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ComEngApp : Computer Engineering and Applications Journal

comengapp
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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 318 Documents

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Application of the Relief-f Algorithm for Feature Selection in the Prediction of the Relevance Education Background with the Graduate Employment of the Universitas Sriwijaya Sugandi Yahdin; Anita Desiani; Nuni Gofar; Kerenila Agustin
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

Career Development Center (CDC) at Universitas Sriwijaya provided a tracer study dataset for graduates. The data contained feature questions about the relevance of background education and graduate employment, namely about lectures, research projects experience, internships experience, English skill, internet knowledge, computer skill and others. the data was filled in by graduates in 2014, 2015, and 2016. Applying the Relief-f algorithm was to select the pattern features that most influence the relevance of education background and graduate employment. This study used Naive Bayes and KNN methods to measure the success rate of the Relief-f algorithm. The results of the accuracy of the data before the feature selection process for the naïve Bayes method were 73.43% and the KNN method was 66.24%, after the feature selection process the accuracy obtained in both methods increased to 74.38% for the Naive Bayes method and 72.22% for the KNN method. The best pattern features selected were 8 features: department relationship with work, the competence of education background, English skill, research projects experience, extracurricular activities, the competence of education background, internships experience, and communication skills. Based on the accuracy obtained, it was concluded that the Relief-f algorithm worked well in the feature selection and improved the accuracy.

Traffic Violation Detection System Using Image Processing Buhari Ugbede Umar; Olayemi Mikail Olaniyi; James Agajo; Omeiza Rabiu Isah
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

Over the last three decades, the global population of human beings has increased at an exponential rate, resulting in an equal rise in the number of vehicles owned and used globally. Vehicle traffic is a major economic component in both urban and rural areas, and it requires proper management and monitoring to ensure that this mass of vehicles coexists as smoothly as possible. The amount of vehicular traffic on roads around the world, with Nigeria as a case study, results in varying degrees of traffic rule violations, especially red light jumping. To arrest offenders and resolve the weaknesses and failures of human traffic operators who cannot be everywhere at once, efficient traffic violation and number plate recognition systems are needed. There are several methods for reading characters, which can be alphabets, numbers, or alphanumeric. To minimize processing time and computational load on the machine, this research proposed k-Nearest Neighbour for plate number character recognition. The system was developed and evaluated. From the result, the localization of license plate regions within an image was 92 percent accurate, and character recognition was 73 percent accurate.

Aorta Detection with Fetal Echocardiography Images Using Faster Regional Convolutional Neural Network (R-CNNs) Ade Iriani Sapitri; Annisa Darmawahyuni
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

The fetal heart structure has an important role in analyzing the location of abnormalities in the heart. The aorta is one of the fetal heart structures, which has an essential part in exploring how the fetal heart is structured. To see the fetal heart structure can be seen with the help of an echocardiography tool in the form of ultrasound to see ultrasound images of the fetal heart. In ultrasound image data, detection is challenging because of its low image features, shadows, and contrast levels. So that is the first to do it yourself in one of the points of the culture in the culture in the aorta. The approach in this study uses deep learning in cases using Faster Regional Convolutional Neural Network (R-CNNs) with the R-CNNs mask method. The proposed approach has been applied to 151 ultrasound images of the fetal heart for the aortic region. The evaluation results were tested by evaluating metrics on the detection object with an mAP value of 83.71%.

Wireless Controlling for Garbage Robot (G-Bot) Nyayu Latifah Husni; Robi Robi; Ekawati Prihatini; Ade Silvia Handayani; Sabilal Rasyad; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

This paper presents one of the solutions in overcoming the garbage problems. The people sometimes feel too lazy to throw the garbage into proper place due to their habit that has been grown since little kids. In this research, A G-Bot, a robot that has function as the garbage container is offered. By using an Internet of Things (IoT) application, the users can control the motion of the G-Bot wirelessly, so that it can move to the users’ desired location. In addition, the covers of the G-Bot can also be opened using smart phones that connected to the G-Bot. A Blynk that acts as the IoT Application is used in order to set up the G-Bot communication. From the experimental result, it can be concluded that the proposed research has been successful to be implemented. The users can move the G-Bot to the targeted location wirelessly, and they can also open and close the G-Bot’s lids wirelessly trough the mobile phones.

Classification of Finger Spelling American Sign Language Using Convolutional Neural Network Anna Dwi Marjusalinah; Samsuryadi Samsuryadi; Muhammad Ali Buchari
Computer Engineering and Applications Journal Vol 10 No 2 (2021)
Publisher : Universitas Sriwijaya

Sign language is a combination of complex hand movements, body postures, and facial expressions. However, only a limited number of people can understand and use it. A computer aid sign language recognition with finger spelling style utilizing a convolutional neural network (CNN) is proposed to reduce the burden. We compared two CNN architectures such as Resnet 50, and DenseNet 121 to classify the American sign language dataset. Several data splitting proportions were also tested. From the experimental result, it is shown that the Resnet 50 architecture with 80:20 data splitting for training and testing indicates the best performance with an accuracy of 0.999913, sensitivity 0.998966, precision 0.998958, specificity 0.999955, F1-score 0.999913, and error 0.0000898.

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

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

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

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

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

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.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Siti Nurmaini

Contact Email
comengappjournal@unsri.ac.id

Phone
+6285268048092

Journal Mail Official
comengappjournal@unsri.ac.id

Editorial Address
Jurusan Sistem Komputer, Fakultas Ilmu Komputer, Universtas Sriwijaya, KampusUnsri Bukit Besar, Palembang

Location
Kab. ogan ilir,

Sumatera selatan

INDONESIA

Abstract

Abstract

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Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Siti Nurmaini

Contact Email comengappjournal@unsri.ac.id

Phone +6285268048092

Journal Mail Official comengappjournal@unsri.ac.id

Editorial Address Jurusan Sistem Komputer, Fakultas Ilmu Komputer, Universtas Sriwijaya, KampusUnsri Bukit Besar, Palembang

Location Kab. ogan ilir, Sumatera selatan INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Siti Nurmaini

Contact Email
comengappjournal@unsri.ac.id

Phone
+6285268048092

Journal Mail Official
comengappjournal@unsri.ac.id

Editorial Address
Jurusan Sistem Komputer, Fakultas Ilmu Komputer, Universtas Sriwijaya, KampusUnsri Bukit Besar, Palembang

Location
Kab. ogan ilir,

Sumatera selatan

INDONESIA