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INDONESIA
Indonesian Journal on Computing (Indo-JC)
Published by Universitas Telkom
ISSN : 24609056     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
Arjuna Subject : -
Articles 12 Documents
 1   2 
Search results for , issue "Vol. 5 No. 3 (2020): December, 2020" : 12 Documents clear
Grid-based Image Encryption using Code-based Cryptography Dian Anggoro Putro Bhagaskoro; Ari Moesriami Barmawi
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.493

Abstract

Recently, image is frequently sent or exchanged electronically, such that image security is important. A method for securing images is using RSA. However, RSA needs more time for securing an image. For overcoming the RSA problem, McEliece Cryptosystem is introduced to grid-based image encryption. The image is divided into blocks and each block is divided into grids, then finally McEliece Cryptosystem is applied to the pixels in the grids. Based on the experiment’s result, it was proven that the execution time of the proposed method is less than the previous one, while maintaining the security. Keywords: McEliece Cryptosystem, RSA, Image Encryption, Image Decryption, Grid 
Implementation of Dependency Parser Using Artificial Neural Network Methods Nurul Izzah; Moch Arif Bijaksana; Arief Fatchul Huda
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.504

Abstract

In recent years, parsing has become very popular within the scope of NLP (Natural Language Processing) with the presence of Dependency Parser. However, almost all existing Dependency Parser do classifications based on millions of sparse indicator features. This feature is not only bad in drawing conclusions, but also significantly limits the speed of parsing so that the resulting parsing is not optimal. To overcome these problems, changing the use of sparse features becomes dense features to reduce sparsity between words. The Artificial Neural Network classification method is used to produce fast and concise parsing in the Transition-Based Dependency Parser by using 2 hyperparameters. The dataset used in this study is Arabic, Chinese, English, and Indonesian. Based on the evaluation that has been done, it shows a higher result using the second hyperparameter. In testing with English test data, the accuracy value of LAS (Labeled Attachment Score) is 80.4% and UAS (Unlabelled Attachment Score) is 83%, Then with dev data obtained an accuracy value of LAS 81.1% and UAS 83.7%, and parsing speed of 98 sentences per second (sent/s).Keywords: Parsing, dependency parser, transition-based dependency parsing.
Implementation Information Gain Feature Selection for Hoax News Detection on Twitter using Convolutional Neural Network (CNN) Husnul Khotimah Farid; Erwin Budi Setiawan; Isman Kurniawan
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.506

Abstract

The development of information and communication technology is currently increased, especially related to social media. Nowadays, many people get information through social media, especially Twitter, because of its easy access and it doesn't cost much. However, it has a negative impact in the form of spreading fake news or hoaxes that are difficult to detect. In this research, the authors developed a hoax news detection model using the Convolutional Neural Network and the TF-IDF weighting method. Feature selection is performed using Information Gain with various features, such as unigram, bigram, trigram and a combination of the three. Testing is done with 3 scenarios, classification, classification by weighting, classification by weighting and feature selection. The parameter used in the information gain feature selection is the threshold 0.8. The results showed that the classification by weighting and feature selection produced the highest accuracy that is equal to 95.56% on the unigram + bigram features with a comparison of training data and test data 50:50.
Audit of IT Governance Diskominfo Kota Serang Using COBIT 5 Mochamad Arie Rafli Katami; Eko Darwiyanto; Yanuar Arie Firdaus
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.518

Abstract

The existing IT governance in Department of Communication and Informatics (Diskominfo) Serang City has an obstacle. The obstacle is innovation that has not fully facilitated the day-to-day governance and operational processes. Because good IT governance will greatly support the activities of the organization in achieving the goals set by the organization's vision and mission because it requires a harmony in business strategy and IT strategy. IT Governance is also able to find new opportunities through the application of innovative technology. To find out the current level of capability in Department of Communication and Informatics Serang City, IT governance audits are needed. COBIT 5 generates profits through effective IT management and management. The Department of Communication and Informatics Serang City target ability level is level 2 (Managed Process).
Hybrid Array List: An Efficient Dynamic Array with Linked List Structure Mutaz Rasmi Abu Sara; Mohammad F. J. Klaib; Masud Hasan
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.527

Abstract

In this paper, we present an efficient dynamic array, called hybrid array list (HAL), whose structure is a linked list and each node is an array. In a HAL H, each node, called a chunk, is an array of size at most 2c, where c is an initial array size determined by the user. As the elements are added or deleted in H, it grows or shrinks by the number of nodes in the linked list as well as by the sizes of the chunks. We consider the operations append, insert and delete as well as a helping operation actual position in H. These operations run in O(1), O(m+c), O(m+c) and O(m) time, respectively, in worst case, where m is the number of chunks in H. These running times are much less than the worst case running time, which is O(n), where n is the total number of elements in H, taken by these operations in linked list or array. We implement HAL and compare these operations with similar operations in array list of Java and vector of C++. Our results show that H can perform substantially better when c is about half of the total number of elements.
Study of Machine Learning Algorithm on Phonocardiogram Signals for Detecting of Coronary Artery Disease Satria Mandala; Miftah Pramudyo; Ardian Rizal; Maurice Fikry
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.536

Abstract

Several methods of detecting coronary artery disease (CAD) have been developed, but they are expensive and generally use an invasive catheterization method. This research provides a solution to this problem by developing an inexpensive and non-invasive digital stethoscope for detecting CAD. To prove the effectiveness of this device, twenty-one subjects consisting of 11 CAD patients and 10 healthy people from Hasan Sadikin Hospital Bandung were selected as validation test participants. In addition, auscultation was carried out at four different locations around their chests, such as the aorta, pulmonary, tricuspid, and mitral. Then the phonocardiogram data taken from the stethoscope were analyzed using machine learning. To obtain optimal detection accuracy, several types of kernels such as radial basis function kernel (RBF), polynomial kernel and linear kernel of Support Vector Machine (SVM) have been analyzed. The experimental results show that the linear kernel outperforms compared to others; it provides a detection accuracy around 66%. Followed by RBF is 56% and Polynomial is 46%. In addition, the observation of phonocardiogram signals around the aorta is highly correlated with CAD, giving an average detection accuracy for the kernel of 66%; followed by 44% tricuspid and 43% pulmonary.
Grid-based Image Encryption using Code-based Cryptography Bhagaskoro, Dian Anggoro Putro; Barmawi, Ari Moesriami
Indonesian Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.493

Abstract

Recently, image is frequently sent or exchanged electronically, such that image security is important. A method for securing images is using RSA. However, RSA needs more time for securing an image. For overcoming the RSA problem, McEliece Cryptosystem is introduced to grid-based image encryption. The image is divided into blocks and each block is divided into grids, then finally McEliece Cryptosystem is applied to the pixels in the grids. Based on the experiment’s result, it was proven that the execution time of the proposed method is less than the previous one, while maintaining the security. Keywords: McEliece Cryptosystem, RSA, Image Encryption, Image Decryption, Grid 
Implementation of Dependency Parser Using Artificial Neural Network Methods Izzah, Nurul; Bijaksana, Moch Arif; Huda, Arief Fatchul
Indonesian Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.504

Abstract

In recent years, parsing has become very popular within the scope of NLP (Natural Language Processing) with the presence of Dependency Parser. However, almost all existing Dependency Parser do classifications based on millions of sparse indicator features. This feature is not only bad in drawing conclusions, but also significantly limits the speed of parsing so that the resulting parsing is not optimal. To overcome these problems, changing the use of sparse features becomes dense features to reduce sparsity between words. The Artificial Neural Network classification method is used to produce fast and concise parsing in the Transition-Based Dependency Parser by using 2 hyperparameters. The dataset used in this study is Arabic, Chinese, English, and Indonesian. Based on the evaluation that has been done, it shows a higher result using the second hyperparameter. In testing with English test data, the accuracy value of LAS (Labeled Attachment Score) is 80.4% and UAS (Unlabelled Attachment Score) is 83%, Then with dev data obtained an accuracy value of LAS 81.1% and UAS 83.7%, and parsing speed of 98 sentences per second (sent/s).Keywords: Parsing, dependency parser, transition-based dependency parsing.
Implementation Information Gain Feature Selection for Hoax News Detection on Twitter using Convolutional Neural Network (CNN) Farid, Husnul Khotimah; Setiawan, Erwin Budi; Kurniawan, Isman
Indonesian Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.506

Abstract

The development of information and communication technology is currently increased, especially related to social media. Nowadays, many people get information through social media, especially Twitter, because of its easy access and it doesn't cost much. However, it has a negative impact in the form of spreading fake news or hoaxes that are difficult to detect. In this research, the authors developed a hoax news detection model using the Convolutional Neural Network and the TF-IDF weighting method. Feature selection is performed using Information Gain with various features, such as unigram, bigram, trigram and a combination of the three. Testing is done with 3 scenarios, classification, classification by weighting, classification by weighting and feature selection. The parameter used in the information gain feature selection is the threshold 0.8. The results showed that the classification by weighting and feature selection produced the highest accuracy that is equal to 95.56% on the unigram + bigram features with a comparison of training data and test data 50:50.
Audit of IT Governance Diskominfo Kota Serang Using COBIT 5 Katami, Mochamad Arie Rafli; Darwiyanto, Eko; Firdaus, Yanuar Arie
Indonesian Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.518

Abstract

The existing IT governance in Department of Communication and Informatics (Diskominfo) Serang City has an obstacle. The obstacle is innovation that has not fully facilitated the day-to-day governance and operational processes. Because good IT governance will greatly support the activities of the organization in achieving the goals set by the organization's vision and mission because it requires a harmony in business strategy and IT strategy. IT Governance is also able to find new opportunities through the application of innovative technology. To find out the current level of capability in Department of Communication and Informatics Serang City, IT governance audits are needed. COBIT 5 generates profits through effective IT management and management. The Department of Communication and Informatics Serang City target ability level is level 2 (Managed Process).

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