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Data Science: Journal of Computing and Applied Informatics
Published by Universitas Sumatera Utara
ISSN : 25806769     EISSN : 2580829X     DOI : -
Core Subject : Science,
Computer Science & IT
Data Science: Journal of Computing and Applied Informatics (JoCAI) is a peer-reviewed biannual journal (January and July) published by TALENTA Publisher and organized by Faculty of Computer Science and Information Technology, Universitas Sumatera Utara (USU) as an open access journal. It welcomes full research articles in the field of Computing and Applied Informatics related to Data Science from the following subject area: Analytics, Artificial Intelligence, Bioinformatics, Big Data, Computational Linguistics, Cryptography, Data Mining, Data Warehouse, E-Commerce, E-Government, E-Health, Internet of Things, Information Theory, Information Security, Machine Learning, Multimedia & Image Processing, Software Engineering, Socio Informatics, and Wireless & Mobile Computing. ISSN (Print) : 2580-6769 ISSN (Online) : 2580-829X Each publication will contain 5 (five) manuscripts published online and printed. JoCAI strives to be a means of periodic, accredited, national scientific publications or reputable international publications through printed and online publications.
Arjuna Subject : -
Articles 86 Documents
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The Cluster Analysis of Online Shop Product Reviews Using K-Means Clustering Nainggolan, Rena; Eviyanti Purba
Data Science: Journal of Computing and Applied Informatics Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v4.i2-2855

Abstract

Technological developments have made changes in people's lifestyles, namely changes in the behavior of people who had shopped directly or offline to online. Many benefits are obtained from shopping online, namely the many conveniences offered by shopping online, besides that there are also many disadvantages of shopping online, namely the many risks in using e-commerce facilities, namely the problem of product or service quality, safety in payments, fraud. This research aims to mine review data on one of the e-commerce sites which ultimately produces clusters using the K-Means Clustering algorithm that can help potential customers to make a decision before deciding to buy a product or service
Analysis of Knowledge Management in Information Systems Faculty of Da'wah and Communication Studies UIN Syarif Hidayatullah Jakarta based on Usability Evaluation Hardi, Tomi
Data Science: Journal of Computing and Applied Informatics Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v4.i2-3969

Abstract

Information systems are media used to channel information. each campus has a medium for channeling information. One of them is the UIN Syarif Hidayatullah Jakarta campus. One of the information systems owned by Uin Syarif Hidayatullah Jakrta is the information system at the Faculty of Da'wah and Communication Studies. In this system there are several parts, namely the homepage, accreditation, academic, student affairs, library and others. The purpose of this study is to evaluate Usability to improve user satisfaction in using this information system. The research method used is literature study, field studies and SUMI (Software Usability Measurement Inventory) questionnaire. The questionnaire was conducted on 20 respondents namely 10 lecturers and 10 students of the da'wah and communication faculty. The questionnaire was carried out in 3 categories, namely effectiveness, efficiency and satisfaction with the linker agreed, disagreed and did not know. The results of the SUMI questionnaire calculation of the information system are 80, 75,75,70,70,87.5. The usability evaluation results are above average, meaning that usability in the Da'wah and Communication faculty information system has been going well.
Comparison Encryption of How to Work Caesar Cipher, Hill Cipher, Blowfish and Twofish Haryono, Wasis
Data Science: Journal of Computing and Applied Informatics Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v4.i2-4004

Abstract

Security is the level of confidentiality of data stored using cryptography. There are many ways you can do to improve security. In this study, the writer will use a method by encrypting the database with the Caesar Cipher Algorithm, Hill Cipher and Blowfish. Caesar Cipher, Hill Cipher and Blowfish are part of the symmetric algorithm, which means that the encryption and decryption process have the same key. The encryption and decryption process in Caesar Cipher, Hill Cipher and Blowfish Algorithms each has one key. algorithm encryption techniques using symmetric passwords have 2 types, namely block ciphers and stream ciphers. Caesar Cipher, Hill Cipher and Blowfish and Twofish Algorithms are the encryption of the block cipher that breaks or creates blocks to encrypt and obtain cipher text. Result in this paper In Caesar Cipher, it is carried out like 3 blocks of encryption. Whereas in Hill Cipher a word is divided into several blocks and each block is encrypted. In Blowfish, several iterations are performed to get the text cipher, the input is 64 bits of data that can be done as many as 16 iterations. In Twofish the input is 128 bits, in contrast to Blowfish which is only 64 bits, Twofish can also accept 256 bits long and do 16 iterations to get the cipher text. Twofish has stronger security than the 3 algorithms above, Twofish also takes up more memory and takes longer to encrypt.
Impact of Evaporation on the Performance of Ant Colony Optimization-Based Routing Protocols on the Wireless Sensor Network Huzaifah, Ade Sarah; R.A. Fattah Adriansyah; Reza Firsandaya Malik
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i1-4103

Abstract

Wireless Sensor Network (WSN) has the characteristics limited computing, memory and energy, so a routing protocol that supports WSN network performance is needed. Routing protocols based Ant Colony Optimization (ACO) are very suitable for use in WSN for routing data packets. In this report, we will try out several kinds of parameter values that bear on the pheromone evaporation (ρ) on the ACO algorithms applied to the WSN routing protocol with grid topology on the number of nodes variables in the WSN network. Where this can increase the number of delivery packets on a busy WSN network and each node transmits a packet continuously. From the results, the value of ρ 0.75 makes WSN performance on the grid topology with the number of nodes 12 and 30 very good in terms of the delivery packet, but with the number of nodes 70 the value of ρ 0.70 makes WSN performance better than the delivery packet side.
A Hybrid Cryptosystem Using Vigenère Cipher and Rabin-p Algorithm in Securing BMP Files Budiman, Mohammad Andri; Muhammad Yogi Saputra; Handrizal
Data Science: Journal of Computing and Applied Informatics Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v4.i2-4173

Abstract

Vigenère cipher is a classical cryptography algorithm and similar to other classical algorithms, it produces smaller but less secure ciphertexts than a public key cryptography algorithm. Meanwhile, Rabin-p is a public key cryptography algorithm with a stronger encryption than Vigenère cipher. Nevertheless, as a public key algorithm, Rabin-p is inefficient to encrypt vast amounts of messages such as BMP image files, since the size of the cipherimages will increase manyfold and this would lead to a problem in storing and sending the cipherimages. To overcome these problems, in this study, we combined the Vigenère cipher and the Rabin-p algorithm in a hybrid cryptosystem scheme. In the experiment, the Vigenère cipher was used to encrypt the BMP files and the Rabin-p algorithm was used to encrypt the Vigenère keys. The result showed that the size of the cipherimages did not increase and the decryption procedure could recover the original BMP files while maintaining their integrity.
Impact of Cloud-based Infrastructure on Telecom Managed Services Models Anicho, Ogbonnaya; Tariq Abdullah
Data Science: Journal of Computing and Applied Informatics Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v4.i2-4339

Abstract

This paper examines how cloud-based infrastructure is impacting classical implementations of telecom Managed Services (MS) models with focus on network operations and maintenance (O&M). The migration of legacy network assets to the ‘cloud’ has altered traditional telecom network configuration. This work explores how cloud-based network infrastructure may alter MS models in the telecom network domain. It is expected that the unique offerings of cloud-based solutions will impact existing MS models and may require redesigning or adjusting operation and maintenance processes and frameworks. As network infrastructure migrates to the cloud, telecom MS delivery models must evolve as well to satisfy new requirements. This paper lays out essential aspects of traditional MS models that may be impacted as a result of cloud-based infrastructure. It further proposes a framework, and conceptual software design for systematically analysing the gaps in current MS models in order to identify requirements for improved MS delivery in the cloud era.
A Development of E-Learning-Based Instructional Media for English At Medan Civil Aviation Academy Tiara Sylvia; Liber Tommy Hutabarat
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i1-4350

Abstract

The research aims to: (1) give comprehension of the concept of E-Learning as an instructional media; (2) develop E-Learning based instructional media for English; (3) know the effectiveness of E-Learning as an instructional media to improve cadets’ skill in English. E-Learning based instructional media was developed in Learning Management System (LMS) of Medan Civil Aviation Academy consisting of applicable features to be used easily and effectively by lecturer and cadets based on Elementary English lesson plan. The research was conducted at Medan Civil Aviation Academy in the odd semester of 2019/2020 academic year. The population was 144 cadets of first year and 24 cadets were taken as the sample through cluster random sampling technique. The method used in this research was research and development method and the technique of collecting data were by test and questionnaire.The results of the research concluded that: (1) cadets conducting E-Learning based instructional media achieved higher score (70,10) than conventional method (56,67); (2) development of E-Learning based instructional media showed high effectiveness in learning process gained from valid and reliable questionnaire (r11 = 0.8205); (3) development of E-Learning based instructional media was stated in “ a very good category” in term of usability aspect.
Expertise Locator For Lecturers Based on Publication Rahmat Izwan Heroza; Haniifah Putriani; Ahmad Rifai; Putri Eka Sevtiyuni
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i1-5112

Abstract

Among the KM processes that function to guarantee access to knowledge is knowledge sharing. This process allows knowledge assets and experiences possessed by the organization to be accessed by anyone in the organization. Especially by using IT, this process can be done more optimally by capturing existing knowledge into a system so that this valuable information can be monitored anytime and anywhere. There are times when the knowledge possessed by experts is difficult to capture and represent in the system as in the case of tacit knowledgesuch as instincts, insights, and experiences of the experts. One of the challenges in inventorying these experts is the process of creating expert profiles automatically based on a particular approach. This research create an Expert Locator for lecturers who are considered as experts in their field of research using publication data produced by these lecturers as an indication of their expertise. The search feature is made as an implementation of the extraction results that can be used by other parties to find experts by entering keywords in the form of the desired expertise.
Experimenting Diabetic Retinopathy Classification Using Retinal Images Muhammad Fermi Pasha; Mark Dhruba Sikder; Asif Rana; Maya Silvi Lidya; Ronsen Purba; Rahmat Budiarto
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i1-5232

Abstract

Along with many complications, diabetic patients have a high chance to suffer from critical level vision loss and in worst case permanent blindness due to Diabetic Retinopathy (DR). Detecting DR in the early stages is a challenge, since it has no visual indication of this disease in its preliminary stage, thus becomes an important task to accomplish in the health sector. Currently, there have been many proposed DR classifier models but there is a lot of room to improve in terms of efficiency and accuracy. Despite having strong computational power, current deep learning algorithm is not able to gain the trust of the medical experts in classifying DR. In this work, we investigate the possibility of classifying DR using deep learning with Convolutional Neural Network (CNN). We implement preprocessing combined with InceptionV3 and VGG16 models. Experimental results show that InceptionV3 outperforms VGG16. InceptionV3 model achieves an average training accuracy of 73.5 % with a validation accuracy of 68.7%. VGG16 model achieves an average training accuracy of 66.4% with a validation accuracy of 63.13%. The highest training accuracy for InceptionV3 and VGG16 is 79% and 81.2%, respectively. Overall, we achieve an accuracy of 66.6% on 52 images from 3 different classes.
Computing the Value of Pi in the Manner of Lambda Function with R Statistical Programming Language Muhammad Reza Fahlevi; Mohammad Andri Budiman
Data Science: Journal of Computing and Applied Informatics Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v5.i1-5556

Abstract

The value of π is one of the famous mathematical constant, not only to mathematicians, but also to physicists and to engineers. Numerous algorithm is used to compute what is the value of π, but most of programmer do not use lambda function and neglect the aesthetic of their script. This study aims to compute the value π by write it first as infinite series using Riemann sum, and then the computing of it is conducted in R programming language. We involved the role of anonymous function or known as lambda function to make the R code is more beautiful, artistic, and elegant.

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