cover
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
ComEngApp : Computer Engineering and Applications Journal
Published by Universitas Sriwijaya
ISSN : 22524274     EISSN : 22525459     DOI : 10.18495
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.
Articles 318 Documents
Drowsing Driver Alert System for Commercial Vehicles Benjamin Kommey; Seth Djanie Kotey; Andrew Selasi Agbemenu
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (204.822 KB) | DOI: 10.18495/comengapp.v8i3.308

Abstract

A number of accidents on our roads are caused by driver fatigue or drowsiness. Human fatalities as a result of driver drowsiness has been a major challenge for road safety bodies worldwide. Various road safety campaign messages have been put out to discourage drivers from driving whilst tired, but the problem still persists. Different technologies have been proposed over the years, but most seem to be too expensive to implement on a large scale. We present an inexpensive drowsing driver alert system in this paper. The system, known as Drowsing Driver Alert System (DDAS) is a smart system intended to effectively keep commercial drivers alert when driving. The system is able to detect when a driver is drowsy and alert him/her in real-time to prevent a potential accident. Using a camera, the eyes of the driver are monitored continuously whiles driving and analyzed to determine if they are shut or the blink rate is not normal. Two stages of alerts are given if the driver is determined to be drowsy. Log files of activities performed by the system are also saved to an external storage device to enable further analysis later.
Measuring Inter-VM Performance Interference in IaaS Cloud Kenga Mosoti Derdus; Vincent Omwenga Oteke; Patrick Job Ogao
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (124.565 KB) | DOI: 10.18495/comengapp.v8i3.311

Abstract

Virtualization has enabled cloud computing to deliver computing capabilities using limited computer hardware. Server virtualization provides capabilities to run multiple virtual machines (VMs) independently in a shared host leading to efficient utilization of server resources. Unfortunately, VMs experience interference from each other as a result of sharing common hardware. The performance interference arises from VMs having to compete for the hypervisor capacity and as a result of resource contention, which happens when resource demands exceed the allocated resources. From this viewpoint, any VM allocation policy needs to take into account VM performance interference before VM placement. Therefore, understanding how to measure performance interference is crucial. In this paper, we propose a simple experimental approach that can be used to measure performance interference in Infrastructure as a Service (IaaS) cloud during VM consolidation.
The Application of Push Button Switch as Inverse Kinematics Input on Adaptive Walking Method for Hexapod Robot Pola Risma; Muhammad Bagaskara; Nyayu Husni Latifah; Masayu Anisah; Adella Rialita
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.481 KB) | DOI: 10.18495/comengapp.v9i1.313

Abstract

Any kinds of natural disaster are undesirable. Loss and damage are the most experienced as they come. Property and people have to be relieved, and it's not an easy matter. Among the deaths caused by buildings, some may still be alive and need helps as soon as possible, but this is too risky for the rescue team since the location is still in dangerous level. Therefore, we created the detector hexapod robot to replace the tasks of the rescue teams in searching for the victims of the disasters, so there are no more victims from the rescue team. The hexapod robot is a six-legged robot which shapes and runs like a spider. This research focuses on the analysis of the push button switch as a robotic foot control input. This is because walking technique is an effective major factor in navigation of robots. A good method is required to maintain the height of the robot's foot while it is walking. So to solve this, the push button switch application is used along with the inverse kinematics calculations on each routine program in adjusting the position of the end effector on the floor surface. In shifting, the navigation runs well without any failure if the position of the foot does not touch the floor. The test is done in 2 steps, comparing the inverse kinematics calculations with x and y inputs which are applied to the robot program code then comparing the travel time condition by using push button switch and without push button switch. The result of robot in this study can be re-developed in the future, using servos with greater torque and better control input than push button switch.
Optimal Control of Jebba Hydropower Operating Head by a Dynamic Programming Olalekan Ogunbiyi; Cornelius T Thomas
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.919 KB) | DOI: 10.18495/comengapp.v8i3.315

Abstract

Nigeria with a generating potential of roughly 12,522 MW only supplies less than 20% of the national demand. This necessitates an optimal use of the Jebba Hydroelectric Power Plant whose optimal generation depends on the operating head. This paper presents the solution to an optimal control problem involving the operating head of the plant. An optimal control problem consisting of a model of the system dynamics, performance index and system constraints was solved using a dynamic programming approach. The control procedure was built on the integration of the nonlinear dynamical model by an Adams-Moulton technique with Adams-Bashfort as predator and Runge-Kutta as a starter. The numerical solution, coupled with dynamic programming was employed in developing an optimal control procedure for the regulation of the operating head. Result presented shows the potential of the control procedure in determining the amount of inflow required to restore the operating head to a nominal level whenever there is a disturbance.
Predicting the Occurrence and Causes of Employee Turnover with Machine Learning Xiaojun Ma; Shengjun Zhai; Yingxian Fu; Leonard Yoonjae Lee; Jingxuan Shen
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.959 KB) | DOI: 10.18495/comengapp.v8i3.316

Abstract

This paper looks at the problem of employee turnover, which has considerable influence on organizational productivity and healthy working environments. Using a publicly available dataset, key factors capable of predicting employee churn are identified. Six machine learning algorithms including decision trees, random forests, naïve Bayes and multi-layer perceptron are used to predict employees who are prone to churn. A good level of predictive accuracy is observed, and a comparison is made with previous findings. It is found that while the simplest correlation and regression tree (CART) algorithm gives the best accuracy or F1-score, the alternating decision tree (ADT) gives the best area under the ROC curve. Rules extracted in the if-then form enable successful identification of the probable causes of churning.
Finger Cue for Mobile Robot Motion Control Tresna Dewi; Amperawan Amperawan; Pola Risma; Yurni Oktarina; Dicky Astra Yudha
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (593.467 KB) | DOI: 10.18495/comengapp.v9i1.319

Abstract

The current technology enables automation using a robot to help or substitute humans in industry and domestic applications. This robot invasion to human life emerges a new requirement to set a method of communication between a human and a robot. One of the oldest languages is finger gesture, and this is easy to be applied method by implementing image detection that connected to the actuators of the robot to respond to human orders. This paper presents a method to navigate robots based on human fingers cue, including "Forward," "Backward," "Turn right," "Turn left," and "Stop" to generate the forward, backward, turn right, turn left, and stop motion. The finger detection is facilitated by a camera module (NFR2401L) with the image plane of 640 x 480 and 30 fps speed. The detection in coordinates x <43 and y <100, robot moves forward, in x <29 and y <100-coordinates , robot turns left, and in x <19 and y <100-coordinates , robot turns right. The experiment was conducted to show the effectiveness of the proposed method, and to some extent robot can follow human cues to navigate in its assigned location.
Evaluating Naïve Bayes Automated Classification for GBAORD Hani Febri Mustika; Arida Ferti Syafiandini; Lindung Parningotan Manik; Yan Rianto
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.555 KB) | DOI: 10.18495/comengapp.v9i1.320

Abstract

The Indonesian Government Budget Appropriations or Outlays for Research and Government (GBAORD) has been analyzed manually every year to measure the government expenditures in research and development. The analysis process involved several experts in making the budget classification. This method, commonly known as manual classification, has its downsides, which are time consumption and inconsistent result. Therefore, a study about implementing the machine learning method in GBAORD budget classification to avoid inconsistency is proposed in the previous research. For further analysis, this paper evaluates the performance of the Naïve Bayes algorithm for the GBAORD budget classification. This paper aims to measure the robustness of the Naïve Bayes to classify GBAORD data taken from 2017 until 2019. This paper uses three models of Naive Bayes with different preprocessing methods and features. This paper concludes that using the Naïve Bayes algorithm in Indonesian GBAORD budget classification is suitable since the robustness of the algorithm is proved to be high with 96.788+-0.185% average accuracy.
Environmental Application with Multi Sensor Network Ade Silvia Handayani; Nyayu Latifah Husni; Rosmalinda Permatasari
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (459.163 KB) | DOI: 10.18495/comengapp.v9i1.322

Abstract

This paper aimed to monitor temperature, humidity, and CO gas level using environmental application with multi sensor network (MSN). This system was applied in real life and real time, to be able to obtain data and information through mobile devices and other on internet network. In this research, environmental application is monitored remotely using displays on the web and sensors as device. This research obtained data in outdoor and indoor parking area also with obstacles and without obstacles, so it obtained the results from each of the different environmental conditions.
Traffic Scheduling Strategy of Power Communication Network Based on SDN Xiang Min; Zhang Jin Jin; Rao Hua Yang; Ma Rui Heng; Chen Meng Xin
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.042 KB) | DOI: 10.18495/comengapp.v9i1.324

Abstract

Due to the complicated structure, power communication network is difficult to guarantee the quality of service (QoS) of power services. A two-level scheduling algorithm based on software defined network (SDN) is proposed in this paper. Firstly, the priority-based scheduling method is used to meet the latency-sensitive of power service. Then, in order to alleviate congestion, queue bandwidth is adjusted according to network state information, which can be collected by the centralized control of SDN. Finally, the Mininet and Ryu controller are made use of building simulation environment. The test results show that the algorithm proposed in this paper reduce delay and packet loss rate significantly, which achieves QoS.
A Deep Learning Approach to Integrate Medical Big Data for Improving Health Services in Indonesia Bambang Tutuko; Siti Nurmaini; Muhammad Naufal Rachmatullah; Annisa Darmawahyuni; Firdaus Firdaus
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (426.189 KB) | DOI: 10.18495/comengapp.v9i1.328

Abstract

Medical Informatics to support health services in Indonesia is proposed in this paper. The focuses of paper to the analysis of Big Data for health care purposes with the aim of improving and developing clinical decision support systems (CDSS) or assessing medical data both for quality assurance and accessibility of health services. Electronic health records (EHR) are very rich in medical data sourced from patient. All the data can be aggregated to produce information, which includes medical history details such as, diagnostic tests, medicines and treatment plans, immunization records, allergies, radiological images, multivariate sensors device, laboratories, and test results. All the information will provide a valuable understanding of disease management system. In Indonesia country, with many rural areas with limited doctor it is an important case to investigate. Data mining about large-scale individuals and populations through EHRs can be combined with mobile networks and social media to inform about health and public policy. To support this research, many researchers have been applied the Deep Learning (DL) approach in data-mining problems related to health informatics. However, in practice, the use of DL is still questionable due to achieve optimal performance, relatively large data and resources are needed, given there are other learning algorithms that are relatively fast but produce close performance with fewer resources and parameterization, and have a better interpretability. In this paper, the advantage of Deep Learning to design medical informatics is described, due to such an approach is needed to make a good CDSS of health services.