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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 5 Documents
 1 
Search results for , issue "Vol 6 No 2 (2017)" : 5 Documents clear
TOU-AR:Touchable Interface for Interactive Interaction in Augmented Reality Environment Ahmad Hoirul Basori; Hani Moaiteq Abdullah AlJahdali
Computer Engineering and Applications Journal Vol 6 No 2 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (365.191 KB) | DOI: 10.18495/comengapp.v6i2.194

Abstract

Touchable interface is one of the future interfaces that can be implemented at any medium such as water, table or even sand. The word multi touch refers to the ability to distinguish between two or more fingers touching a touch-sensing surface, such as a touch screen or a touch pad. This interface is provided tracking the area by using depth camera and projected the interface into the medium. This interface is widely used in augmented reality environment. User will project the particular interface into real world medium and user hand will be tracked simultaneously when touching the area. User can interact in more freely ways and as natural as human did in their daily life
Always Best Connected Mobile Sensor Network to Support High Accuracy Internet of Farming Ahmed H. Alahmadi
Computer Engineering and Applications Journal Vol 6 No 2 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (675.833 KB) | DOI: 10.18495/comengapp.v6i2.202

Abstract

The Internet of Farming be dependent on data gathered from sensor of Wireless Sensor Network (WSN). The WSN requires a reliable connectivity to provide accurate prediction data of the farming system. This paper introduces a mechanism that gives always best connectivity (ABC). The mechanism considers all stakeholders (mobile node, corresponding node and users) attributes. An empirical simulation shows that the proposed mechanism provides an acceptable ABC to the mobile sensors in the WSN.
Assistive Robotic Technology: A Review Anton Satria Prabuwono; Khalid Hammed S. Allehaibi; Kurnianingsih Kurnianingsih
Computer Engineering and Applications Journal Vol 6 No 2 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (294.089 KB) | DOI: 10.18495/comengapp.v6i2.203

Abstract

Older people with chronic conditions even lead to some disabilities face many challenges in performing daily life. Assistive robot is considered as a tool to provide companionship and assist daily life of older people and disabled people. This paper presents a review of assistive robotic technology, particularly for older people and disabled people. The result of this review constitutes a step towards the development of assistive robots capable of helping some problems of older people and disabled people. Hence, they may remain in at home and live independently.
Comparative classification of student's academic failure through Social Network Mining and Hierarchical Clustering Andi Besse Firdausiah Mansur; Norazah Yusof
Computer Engineering and Applications Journal Vol 6 No 2 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (982.539 KB) | DOI: 10.18495/comengapp.v6i2.204

Abstract

Student academic failure are caused by several factors such as: family relationship, study time, absence, parent education, travel time and etc. This study observe several factors which are related to student academic failure by calculating the centrality degree between students to find the correlation between failure factors for each students. Furthermore, each student will be measured by measuring the geodesic distance for each factors for hierarchical clustering. The flow betwenness measure and hierarchical clustering show the promising result, where students who has similar factors value are tends to be grouped together in the same cluster. The student with high value of flow betwenness is considered as broker of network and play vital character inside network. The result of study is believed can bring important and useful information toward the student performance analysis for future better education.
Creating a Business Value while Transforming Data Assets using Machine Learning Ivana Dimitrovska; Toni Malinovski
Computer Engineering and Applications Journal Vol 6 No 2 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (320.437 KB) | DOI: 10.18495/comengapp.v6i2.205

Abstract

Machine learning enables computers to learn from large amounts of data without specific programming. Besides its commercial application, companies are starting to recognize machine learning importance and possibilities in order to transform their data assets into business value. This study explores integration of machine learning into business core processes, while enabling predictive analytics that can increase business values and provide competitive advantage. It proposes machine learning algorithm based on regression analysis for a business solution in large enterprise company in Macedonia, while predicting real-value outcome from a given array of business inputs. The results show that most of the machine learning predictive values for the desired process output deviated from 0 to 15% of actual employees' decision. Hence, it verifies the appropriateness of the chosen approach, with predictive accuracy that can be meaningful in practice. As a machine learning case study in business context, it contains valuable information that can help companies understand the significance of machine learning for enterprise computing. It also points out some potential pitfalls of machine learning misuse.

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