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Jurnal CoreIT
Published by Universitas Islam Negeri Sultan Syarif Kasim Riau
ISSN : 2460738X     EISSN : 25993321     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi published by Informatics Engineering Department – Universitas Islam Negeri Sultan Syarif Kasim Riau with Registration Number: Print ISSN 2460-738X | Online ISSN 2599-3321. This journal is published 2 (two) times a year (June and December) containing the results of research on Computer Science and Information Technology.
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Articles 162 Documents
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Comparative Analysis Between Advanced Encryption Standard and Fully Homomorphic Encryption Algorithm to Secure Data in Financial Technology Applications Nurdin, Nurdin
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.30809

Abstract

This research discusses the comparison between two encryption algorithms, namely Advanced Encryption Standard (AES) and Fully Homomorphic Encryption (FHE), in the context of data security in Financial Technology (Fintech) applications. The main aim of this research is to analyze the speed and efficiency of the two algorithms to provide information and motivation to Fintech Application business actors to determine the right algorithm for securing data. The research results show that AES is faster and more efficient in terms of encryption and decryption compared to FHE. For encryption, the AES algorithm is 1,100 times faster than the FHE algorithm. For decryption, the AES algorithm is 581 times faster than the FHE algorithm. For arithmetic processing, AES is 132 times faster than FHE. CPU consumption for AES encryption is 35.93% lower CPU usage than FHE. In AES decryption 10.31% lower than FHE for CPU usage. In the arithmetic process AES is 9.33% lower in usage than FHE. For memory usage in the FHE encryption process, it has an advantage, namely 2.3 times lower than AES for memory usage. During decryption, AES memory usage is superior with memory consumption 54 times lower than FHE. For the arithmetic process, AES uses 4.3 times lower memory than FHE. Overall AES provides speed and low resource consumption, this makes AES very suitable for use in Fintech applications that require speed and efficiency. Even though FHE has advantages in memory usage during encryption alone, this is not enough because it takes a long time to carry out the encryption process. This research suggests that further research will attempt to make the FHE algorithm more efficient and faster in processing data, this is considering the potential of FHE which is able to process encrypted data
An Analysis And Forecasting The Foodstuffs Prices In Surabaya Traditional Market Using LSTM Ericko, Teddy; Lauro, Manatap Dolok; Winata, Andry; Handhayani, Teny
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.27855

Abstract

Food is one of the essential things in society. Foodstuffs prices are important factors in the stability economy. In Indonesian society, some foodstuffs, e.g., rice, beef, chicken egg, cooking oil, and sugar are the main ingredients in their cuisine. Analyzing and predicting the foodstuffs price is interesting job. This research is conducted to develop models for forecasting the price of rice, beef, chicken egg, cooking oil, and sugar. It implements the Long Short-Term Memory (LSTM) model and a daily time-series dataset from a traditional market in Surabaya. Surabaya is the capital city of East Java province, and it is one of the densest cities in Indonesia. The experiments run univariate time-series forecasting. The experimental results show that LSTM works well to forecast the price of rice, beef, chicken egg, cooking oil, and sugar. The evaluation results obtain MAPE scores as 0.12%, 0.03%, 0.72%, 0.36%, and 0.08% for models of rice, beef, chicken egg, cooking oil, and sugar, respectively. The annual average price of beef, chicken egg, and cooking oil show an increasing trend and those foodstuffs have positive correlations with each other.
The Implementation of Data Mining to Determine the Level of Students' Understanding in Utilizing E-Learning Using the K-Nearest Neighbor Method Iskandar (Scopus ID: 55316114000), Iwan; Candra, Reski Mai
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.33728

Abstract

The implementation of Information Technology is increasingly developing due to the growing demand. According to data obtained from the Indonesian Internet Service Providers Association (APJII) 2022 report, the number of internet users in Indonesia is 210.02 million, an increase of 27.9 million from the previous year. The application of E-Learning in various schools, campuses, and educational courses has been carried out. The utilization of e-learning media undoubtedly facilitates educators in transferring their knowledge to students. This research evaluates the level of understanding of each student who has used E-Learning during Covid-19 as a learning medium. In obtaining this level of understanding, the K-Nearest Neighbor (K-NN) method is applied. The data analyzed are based on assignment scores, quizzes, mid-term exams, and final exams from various related courses, namely Science and Mathematics Course Group, Programming Course Group, and Basic Informatics Course Group. A total of 1,627 data points were collected from the period between 2020 and 2021 when online learning was conducted using E-Learning. The data was processed using the KNN method with an 80:20 split between training and testing data. The analyzed K values were 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21. The calculation results showed an accuracy of 75.69% at K=17 for the Basic Informatics Course Group, 77.61% at K=15 for the Science and Mathematics Course Group, and 96.20% at K=3 for the Programming Course Group.
THE INFLUENCE OF MAJOR EXPERTISE COURSES ON ALUMNI EMPLOYMENT USING THE APRIORI METHOD Irsyad (Scopus ID: 57204261647), Muhammad; Iskandar, Iwan; Gusti, Siska Kurnia
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 2 (2024): December 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i2.34144

Abstract

The role of alumni in university progress and quality is vital. This study used data from the tracer study application to analyze the relationship between skill courses and alumni employment. The data mining technique of association was employed to find linkages between different parameters. The Apriori algorithm was used to identify patterns that described the relationship between skill courses and alumni employment. The findings revealed that the most sought-after professions by alumni of the Informatics Engineering Study Program were educators, such as teachers and lecturers, with a support value of 18.7692%. Programmers were also in high demand, with a support value of 15.3846%. The subjects that were found to have the greatest influence on employment were Database, Computer Network, Computer Human Interaction, and Software Engineering. These findings provide valuable insights for the Informatics Engineering Study Program to prioritize and enhance these influential courses in terms of curriculum, teaching methods, and teaching materials, with the aim of improving the relevancy and quality of the courses in supporting alumni employment.
Utilization Of Privilege Escalation Vulnerability In Manipulating Administrator Access Of PT XYZ Ritonga, Jody Jeremi Hadrian; Sihotang, Jay Idoan
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.32985

Abstract

PT.XYZ is a CRM solutions provider that helps businesses manage their interactions with customers. Through in-depth research, a security vulnerability was discovered on PT.XYZ's platform that could be exploited by unauthorized parties to escalate their access rights unlawfully. This research involved a comprehensive analysis of CRM system. The research method included application analysis, exploitation, impact evaluation, solution development, and reporting. The findings revealed a vulnerability in the user management mechanism, allowing a regular user to escalate their access rights to an administrator level. This could potentially lead to customer data misuse, operational disruptions, and financial losses for the company. The research process involved penetration testing, impact analysis, and the development of mitigation solutions. Thanks to these findings, PT.XYZ has implemented system improvements to address the security gap. This research demonstrates the importance of conducting regular security testing to ensure a company's information systems remain protected from cyber threats.
Optimization Of Social Media Phishing Detection Models Syafitri (Scopus ID: 57200085316), Wenni; Guntoro, Guntoro; Zamsuri, Ahmad; Waldelmi, Idel
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.37602

Abstract

Phishing is one of the most dangerous attacks in the cyber world. Very few researchers have focused on social media phishing, although SMS phishing can be related to the messaging features available on various social media platforms. This study will utilize PSO and PCA techniques to optimize the performance of RF in social media phishing. This study will compare the performance of PSO and RF with that of PCA and RF. An optimized phishing message detection model was built using NLP, incorporating TF-IDF for feature extraction, PCA and PSO for feature optimization, and Random Forest as a classifier to distinguish phishing messages from normal messages. The RF model optimized by PSO produces nearly balanced metrics: precision (0.9877), recall (0.9728), and F1 (0.9802), all of which are high. The RF model with PCA optimization achieves a slightly lower Accuracy (0.9639) and the lowest Precision (0.9585). Although there were no significant differences in the classification process, PSO and PCA made a real contribution to future research development.
Assessment of the President of BEM Using the Weighted Product Method at XYZ University Tundo, Tundo; Nugroho, Agung Yuliyanto; Saidah, Andi
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.21075

Abstract

The election of the BEM President is a hereditary tradition at XYZ University every year. This election was carried out to find a leader who has a firm personality and broad insight. As the number of students at XYZ University increased, we doubled the election using the Weighted Product (WP) method with the conditions that we had determined with the campus. So we are sure that this method will produce the leaders we expect, and also in this way the campus automatically saves budget for voting or direct elections. The WP method which is quantitative in decision making, the WP method uses multiplication to link attribute ratings, where the rating of each attribute must be raised to the first power of the attribute weight in question. By applying the WP method to decision support system, then implementing it into a ranking system, it will produce students who deserve to become BEM in the next period. There is a WP method at XYZ University in order to get a BEM President who meets the criteria we set. Where the existing criteria consist of TPA criteria, Liveliness, Commitment, GPA, Absent, and Age. After calculating using the WP method, it was found that the strongest student who deserved to be president of BEM was Siti Munawaroh who was ranked first. The results of the recommended method by conducting a questionnaire to the BEM management by producing an accuracy of 0.01356.
SMS Phishing Detection Model with Hyperparameter Optimization in Machine Learning Abdillah, Rahmad; Insani, Fitri
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.35547

Abstract

Phishing is one of the growing cybersecurity threats, including through SMS, known as smishing. This research aims to build a model for SMS phishing detection using a machine learning approach optimized through hyperparameter tuning techniques. The data used is obtained from personal SMS messages collected through questionnaires, which are then labeled by information security experts. The SMS text is cleaned using Natural Language Processing (NLP) techniques and represented using the TF-IDF method. Ten classification algorithms are tested in this study: K-NN, Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, AdaBoost, Bagging, ExtraTree, Gradient Boosting, and XGBoost. Hyperparameter optimization is performed using Grid Search and Optuna, and performance is evaluated using accuracy, F1-score, and ROC-AUC metrics. The results show that the SVM and Logistic Regression models performed the best, achieving accuracy up to 98.5%. Hyperparameter optimization techniques have proven effective in improving the performance of SMS phishing classification models. This research is expected to contribute to the development of accurate and efficient SMS phishing detection systems.
Sentiment Analysis on Reviews of the Documentary Film "Dirty Vote" Using Lexicon-Based and Support Vector Machine Approaches Ramadhan, Apri; Irianto, Suhendro Yusuf
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.34603

Abstract

The general election (Pemilu) is a state agenda in Indonesia held every five years. During this democratic event, citizens have the right to freely and fairly choose their leaders. Rules and procedures related to elections are regulated under Law No. 7 of 2017 on General Elections. One of the provisions in this law is the electoral silence period. In the 2024 election, February 11–13, 2024, is designated as the electoral silence period. During this period, Article 287, Paragraph 5 of the Election Law states that print media, online media, social media, and broadcasting institutions are prohibited from disseminating news, advertisements, or any content that benefits or harms election participants. On February 11, 2024, during the silence period, a video titled "Dirty Vote" was uploaded on YouTube, drawing significant public attention. Its release during the silence period sparked controversy and prompted various opinions in the video’s comment section. Sentiment analysis is a suitable method to determine whether public opinions regarding the video are predominantly positive, negative, or neutral. This study utilized the Support Vector Machine (SVM) classification method with different kernels, including linear and non-linear (polynomial, RBF, and sigmoid). To accelerate labeling for large datasets, a Lexicon-Based approach was employed. The combination of SVM and Lexicon-Based methods demonstrated that the linear kernel outperformed others, achieving evaluation metrics of 91.1% accuracy, 91.1% recall, 90.9% precision, and 90.8% F1-score.
The Success Evaluation of Platform Merdeka Mengajar (PMM) Implementation in Purbalingga Regency Using HOT-Fit Model Abidin, Uun; Hariguna, Taqwa; Barkah, Azhari Shouni
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.33441

Abstract

The industrial 4.0 revolution increasingly develops. It also affects the education field. This issue can be used to improve the quality of education by improving teachers quality. The Merdeka Mengajar platform (PMM) is used to improve the quality of teachers in implementing the Merdeka curriculum (Independent Platform). When it is implemented, teachers have difficulty to adapt the independent teaching platform and not all teachers understand technology. The purpose of this research is to analyze the factors that influence the successful implementation of the Merdeka Mengajar Platform (PMM) using the Hot fit method which assesses system success from the aspects of human, organization and technology. The research sample was 220 vocational high school teachers in Purbalingga Regency. The results of this research can be concluded that all variables contained in the Hot Fit model. They are Service Quality, System Quality and Information Quality, System Use and User Satisfaction. Structure and Environment have a positive and significant effect on the successful implementation of the Merdeka Mengajar Platform (PMM) used by vocational teachers in Purbalingga Regency. The Research Model in this study has a level of feasibility and accuracy of 71.6%, while the rest is influenced by other variables which is not included in this study. By this research, we can find out the factors that influence the successful implementation of the Merdeka Mengajar Platform (PMM) in Purbalingga Regency.

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