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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JURNAL NASIONAL TEKNIK ELEKTRO JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Information Technology and Computer Engineering Jurnal Hilirisasi IPTEKS (JHI) Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG) Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Andalas Journal of Electrical and Electronic Engineering Technology Jurnal Andalas: Rekayasa dan Penerapan Teknologi Kreativitas Pada Pengabdian Masyarakat (Krepa)
Rusydi, Muhammad Ilhamdi
Universitas Andalas
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Veterinary Other

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Pengembangan Instrumen Pewarnaan Alam pada Studio Wastra Pinankabu Muhammad Ilhamdi Rusydi; Prima Fithri; Haznam Putra; Andi Pawawoi; Muhammad Imran Hamid; Riko Nofendra
Warta Pengabdian Andalas Vol 28 No 4 (2021)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jwa.28.4.514-520.2021

Abstract

One of the obstacles the Pinankabu studio faces is the lack of adequate equipment for processing silk threads and the currently available dyeing equipment for natural dyeing. Some equipment such as degumming pans, hangers, furnaces, and stoves are no longer suitable for needs. The properties of silk, which vary with demand and temperature, must be studied under appropriate conditions. Currently, partners can not confirm whether these conditions are met at work. The planned solution to this problem is the design of degumming pans, hangers, furnaces, and stoves that can increase work effectiveness and improve the quality of production and design systems to measure pH and temperature accurately and in real-time. This activity aims to develop yarn processing equipment at Pinankabu studio to increase productivity and maintain product quality. The expected benefits of this activity are that partners have natural colouring instruments that can improve the quantity and quality of production. Operators can work comfortably because the equipment is designed to design ergonomic users. Equipment that will be developed is an example of a similar business. The method used was the implementation of engineered products on partners. The implementation stages consisted of problem formulation, solution determination, solution design, implementation, evaluation, and activity outputs. The expected result is that partners can increase the productivity and quality of the yarn produced.
Pattern Recognition of Overhead Forehand and Backhand in Badminton Based on the Sign of Local Euler Angle Muhammad Ilhamdi Rusydi; Syamsul Huda; Febdian Rusydi; Muhammad Hadi Sucipto; Minoru Sasaki
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i3.pp625-635

Abstract

Studying the badminton skill based on the arm movement is a challenge since the limitation of the sensor such as camera to record the movement parameter. This study proposed a new method to determine the pattern of arm movement for forehand and backhand strokes in badminton based on the sign of the local Euler angle gradient from four points of right arm segments. Each segment was identified by motion sensor attached to the dorsal surface of the hand (sensor 1), wrist (sensor 2), elbow (sensor 3) and shoulder (sensor 4). Three certified coaches participated in this research to determine the arm movement patterns for forehand and backhand strokes. Skills in forehand and backhand strokes from eight professional players and eight amateur players were observed to determine the pattern. The result showed that the local Euler angle can be used to recognize the arm movement pattern. Based on the observed patterns, the professional players had a higher similarity to the coaches’ patterns than those amateur players to the coaches’.
Pengaruh Media Ajar Interaktif dalam Pengajaran Sistem Tubuh Manusia di SDN 01 Sawahan Kota Padang Muhammad Ilhamdi Rusydi; Devianda Ananta Sandri; Riko Chandra; Avelia Fairuz Faadhilah; Khairunnisa Lizzikrillah; Robbi Noberlam Dasyura; Vinoza Shalsabila
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 1 No. 1 (2021): Juni 2021
Publisher : Jurusan Teknik Elektro, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (307.663 KB) | DOI: 10.25077/jarpet.v1i1.3

Abstract

Media ajar berperan penting dalam memberi pemahaman sebuah materi kepada siswa. Guru kelas lima SDN 01 Sawahan, Padang mengalami permasalahan dalam pelaksanaan pembelajaran Ilmu Pengetahuan Alam (IPA) mengenai Sistem Tubuh Manusia. Selama ini pembelajaran masih menggunakan media ajar konvensional yaitu gambar dua dimensi tubuh manusia dan patung manusia. Hal ini menyebabkan siswa terkendala dalam memahami proses yang terjadi di dalam sistem tubuh manusia karena media ajar sebelumnya bersifat statis dan tidak interaktif. Untuk mengatasi kendala tersebut,dirancang sebuah situs web pembelajaran bernama TEORITY yang dapat membantu guru dalam mengajar sistem tubuh manusia secara visual dan rinci. Materi website membantu siswa dalam memahami sisi dalam dan sisi luar organ dalam tubuh.Situs web TEORITY di laman www.teoritypkmunand.ikonyoa.com telah dirancang dengan fitur menarik seperti animasi, kuis, dan permainan edukatif yang dapat membantu siswa memahami materi sistem tubuh secara visual dan rinci. Dari uji coba yang telah dilakukan dapat diamati bahwa situs web TEORITY yang dirancang berhasil memudahkan guru dalam menjelaskan materi sistem tubuh secara visual,rinci dan interaktif. Sesuai dengan hasil ini pihak sekolah berencana untuk menggunakan dan mengembangkan situs web ini kedepannya dengan bekerja sama dengan Tim pembuat situs web TEORITY
Penerapan Sel Surya sebagai Energi Listrik Alternatif di Alfi Hidroponik Padang Zaini Zaini; Heru Dibyo Laksono; Rahmadi Kurnia; Darwison Darwison; Darmawan Darmawan; Mumuh Muharram; Syarkawi Syamsuddin; Riko Nofendra; Muhammad Ilhamdi Rusydi
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 1 No. 2 (2021): Desember 2021
Publisher : Jurusan Teknik Elektro, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (562.152 KB) | DOI: 10.25077/jarpet.v1i2.15

Abstract

Energi listrik adalah salah satu kebutuhan utama bagi usaha pertanian hidroponik. Mereka butuh untuk mengalirkan nutrisi tanaman melalui air secara terus-menerus menggunakan pompa. Jika sumber energi listrik terputus, maka akan menyebabkan tanaman tidak tumbuh sempurna. Oleh karena itu, pada kegiatan ini dilakukan penerapan sel surya sebagai energi listrik alternatif pada mitra pengabdian Alfi Hidroponik. Kegiatan dilaksanakan dengan merancang kebutuhan sel surya pada usaha hidroponik. Batrai Aki 40 Ah dapat menjadi sumber energi listrik bagi usaha mitra yang kebutuhan dayanya 85 watt selama minimal 10 jam. Selain penerapan sel surya, pada pengabdian ini juga dikembangkan beberapa sensor untuk memonitor suhu dan kelembaban lahan pertahian. Kegiatan ini dapat menjawab kebutuhan mitra dan masih diperlukan penerapan teknologi lainnya pada usaha hidroponik untuk optimalisasi produksi mitra.
Faktor Penyebab dan Upaya Mengatasi Area Titik Buta pada Truk Muhammad Ilhamdi Rusydi; Yoan Winata; Dhiny Yurichy Putri; Muhammad Fikri
Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG) Vol 8, No 3 (2021): NOVEMBER
Publisher : Institut Transportasi dan Logistik Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54324/j.mtl.v8i3.505

Abstract

Truck drivers cannot see the entire area around the vehicle. This area that cannot be seen is called a blind spot. This article aims to analyze the factors causing blind spot areas on trucks and discuss the efforts that have been made to address the blind spots on trucks. The writing method used is a literature study of the research that has been done. The keywords used in the reference search include blind spot, driver and anthropometry. The search results show that the blind spot area is on each side of the truck, either caused by the vehicle design or the driver's anthropometry. Various attempts have been made to address blind spot areas, such as the use of mirrors, cameras and sensors. In addition, expanding the driver's vision area from inside the cabin can also be a solution. Based on the results of the literature study, it is concluded that the blind spot area is influenced by vehicle design and driver anthropometry
The Use of Artificial Neural Networks in Agricultural Plants Roza Susanti; Riko Nofendra; Zaini Zaini; Muhammad Syaiful Amri bin Suhaimi; Muhammad Ilhamdi Rusydi
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 2 No. 2 (2022): November 2022
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v2i2.32

Abstract

Artificial Neural Networks use high-performance computing and big data technology, opportunities for science to create new opportunities in agriculture. The purpose of writing this article is to analyze the use of artificial neural networks on (a) plant diseases based on plant leaf diseases, (b) plant pests, (c) growth or quality, and (d) agricultural products. The writing method used is a literature study of the research that has been done. The keywords used in the search for references include ANN, plant, diseases, pests, growth or quality, and agricultural products. Publishers for the reference in this article are ScienceDirect and IEEE. The years of publication of the references are restricted from 2015 to 2022. Based on the literature study results, it was concluded that Artificial Neural Networks' deep learning models are accurate for detecting and classifying leaf diseases and pests, detecting growth, and application to agricultural plant products.
A Systematic Literature Review of Automation Quality of Service in Computer Networks: Research Trends, Datasets, and Methods Budi Sunaryo; Muhammad Ilhamdi Rusydi; Ariadi Hazmi; Minoru Sasaki
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4810

Abstract

The article is a systematic literature review of the use of automation for quality of service (QoS) in computer networks. It summarizes the research trends, datasets, and methods used in the field and provides an overview of the current state of the art. The focus of the review is on the use of automation for QoS management and improvement in computer networks, including the use of machine learning, artificial intelligence, and other computational techniques. The review highlights the need for further research and development in this area and provides insights into future directions for the field. The review covered a wide range of studies, including research papers and conference proceedings, and involved a comprehensive database search of the Scopus database covering journals and proceedings such as the Institute of Electrical and Electronics Engineers (IEEE) Xplore, Association for Computing Machinery (ACM) Digital Library, Springer, and ScienceDirect databases between 2017 and September 2022. From these databases, 1856 metadata were found, which eventually became seventy-three metadata after going through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.
Hand Gesture to Control Virtual Keyboard using Neural Network Arrya Anandika; Muhammad Ilhamdi Rusydi; Pepi Putri Utami; Rizka Hadelina; Minoru Sasaki
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.40-48.2023

Abstract

Disability is one of a person's physical and mental conditions that can inhibit normal daily activities. One of the disabilities that can be found in disability is speech without fingers. Persons with disabilities have obstacles in communicating with people around both verbally and in writing. Communication tools to help people with disabilities without finger fingers continue to be developed, one of them is by creating a virtual keyboard using a Leap Motion sensor. The hand gestures are captured using the Leap Motion sensor so that the direction of the hand gesture in the form of pitch, yaw, and roll is obtained. The direction values are grouped into normal, right, left, up, down, and rotating gestures to control the virtual keyboard. The amount of data used for gesture recognition in this study was 5400 data consisting of 3780 training data and 1620 test data. The results of data testing conducted using the Artificial Neural Network method obtained an accuracy value of 98.82%. This study also performed a virtual keyboard performance test directly by typing 20 types of characters conducted by 15 respondents three times. The average time needed by respondents in typing is 5.45 seconds per character.
ANN Models for Shoulder Pain Detection based on Human Facial Expression Covered by Mask Rizka Hadelina; Muhammad Ilhamdi Rusydi; Mutia Firza; Oluwarotimi Williams Samuel
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.7.01.49-55.2023

Abstract

Facial expressions are a method to communicate if someone feels pain. Moreover, coding facial movements to assess pain requires extensive training and is time-consuming for clinical practice. In addition, in Covid 19 pandemic, it was difficult to determine this expression due to the mask on the face. There for, it needs to develop a system that can detect the pain from facial expressions when a person is wearing a mask. There are 41 points used to form 19 geometrical features. It used 20.000 frames of 24 respondents from the dataset as secondary data . From these data, training, and testing were carried out using the ANN (Artificial Neural Network) method with a variation of the number of neurons in the hidden layer, i.e., 5, 10, 15, and 20 neurons. The results obtained from testing these data are the highest accuracy of 86% with the number of 20 hidden layers.
Identification of Coffee Types Using an Electronic Nose with the Backpropagation Artificial Neural Network Roza Susanti; Zaini Zaini; Anton Hidayat; Nadia Alfitri; Muhammad Ilhamdi Rusydi
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1375

Abstract

Coffee is one of the famous plants’ commodities in the world. There are some coffee powders such as Arabica dan Robusta. This study aimed to identify two various coffee powders, Arabica and Robusta based on the blended aroma profiles, employing the backpropagation Artificial Neural Network (ANN). Four taste sensors were employed, namely TGS 2602, 2610, 2611, and 2620, to capture the diverse coffee aroma. These detectors were combined with the aroma sensors having transducers integrated with signal amplifiers or processors, which featured a load of 10 KΩ resistance. Three aroma types were investigated, namely Arabica coffee, Robusta coffee, and without coffee beans. The neural network architecture consisted of four inputs from all sensors, with one hidden layer housing eight neurons. Two neuron outputs were employed for classification, with 70 samples used for training ANN for each type. During the training phase, the developed neural network showed an impressive accuracy rate of 91.90%. TGS 2602 and 2611 sensors showed the most significant differences among the three aroma types. When analyzing ground Robusta coffee, TGS 2602 and 2611 sensors recorded 2.967 volts and 1.263 volts, with a gas concentration of 17.92 ppm and 2441.8 ppm. Similarly, the sensors for ground Arabica coffee displayed 3.384 volts and 1.582 volts with a gas concentration of 20.445 ppm and 3058.5 ppm in both TGS 2602 and 2611, respectively. The implemented ANN with aroma sensor as input successfully identify the coffee powders.
Co-Authors . Darwison Agung W. Setiawan Agung Wibowo Ardiyanta Surbakti Andi Pawawoi Andrivo Rusydi Andrivo Rusydi Anton Hidayat Ariadi Hazmi Arrya Anandika Aulia Novira Aulia Rahman Avelia Fairuz Faadhilah Azmi, Luxfy Roya Budi Agung Santoso Budi Sunaryo Chatarina Umbul Wahyuni Daelita Berliana H. Devianda Ananta Sandri Dhiny Yurichy Putri Dhiny Yurichy Putri Elmiyasna Kimin Febdian Rusydi Hafidzah Putri Rahmadani Haznam Putra Hermawan Nugroho Ikhwan Arief Jack Febrian Rusdi Joseph Muguro Joseph Muguro Khairunnisa Lizzikrillah Kojiro Matsushita Laksono, Heru Dibyo M. Farhan Minoru Sasaki Minoru Sasaki Minoru Sasaki Muhammad Dani Anwar Muhammad Fikri muhammad fikri Muhammad Hadi Sucipto Muhammad Imran Hamid Muhammad Ismail Opera Muhammad Khalish Muhammad Naufalun Nabil Muhammad Syaiful Amri bin Suhaimi Muhammad Syaiful Amri bin Suhaimi Mumuh Muharram Mutia Firza Nadia Alfitri Nurul Azizah Dhuha Oluwarotimi Williams Samuel Pepi Putri Utami Pepi Putri Utami Pratama Halim Prima Fithri Pringgo Widyo Laksono Rahdian Hadi Farhan Rahmadi Kurnia Ramadhani, Salisa 'Asyarina Ridho Tullah Syahputra Rifda Suriani Riko Chandra Riko Nofendra Riko Nofendra Rio Nakajima Rizka Hadelina Robbi Noberlam Dasyura Roza Susanti Roza Susanti Sunaryo, Budi Syafii . Syafril Daus Syamsul Huda Syarkawi Syamsuddin Takaaki Iida Takayuki Nakagome Taufiqurrahman Vinoza Shalsabila Waweru Njeri Waweru Njeri Yoan Winata Yoan Winata Zaini Zaini Zaini, Zaini