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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Sinergi Jurnal Teknologi Elektro InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Abdi Masyarakat (JAM) Indonesian Journal of Electrical Engineering and Computer Science Journal of Integrated and Advanced Engineering (JIAE) Internet of Things and Artificial Intelligence Journal
Rachmat Muwardi
Universitas Mercu Buana
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Fiber Optic Attenuation Analysis Based on Mamdani Fuzzy Logic in Gambir Area, Central Jakarta Yuliza Yuliza; Ninda Sari; Rachmat Muwardi; Lenni Lenni; Yosy Rahmawati
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 4 (2022): Desember
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i4.24549

Abstract

In this study, the authors conducted an analysis of the quality of fiber optic network maintenance based on attenuation value and maintenance time using fuzzy Mamdani logic and simulated using Matlab software, to improve accuracy in drawing conclusions on maintaining quality. This study uses a quantitative method, in which the author obtains a summary of customer data from PT. Telkom Indonesia in a period of 4 months of observation from August to November 2021. In August there were 776 customers, in September there were 362 customers, in October there were 359 customers, and in November 445 customers who underwent Indihome fiber optic cable maintenance. The test results with the centroid method with an input Handling Time of 1.5 hours and an Attenuation of 15 dB, then the output Repair Quality is 5.5 or categorized as Good. The greater the attenuation value generated, the more time it takes to maintain the IndiHome internet network disturbance. This is due to the many technical maintenance of fiber optic cables carried out by technicians to adjust for damage/trouble in the field. It is expected that maintenance can be carried out routinely in order to avoid fatal internet disturbances on the customer's side, and maximize maintenance time according to the dosage determined by the company, which is less than 3 hours, taking into account the work performance of technicians and also the quality of maintenance.
Fast Human Recognition System on Real-Time Camera Yuliza Yuliza; Rachmat Muwardi; Mustain Rhozaly; Lenni Lenni; Mirna Yunita; Galatia Erica Yehezkiel
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27009

Abstract

Technology development is very rapid, so all fields are required to develop technology to increase the effectiveness and efficiency of work. One of the focuses is related to image processing technology. We can get many benefits by implementing this system, so various fields have implemented image processing systems, such as security, health, and education. One of the current obstacles is in the area of safety, namely in the field of searching for people, which is still done manually. Often search teams find it challenging to find people because of the significant search area, low light conditions, and complex search fields. Therefore, we need a tool capable of detecting humans to assist in finding people. Therefore, to detect human objects, the authors try to research human object detection using a simple device for the human object detection system. The authors use the You only look once (YOLO) method with the YoloV4-Tiny type, where this algorithm has high detection speed and accuracy. Using the YOLOV4-Tiny simulation method for human object recognition, a detection rate of 100% is obtained with an FPS value of 5.
Design Human Object Detection Yolov4-Tiny Algorithm on ARM Cortex-A72 and A53 Rachmat Muwardi; Ahmad Faizin; Puput Dani Prasetyo Adi; Rizky Rahmatullah; Yanxi Wang; Mirna Yunita; Dendi Mahabror
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27402

Abstract

Currently, many object detection systems still use devices with large sizes, such as using PCs, as supporting devices, for object detection. This makes these devices challenging to use as a security system in public facilities based on human object detection. In contrast, many Mini PCs currently use ARM processors with high specifications. In this research, to detect human objects will use the Mini PC Nanopi M4V2 device that has a speed in processing with the support of CPU Dual-Core Cortex-A72 (up to 2.0 GHz) + Cortex A53 (Up to 2.0 GHz) and 4 Gb DDR4 Ram. In addition, for the human object detection system, the author uses the You Only Look Once (YOLO) method with the YoloV4-Tiny type, With these specifications and methods, the detection rate and FPS score are seen which are the feasibility values for use in detecting human objects. The simulation for human object recognition was carried out using recorded video, simulation obtained a detection rate of 0,9845 or 98% with FPS score of 3.81-5.55.  These results are the best when compared with the YOLOV4 and YOLOV5 models. With these results, it can be applied in various human detection applications and of course robustness testing is needed.
Optimization of YOLOv4-Tiny Algorithm for Vehicle Detection and Vehicle Count Detection Embedded System Rachmat Muwardi; Ivan Prasetyo Nugroho; Ketty Siti Salamah; Mirna Yunita; Rizky Rahmatullah; Gregorius Justin Chung
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29693

Abstract

Currently, the implementation of object detection systems in the traffic sector is minimal. CCTV cameras on highways and toll roads are primarily used to monitor traffic conditions and document violations. However, the data recorded by these cameras can be further utilized to enhance traffic management systems. The author proposes a vehicle detection and counting system using YOLOv4-Tiny. The research aims to improve vehicle detection and counting accuracy by employing a median filter and grayscale processing, which simplify object detection. The proposed YOLOv4-Tiny algorithm has shown impressive results on various datasets, including MAVD, GRAM-RTM, and author dataset. The system achieved a detection accuracy of 98.95% on the MAVD dataset, 99.5% on the GRAM-RTM dataset (comparable to YOLOv4), and 99.1% on the author dataset. Furthermore, the system operates at 25 frames per second (FPS), a notably high rate compared to other methods. While the system demonstrates excellent accuracy in counting cars, it encounters some accuracy loss with other vehicle classifications. The author concludes that the system is highly suitable for real-world applications but notes that inaccurate labeling can lead to vehicle counting errors.
Co-Authors Ahmad Faizin Akhmad Wahyu Dani Alvin Sepbrian Andika Arrizki Asif Khan Bugi Nur Rohman Danang Widya Pratama Dendi Mahabror Diah Septiyana Firman Andika Freddy Artadima Silaban Galang P. N. Hakim Galang Persada Nurani Hakim Galatia Erica Yehezkiel Gao Hongmin Gregorius Justin Chung Harun Usman Ghifarsyam Harun Usman Ghifarsyam Hendy Juliyanto Heri Santoso, Makmur Hongmin Gao Hongmin Gao Ihsan, Hafid Ivan Prasetyo Nugroho Joe Mada Ranseda Permana Julpri Andika Kartika, Eka Anggara Yuda Ketty Siti Salamah Kusuma, Prima Wijaya Lenni Lenni Lenni Lenni Lenni Lenni, Lenni Lukman Medriavin Silalahi Mhd Adanan Purba Mirna Yunita Mirna Yunita Mirna Yunita Mirna Yunita Muhammad Hafizd Ibnu Hajar Mustain Rhozaly Ninda Sari Puput Dani Prasetyo Adi Rahmatullah, Rizky Reyhan Rahmat Adisaputro Rizky Rahmatullah Septiyana, Diah Setiyo Budiyanto Suwoyo, Heru Triyanto Pangaribowo Yanxi Wang Yehezkiel, Galatia Erica Yosy Rahmawati Yudhi Gunardi Yuliza Yuliza Yuliza Yuliza Zendi Iklima Zody Arifiansyah