cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota bandung,
Jawa barat
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 251 Documents
 12   13   14   15   16 
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).
Implementation of Analytical Hierarchy Process (AHP) for Determining Priority of Software Assessment in West Java Provincial Government Based on ISO/IEC 25010 (Case Study: Sapawarga Application) Nisrina Nurhuda; Eko Darwiyanto; Sri Widowati
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.525

Abstract

The quality of the software is defined ISO as the totality of the features and characteristics of the product or services that depend on the ability to satisfy user needs. Sapawarga is software used to meet the needs of citizens in channeling aspirations, proposals, and obtaining information in one application. There are some negative comments about the app on Google’s app store. This indicates there are quality issues in sapawarga software. The results of a follow-up survey showed users of the application experienced a 45.20% decrease, due to the server not responding, difficulty finding information, etc. This research was conducted to evaluate the quality of the software based on ISO 25010 consisting of eight characteristics including functional suitability, reliability, usability, performance efficiency, maintainability, portability, security, and compatibility. The AHP pairing comparison method is used to select the three most important ISO characteristics. These three most important characteristics are then used to assess the application of sapawarga and propose recommendations for improvement. Based on expert judgment using AHP pair comparison method, the three characteristics that most affect the application of sapawarga are functional suitability, usability, and performance efficiency with interest rates of 24.9%, 23.2%, 16.5%.
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.
The Implementation of f(x) = 3(x 3 − x 2 − x) + 2 as CSPRNG Chaos-Based Random Number Generator Maria Rosalina Yopeng; Alz Danny Wowor
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.546

Abstract

This research implemented the cubic function f(x) = 3(x^3 − x^2 − x) + 2 using a FixedPoint Iteration to produce several iteration functions that can be used as random number generator. The test results obtain six iteration functions, and based on graphic visualizationwith Scatter plot and randomness test with mono bit test, bit block, and run test, the results only obtain two iteration functions namely x2 − 1 + 2/(3x) and f(x) = 1 + 1/x − 2/(3x^2)which can produce CSPRNG Chaos-based random number. Encryption testing shows that both functions can generate keys that make plaintext and ciphertext statistically unrelated, so the f(x) = 1 + 1/x − 2/(3x^2) function can be used as a CSPNRG chaos-based random number generator function.
Implementation of K-Means++ Algorithm for Store Customers Segmentation Using Neo4J Arief Chaerudin; Danang Triantoro Murdiansyah; Mahmud Imrona
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.547

Abstract

In the era of data and information, data has become one of the most useful and desirable things. Data can be useful information if the data is processed properly. One example of the results of data processing in business is by making customer segmentation. Customer segmentation is useful for identifying and filtering customers according to certain categories. Analysis of the resulting segmentation can produce information about more effective target market, more efficient budget, more accurate marketing or promotion strategies, and much more. Since segmentation aims to separate customers into several categories or clusters, a clustering algorithm can be used. In this research, customer segmentation is carried out based on the value of income and value of expenditure. The categorization method that will be used for this research is to use the K-Means ++ algorithm which is useful for determining clusters of the given data. In this study, the implementation of K-Means ++ is carried out using Neo4J. Then in this research, a comparison of K-Means ++ and K-Means is carried out. The result obtained in this study is that K-Means ++ has a better cluster than K-Means in term of silhouette score parameter.
Analysis of Website Portal Rumah Belajar Using WebQual 4.0 Method and Important Performance Analysis ADE BAYU SEPTIAN; Eko Darwiyanto; Hetti Hidayati
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.548

Abstract

Portal Rumah Belajar is implementing E-Government in Presidential Instruction No. 3 of 2003 concerning National Development Policy and Strategy. The government is required to take advantage of advances in information and communication technology by developing e-government-based public services. The Portal Rumah Belajar is a means for students to get various information about the learning material. Therefore this website must be able to present quality information based on user perceptions. Based on previous research that analyzed the Rumah Belajar website, there are deficiencies in usability factors and information quality factors that affect user satisfaction. Therefore, the study discusses the Portal Rumah Belajar Website Analysis topic using the WEBQUAL 4.0 method and Importance Performance Analysis to evaluate the Portal Rumah Belajar website's quality. WEBQUAL 4.0 as a reference for making a questionnaire and Importance Performance Analysis as an analysis in the form of a level of conformity to the gap quantification. The results obtained from the evaluation that the website's quality has a conformity level of 101.16% concluded that the user feels satisfied with the site's service. The gap level has a positive value of 0.04. It can be concluded that users experience satisfaction with the website
The Quality Comparison of WebRTC and SIP Audio and Video Communications with PSNR Muhhamad Affan Hasby; Aji Gautama Putrada; Febri Dawani
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.549

Abstract

Video and audio communications have become part of all areas of work. Two real-timecommunication protocols commonly used for IP-based video and audio communicationsare Session Initiation Protocol (SIP) and real-time web communications (WebRTC). Bothprotocols have been widely used in softphone and video conferencing applications. Themain objective of this research is to make an analysis of the performance of a client serverapplication for video and audio communications developed by SIP and WebRTC. The SIPsystem consists of a softphone on the client side using Bria and a FreePBX server, forWebRTCapplications, using JavaScript and a server at Node.js. The results showed that the WebRTCaudio and video communication provided better quality in terms of PSNR. This is due tothe different codecs used between WebRTC and SIP. WebRTC uses VP8 as video codec, SIPuses H.246 as video codec, WebRTC uses G.711 as audio codec, and implemented SIP usesG.729 as audio codec.
Classification Model of Consumer Question about Motorbike Problems by Using Naïve Bayes and Support Vector Machine Ekky Wicaksana; Danang Triantoro Murdiansyah; Isman Kurniawan
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.2.561

Abstract

The motorbike plays an important role in supporting daily activity. The motorbike is known as one of the transportation modes that is frequently used in Indonesia. The number of motorbikes used in Indonesia is continuously increasing time by time. Hence, the occurrence of motorbike problems can affect community activity and disturb the economic condition in society. Since the problem of the motorbike can occur at any time, a prevention action is required by providing an online consultation platform. However, a classification model is required to handle a wide range of questions about the motorbike problem. By classifying those questions into a specific class of problems, the solution can be delivered to the consumer faster. In this study, we developed prediction models to classify consumer questions. The data set was collected from consumer questions regarding motorbike problems that are commonly occurring. The model was developed using two machine learning algorithms, i.e., Naïve Bayes and Support Vector Machine (SVM). Text vectorization was performed by using the n-gram and term frequency-inverse document frequency (TF-IDF) method. The results show that the SVM model with the uni-trigram model performs better with the value of accuracy and F-measure, which are 0.910 and 0.910, respectively.

Page 14 of 26 | Total Record : 251

 12   13   14   15   16 

Filter by Year

2016 2024


Reset
Filter By Issues
All Issue Vol. 9 No. 3 (2024): December, 2024 Vol. 9 No. 2 (2024): August, 2024 Vol. 9 No. 1 (2024): April, 2024 Vol. 8 No. 3 (2023): December 2023 Vol. 8 No. 2 (2023): August, 2023 Vol. 8 No. 1 (2023): April, 2023 Vol. 7 No. 3 (2022): December, 2022 Vol. 7 No. 2 (2022): August, 2022 Vol. 7 No. 1 (2022): April, 2022 Vol. 6 No. 3 (2021): December, 2021 Vol. 6 No. 2 (2021): September, 2021 Vol. 6 No. 1 (2021): April, 2021 Vol. 5 No. 3 (2020): December, 2020 Vol. 5 No. 2 (2020): September, 2020 Vol. 5 No. 1 (2020): Maret, 2020 Vol. 4 No. 3 (2019): December, 2019 Vol. 4 No. 2 (2019): September, 2019 Vol. 4 No. 1 (2019): Maret, 2019 Vol. 3 No. 2 (2018): September, 2018 Vol. 3 No. 1 (2018): Maret, 2018 Vol. 2 No. 2 (2017): September, 2017 Vol. 2 No. 1 (2017): Maret, 2017 Vol. 1 No. 2 (2016): September, 2016 Vol. 1 No. 1 (2016): March, 2016 More Issue