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30,907 Article Results

Assessing students’ continuance intention in using multimedia online learning

10.12928/telkomnika.v17i1.10328
Taqwa; STMIK AMIKOM Purwokerto Hariguna , Akmal; Universitas Ahmad Dahlan Akmal
The study aimed to assess the students’ continuance intention (SCI) in using multimedia online learning including students’ perceived usefulness (SPU), students’ ease of use (SPE), and students’ flow experience (SFE). There is no,so far, the assessment of students’ activity in using multimedia online learning within the extended Technology Acceptance Model (TAM).This study revealed the students’ continuance intentions in using online lessons.There were 523 students as the samples. They learned and examined the content of online English learning resources as well as multimedia aspects.TAM was used to predict the SCI. The results indicate that the students’ intentions are influenced positively by perceived usefulness, ease of use, and the flow experience. The SPU influenced more students’ motivation than SPE. It is recommended that designers of online learning should be more specific in determining target users. The online learners’ skill on ICT, pedagogical principles, and technological barrier in different region are among the determinant aspects for receiving positive enduring intention.
Volume: 17
Issue: 1
Page: 187-193
Publish at: 2019-02-01

Cognitive artificial-intelligence for doernenburg dissolved gas analysis interpretation

10.12928/telkomnika.v17i1.11612
Karel Octavianus; Bandung Institute of Technology Bachri , Umar; Bandung Institute of Technology Khayam , Bambang Anggoro; Bandung Institute of Technology Soedjarno , Arwin Datumaya Wahyudi; Bandung Institute of Technology Sumari , Adang Suwandi; Bandung Institute of Technology Ahmad
This paper proposes Cognitive Artificial Intelligence (CAI) method for Dissolved Gas Analysis (DGA) interpretation adopting Doernenburg Ratio method. CAI works based on Knowledge Growing System (KGS) principle and is capable of growing its own knowledge. Data are collected from sensors, but they are not the information itself, and thus, data needs to be processed to extract information. Multiple information are then fused in order to obtain new information with Degree of Certainty (DoC). The new information is used to identify faults occurred at a single observation. The proposed method is tested using the previously published dataset and compared with Fuzzy Inference System (FIS) and Artificial Neural Network (ANN). Experiment shows CAI implementation on Doernenburg Ratio performs 115 out of 117 accurate identification, followed by Fuzzy Inference System 94.02% and ANN 78.6%. CAI works well even with small amount of data and does not require trainings.
Volume: 17
Issue: 1
Page: 268-274
Publish at: 2019-02-01

Feature analysis for stage identification of Plasmodium vivax based on digital microscopic image

10.11591/ijeecs.v13.i2.pp721-728
Hanung Adi Nugroho , I Md. Dendi Maysanjaya , Noor Akhmad Setiawan , E. Elsa Herdiana Murhandarwati , Widhia K.Z Oktoeberza
Plasmodium parasite is identified to confirm malaria disease.  Paramedics need to observe the presence of this parasite prepared on thick and thin blood films under microscope.  However, false identification still occurs which is caused by human factor during the examination.  Thus, malaria identification based on digital image processing has been widely developed to overcome the error possibility.  This paper proposes a scheme to identify and classify the stages of Plasmodium vivax parasite on digital microscopic image of thin blood films based on feature analysis.  Shape and texture features are extracted from segmented parasite objects.   Feature selection based on wrapper method is then conducted to obtain relevant features which may contribute in improving the classification result.  The classification process is conducted based on Naïve Bayes classifier.  The performance of proposed method is evaluated using 73 digital microscopic images of P.vivax parasite on thin blood films comprising of 29 trophozoites, 10 schizonts and 34 gametocytes stages.  By using six selected features including perimeter, dispersion, mean of intensity, ASM, contrast GLCM and entropy GLCM, the proposed scheme achieves the best classification rate with the accuracy, sensitivity and specificity of 97.29%, 97.30% and 97.30%, respectively.  This indicates that the proposed scheme has a potential to be implemented in the development of a computerised aided malaria diagnosis system for assisting the paramedics.
Volume: 13
Issue: 2
Page: 721-728
Publish at: 2019-02-01

Generating similarity cluster of Indonesian languages with semi-supervised clustering

10.11591/ijece.v9i1.pp531-538
Arbi Haza Nasution , Yohei Murakami , Toru Ishida
Lexicostatistic and language similarity clusters are useful for computational linguistic researches that depends on language similarity or cognate recognition. Nevertheless, there are no published lexicostatistic/language similarity cluster of Indonesian ethnic languages available. We formulate an approach of creating language similarity clusters by utilizing ASJP database to generate the language similarity matrix, then generate the hierarchical clusters with complete linkage and mean linkage clustering, and further extract two stable clusters with high language similarities. We introduced an extended k-means clustering semi-supervised learning to evaluate the stability level of the hierarchical stable clusters being grouped together despite of changing the number of cluster. The higher the number of the trial, the more likely we can distinctly find the two hierarchical stable clusters in the generated k-clusters. However, for all five experiments, the stability level of the two hierarchical stable clusters is the highest on 5 clusters. Therefore, we take the 5 clusters as the best clusters of Indonesian ethnic languages. Finally, we plot the generated 5 clusters to a geographical map.
Volume: 9
Issue: 1
Page: 531-538
Publish at: 2019-02-01

Knowledge management system SOP using semantic networks connected with personnel information system: case study Universitas Singaperbangsa Karawang

10.12928/telkomnika.v17i1.9107
Intan; University of Singaperbangsa Karawang Purnamasari , Irman; Bogor Agricultural University Hermadi , Yani; Bogor Agricultural University Nurhadryani
Document Standard Operating Procedures (SOP) can manage business processes and employee performance in an organization. This study aims to develop a system that can publish SOP documents automatically distributed to employees. In this study, an analysis of the relationship between SOP documents and employees is carried out so that it can be directly allocated to employees according to the position. Knowledge analysis of the relationship between SOP documents and employees is done using semantic network analysis. Semantic networks are used to analyze components of knowledge and the relationship between SOP documents and employees. The results of the report of the elements of knowledge and the relationship between SOP documents found 25 SOP documents were consisting of 6 types of central nodes with 156 child nodes and had 7 types of relations containing 207 relations. SOP knowledge management system is connected to the personnel information system (SIPEG) so that it makes it easier for users to find, accommodate, and manage the knowledge contained in SOP documents. System implementation is done using PHP programming language with CodeIgniter framework, Rest API, and MySQL database.
Volume: 17
Issue: 1
Page: 179-186
Publish at: 2019-02-01

PVPF tool: an automatedWeb application for real-time photovoltaic power forecasting

10.11591/ijece.v9i1.pp34-41
Mohammad H. Alomari , Jehad Adeeb , Ola Younis
In this paper, we propose a fully automated machine learning based forecasting system, called Photovoltaic Power Forecasting (PVPF) tool, that applies optimised neural networks algorithms to real-time weather data to provide 24 hours ahead forecasts for the power production of solar photovoltaic systems installed within the same region. This system imports the real-time temperature and global solar irradiance records from the ASU weather station and associates these records with the available solar PV production measurements to provide the proper inputs for the pre-trained machine learning system along with the records’ time with respect to the current year. The machine learning system was pre-trained and optimised based on the Bayesian Regularization (BR) algorithm, as described in our previous research, and used to predict the solar power PV production for the next 24 hours using weather data of the last five consecutive days. Hourly predictions are provided as a power/time curve and published in real-time at the website of the renewable energy center (REC) of Applied Science Private University (ASU). It is believed that the forecasts provided by the PVPF tool can be helpful for energy management and control systems and will be used widely for the future research activities at REC.
Volume: 9
Issue: 1
Page: 34-41
Publish at: 2019-02-01

Prediction of PID control model on PLC

10.12928/telkomnika.v17i1.11589
Erwani Merry; Universitas Kristen Maranatha Sartika , T. Rudi; Universitas Kristen Maranatha Sarjono , Diki Dwi; Universitas Kristen Maranatha Saputra
PID (Proportional Integral Derivative) is a control algorithm that mostly used in industry. However, users have never known what the PID model that used inside the PLC. By knowing the PID model that used in PLC, users will have more choice in determining the more appropriate tuning algorithm. Also, users can use MATLAB to perform analysis and can implement it to PLC. Through OPC Server (Object Linking and Embedding for Process Control Server) as a software interface, programs on a windows operating system can communicate with industry devices universally. PID model prediction method is done by comparing the output of the plant controlled by PID model in PLC and PID model in SIMULINK MATLAB using OPC Server intermediaries. Based on comparison result in graph and analysis using integral error method, PLC M221 using Parallel PID model and PLC S7-1200 using Ideal PID model.
Volume: 17
Issue: 1
Page: 529-536
Publish at: 2019-02-01

Design of spiral labyrinth microstrip antenna for DVB-T application

10.12928/telkomnika.v17i1.11628
Indra; Universitas Trisakti Surjati , Syah; Universitas Trisakti Alam , Juliarto; Universitas Trisakti Karnadi
Digital television broadcasting is technologies that have been developed by any country in the world. The advantages implementations of digital television broadcasting include reception of picture and sound sharper and better. This paper proposes a new design of spiral labyrinth microstrip antenna feed by microstrip line with array two element for Digital Video Broadcasting Technology (DVB-T) application at work frequency of 586 MHz. The design of spiral labyrinth is used to minimize the dimensions of microstrip patch antenna while maintaining the working frequency at 586 MHz and array technique used to improve gain of antenna. The proposed antenna design was originally a rectangular patch that has been modified by the labyrinth spiral method. From the measurement result obtained return loss of -14.15 dB and VSWR of 1.54 at working frequency of 586 MHz. Bandwidth of proposed antenna is 117 MHz (547 MHz–664 MHz) while gain of antenna is 7.78 dBi. Beside that, using of the labyrinth spiral patch successfully reduced the dimensions of the microstrip antenna until 62.2% compared with the conventional rectangular patch of microstrip antenna. This study is usefull for DVB-T application in order to achieve the maximum signal quality and picture.
Volume: 17
Issue: 1
Page: 76-85
Publish at: 2019-02-01

Black hole attack behavioral analysis general network scalability

10.11591/ijeecs.v13.i2.pp677-682
Layth A. Khalil Al Dulaimi , R. Badlishah Ahmad , Naimah Yaakob , Mohd Hafiz Yusoff , Mohamed Elshaikh
A mobile ad hoc network (MANET) is a frameworkless system of different mobile devices known for its self-arranging conduct. MANETs can convey over moderately data transfer capacity compelled routing connections. In a blackhole assault, a malicious node falsely advertises the shortest path to the destination node, intending to disrupt communication. Our objective was to review the impact of a blackhole assault on networks. To accomplish this, we simulated MANET situations, which include the blackhole node, using the OMNET++ simulator to demonstrate the effects of a single blackhole attack and multiple blackhole attacks on MANET performance have examined for networks. We analysed MANET performance under blackhole assaults through the use of performance grids. A mobile ad hoc network (MANET) is a frameworkless system of different mobile devices known for its self-arranging conduct. MANETs can convey over moderately data transfer capacity compelled routing connections. In a blackhole assault, a malicious node falsely advertises the shortest path to the destination node, intending to disrupt communication. Our objective was to review the impact of a blackhole assault on networks. To accomplish this, we simulated MANET situations, which include the blackhole node, using the OMNET++ simulator to demonstrate the effects of a single blackhole attack and multiple blackhole attacks on MANET performance have examined for networks. We analysed MANET performance under blackhole assaults through the use of performance grids..
Volume: 13
Issue: 2
Page: 677-682
Publish at: 2019-02-01

New instances classification framework on Quran ontology applied to question answering system

10.12928/telkomnika.v17i1.9794
Fandy Setyo; STMIK AMIKOM Purwokerto Utomo , Nanna; Universiti Teknikal Malaysia Melaka Suryana , Mohd Sanusi; Universiti Teknikal Malaysia Melaka Azmi
Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. However, this method has a drawback; if the training set amount is small, then the classifier accuracy could decline. Unfortunately, Holy Quran has a small corpus. Based on this problem, our study aims to formulate new instances classification framework for small training corpus applied to semantic question answering system. As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. This algorithm is chosen since it robustness to noisy data and has an excellent achievement to handle small dataset. Furthermore, document processing module on question answering system is used to access instances classification result in Quran ontology.
Volume: 17
Issue: 1
Page: 139-146
Publish at: 2019-02-01

WSN performance based on node placement by genetic algorithm at smart home environment

10.12928/telkomnika.v17i1.11621
Mochammad Hannats Hanafi; University of Brawijaya Ichsan , Wijaya; University of Brawijaya Kurniawan , Gembong Edhi; University of Brawijaya Setyawan , Irma Asri Kartika; University of Brawijaya Sandy
Wireless sensor connectivity is one of several factors that determines the communication reliability of each node. The placement of the node depends on the area that covered by wireless coverage area, so the node placement should be optimally placed. But the other aspect is the sensor coverage area. Sensor coverage area sometimes could be different with wireless sensor coverage area. Based on that situation, it needs to optimize that situation. Genetic Algorithm is an algorithm that utilizes a heuristic approach that uses biological mechanism evolution. It used to evolution the best position of Sensor Node based on Wireless and Sensor coverage area. After the position of each node generated by Genetic Algorithm, it still needs to evaluate the wireless sensor node performance. The performance indicates that the genetic algorithm can be used to determine sensor node placement in the smart home environment. The smart home environment used to monitor event at the house such as wildfire. In this research used Quality of Services (QoS) to measure wireless sensor performance. The experimental testing scenario will be used to place several nodes that generated. The QoS performed systems reliability that produced based on 3, 4 and 5 testing nodes, the minimum and maximum of each: delay is 6.21 and 8.74 milliseconds, jitter is 0.11 and 1.59 Hz and throughput is 68.83 and 90.49 bps. Based on ETSI classification, the performance of sensor node placement is Good and acceptable in real-time systems.
Volume: 17
Issue: 1
Page: 299-306
Publish at: 2019-02-01

Dual resonance element for broadband reflectarray antenna

10.11591/ijeecs.v13.i2.pp556-561
M. Hashim Dahri , M.R. Kamaruddin , M.H. Jamaluddin , M. Inam , S. Z. N. Zool Ambia , N. Shafie
A dual resonance reflectarray unit cell element has been proposed which evolved from a square patch element to enhance its bandwidth performance. A bend in the width of the element is used to modify its dimensions and surface currents for broadband operation. The results have been analyzed in the frequency band of 24 GHz to 28 GHz. Two different combinations of its dimensions are selected for the investigating of its various performance parameters. A maximum static phase range of 432° and 255° have been obtained with selected dimensions. The wide-band features of proposed unit cell element can be used particularly to design a broadband reflectarray antenna for future fast communication systems.
Volume: 13
Issue: 2
Page: 556-561
Publish at: 2019-02-01

Architecture design for a multi-sensor information fusion processor

10.12928/telkomnika.v17i1.10180
Catherine Olivia; Institut Teknologi Bandung Sereati , Arwin Datumaya Wahyudi; Synergy of the State Apparatus' Social Media (SIMAN) Sumari , Trio; Institut Teknologi Bandung Adiono , Adang Suwandi; Institut Teknologi Bandung Ahmad
This paper discusses the design of the architecture of an information fusion processor. This processor emulates the way of human thinking, namely by drawing conclusions from the obtained collection of information. Architecture design for this processor is based on Knowledge Growing System (KGS) algorithm. KGS is a novelty in Artificial Intelligence field. Compared to other AI methods, KGS focuses on the observation of the process of the knowledge growth within human brain based on information received from the surrounding environment. By using KGS algorithm, this processor works by receiving inputs from a set of sensors and possible hypotheses obtained after the processing of the information. The processor generates a value which is called as Degree of Certainty (DoC), which show the most possible hypothesis among all alternative ones. The Processor Elements which are used to perform KGS algorithm is designed based on systolic array architecture. The design of this processor is realized with VHSIC Hardware Design Language (VHDL) and synthesized by using FPGA Quartus II.13.1. The results show that the data path which has been design is able to perform the mechanism of KGS computation.
Volume: 17
Issue: 1
Page: 362-369
Publish at: 2019-02-01

Natural Automatic Musical Note Player using Time-Frequency Analysis on Human Play

10.12928/telkomnika.v17i1.11606
Khafiizh; Universitas Dian Nuswantoro Hastuti , Arry Maulana; Universitas Dian Nuswantoro Syarif , Ahmad Zainul; Universitas Dian Nuswantoro Fanani , Aton Rustandi; Universitas Dian Nuswantoro Mulyana
This research aims to develop an automatic gamelan musical note player that can naturally play musical note as human does. A musician estimates time to hit an instrument button in an approximate time which is as close as to the target time. The tolerated time to play a note was identified based on the human play. A gamelan musician was selected to play five note sequences of songs, and the play was recorded to be analyzed. Execution time in hitting instrument buttons in human play was identified using time-frequency analysis and peak detection to define time range which can be tolerated as time value that not too fast or not too late in hitting buttons, and then the result of the analysis was used as parameters to randomize approximate time to play a note. The evaluation shows that the program played all note sequences in the approximate time as human does and the program played more natural and better than another program which played a note as exact as its time target.
Volume: 17
Issue: 1
Page: 235-245
Publish at: 2019-02-01

Private cloud storage implementation using OpenStack Swift

10.12928/telkomnika.v17i1.11599
Agustinus; Petra Christian University Noertjahyana , Juan; Petra Christian University Reno , Henry Novianus; Petra Christian University Palit , Justinus; Petra Christian University Andjarwirawan
The use of distributed and parallel computer systems is growing rapidly, requiring an appropriate system to support its work processes. One technology that supports distributed computer systems is cloud computing. This system can generate the need to maximize the use of existing computing resources, one of which is in the form of cloud-based storage. The computer laboratory of Informatics Department of Petra Christian University has very large resources, but they have not been optimized in the utilization of existing storage devices. This condition gives the idea to utilize computers in the laboratory with cloud, so the storage can be used well. This implementation used the OpenStack cloud framework, which could provide IaaS service. From some existing OpenStack services, storage management used OpenStack Swift on its processing. OpenStack Swift is a cloud-based storage service that leverages various computing resources. After the implementation process, testing was done by way of data management, so storage could store, retrieve, and delete data. In addition, testing was also done by turning off some physical machines to ensure cloud services could remain well accessible, and measure the speed of data transfer in cloud storage. The resulting data was used to evaluate the cloud storage systems that had been created.
Volume: 17
Issue: 1
Page: 218-225
Publish at: 2019-02-01
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