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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 26 Documents
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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.
Development of 2D Animation Video Learning Media Mukashibanashi: Saru Kani Gassen at SMA Negeri 12 Bekasi Erlina Yuliana; Hamidillah Ajieb; Murien Nugrahenic
Journal of Computers for Society Vol 5, No 1 (2024): JCS: June 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i1.70794

Abstract

According to a poll done in 2021 by The Japan Foundation, Indonesia has the second-highest population of Japanese language learners worldwide. Japanese is now available for study in schools as one of the specialized courses, according to the government. Using learning material is one way to try and maximize the learning process. Learning materials for Mukashibanashi material: Saru Kani Gassen at SMA Negeri 12 Bekasi City are still ineffective, according to the interview's findings. Based on this, Mukashibanashi: Saru Kani Gassen, a 2D animated film, was created as educational material to assist third-grade high school students at SMA Negeri 12 Bekasi City in their studying. The Multimedia Development Life Cycle (MDLC) approach is used in this learning media development to create a 2D animation video that lasts 6 minutes and 40 seconds in mp4 format. Two testing phases, known as alpha and beta testing, are used to conduct feasibility testing on 2D animation video learning media products. A percentage of 89% was obtained from the feasibility test results, placing the responders in the "Very Good" category. Therefore, the product of 2D animation can be declared feasible as learning media.
Stemming Algorithm Modification for Overstemming Cases Stephanie Betha R.H.
Journal of Computers for Society Vol 4, No 2 (2023): JCS: September 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v4i2.71186

Abstract

The stemming process plays an important role in the preprocessing of the text. One of the problems that occur in the stemming process is overstemming. Overstemming is an exaggerated word cut causing situations where a word has a very different meaning, but it produces the same stem. Therefore, to overcome these problems, it will be modified on the stemming process. This modification is done by combining two stemming algorithms (hybrid stemming) that is the look-up algorithm of dictionary table and affix removal algorithm using stemming porter. The modification of this stemming algorithm will be tested on title in scientific publication documents. The test results show that stemming process with modification of stemming algorithm can increase the recall value in the title attribute, although not very significant. The recall in an experiment using title attribute is 89,9%.
Web e-Learning Component Analysis: A Metamodel Narti Prihartini
Journal of Computers for Society Vol 1, No 1 (2020): JCS: June 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v1i1.25511

Abstract

Research focus on learning technologies currently classified into three main themes included pedagogical aspect, underpinning technology, and organizational issues. In particular, there is an expand research on how to explore learning technologies in order to support the communication and collaboration by increasing focus on relevant pedagogical and organizational issues. Concerns that appear in every research focus can be related to determine the specific component of web e-learning. Analysis of specific component then required to describe all aspects that support the web e-learning implementation. Final result from this analysis is initialization of web e-learning component in logical and technical along with it relations by proposed a web e-learning component metamodel.
Detection of Motorcycles on Highways Using Faster R-CNN Based on VGG16 Moch Dian Lazuardi Yudha; Wawan Setiawan; Yaya Wihardi
Journal of Computers for Society Vol 4, No 1 (2023): JCS: June 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v4i1.71179

Abstract

This research aims to develop an object detection system with input in the form of image data in free size. The development of an object detection system model was carried out by applying Machine Learning to overcome object detection in an image using the Faster R-CNN method based on the VGG16 algorithm. The system developed produces a bounding box for an object in the image. System development was carried out in the Python programming language by utilizing several libraries such as Keras. Experiments were carried out by measuring the loss value of the training data entered into the system. The experimental results show that the resulting information is proven to be able to detect objects in a given image. This system can produce information based on image data that has been trained with this system. This study used two experiments which obtained a loss value of 0.0601 in the first study and 0.1211 in the second study.
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.
Zero day attack vulnerabilities: mitigation using machine learning for performance evaluation Idris Olanrewaju Ibraheem; Abdulrauf Uthman Tosho
Journal of Computers for Society Vol 5, No 1 (2024): JCS: June 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i1.70795

Abstract

The paper explores and investigate how machine learning methods can help defend against zero-day cyber-attacks, which are a major concern in cybersecurity. The study focuses on several machine learning algorithms, such as gradient boosting classifiers, random forests, decision trees, and support vector machines (SVM). The study examines how well these algorithms can detect and prevent zero-day attacks. To do this, we carefully prepare a dataset containing different network characteristics for analysis, ensuring that categorical variables are handled properly. We then train and test the selected algorithms using this dataset. Based on the data, random forest outperforms the other algorithms in terms of detection rates and accuracy. This is due to the fact that random forest's ability to recognize intricate patterns linked to zero-day assaults is enhanced by its continuous learning of weaker models. The results demonstrate how machine learning may be used to improve cybersecurity defenses against new threats like zero-day assaults. The CSE-CIC-IDS2018 Dataset was used in the study's execution and assessment.
A Text Mining Implementation Based on Twitter Data to Analyse Information Regarding Corona Virus in Indonesia Enda Esyudha Pratama; Rizqia Lestika Atmi
Journal of Computers for Society Vol 1, No 1 (2020): JCS: June 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v1i1.25502

Abstract

CORONA virus outbreak (COVID-19) began to infect almost all countries in early 2020 including Indonesia. Since its distribution, various information has been spread in the community from various sources, one of them is social media. Various terms also appear on social media related to the corona virus. This study analyzes related terms that emerge from social media-based. The data used was sourced from Twitter in the past month where the data processed was text data. The method used is text mining. Text Mining is a method used to extract important information from a group of texts. From the results of the research conducted, there are several terms or information that tend to appear frequently on social media, namely “PSBB”, “new normal”, “karantina”, and “juru bicara Dr. Reisa”.
Security Analysis and The Effect of Codec Changes on Quality of Service of Encrypted Voice Phones on Voice Over IP Freepbx Asep Saepul Achmad; Muhammad Nursalman; Rizky Rachman J.
Journal of Computers for Society Vol 4, No 2 (2023): JCS: September 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v4i2.71181

Abstract

VoIP is one of the technologies as communication with audio and video media online. The server secures voice phone data on VoIP supporting VoIP phone data encryption. In addition to security, in order to improve sound quality FreePBX also uses the latest codecs such as Alaw, Ulaw, G722, G729. The purpose of this study was to display the results of VoIP voice phone security testing on FreePBX Server, analyze the Quality of Service of voice codecs on VoIP phones, and compare encrypted and unencrypted VoIP voice phones. The Quality-of-Service criteria of voice telephony consist of packet loss, jitter, and delay or delta. Then, test VoIP security using the Man in The Middle Attack (ARP Poisioning) attack method on the Cain and Abel application. Next, analyze the comparison between encrypted and unencrypted phones using SoftPhone SIPSoercery. Test results for QoS of encrypted VoIP phones with different audio codecs are very good and this assessment is based on the TIPHON QoS standard. The best delta value is found in the Ulaw codec and the best jitter value is found in the Alaw codec. After VoIP phones are attacked with ARP Poisoning, there is a decrease in QoS quality. For all codecs tested, the delta value decreased from 9.34% to 104.12%, the jitter value decreased from 235.49% to 767.97%, and the packet loss value decreased from 5.56% to 181.82%.
Natural Language Processing and Levenshtein Distance for Generating Error Identification Typed Questions on TOEFL Lala Septem Riza; Faisal Syaiful Anwar; Eka Fitrajaya Rahman; Cep Ubad Abdullah; Shah Nazir
Journal of Computers for Society Vol 1, No 1 (2020): JCS: June 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v1i1.24940

Abstract

Test of English as a Foreign Language (TOEFL) is one of the evaluations requiring good quality of the questions so that they can reflect the English abilities of the test takers. However, it cannot be denied that making such questions with good quality is time consuming. In fact, the use of computer technology is able to reduce the time spent in making such questions. This study, therefore, develops a model to generate error identification typed questions automatically from news articles. Questions from the sentences on news sites are created by utilizing Natural Language Processing, Levenshtein Distance, and Heuristics. This model consists of several stages: (1) data collection; (2) preprocessing; (3) part of speech (POS) tagging; (4) POS similarity; (5) choosing question candidates based on ranking; (6) determining underline and heuristics; (7) determining a distractor. Testing ten different news articles from various websites, the system has produced some error identification typed questions. The main contributions of this study are that (i) it can be used as an alternative tool for generating error identification typed questions on TOEFL from news articles; (ii) it can generate many questions easily and automatically; and (iii) the question quality are maintained as historical questions of TOEFL.

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