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All Journal Informatik : Jurnal Ilmu Komputer Jurnal Teknologi Terapan JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer International Journal of Marine Engineering Innovation and Research JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Hendy Rudiansyah
Politeknik Manufaktur Bandung
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Transportation

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Pengendalian Robot Humanoid Menggunakan Metode Speech Recognation Berbasis Android Hendy Rudiansyah; Gun Gun Maulana; Atep Puja T H
Jurnal Teknologi dan Rekayasa Manufaktur Vol 2 No 1 (2020): Vol 2 No 1 (2020): Volume: 2 | Nomor: 1 | April 2020
Publisher : Pusat Pengembangan, Penelitian dan Pengabdian kepada Masyarat (P4M) Politeknik Manufaktur Bandung (Polman Bandung)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48182/jtrm.v2i1.14

Abstract

Pengendalian Robot saat ini memerlukan sistem kontrol yang dapat memudahkan interaksi antara manusia dan robot sehingga dalam hal ini dibutuhkan sebuah sistem pengendalian dengan perangkat yang banyak digunakan dalam kehidupan sehari-hari yaitu Smartphone dengan Sistem Operasi Android. Penelitian ini bertujuan untuk merancang dan membuat sistem pengendalian robot humanoid dengan memanfaatkan smartphone android sebagai media komunikasi dan intruksi dengan menggunakan perintah suara. pada Android serta sebagai data perintah pergerakan robot humanoid yang ditransmisikan secara online melalui Firebase yang berarti Aplikasi Smartphone dan Robot harus terkoneksi internet. Perangkat pengolah data yang digunakan pada robot adalah Raspberry Pi 3 Model B dengan protokol komunikasi serial dalam mengirim data pergerakan ke motor servo. Hasil penelitian menunjukan bahwa robot dapat dikendalikan dengan perintah suara secara jarak jauh pada Smartphone, serta mudah dioperasikan tanpa membutuhkan perangkat khusus, dari hasil uji kecepatan pengiriman data yaitu rata-rata 5,58 detik dengan kecepatan internet sebesar 7,79Mbps, kemudian penangkapan suara rata-rata error sebesar 1,86%.
IMPLEMENTASI KONTROLER PID DENGAN METODE TUNING ZIEGLER-NICHOLS DAN COHEN-COON PADA SISTEM SCADA KENDALI LEVEL AIR Hadi Supriyanto; Fitria Suryatini; Abdur Rohman Harits Martawireja; Hendy Rudiansyah
Jurnal Teknologi Terapan Vol 8, No 2 (2022): Jurnal Teknologi Terapan
Publisher : P3M Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31884/jtt.v8i2.410

Abstract

Didactics or mini plant teaching aids help students in colleges to understand the use of industrial equipment The SCADA-based water level control system is one of the teaching aid simulator equipment for monitoring and controlling water levels. In this research, PLC is used as a controller with three I/O modules  digital input module, digital output, and analog input and output. Arduino is also used as an analog output converter from PLC to actuator. The control method used is PID control. In the PID control, there are control parameters, namely Kp, Ki, and Kd. The third parameter was determined by the Ziegler-Nichols tuning method and compared with the Coohen-Coon method. The SCADA software that used is Wonderware Intouch on a system using a kepserver. The results of this study indicate that the Cohen-Coon tuning method for proportional control Kp = 1 produces the best response in water level control with a settling time of 21s and a rise time of 18s.
Automation Forklift System untuk Penyimpanan Produk pada Gudang Berbasis Labview Gun Gun Maulana; Hendy Rudiansyah; Salwa Nahlya Tazkia
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 1 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i1.2334

Abstract

One of the functions of the warehouse is to store finished products. Stored products will be grouped based on the same type of material or goods, with boxes that have been marked in color or other codes in accordance with the specified classification. In the warehousing system, vertical storage helps in maximizing the use of warehouse areas. Storage of goods that are still manual with the aid of a forklift also has a high risk of damage due to work equipment accidents. The application of automation technology to the warehousing system is needed because it allows the storage and retrieval of products to run more easily and regularly than done manually. This study aims to create an automatic multilevel storage system as a solution to improve work safety and facilitate workers in storing finished products. This system is made in the form of an elevator with a rack containing 12 cells. The elevator is driven by a stepper motor to move in the direction of the X, Y, and Z axis and is controlled through an Arduino Mega 2560 microcontroller. Object identification is carried out by the TCS 3200 color sensor and the infrared obstacle sensor to read the height of the object. In this study, prototype storage and lifter systems have been achieved as movers for storing boxes on shelves. The results showed success in shipping boxes according to the intended address, but there were still average error values on the x-axis motion of 0.125%, and on the z-axis of 0.11%. Keywords— Arduino Mega 2560; Forklift; Labview; Sensor TCS 3200; Warehouse
Implementasi Sistem Kendali Kecepatan Motor Induksi Berbasis IoT (ESP32-Blynk) pada Indoor Wall Climbing Narwikant Indroasyoko; Ike Yuni Wulandari; Hendy Rudiansyah; Muhamad Fauzi
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 10 No. 1 (2026): Volume 10 Nomor 1 Januari 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v10i1.15633

Abstract

Pertumbuhan fasilitas indoor wall climbing di Indonesia mendorong kebutuhan sistem penggerak yang lebih aman, fleksibel, dan mudah dikendalikan. Pada umumnya, pengaturan kecepatan motor induksi pada fasilitas tersebut masih dilakukan secara manual melalui panel inverter, sehingga kurang responsif dan tidak praktis. Penelitian ini merancang dan membangun sistem kendali kecepatan motor induksi satu fasa berbasis mikrokontroler ESP32 yang terintegrasi dengan Internet of Things (IoT) menggunakan aplikasi Blynk. Sistem menggabungkan dua mode kendali, yaitu kendali manual melalui potensiometer dan push button, serta kendali jarak jauh melalui aplikasi IoT. Metode perancangan menggunakan pendekatan VDI 2206 yang mencakup analisis kebutuhan, desain sistem mekanik, elektrik, dan perangkat lunak, integrasi komponen, serta verifikasi dan validasi. Sinyal kecepatan motor dihasilkan melalui DAC MCP4725 yang mengonversi output digital ESP32 menjadi tegangan analog 0–5 V sebagai referensi frekuensi inverter Yuanshin V9. Pengujian dilakukan untuk melihat hubungan antara potensiometer, tegangan DAC, frekuensi inverter, dan kecepatan putaran dinding. Hasil menunjukkan bahwa sistem mampu menghasilkan kendali kecepatan yang linier, stabil, dan responsif pada rentang 0–50 Hz. Perbandingan antara input manual dan IoT menunjukkan performa yang konsisten dengan deviasi sangat kecil. Tombol start/stop fisik dan virtual juga bekerja dengan baik tanpa keterlambatan yang signifikan. Sistem ini terbukti meningkatkan fleksibilitas kontrol, kemudahan operasi, dan keamanan penggunaan pada fasilitas indoor wall climbing
Implementation of Waypoint Navigation and Computer Vision for Monitoring Markers on a Quadcopter Based on ROS (Robot Operating System) Setyawan Ajie Sukarno; Hendy Rudiansyah; Ahsan Basyar
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 1 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i1.4735

Abstract

Indonesia shares borders with Papua New Guinea, Malaysia, and Timor Leste, where border markers often face displacement or disputes due to challenging and inaccessible terrain. This research develops a waypoint navigation system on a quadcopter, integrating computer vision to enhance the detection and monitoring of border markers. The system leverages the Robot Operating System (ROS) as middleware for seamless integration and control, while a camera detects ArUco markers placed on boundary markers. Image processing, implemented using OpenCV integrated with ROS, facilitates efficient data conversion. The quadcopter autonomously navigates to target coordinates based on marker detection, with an average percentage error of 3.3% for the X-axis and 2.5% for the Y-axis. Tests showed the system could detect a 40x40 cm marker from a height of 5 meters up to a distance of 14 meters, with an average position error of 3.75%. The communication range was effective up to 150 meters before timing out. Despite the computational limitations of the Raspberry Pi hardware, the system demonstrated efficiency, scalability, and ease of deployment. Future research will focus on hardware enhancements, the exploration of advanced image processing methodologies, improved camera resolutions, and the extension of communication networks to support deployment in national boundary monitoring operations.
Implementation Of Kalman Filter at IoT Animal Weighing Nuryanti; Danu Jaya Saputro; Ismail Rokhim; Hendy Rudiansyah; Sandy Bhawana Mulia; Wahyu Adhie Candra; M Wahyu Firmansyah
Informatik : Jurnal Ilmu Komputer Vol 22 No 2 (2026): August 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i2.13604

Abstract

Animal weighing is an important aspect of livestock farming, as it plays a role in feed determination, growth monitoring, and economic evaluation. However, accuracy is often compromised by animal movement, which causes fluctuations in sensor data and unstable readings, making it difficult to determine the actual weight. To address this, this study proposes an IoT-based animal weighing system equipped with a Kalman Filter algorithm to reduce noise and improve measurement stability. The system utilizes four 200 kg load cells, connected via HX711 and controlled by an ESP32 microcontroller, which is supported by an RFID module for automatic animal identification, an RTC for time logging, and Firebase as a cloud storage platform with real-time visualization capabilities through Node-RED. Experimental for moving object weighing results show that the Kalman Filter reduces measurement errors to less than 2% and maintains the coefficient of variation below 2%, demonstrating high precision and stability. Therefore, this system is proven effective for automatic, accurate, and remote-accessible animal weight monitoring, with strong potential for implementation in modern livestock industries.
Co-Authors Abdur Rohman Harits Martawireja Ahsan Basyar Atep Puja T H Danu Jaya Saputro Fitria Suryatini Gun Gun Maulana Hadi Supriyanto Ike Yuni Wulandari Ismail Rokhim M Wahyu Firmansyah Muhamad Fauzi Narwikant Indroasyoko Nuryanti Salwa Nahlya Tazkia Sandy Bhawana Mulia Setyawan Ajie Sukarno Wahyu Adhie Candra