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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Mikrotek Jurnal Simantec REKAYASA Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) International Journal of Science, Engineering and Information Technology
Dafid, Ach
Program Studi Teknik Mekatronika, Fakultas Teknik, UniversitasTrunojoyo Madura Jl. Raya Telang, PO BOX 2, Kamal, Bangkalan - 69162
Aerospace Engineering Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics Other

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Enhanced Precision Control of a 4-DOF Robotic Arm Using Numerical Code Recognition for Automated Object Handling Sukri, Hanifudin; Ibadillah, Achmad Fiqhi; Thinakaran, Rajermani; Umam, Faikul; Dafid, Ach.; Kurniawan, Adi; Morshed, Md. Monzur; Kurniawan, Denni
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

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

Abstract

This research develops a 4-DOF robotic arm system that utilizes numerical codes for accurate, automated object handling, supporting advancements in sustainable industrial automation aligned with the UN Sustainable Development Goals (SDGs), particularly Industry, Innovation, and Infrastructure (SDG 9). Key contributions include the integration of EasyOCR for reliable code recognition and a control mechanism that enables precise positioning. The robotic system combines a webcam for visual sensing, servo motors for movement, and a gripper for object manipulation. EasyOCR effectively recognizes numerical codes on randomly positioned objects against a uniform background while the microcontroller calculates servo angles to guide the arm accurately to target positions. Testing results show a success rate exceeding 94% for detecting codes 1 to 4, with minor servo angle errors requiring adjustments in arm extension by 30 mm to 50 mm. Positional error analysis reveals an average error of less than 1.5 degrees. Although environmental factors like lighting can influence code visibility, this approach outperforms traditional methods in adaptability and precision. Future research will focus on enhancing code recognition under variable lighting and expanding the system's adaptability for diverse object types, broadening its applications in industries demanding high efficiency.
Optimizing K-Nearest Neighbors with Particle Swarm Optimization for Improved Classification Accuracy Dafid, Ach.; Sudianto, Achmad Imam; Thinakaran, Rajermani; Umam, Faikul; Adiputra, Firmansyah; Izzuddin; Sitepu Debora , Ribka
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i2.30775

Abstract

This study aims to improve the performance of the K-Nearest Neighbors (KNN) algorithm in classifying public reviews of Batik Madura through optimizing the K value using the Particle Swarm Optimization (PSO) algorithm. Public reviews collected from the Google Maps platform are used as a dataset, with positive, negative, and neutral sentiment categories. Optimization of the K value is carried out to overcome the constraints of KNN performance, which is highly dependent on the K parameter, with PSO providing a more efficient approach than the grid search method. However, PSO also presents challenges such as sensitivity to parameter tuning and potential computational overhead. This study has succeeded in developing a web-based system using the Python Streamlit framework, which makes it easy for users to access sentiment analysis results. Testing shows that optimizing the K value with PSO increases the accuracy of KNN to 88.5% with an optimal K value of 19. However, this accuracy is not compared to other optimization techniques, leaving its relative advantage unverified. The results are expected to help Batik Madura entrepreneurs in evaluating public perception and guiding strategic innovations. Research outputs include a prototype, intellectual property registration, and journal publication, although the role of deep learning models is only briefly noted without further development.
Penerapan Sistem Kontrol Adaptif Proportional Integral Derivative (PID) pada Mesin Penimbang Mie dengan Konveyor Dafid, Ach; Umam, Faikul; Budiarto, Hairil
Rekayasa Vol 18, No 2: Agustus, 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i2.31610

Abstract

Indonesia is the second-largest instant noodle consumer in the world after China, with consumption reaching more than 12 billion packs per year. This high demand drives the need for innovation in the production process, especially in the weighing and cutting aspects, which are still carried out manually in small and medium industries. Manual processes not only require more time and energy, but also result in variations in packaging weight that are not uniform and reduce production efficiency. This study aims to design and implement a Proportional Integral Derivative (PID) adaptive control system on a noodle weighing machine with a conveyor. The system was developed using a load cell sensor to measure the noodle dough weight, a servo motor as a cutting actuator, and a DC motor as a conveyor drive, all of which are controlled by an Arduino ATmega 2560 microcontroller. The research methodology includes mechanical design, electronic design, control system programming, sensor calibration, and performance testing. The test results show that the system is able to produce noodle portions with a target weight of 50 grams consistently. The prototype has conveyor dimensions of 100×20×8 cm with a speed of 26 cm/ms, controlled using tuned PID parameters (Kp=1.5; Ki=1; Kd=1.7). From 20 trials, the system produced an average error of 0.75% and a success rate of 99.25%. Thus, the application of the PID adaptive control system has been proven to improve weighing precision, conveyor speed stability, and production efficiency. This innovation is expected to be a simple and affordable solution to support the automation of small and medium industries in Indonesia in facing increasingly fierce food market competition.
Implementation Of Fuzzy Logic Control Method On Chilli Cultivation Technology Based Smart Drip Irrigation System Umam, Faikul; Dafid, Ach.; Cahyani, Andharini Dwi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 1 (2023): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i1.25878

Abstract

Herbal chili plants are very beneficial from a health and economic perspective. In the process of cultivating herbal chili plants, there are still many problems that need to be faced, including unfavorable climatic conditions and less intensive cultivation processes. Based on this description, to overcome these problems, technological innovation is needed that can be implemented directly in the cultivation of herbal chili plants. This situation can be achieved by applying a drip irrigation system. This system makes it possible to control the water supply requirements of chili herbs efficiently. System stability can run optimally when combined with a method that can make a decision quickly. Fuzzy logic is used in research because it is able to provide appropriate decisions on temperature and soil moisture data in chili herbs. This research is expected to overcome the problem of water shortages in barren areas. And increase people's interest in the cultivation of herbal chili plants. This research is also an overview and framework for developing the agricultural sector in Madura in the technology field. The results of this study indicate that technology can be designed and integrated with the fuzzy logic control method, then the results of testing the tool also show a 99,98% success rate. This is shown by the results of testing in the morning, afternoon, and evening. The contribution of this study is the control of temperature and humidity which in other studies only focused on the soil, not on the temperature and humidity of the air around the herbal chili plants with a system that has been controlled using the fuzzy method.
Smart Cold Storage Based on Photovoltaic with Adaptive Fuzzy Control Approach for Guard Quality of Fish Catch on Fishing Vessels Findiastuti, Weny; Umam, Faikul; Sulaiman, Yoga Aulia; Thinakaran, Rajermani; Dafid, Ach.; Andriansyah, Adi; Yusuf, Ahcmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.14508

Abstract

This research is motivated by the importance of maintaining the quality of fish catches on fishing vessels, which generally experience a decline in quality due to suboptimal conventional fish storage systems and limited energy supplies at sea. To address these challenges, the development of renewable energy-based cold storage technology through a Solar Power Plant (PLTS) or Photovoltaic system is needed. This research aims to design a PLTS-based smart cold storage system capable of optimally maintaining temperature stability using the Adaptive Fuzzy Control method. It is hoped that fish quality can be maintained and the economic value of fishermen's catches can be increased. This research uses an experimental approach through the design, implementation, and testing of a fuzzy logic-based adaptive control system in real-time. The performance results are then evaluated in maintaining the temperature stability of the cooling room and the efficiency of electrical energy sourced from solar panels. It is hoped that this research can provide real solutions for fishermen, support the economic independence of the fisheries sector, and support the achievement of sustainable development targets (SDGs) 7, 9 12, and 14. During the 24-hour test, the Adaptive Fuzzy Control system in a solar-based refrigerator demonstrated consistent performance in maintaining temperature stability (standard deviation σ = 3.28 °C–3.45 °C). The average refrigerator temperature was recorded at -5.44 °C with a range of -0.9 °C to -12 °C, which remains acceptable for marine fish preservation under superchilling and mild freezing conditions. The battery capacity was at an average of 89.95%, decreasing when there was no power supply and then increasing again during charging, thus reflecting adaptive energy management. The average charging speed was 3.14 A, with a peak of up to 15.6 A at 7–8 hours, then decreasing gradually as the battery was full to prevent overcharging. These findings confirm that the proposed system effectively balances cooling performance and renewable energy utilization. The use of solar photovoltaic energy directly supports SDG 7 (Affordable and Clean Energy), while system innovation and energy optimization align with SDG 9 (Industry, Innovation, and Infrastructure). The prototype demonstrates stable and efficient operation, and the design concept is scalable for practical implementation on small to medium-sized fishing vessels. A preliminary cost analysis indicates up to 50% lower operating costs compared to conventional diesel refrigeration systems.
PEMETAAN HARGA RUMAH DENGAN MENGGUNAKAN MODEL STATISTIK : GEOGRAPHICALLY WEIGHTED REGRESSION Winarso, Kukuh; Dafid, Achmad
Rekayasa Vol 15, No 3: Desember 2022
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v15i3.21818

Abstract

Penentuan harga rumah di sebagian kota-kota besar di Indonesia dipengaruhi oleh banyak faktor, salah satunya adalah lokasi rumah. Lokasi rumah menunjukkan hubungan yang positip dengan harga rumah. Lokasi rumah dekat dengan pusat bisnis adalah salah satu hal yang menyebabkan harga rumah menjadi mahal. Disamping itu pusat pemukiman berdasar kepadatan penduduk di satu sisi menyebabkan harga rumah menjadi naik pada posisi yang lain menyebabkan harga rumah menjadi turun. Penelitian ini berbasis pada pemetaan harga rumah yang dipengaruhi oleh pusat bisnis dan pusat pemukiman penduduk dikota Surabaya. Pemetaan Harga rumah ini menggunakan metode Geographically Weighted Regression (GWR). adalah suatu teknik yang membawa kerangka dari model regresi sederhana menjadi model regresi terboboti.
Evaluation of the Effectiveness of Hand Gesture Recognition Using Transfer Learning on a Convolutional Neural Network Model for Integrated Service of Smart Robot Umam, Faikul; Dafid, Ach.; Sukri, Hanifudin; Asmara, Yuli Panca; Morshed, Md Monzur; Maolana, Firman; Yusuf, Ahcmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.14507

Abstract

This study aims to develop and evaluate the effectiveness of a transfer learning model on CNN with the proposed YOLOv12 architecture for recognizing hand gestures in real time on an integrated service robot. In addition, this study compares the performance of MobileNetV3, ResNet50, and EfficientNetB0, as well as a previously funded model (YOLOv8) and the proposed YOLOv12 development model. This research contributes to SDG 4 (Quality Education), SDG 9 (Industry, Innovation and Infrastructure), and SDG 11 (Sustainable Cities and Communities) by enhancing intelligent human–robot interaction for educational and service environments. The study applies an experimental method by comparing the performance of various transfer learning models in hand gesture recognition. The custom dataset consists of annotated hand gesture images, fine-tuned to improve model robustness under different lighting conditions, camera angles, and gesture variations. Evaluation metrics include mean Average Precision (mAP), inference latency, and computational efficiency, which determine the most suitable model for deployment in integrated service robots. The test results show that the YOLOv12 model achieved an mAP@0.5 of 99.5% with an average inference speed of 1–2 ms per image, while maintaining stable detection performance under varying conditions. Compared with other CNN-based architectures (MobileNetV3, ResNet50, and EfficientNetB0), which achieved accuracies between 97% and 99%, YOLOv12 demonstrated superior performance. Furthermore, it outperformed previous research using YOLOv8 (91.6% accuracy.
Co-Authors Achmad Fiqhi Ibadillah Adi Kurniawan Adi Kurniawan Saputro Andharini Dwi Cahyani Andriansyah, Adi Doni Abdul Fatah Faikul Umam Fifin Ayu Mufarroha Firmansyah Adiputra Firmansyah Adiputra Hairil Budiarto Ika Oktavia Suzanti Izzuddin Khusnul Fatimah Kukuh Winarso Kurniawan, Denni Maolana, Firman Morshed, Md Monzur Morshed, Md. Monzur Ponco Siwindarto Rullie Annisa Sholeh, Mahrus Siswojo, Bambang Sitepu Debora , Ribka Sudianto, Achmad Imam Sukri, Hanifudin Sulaiman, Yoga Aulia Sumarto SUTIKNO Thinakaran, Rajermani Triwidyaningrum, Vivi Weny Findiastuti WENY FINDIASTUTI, WENY Yuli Panca Asmara Yusuf, Ahcmad Ziyyad Yassar