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Erna Piantari
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jcs@upi.edu
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+6285222044331
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Department of Computer Science Education, Universitas Pendidikan Indonesia, Jl. Setiabudhi 229, Bandung, Indonesia
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Kota bandung,
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INDONESIA
Journal of Computers for Society
Published by Universitas Pendidikan Indonesia
ISSN : -     EISSN : 27234088     DOI : https://doi.org/10.17509/jcs.v5i2
Core Subject : Science, Education, Engineering,
Computer Science & IT Engineering Library & Information Science Mathematics
The Journal invites original articles and not simultaneously submitted to another journal or conference. The whole spectrum of computer science are welcome, which includes, but is not limited to - Artificial Intelligence, IoT and Robotics - Data Analysis and Big Data - Multimedia and Design, - Software Engineering, - Computer Networking, - Information System, and - Applications of computer science in education, agriculture, government, smart city, bioinformatics, astrophysics, simulation and modelling, etc.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
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Search results for , issue "Vol 5, No 2 (2024): JCS: September 2024" : 5 Documents clear
Development of a data-to-text (D2T) system to generate news on streaming data Ahmad Zainal Abidin; Enjang Ali Nurdin; Lala Septem Riza
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70799

Abstract

This research aims to develop a Data-to-Text system with input in the form of streaming data in batch form, to generate news in general. The development of a Data-to-Text system model is carried out by applying Machine Learning to overcome Streaming data, with the Piecewise Linear Approximation technique using the Least Square method. The developed system produces data summary information, current data information, and prediction information. System development is carried out in the R programming language by utilizing several available packages. The experiment was conducted by measuring the Readability level of the news raised, Computation Time, and comparing the results withrelated research. The experimental results show that the information produced is proven to represent the data provided and can be understood by the student level or above, and the computational time is quite good. The system can generate information based on meteorological data, climatological data, and financial data.
Development of Academic Information System Mobile Application Prototype at SD Inpres Touiu, Rote Vienda Miccela Seldry; Hamidillah Ajie; Murien Nugraheni
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70801

Abstract

In era society 5.0, where technology is generally a supporting factor in many ways, it turns out that there are still some aspects that have not taken advantage of existing technology. For example, Inpres Touiu Elementary School, Rote in providing information is still done manually, such as the recipient of the information coming directly to the location of the information or information being delivered by the school to the recipient of the information such as the teacher coming directly to the house of each student. The purpose of this research is to produce a prototype of an Android-Based School Academic Information System with a Case Study of SD Inpres Touiu, Rote which is useful in providing an information system design in the form of a front-end, so that in the future it can be redeveloped into a real android application. The results of the development in the form of a high-fidelity prototype using the Flutter framework with the Waterfall Method resulted in the SIKALA prototype being tested for Usability Testing using Black box testing and the Think-aloud method. The results of the test got 94% good response and 100% overall task success.
A support vector machine credit card fraud detection model based on high imbalance dataset Kehinde Musliudeen Odeyale; Oyelakin A Moruff; Salau Ibrahim T Taofeekat; Saka M Kayode
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70802

Abstract

Credit card transactions are exposed to fraudulent activities owing to their sensitive nature. The illegal activities of the fraudsters have been reported to cost financial institutions a lot of money globally as reported in many notable research works. In the past, several machine learning-based approaches have been proposed for the detection of credit card fraud. However, little attention has been given to classification of fraud in high imbalance dataset. Generally, if a dataset is imbalanced, a learning algorithm will give a bias result in terms of the accuracy resulting in poor performance of the model. This study focuses on using Synthetic Minority Oversampling Technique (SMOTE) to address the class imbalance in the selected credit card dataset. Then, ANOVA-F statistic was applied for the selection of promising features. Both the class imbalance and attribute selection techniques were targeted at improving the SVM-based credit card fraud classification. With the balanced dataset, the study achieved an accuracy of 93.9%, recall of 97.3%, precision of 90.3%, and f1 score of 93.5% respectively. It was observed that the result of the Support Vector VM based credit card fraud detection model with class imbalance is better than that of the standard SVM. The study concluded that the class imbalance addressing and attribute selection techniques used were very promising for the credit card fraud detection tasks.
Front-End Development on A Web-Based Teaching Material Repository System at SMK Diponegoro 1 Jakarta Tina Audina; Hamidillah Ajie; Z.E. Ferdi Fauzan Putra
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70803

Abstract

In the current digital era, information technology has greatly dominated the field of education, and the use of websites stands as a primary example. Websites play a crucial role in storing and conveying information. One such example is the school repository website. Having a storage medium for instructional materials can provide advantages to users, especially schools. Currently, at SMK Diponegoro 1 Jakarta, there is no dedicated storage for instructional materials. A single information system, Google Drive, is used to store all documents and information. The purpose of this research is to present and enhance the front-end appearance and functionality of the web-based Instructional Material Repository System. The development method employed is the Waterfall model, utilizing the Bootstrap framework and Javascript to construct a high-fidelity prototype of the system's front-end. Throughout the development process, black box testing was conducted to ensure the success of the system's functionality and usability. The testing results demonstrated that all tasks were successfully executed with a 100% success rate.
Correlation Analysis of Open Street Map, Demography, and Vaccination on the Number of Covid-19 Cases Using Multiple Linear Regression and Pearson Correlation Product Moment Aqhbar Habib; Erna Piantari; Lala Septem Riza
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70798

Abstract

At the beginning of 2020, the world was shocked by the spread of Coronavirus Disease 2019 (Covid-19). The resulting losses cover various areas. This research aims to analyze the correlation between spatial data, demographic data, and vaccination data on the spread of Covid-19 in Bandung City using Multiple Linear Regression (MLR) and Pearson Correlation Product Moment (Pearson's r). The results show that there are only 3 variables that are significantly correlated with Covid-19 cases. The lowest variables are Residential, Population Density, and Healthy Homes. Has a significant simultaneous correlation with Covid-19 cases with a coefficient of determination (R^2) of 0.55404. The model built also passed the 3 Classical Assumptions test so that the results can be trusted for their level of truth and feasibility. The results of experiments using the Pearson's r model involving 5 vaccination periods show that out of 30 sub-districts in Bandung City, there are 20 sub-districts that have a significant correlation between vaccination and the addition of Covid-19 cases and have a negative correlation direction of 80.54%. The results of the Pearson's r model experiment involving 6 vaccination periods show that there are 9 sub-districts that have a relationship. With a negative correlation direction of 72.93%.

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