International Journal Software Engineering and Computer Science (IJSECS)
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Articles
387 Documents
<![CDATA[Application of the Naive Bayes Algorithm in Twitter Sentiment Analysis of 2024 Vice Presidential Candidate Gibran Rakabuming Raka using Rapidminer ]]>
<![CDATA[Amini, Tasya Aisyah]]>;
<![CDATA[Setiawan, Kiki]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2236
<![CDATA[In the current era of digital democracy, social media sentiment analysis has become a relevant method for understanding public views of political figures. As one of the leading social media platforms, Twitter provides a public space for sharing opinions and expressions regarding political issues. This research aims to classify and measure the accuracy of people's responses to the positive and negative sides. Sentiment analysis was carried out using the Naïve Bayes method using a dataset of 3223 tweets. The final results of this research show that implementing the Naïve Bayes Method in sentiment analysis regarding political dynasty polemics, especially regarding the 2024 Cawapres Gibran Rakabuming Raka, provides an accuracy value of 82.19%. Of the 1696 negative and 112 positive sentiments predicted, there were 462 harmful and 953 positive predicted data. These results indicate that most public responses tend to be detrimental to the Constitutional Court's (MK) decision, which grants political legitimacy to Gibran Rakabuming Raka as the 2024 vice-presidential candidate.]]>
<![CDATA[Leveraging Neural Matrix Factorization (NeuralMF) and Graph Neural Networks (GNNs) for Enhanced Personalization in E-Learning Systems ]]>
<![CDATA[Aji, Achmad Maezar Bayu]]>;
<![CDATA[Nurdiyanti, Dewi]]>;
<![CDATA[Basri, Hasan]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i2.2238
<![CDATA[This study investigates the application of a combined approach utilizing Neural Matrix Factorization (NeuralMF++) and Graph Neural Networks (GNNs) to enhance personalization in e-learning recommendation systems. The primary objective is to address significant challenges commonly encountered in recommendation systems, such as data sparsity and the cold start problem, where new users or items need prior interaction history. NeuralMF++ leverages neural networks in matrix factorization to capture complex non-linear interactions between users and content. GNNs model intricate relationships between users and items within a graph structure. Experimental results demonstrate a substantial improvement in recommendation accuracy, measured by metrics such as Hit Ratio (HR) and Normalized Discounted Cumulative Gain (NDCG). Additionally, the proposed model exhibits greater efficiency in training time than traditional methods, achieving this without compromising recommendation quality. User feedback from several universities involved in this research indicates high satisfaction with the recommendations provided, suggesting that the model effectively adapts recommendations to align with evolving user preferences. Thus, this study asserts that integrating NeuralMF++ and GNNs presents significant potential for broad application in e-learning platforms, offering substantial benefits in personalization and system efficiency]]>
<![CDATA[Message Security in Classical Cryptography Using the Vigenere Cipher Method ]]>
<![CDATA[Purwanti]]>;
<![CDATA[Nurcahya , Saputra Dwi]]>;
<![CDATA[Nazelliana, Dian]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2263
<![CDATA[Ensuring message confidentiality is a fundamental aspect of classical cryptography. This study uses the Vigenere Cipher, a prominent polyalphabetic substitution technique, to secure alphabetic text. The historical development of the Vigenere Cipher, introduced by Blaise de Vigenère, marked a significant advancement in cryptographic practices by offering enhanced security over monoalphabetic ciphers. The method's ability to obscure letter frequency analysis made it a robust choice for protecting sensitive information. However, the Vigenere Cipher has vulnerabilities, particularly in brute force attacks when short keys are used. This research explores the technical specifications, strengths, and limitations of the Vigenere Cipher, comparing it with other classical and modern cryptographic algorithms. Additionally, potential enhancements and practical applications of the Vigenere Cipher in contemporary data security contexts are discussed, emphasizing the need for ongoing innovation and adaptation in cryptographic methods to address evolving security challenges.]]>
<![CDATA[Implications of Deep Learning for Stock Market Forecasting ]]>
<![CDATA[Supendi]]>;
<![CDATA[Kumala, Devi]]>;
<![CDATA[Yulianti, Maria Lusiana]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2281
<![CDATA[This research explores the effectiveness of using deep learning in predicting stock market movements. This research uses rigorous methods to bring out the performance of deep learning models, compare them with traditional methods, and identify critical factors that influence stock market predictions. The research results show that deep learning models, especially LSTM and CNN-LSTM architectures, can achieve satisfactory levels of accuracy and outperform traditional methods by capturing patterns in complex stock market data. In addition, this research identifies external and internal factors that influence predictions of stock market movements. This research's practical and theoretical implications highlight the potential of deep learning in improving investment decision-making and understanding financial market dynamics. Recommendations for future research include exploration of advanced deep learning techniques, integration with traditional methods, emphasis on risk management strategies, continuous evaluation of model performance, and provision of training and education to encourage analysts and investors to adopt this technology. By implementing these recommendations, the potential of deep learning models in financial analysis can be optimized, ultimately improving market efficiency and investment returns.]]>
<![CDATA[Optimizing the 2024 Governor Election Quick Count with Extreme Gradient Boosting (XGBoost) to Increase Voting Prediction Accuracy ]]>
<![CDATA[Suacana, I Wayan Gede]]>;
<![CDATA[Suhariyanto, Didik]]>;
<![CDATA[Nuru, Ferdinant]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2286
<![CDATA[This research aims to increase the accuracy of vote predictions in the Quick Count process in the 2024 Governor Election using the XGBoost algorithm. Quick Count is a fast method for obtaining estimates of election results based on some of the data that has been calculated. The XGBoost algorithm was chosen because it has proven effective in various applications, including predictive modeling. This research analyzes the implementation of the XGBoost algorithm in modeling vote predictions for Quick Count, especially in the context of the 2024 gubernatorial election. By using various evaluation metrics such as accuracy, precision, recall, and F1-score, this research provides a comprehensive understanding of the performance of the XGBoost model. The research results show that the XGBoost algorithm achieves high accuracy, precision, recall, and F1 score, demonstrating its ability to classify sounds accurately. The practical implications of this research are significant in improving the integrity of the democratic process by providing more reliable and transparent election results. Additionally, this research paves the way for developing more sophisticated Quick Count methods by leveraging insights from previous research on machine learning techniques and data security.]]>
<![CDATA[IoT and Cloud Storage Implementation for Wheat Plant Monitoring at the Tropical Study Center UKSW ]]>
<![CDATA[Marpaung, Kristian Vieri]]>;
<![CDATA[Widiasari, Indrastanti R.]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2301
<![CDATA[Information technology in the agricultural sector has been widely discovered, producing large amounts of agricultural products. This research aims to design and build a tool that implements IoT for monitoring agricultural systems using several sensors, converging data communication simultaneously. The real-time between IoT sensors and databases in Cloud Storage and analyzing the performance of agrarian system monitoring systems by implementing IoT and Cloud Storage in the application link which can be accessed on Android or PC. The test results from this research are the performance of the IoT system, which can be accessed using the application Blynk. This IoT works well. MomentBlynkIoT gives commands to the DHT11 sensor and soil moisture sensor to start reading temperature and humidity and then pass it on to the microcontroller and pass it back; BlynkIoT will provide output to the application display in the form of data resulting from sensor performance.]]>
<![CDATA[Interaction Design on Basic Hand Movement Training Game in Taekwondo Using User-Centered Design ]]>
<![CDATA[Ramdani, Rahmat Muhamad]]>;
<![CDATA[Yuniarti, Rezki]]>;
<![CDATA[Komarudin, Agus]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2314
<![CDATA[This research will develop an interaction design for basic hand movement games in taekwondo with the hope that it can become an alternative physical exercise for hand stretching. UCD is one of the methods in interaction design that focuses on the user. By designing interactions in hand movement training games using the UCD method and present technology, it is hoped that this can be a stretch in the dense student activities. The results of the interaction design evaluation using UCD obtained an average of 90.24% for the 6th heuristic based on ten evaluation heuristics. Combining the UCD method at the design stage and utilizing present technology is an innovation in designing easy-to-use game-based interaction designs. The study results show that the UCD method for interaction design is suitable for use in the game design process.]]>
<![CDATA[Designing A Cooking Procedure Simulation Game During the Pandemic In The Food and Beverage Industry Using The Design Play Experience Method ]]>
<![CDATA[Azhari, Anissa]]>;
<![CDATA[Yuniarti, Rezki]]>;
<![CDATA[Komarudin, Agus]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2315
<![CDATA[Covid-19 has become one of the world's problems after its first appearance at the end of 2019. At its peak, the COVID-19 pandemic affected many industrial sectors, including the food and beverage industry and, in this case, Indonesia. The main focus in running the industry is health protocols for handling both the cooking and serving processes, which must pay more attention to cleanliness and health to reduce the spread of the COVID-19 virus. Standard operating procedures can be simulated in the game as a lesson in cooking procedures for professionals and the general public. Learning and experience in playing games is a challenge in developing simulation games, so the DPE (Design, Play, and Experience) framework is the choice for the game design method in this research. The study results were evaluated by 15 respondents who tried this game with a distribution of 6 workers in the food and beverage industry and 9 people who were not workers in the food and beverage industry. Game development with the DPE framework gets results in the learning aspect of the experience component for simulation with an average value of 88.70%. For the experience learning aspect, the knowledge players gain after playing the game is 84.87%, with very appropriate criteria.]]>
<![CDATA[Development of Operational Application System at PT. XYZ with Flask Overriding ]]>
<![CDATA[Hattu, Aryudha]]>;
<![CDATA[Susetyo, Yeremia]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2318
<![CDATA[Advances in information technology have become a critical factor in increasing company operational efficiency. PT.XYZ, a business entity in the retail sector, faces an urgent need to design an operational application system that can adapt to current business dynamics. This research discusses and applies the development of operational application systems at PT.XYZ uses the Flask Overriding concept in the Flask framework. Flask Overriding is an idea in object-based programming that allows changing or replacing existing behavior in a system. This study explores the potential for implementing Flask Overriding to increase PT functionality, adaptability, and flexibility. PT XYZ operational application systems. Implementing this concept involves an in-depth analysis of a company's specific business needs, application architecture design, and practical implementation using Flask as the main framework. This research produces an operating system application head office application that is useful for assisting PT XYZ in storing and sending non-physical products needed by PT XYZ branches and head office so that the business processes and dissemination of information required for PT XYZ and its branches become efficient, fast, and structured.]]>
<![CDATA[Design and Development of an Android-Based Point of Sale Application: A Case Study of Warung Dapur Barokah, Pangkalpinang ]]>
<![CDATA[Hanif, Ahmad]]>;
<![CDATA[Suhendar, Agus]]>;
<![CDATA[Sejati, Rr. Hajar Puji]]>
<![CDATA[ International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024 ]]>
Publisher : <![CDATA[Lembaga Komunitas Informasi Teknologi Aceh (KITA) ]]>
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DOI: 10.35870/ijsecs.v4i1.2325
<![CDATA[Warung Dapur Barokah is a food stall in Pangkalpinang City and was founded in 2022. This application was designed to overcome obstacles that generally arise in manual transaction processes, which are often slow, inefficient, and difficult to manage accurately sales data. This application was developed using Android Studio and adopted the Kotlin programming language. Apart from that, the database section uses Firebase. I am using Firebase because Firebase has a real-time databaseRealtime that can update data in the database in realtime. This will make the transaction data storage process synchronized, fast, and optimal. The hope is that the results of implementing this application will include increased efficiency and speed in the transaction process and potentially improve the profitability of Warung Dapur Barokah's operations. This innovation is hoped to positively contribute to advancing the operational performance of this food stall in the current digital era, as well as creating effective solutions to increase the competitiveness and sustainability of local businesses in the culinary sector.]]>
