Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Kursor Indonesian Journal of Electrical Engineering and Computer Science Jurnal Rekayasa Sistem Informasi dan Teknologi
Muhammad Fajrul Falah
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
INTELLIGENT SYSTEM FOR AUTOMATIC CLASSIFICATION OF FRUIT DEFECT USING FASTER REGION-BASED CONVOLUTIONAL NEURAL NETWORK (FASTER R-CNN) Hasan Basri; Iwan Syarif; Sritrusta Sukaridhoto; Muhammad Fajrul Falah
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.187

Abstract

In 2018, the Indonesian fruit exports increased by 24% from the previous year. The surge in demand for tropical fruits from non-tropical countries is one of the contributing factors for this trend. Some of these countries have strict quality requirements – the poor level quality control of fruit is an obstacle in achieving greater export yield. This is because some exporters still use manual sorting processes performed by workers, hence the quality standard varies depending on the individual perception of the workers. Therefore, we need an intelligent system that is capable of automatic sorting according to the standard set. In this research, we propose a system that can classify fruit defects automatically. Faster R-CNN (FRCNN) architecture proposed as a solution to detect the level of defect on the surface of the fruit. There are three types of fruit that we research, its mangoes (sweet fragrant), lime, and pitaya fruit. Each fruit divided into three categories (i) Super, (ii) middle, (iii) and fruit defects. We exploit join detection and video tracking to calculate and determine the quality fruit in real-time. The datasets are taken in the field, then trained using the FRCNN Framework using the Tensorflow platform. We demonstrated that this system can classify fruit with an accuracy level of 88% (mango), 83% (lime), and 99% (pitaya), with an average computation cost of 0.0131 m/s. We can track and calculate fruit sequentially without using additional sensors and check the defect rate on fruit using the video streaming camera more accurately and with greater ease.
Comparison of cloud computing providers for development of big data and internet of things application Muhammad Fajrul Falah; Yohanes Yohanie Fridelin Panduman; Sritrusta Sukaridhoto; Arther Wilem Cornelius Tirie; M. Cahyo Kriswantoro; Bayu Dwiyan Satria; Saifudin Usman
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1723-1730

Abstract

The improved technology of big data and the internet of things (IoT) increases the number of developments in the application of smart city and Industry 4.0. Thus, the need for high-performance cloud computing is increasing. However, the increase in cloud computing service providers causes difficulties in determining the chosen service provider. Therefore, the purpose of this study is to make comparisons to determine the criteria for selecting cloud computing services following the system architecture and services needed to develop IoT and big data applications. We have analyzed several parameters such as technology specifications, model services, data center location, big data service, internet of things, microservices architecture, cloud computing management, and machine learning. We use these parameters to compare several cloud computing service providers. The results present that the parameters able to use as a reference for choosing cloud computing for the implementation of IoT and big data technology.
Implementation of Mobile Academic Information System Web Services (Case Study UAM Cybercampus).: Implementasi Web Service Sistem Informasi Akademik Berbasis Mobile (Studi Kasus Cybercampus UAM). Putri Ariatna Alia; Agung Teguh Setyadi; Erik Yohan Kartiko; Rusina Widha Febriana; Rony Kriswibowo; Muhammad Fajrul Falah
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 3 No. 4 (2026): Mei
Publisher : Yayasan Nuraini Ibrahim Mandiri

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

Abstract

Perkembangan teknologi informasi menuntut institusi pendidikan menyediakan layanan akademik yang cepat, akurat, dan mudah diakses. Universitas Anwar Medika memerlukan sistem informasi akademik berbasis mobile yang mampu meningkatkan fleksibilitas akses bagi mahasiswa dan dosen. Penelitian ini bertujuan mengimplementasikan RESTful Web Service sebagai media integrasi antara sistem Cybercampus berbasis web dengan aplikasi mobile sehingga layanan akademik dapat diakses secara real-time tanpa melakukan perubahan pada sistem backend yang telah ada.Pen elitian menggunakan metode pengembangan Waterfall yang meliputi tahap analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan evaluasi. Web Service dikembangkan menggunakan framework Laravel dengan arsitektur REST dan format pertukaran data JSON, sedangkan aplikasi mobile dibangun menggunakan platform Kodular. Pengujian dilakukan melalui black-box testing, beta testing menggunakan skala Likert, serta pengujian kinerja sistem yang meliputi response time, throughput, uptime, dan kompatibilitas aplikasi mobile. Hasil penelitian menunjukkan bahwa sistem berhasil mengintegrasikan layanan akademik ke dalam aplikasi mobile dengan baik. Pengujian kinerja menunjukkan response time sebesar 280 ms, page load time 1,82 detik, uptime 99,87%, throughput 168 request/detik, serta error rate sebesar 0,14%. Selain itu, hasil beta testing memperoleh nilai rata-rata di atas 4,30 pada seluruh indikator, yang menunjukkan bahwa aplikasi diterima dengan baik oleh pengguna. Dengan demikian, implementasi Web Service berbasis REST mampu meningkatkan aksesibilitas layanan akademik secara efektif, responsif, dan andal.
Co-Authors Agung Teguh Setyadi Arther Wilem Cornelius Tirie Erik Yohan Kartiko Hasan Basri iwan Syarif M. Cahyo Kriswantoro Putri Ariatna Alia Rony Kriswibowo Rusina Widha Febriana Satria, Bayu Dwiyan Sritrusta Sukaridhoto Yohanes Yohanie Fridelin Panduman