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ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
Core Subject : Science, Engineering,
Computer Science & IT Engineering
ComEngApp-Journal (Collaboration between University of Sriwijaya, Kirklareli University and IAES) is an international forum for scientists and engineers involved in all aspects of computer engineering and technology to publish high quality and refereed papers. This Journal is an open access journal that provides online publication (three times a year) of articles in all areas of the subject in computer engineering and application. ComEngApp-Journal wishes to provide good chances for academic and industry professionals to discuss recent progress in various areas of computer science and computer engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol 10 No 3 (2021)" : 7 Documents clear
Intelligent Miniature Circuit Breaker Benjamin Kommey; Seth Djanie Kotey; Eric Tutu Tchao; Gideon Adom Bamfi
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.606 KB) | DOI: 10.18495/comengapp.v10i3.378

Abstract

The traditional electrical distribution panel (or breaker panel) is a system that divides the main electrical power feed and distributes them to subsidiary circuits whiles providing a protective mechanism via the use of miniature circuit breakers, residual current devices, etc. The conventional panel distributes electrical power alright but the system does not make provision for any form of real time monitoring and feedback of power consumption levels in the home. This paper presents a design of a miniature circuit breaker distribution panel integrated with other electronic devices which helps achieve real time monitoring of power consumption and also automatically trips the circuit if there is a fault and reconnects the circuit if the fault is cleared to ensure little to no interruption in electricity to appliances.
Fuzzy Logic Controller Application for Automatic Charging System Design of a Solar Powered Mobile Manipulator Fradina Septiarini; Tresna Dewi; Rusdianasari Rusdianasari
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (666.725 KB) | DOI: 10.18495/comengapp.v10i3.380

Abstract

Agriculture is a vital industry that affects the livelihoods of many people. Given the reduction in agricultural employees and the increasing strain on farmers, this sector requires convenience, which the automation system may provide. One of the automations is mobile manipulator implementation to substitute farmers. This study investigates the automatic battery charging system supported by the Fuzzy Logic Controller (FLC) to power a mobile manipulator. The application of solar charging is an ideal power source for the robot applied in the open field with high irradiance all year long. This charging system is equipped with IoT monitoring online to monitor the available power produced by solar panel and the battery capacity condition. The effectiveness of the proposed method is proven by experiments conducted for ten times charging in ten days, where the highest power produced by the panel is 1.080 W with 0.563 W charged to the battery. The highest irradiance comes with the highest surface panel temperature of 58.9OC at the irradiance rate of 1021 W/m2. The experimental results show the possibility of the solar-powered robot, which is ideal for agriculture implementation.
Driver Drowsiness Detection Based on Drivers’ Physical Behaviours: A Systematic Literature Review Femilia Hardina Caryn; Laksmita Rahadianti
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.076 KB) | DOI: 10.18495/comengapp.v10i3.381

Abstract

One of the most common causes of traffic accidents is human error. One such factor involves the drowsy drivers that do not focus on the road before them. Driver drowsiness often occurs due to fatigue in long distances or long durations of driving. The signs of a drowsy driver may be detected based on one out of three types of tests; i.e., performance test, physiological test, and behavioural test. Since the physiological and performance tests are quite difficult and expensive to implement, the behavioural test is a good choice to use for detecting early drowsiness. Behaviour-based driver drowsiness detection has been one of the hot research topics in recent years and is still increasingly developing. There are many approaches for behavioural driver drowsiness detection, such as Neural Networks, Multi Layer Perceptron, Support Vector Machine, Vander Lugt Correlator, Haar Cascade, and Eye Aspect Ratio. Therefore, this study aims to conduct a systematic literature review to elaborate on the development and research trends regarding driver drowsiness detection. We hope to provide a good overview of the current state of research and offer the research potential in the future.
Forward Chaining for Contextual Music Recommendation System Ratih Kartika Dewi; M. Salman Ramadhan; Dwi Yovan Harjananto; Chindy Aulia Sari; Zumrotul Islamiah
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (178.202 KB) | DOI: 10.18495/comengapp.v10i3.382

Abstract

Music is an important aspect of people's daily lives. The reasons people listen to music include to fill their free time and to keep the mood in good condition. Music recommendations are a recommendation system that exists not only because of the many types of music available, but also because people's perceptions of music are still not fully understood. But with so many music choices it makes it difficult for users to find music that fits their context. Examples include considering music based on the current user's location or current activities. A system is required that can recommend music in the context faced by the user.Music Recommendation System Development, Based on user context is a mobile application that uses the Android operating system. The recommendations provided by this system use expert system methods with forward chaining flow. The system will process inputs obtained from users and provide musical recommendations in accordance with the references provided by experts. The result of this study is a rule that is built to produce an average accuracy between user choice and system recommendations of 72%.
Topic Classification of Islamic Question and Answer Using Naïve Bayes and TF-IDF Method Aura Sukma Andini; Danang Triantoro Murdiansyah; Kemas Muslim Lhaksmana
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.608 KB) | DOI: 10.18495/comengapp.v10i3.385

Abstract

Information spread through the internet is widely used by people to find anything. One of the most searched information on the internet is information related to Islamic religious knowledge. However, the large amount of information available from various sources makes it difficult for people to find the correct information. Previous researchers have researched this topic, but the dataset used only comes from one source. Therefore, in this study, a classification system for Islamic question and answer topics was built using the Naïve Bayes and TF-IDF methods. This study using 1000 question and answer article data taken from Islamic consultation websites, namely rumahfiqih.com and islamqa.info. The multi-class classification uses five categories which are manually labeled using the category classes on the website. From several test scenarios in this study, the Naïve Bayes classification method using TF-IDF (n-gram level) with a maximum feature of 1000 at a data separation ratio of 70:30 produces the highest accuracy of 81%. The 81% accuracy value was also generated by the SVM classification method, but the difference was in the SVM the highest accuracy value using TF-IDF (word level). It is expected that in the subsequent research will be used more website sources and the use of other classification and feature extraction methods with more optimal value than previous research.
The Effectiveness of Image Preprocessing on Digital Handwritten Scripts Recognition with The Implementation of OCR Tesseract Lily Rojabiyati Mursari; Antoni Wibowo
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.795 KB) | DOI: 10.18495/comengapp.v10i3.386

Abstract

Optical Character Recognition (OCR) has been widely discussed in various topics in the rise of robotics, artificial intelligence and computer vision. OCR has become a solution in extracting characters from the image into machine-encoded text. This research aims to discuss character recognition from digital handwritten image. However, characters recognition problems using OCR has been more or less solved. OCR mainly implemented in reading characters from scanned of printed documents. In this research, image preprocessing including convert to grayscale, morphological operations and noise removal has been successfully boost the accuracy score of OCR performance. The average success outcome resulted to 79.26% in reading characters from the image.
Segmentation of Squamous Columnar Junction on VIA Images using U-Net Architecture Akhiar Wista Arum; Siti Nurmaini; Dian Palupi Rini; Patiyus Agustiansyah; Muhammad Naufal Rachmatullah
Computer Engineering and Applications Journal Vol 10 No 3 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (319.534 KB) | DOI: 10.18495/comengapp.v10i3.387

Abstract

Cervical cancer is the second most common cancer that affects women, especially in developing countries including Indonesia. Cervical cancer is a type of cancer found in the cervix, precisely in the squamous columnar junction (SCJ). Early screening for cervical cancer can be reduce the risk of cervical cancer. One of the popular screening tool methods for the detection of cervical pre-cancer is the Visual Inspection with Acetic Acid (VIA) method. This is due to the level of effectiveness, convenience and low cost. This paper proposes a method for the detection and segmentation of the SCJ region on VIA images using U-Net. This study is the first research conducted using the CNN method to perform segmentation tasks in the SCJ region. The best performance results are shown from the Pixel Accuracy, Mean IoU, Mean Accuracy, Dice coefficient, Precision and Sensitivity values, namely 90.86%, 56.5%, 75.69%, 34.09%, 41.24%, and 56.91%. Keywords: Cervical Pre-cancer, Screening VIA, SCJ, U-Net.

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