSO) untuk Optimasi Waktu Tunggu pada Sistem Pemesanan Jasa Servis Muhamad Nur; Marisa Marisa; Fadhel Rizky Pratama
Bulletin of Computer Science Research Vol. 6 No. 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i2.962

Abstract

In the competitive service industry, digital transformation of booking management systems has become essential for maintaining customer loyalty. However, many enterprises still rely on manual methods that result in high latency, queue congestion, and imbalanced technician workloads. This study aims to address these inefficiencies by implementing the Particle Swarm Optimization (PSO) algorithm within a web-based service booking system architecture. PSO, a metaheuristic algorithm inspired by the social behavior of animal swarms, is employed to search for globally optimal solutions in a multidimensional search space. The algorithm is configured with 20 particles, a maximum of 100 iterations, and parameters c1 = 2.0, c2 = 2.0, and w = 0.7 to minimize cumulative customer waiting time while balancing technician task allocation based on technician availability, service duration, and operational hour constraints (08:00–16:00). Empirical testing demonstrated significant improvements in operational performance. Prior to optimization, the total customer waiting time over a three-day observation period reached 380 minutes. Following PSO implementation, waiting time was drastically reduced to 150 minutes, representing a 60.53% reduction (230 minutes saved). These findings confirm that the PSO approach not only delivers rapid and adaptive solutions to real-time data fluctuations but also enhances operational system scalability. This research provides a practical contribution for service management system developers seeking to integrate computational intelligence into the optimization of complex business processes.
IMPLEMENTASI ALGORITMA DIJKSTRA UNTUK MENEMUKAN RUTE TERDEKAT PENGAMBILAN BARANG BEKAS BERBASIS WEB PADA LAPAK RONGSOK BROSOT, BEKASI HS. Sulistyowati; Muhammad Nur; Dwi Fajri
Jurnal Teknologi Informasi dan Digital Vol. 3 No. 1 (2025): Teknologi Informasi dan Digital
Publisher : LPPM Universitas Bani Saleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65624/tridi.v3i1.101

Abstract

Pengelolaan sampah dan limbah yang memiliki nilai sebagai bahan baku, khususnya barang bekas, menjadi tantangan dalam hal pengambilan dan rute yang efisien bagi agent pengumpul barang rongsokan. Penelitian ini mengimplementasikan Algoritma Dijkstra untuk menentukan rute terdekat bagi agen rongsokan dalam proses pengambilan barang bekas di Lapak Rongsok Brosot. Aplikasi dirancang agar berjalan pada smartphone dengan platform android yang digunakan mayoritas pada saat ini. Berdasarkan pengujian didapatkan pemilihan rute terpendek menggunakan algoritma dijkstra dinilai sangat efektif berdasarkan pencarian rute terpendek dari setiap perhitungan bobot jarak dengan node yang dijalurkan kearah tujuan. Platform berbasis web yang dikembangkan memanfaatkan algoritma ini mampu mengoptimalkan rute agen, sehingga dapat mengurangi waktu dan tenaga yang dibutuhkan serta meningkatkan efisiensi operasional. Sistem yang dibangun juga memudahkan masyarakat untuk menghubungi agen terdekat, mempercepat proses transaksi, dan meningkatkan jumlah barang yang berhasil dikumpulkan. Selain itu, penelitian ini memberikan peluang bagi pengembangan lebih lanjut melalui penerapan algoritma alternatif serta peningkatan fitur seperti
Komparasi YOLOv8 Nano dan YOLO11 Nano untuk Klasifikasi Penyakit Daun Tomat pada Perangkat Edge Muhammad Nur; Iwan Jaya; Haytsam Adzka Mawla
Progresif: Jurnal Ilmiah Komputer Vol. 22 No. 3 (2026): Juli
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v22i3.3929

Abstract

Tomato leaf diseases pose a significant threat to horticultural productivity, while field identification methods remain highly dependent on expert observation. This study compared the performance of YOLOv8 Nano and YOLO11 Nano for tomato leaf disease classification on an edge device. A dataset of 7,200 tomato leaf images across six disease classes was used; both models were trained under identical configurations with 20 independent seed replications, exported to ONNX format, and evaluated on a Raspberry Pi 5. YOLOv8 Nano achieved a mean accuracy of 88.32% while YOLO11 Nano achieved 87.81%. The Wilcoxon Signed-Rank test confirmed that the accuracy difference was not statistically significant (W = 75.5; p = 0.2706). Nevertheless, YOLOv8 Nano demonstrated shorter mean inference time (8.430 ms vs 8.502 ms; p = 0.0064), smaller model size (5.531 MB vs 5.895 MB), and lower peak memory usage (72.31 MB vs 72.72 MB). Both models proved comparable in classification accuracy, but YOLOv8 Nano is recommended for edge deployment owing to its statistically verified efficiency advantages. Keywords: YOLOv8 Nano; YOLO11 Nano; tomato leaf disease classification; edge device; Wilcoxon Signed-Rank Abstrak Penyakit daun tomat menjadi ancaman serius bagi produktivitas hortikultura, sementara metode identifikasi visual di lapangan masih sangat bergantung pada keahlian pengamat. Penelitian ini membandingkan performa YOLOv8 Nano dan YOLO11 Nano untuk klasifikasi penyakit daun tomat pada perangkat edge. Dataset yang digunakan terdiri dari 7.200 citra daun tomat yang terbagi dalam enam kelas penyakit; kedua model dilatih menggunakan 20 variasi seed independen dengan konfigurasi identik, kemudian diekspor ke format ONNX dan diuji langsung pada Raspberry Pi 5. YOLOv8 Nano memperoleh akurasi rata-rata 88,32%, sedangkan YOLO11 Nano memperoleh 87,81%. Uji Wilcoxon Signed-Rank mengonfirmasi bahwa selisih akurasi tidak signifikan secara statistik (W = 75,5; p = 0,2706). Meski demikian, YOLOv8 Nano menunjukkan waktu inferensi yang lebih singkat (8,430 ms vs 8,502 ms; p = 0,0064), ukuran model lebih kecil (5,531 MB vs 5,895 MB), dan konsumsi memori lebih rendah (72,31 MB vs 72,72 MB). Kedua model terbukti setara dari sisi akurasi klasifikasi, namun YOLOv8 Nano lebih direkomendasikan untuk implementasi edge berkat keunggulan efisiensinya yang terukur.
Co-Authors Danang Santosa Didi Sukayadi Domo Pranowo Kuswandono Dwi Fajri Fadhel Rizky Pratama Haytsam Adzka Mawla HS. Sulistyowati Indriani Iwan Jaya Marisa Marisa Muhammad Dedi Suryadi Rudi Budi Agung Sjaeful Irwan Subekti, Zaenal Mutaqin Widiyawati