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Ainul Hizriadi, S.Kom., M.Sc.
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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.
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Articles 5 Documents
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Search results for , issue "Vol. 5 No. 1 (2021): Data Science: Journal of Computing and Applied Informatics (JoCAI)" : 5 Documents clear
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 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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