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Undergraduate business education students’ perception on information and communication technology use in teaching and learning

10.11591/ijere.v9i2.20326
Patrick Uzo Osadebe , Joyce Frances Osadebe
The study was carried out to assess the undergraduate Business Education Students’ Perception on the use of Information and communication technology (ICT) in teaching and learning in the University. Thus, to achieve the purpose, two research questions and two hypotheses guided the study. A sample of 100 students was randomly drawn using balloting and proportionate stratified random sampling techniques. A questionnaire of 4-point scale was used to collect data. It has face validity determined through expert judgement, and construct validity verified through factor analysis. The reliability of the instrument was obtained through Cronbach Alpha. A reliability coefficient of 0.82 was obtained as a measure of internal consistency. The data collected were analyzed with mean and Z-test. Mean was used to answer the research questions while Z-test was used to test the hypotheses at the 0.05 level of significance. The result showed that there was high perception of students to use ICT in teaching and learning in the university. There was no significant difference between male and female students as well as 300 level and 400 level students on the use of ICT in teaching and learning. Therefore, it was recommended that ICT should be used in teaching and learning Business Education in the University.
Volume: 9
Issue: 2
Page: 359-363
Publish at: 2020-06-01

Knowledge internalization in e-learning management system

10.12928/telkomnika.v18i3.14817
Zahraa Abed Aljasim; Al-Qasim Green University Muhisn , Mazida; Universiti Utara Malaysia Ahmad , Mazni; Universiti Utara Malaysia Omar , Sinan Adnan; Universiti Utara Malaysia Muhisn
Knowledge management (KM) is gaining significance as a worthy research subject due to its contribution to the success of wide range of organizations, including higher education institutions. Knowledge internalization is mainly related to capability to see the relevance of one’s knowledge in a real situation. e-learning management system (eLMS) provides an online teaching and learning platform for students (as novice users) and lecturers (as experts in their specific domains) with the potential to improve students' knowledge acquisition. Thus, this empirical study was conducted to investigate the impact of knowledge internalization in eLMS among students in Iraq. To achieve these aims, survey research design was adopted and the sample comprised of 109 undergraduate students attending College of Information Technology in Iraq, all of whom were actively engaged in eLMS activities. The findings show that knowledge can be effectively transferred from lecturers to students via eLMS. Additionally, eLMS enable students to improve their prior knowledge through the internalization process, while also motivating them to share their knowledge with other students.
Volume: 18
Issue: 3
Page: 1361-1367
Publish at: 2020-06-01

Ant colony algorithm for text classification in multicore-multithread environment

10.11591/ijeecs.v18.i3.pp1359-1366
Ahmad Nazmi Fadzal , Mazidah Puteh , Nurazzah Abd Rahman
This paper presents about Ant Colony Algorithm (ACO) for Text Classification in Multicore-Multithread Environment in Artificial Intelligent domain. We had develop a software which assimilate concurrency concept to multiple artificial ants. Pheromone in ACO is the main concept used to solve the text classification problem. In regards to its role, pheromone value is changed depending on the solution finding that has been discovered at the pseudo random heuristic attempt in selecting path from text words. However, ACO can take up longer time to process larger training document. Based on the cooperative concept of ants living in colony, the ACO part is examined to work in multicore-multithread environment as to cater additional execution time benefit. In running multicore-multithread environment, the modification aims to make artificial ants actively communicate between multiple physical cores of processor. The execution time reduction is expected to show an improvement without compromising the original classification accuracy by the investment of trading on more processing power. The single and multicore-multithreaded version of ACO was compared statistically by conduction relevant test. It was found that the result shows a positive time reduction improvement.
Volume: 18
Issue: 3
Page: 1359-1366
Publish at: 2020-06-01

The impact of noise on detecting the arrival angle using the root-WSF algorithm

10.12928/telkomnika.v18i3.14055
Btissam; Hassan II University Casablanca Boustani , Abdennaceur; Hassan II University Casablanca Baghdad , Aicha; Hassan II University Casablanca Sahel , Abdelhakim; Hassan II University Casablanca Ballouk , Abdelmajid; Hassan II University Casablanca Badri
This article discusses three standards of Wi-Fi: traditional, current and next-generation Wi-Fi. These standards have been tested for their ability to detect the arrival angle of a noisy system. In this study, we chose to work with an intelligent system whose noise becomes more and more important to detect the desired angle of arrival. However, the use of the weighted subspace fitting (WSF) algorithm was able to detect all angles even for the 5th generation Wi-Fi without any problem, and therefore proved its robustness against noise.
Volume: 18
Issue: 3
Page: 1150-1157
Publish at: 2020-06-01

The comparison study of kernel KC-means and support vector machines for classifying schizophrenia

10.12928/telkomnika.v18i3.14847
Sri; University of Indonesia Hartini , Zuherman; University of Indonesia Rustam
Schizophrenia is one of mental disorder that affects the mind, feeling, and behavior. Its treatment is usually permanent and quite complicated; therefore, early detection is important. Kernel KC-means and support vector machines are the methods known as a good classifier. This research, therefore, aims to compare kernel KC-means and support vector machines, using data obtained from Northwestern University, which consists of 171 schizophrenia and 221 non-schizophrenia samples. The performance accuracy, F1-score, and running time were examined using the 10-fold cross-validation method. From the experiments, kernel KC-means with the sixth-order polynomial kernel gives 87.18 percent accuracy and 93.15 percent F1-score at the faster running time than support vector machines. However, with the same kernel, it was further deduced from the results that support vector machines provides better performance with an accuracy of 88.78 percent and F1-score of 94.05 percent.
Volume: 18
Issue: 3
Page: 1643-1649
Publish at: 2020-06-01

Architecture of the regional satellite augmentation system for maritime applications

10.12928/telkomnika.v18i3.15641
Dimov Stojce; Durban University of Technogy Ilcev
This paper describes architecture of regional satellite augmentation system (RSAS) in the function of the maritime space communications, navigation and surveillance (CNS) and global navigation satellite systems (GNSS) networks for enhanced safety and surveying of oceangoing ships, management and tracking of cargo, security of Mariners onboard commercial and passenger ships, yachts, sea platforms and other types of craft. The RSAS network are designed to improve vessel management and transport operation because of the enormous expansion of the world's merchant fleet. However, this network with a special ship tracking system can also improve the protection of merchant ships and their crews against piracy, violence, robbery and terrorist attacks. The international maritime organization (IMO) and shipping flag states have project for development of the international ship and port security (ISPS) and design to implement an approaching and port control system (APCS) by special code for all merchant vessels including determination, tracking and positioning of all ships movements in and out of the seaport area. The Maritime RSAS and CNS systems are integration components of the global satellite augmentation systems (GSAS) of two operational GNSS-1 military networks, such as the US global position system (GPS) and Russian global satellite navigation system (GLONASS). In this paper are also introduced the special effects of the ships RSAS networks and coastal movement guidance and control (CMGC) system for maritime application at sea and in seaports areas.
Volume: 18
Issue: 3
Page: 1610-1620
Publish at: 2020-06-01

A new hyhbrid coefficient of conjugate gradient method

10.11591/ijeecs.v18.i3.pp1454-1463
Nur Syarafina Mohamed , Mustafa Mamat , Mohd Rivaie , Shazlyn Milleana Shaharudin
Hybridization is one of the popular approaches in modifying the conjugate gradient method. In this paper, a new hybrid conjugate gradient is suggested and analyzed in which the parameter is evaluated as a convex combination of  while using exact line search. The proposed method is shown to possess both sufficient descent and global convergence properties. Numerical performances show that the proposed method is promising and has overpowered other hybrid conjugate gradient methods in its number of iterations and central processing unit per time. 
Volume: 18
Issue: 3
Page: 1454-1463
Publish at: 2020-06-01

Industry 4.0 competencies among lecturers of higher learning institution in Malaysia

10.11591/ijere.v9i2.20520
Tan Owee Kowang , Mohamad Fawzy Bakry , Ong Choon Hee , Goh Chin Fei , Lim Kim Yew , Mohd Saiful Izwaan Saadon , Choi Sang Long
Industry 4.0 is a new breed from the past industry revolution. The revolution implies an inevitable impact on professional sectors, including education field. Higher Learning Institution (HLI) is viewed as the platform for the development of Industry 4.0 competencies. However, research related to Industry 4.0 competencies among educators or academicians is scarce. Hence, this study aims to assess the level of Industry 4.0 competencies among lecturers in one of higher learning institution in Malaysia, as well as to identify Industry 4.0 competencies that required further enhancement. Five Industry 4.0 competencies identified from literature review, which are Information and Communication Technologies (ICT), Organizational Learning, Innovative Management, Environment and Continuous Improvement competencies. The importance level and implementation level perceived by the lecturers across the five competencies are assessed via questionnaire which responded by 132 lecturers from a higher learning institution in Malaysia. Data collected is analyzed via descriptive analysis to assess the importance and implementation levels perceived by the respondent. In addition, an improvement opportunity index, namely Focus Index is calculated for each competency. Finding from the study reveals that all the four Industry 4.0 competencies are perceived by respondents as important, however implemented at moderate level. Analysis result of Focus Index also suggests that competencies in term of Organizational Learning and ICT are “over focus”, while Environment competency is viewed as “under focus” which required further enhancement.
Volume: 9
Issue: 2
Page: 303-310
Publish at: 2020-06-01

Vietnamese handwritten character recognition using convolutional neural network

10.11591/ijai.v9.i2.pp276-281
Truong Quang Vinh , Le Hoai Duy , Nguyen Thanh Nhan
Handwriting recognition is one of the core applications of computer vision for real-word problems and it has been gaining more interest because of the progression in this field. This paper presents an efficient model for Vietnamese handwriting character recognition by Convolutional Neural Networks (CNNs) – a kind of deep neural network model can achieve high performance on hard recognition tasks. The proposed architecture of the CNN network for Vietnamese handwriting character recognition consists of five hidden layers in which the first 3 layers are convolutional layers and the last 2 layers are fully-connected layers. Overfitting problem is also minimized by using dropout techniques with the reasonable drop rate. The experimental results show that our model achieves approximately 97% accuracy.
Volume: 9
Issue: 2
Page: 276-281
Publish at: 2020-06-01

Classification of pneumonia from X-ray images using siamese convolutional network

10.12928/telkomnika.v18i3.14751
Kennard Alcander; Universitas Multimedia Nusantara Prayogo , Alethea; Universitas Multimedia Nusantara Suryadibrata , Julio Christian; Universitas Multimedia Nusantara Young
Pneumonia is one of the highest global causes of deaths especially for children under 5 years old. This happened mainly because of the difficulties in identifying the cause of pneumonia. As a result, the treatment given may not be suitable for each pneumonia case. Recent studies have used deep learning approaches to obtain better classification within the cause of pneumonia. In this research, we used siamese convolutional network (SCN) to classify chest x-ray pneumonia image into 3 classes, namely normal conditions, bacterial pneumonia, and viral pneumonia. Siamese convolutional network is a neural network architecture that learns similarity knowledge between pairs of image inputs based on the differences between its features. One of the important benefits of classifying data with SCN is the availability of comparable images that can be used as a reference when determining class. Using SCN, our best model achieved 80.03% accuracy, 79.59% f1 score, and an improved result reasoning by providing the comparable images.
Volume: 18
Issue: 3
Page: 1302-1309
Publish at: 2020-06-01

Towards cognitive artificial intelligence device: an intelligent processor based on human thinking emulation

10.12928/telkomnika.v18i3.14835
Catherine Olivia; Universitas Katolik Indonesia Atma Jaya Jakarta Sereati , Arwin Datumaya Wahyudi; Applied Master on Electrical Engineering State Polytechnic of Malang Sumari , Trio; Institut Teknologi Bandung Adiono , Adang Suwandi; Institut Teknologi Bandung Ahmad
The intervention of computer technology began the era of a more intelligent and independent instrumentation system based on intelligent methods such as artificial neural networks, fuzzy logic, and genetic algorithm. On the other hand, processor with artificial cognitive ability has also been discovered in 2016. The architecture of the processor was designed based on knowledge growing system (KGS) algorithm, a new concept in artificial intelligence (AI) which is focused on the emulation of the process of the growing of knowledge in human brain after getting new information from human sensory organs. KGS is considered as the main method of a new perspective in AI called as cognitive artificial intelligence (CAI). The design is to obtain the architecture of the data path of the processor. We found that the complexity of the processor circuit is determined by the number of combinations of sensors and hypotheses as the main inputs to the processor. This paper addresses the development of an intelligence processor based on cognitive AI in order to realize an Intelligence Instrumentation System. The processor is implemented in field programmable gate array (FPGA) and able to perform human thinking emulation by using KGS algorithm.
Volume: 18
Issue: 3
Page: 1475-1482
Publish at: 2020-06-01

Website quality of Malaysian Technical University

10.11591/ijeecs.v18.i3.pp1624-1628
Lim Pui Jie , Rohaizan Ramlan , Rohayanti Hassan , Rashidah Omar , Chan Shau Wei
University website is the platform for university to interact with people. It is also an interphase for people to infer and getting known about the university. In addition, quality of the university website is vital to let people get positive response to the university. Therefore, university website should be evaluated for better performance. This study evaluate website of Malaysian Technical University (MTUN) on year of 2016 based on the criteria selected using online web diagnostics tools. There are nine criteria selected to measure the website; load time, response time, page rank, traffic, design optimization, page size, number of items, markup validation and broken link. The result shows website of UMP performed better in design optimization, page rank and markup validation. Meanwhile, UTHM performed in page rank, load time and page size. UTEM excellences in response time, number of items and broken link. Lastly, UniMAP performed in traffic criteria only. However, the (MTUN) University website is almost not meets with the criteria that selected with the quality standard that have been suggested. 
Volume: 18
Issue: 3
Page: 1624-1628
Publish at: 2020-06-01

POGIL model on mathematical connection ability viewed from self-regulated learning

10.11591/ijere.v9i2.20321
Enyta Ramadisae Putri , Budiyono Budiyono , Diari Indriati
One area of education which has not escaped efforts to improve the Indonesian government is mathematics education. The Indonesian government must make good use of mathematics learning so that students can use the mathematical mindset to offset the pace of global competition. This research is an experimental research on the Process-Oriented Guided Inquiry Learning (POGIL) model on the ability of mathematical connections in terms of self-regulated learning. The design used in this study was a 2 × 3 factorial. The research sample was 179 students from 7th grade in three State Junior High Schools in Sukoharjo Regency, Central Java, Indonesia. The research sample consisted of an experimental group that subjected to the POGIL model and a control group that subjected to a direct learning model. This research instrument used was a written test and questionnaire. The data analysis technique used was a two-way ANOVA test with unbalanced cells and post hoc test. The results showed that: 1) the POGIL model produces better mathematical connection ability than the direct learning model, 2) Students with high category self-regulated learning have better mathematical connection ability than medium and low categories, and students with self-regulated learning the medium category have better mathematical connection ability than the low category.
Volume: 9
Issue: 2
Page: 394-400
Publish at: 2020-06-01

Photovoltaic solar farm; earthing system design for cost reduction and system compliance

10.11591/ijece.v10i3.pp2884-2893
Mohamad Nassereddine , Khaled Ali , Chadi Nohra
The increasing demand for green sustainable energy source led to a worldwide increase in the installation of large scale photovoltaic (PV) farms. To ensure the PV farms compliance with safety and operational guidelines, earthing systems are essential component of the design. An adequate earthing system for low, medium, and high voltage areas of the PV farm ensures energy under fault condition and system malfunction are absorbed without exceeding the desirable limits. The work in this paper captures the soil resistivity and the earthing system requirements for each voltage level. The paper highlights the boundaries for combined or separate earthing system between low, medium and high voltage. Furthermore, the works focus on the system cost and maintenance without jeopardizing system integrities and safety compliance. Case study is also included.
Volume: 10
Issue: 3
Page: 2884-2893
Publish at: 2020-06-01

Improved quality of service-based cloud service ranking and recommendation model

10.12928/telkomnika.v18i3.11915
Sirisha; Koneru Lakshmaiah Education Foundation Potluri , Katta Subba; Koneru Lakshmaiah Education Foundation Rao
One of the ongoing technologies which are used by large number of companies and users is cloud computing environment. This computing technology has proved that it provides certainly a different level of efficiency, security, privacy, flexibility and availability to its users. Cloud computing delivers on demand services to the users by using various service-based models. All these models work on utility-based computing such that users pay for their used services. Along with the various advantages of the cloud computing environment, it has its own limitations and problems such as efficient resource identification or discovery, security, task scheduling, compliance and sustainability. Among these resource identification and scheduling plays an important role because users always submits their jobs and expects responses in least possible time. Research is happening all around the world to optimize the response time, make span so as to reduce the burden on the cloud resources. In this paper, QoS based service ranking model is proposed for cloud computing environment to find the essential top ranked services. Proposed model is implemented in two phases. In the first phase, similarity computation between the users and their services is considered. In the second phase, computing the missing values based on the computed similarity measures is calculated. The efficiency of the proposed ranking is measured and the average precision correlation of the proposed ranking measure is showing better results than the existing measures.
Volume: 18
Issue: 3
Page: 1252-1258
Publish at: 2020-06-01
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