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Nurul Khairina
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Journal of Computer Networks, Architecture and High Performance Computing
Published by Yayasan Cita Cendekiawan Al Khwarizmi
ISSN : 26559102     EISSN : 26559102     DOI : 10.47709
Core Subject : Science, Education,
Computer Science & IT Education
Journal of Computer Networks, Architecture and Performance Computing is a scientific journal that contains all the results of research by lecturers, researchers, especially in the fields of computer networks, computer architecture, computing. this journal is published by Information Technology and Science (ITScience) Research Institute, which is a joint research and lecturer organization and issued 2 (two) times a year in January and July. E-ISSN LIPI : 2655-9102 Aims and Scopes: Indonesia Cyber Defense Framework Next-Generation Networking Wireless Sensor Network Odor Source Localization, Swarm Robot Traffic Signal Control System Autonomous Telecommunication Networks Smart Cardio Device Smart Ultrasonography for Telehealth Monitoring System Swarm Quadcopter based on Semantic Ontology for Forest Surveillance Smart Home System based on Context Awareness Grid/High-Performance Computing to Support drug design processes involving Indonesian medical plants Cloud Computing for Distance Learning Internet of Thing (IoT) Cluster, Grid, peer-to-peer, GPU, multi/many-core, and cloud computing Quantum computing technologies and applications Large-scale workflow and virtualization technologies Blockchain Cybersecurity and cryptography Machine learning, deep learning, and artificial intelligence Autonomic computing; data management/distributed data systems Energy-efficient computing infrastructure Big data infrastructure, storage and computation management Advanced next-generation networking technologies Parallel and distributed computing, language, and algorithms Programming environments and tools, scheduling and load balancing Operation system support, I/O, memory issues Problem-solving, performance modeling/evaluation
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 795 Documents
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Web Based Production Scheduling Information System for a Shrimp Paste Factory Utilizing the Waterfall Method Hasibuan, Agung Setiawan; Suendri, Suendri; Sibarani, Fathiya Hasyifah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4801

Abstract

Communication was essential in various aspects of life due to the rapid development of information technology, including in the management of educational institutions and companies. PT. Sumber Nelayan Indonesia faced issues in production scheduling, where the process was still done manually using bookkeeping. This caused delays in order fulfillment, primarily due to machine breakdowns and human resource challenges that impacted the production process. Additionally, the company struggled to manage order data and machine capacity, making it difficult to estimate order completion times and the amount of output produced. This research aimed to develop a web-based management information system for scheduling using the Laravel framework to assist PT. Sumber Nelayan Indonesia in managing scheduling more effectively and efficiently. The research method employed was R&D, with the system development model following the waterfall method, utilizing PHP as the programming language and MySQL as the database. System testing was conducted using black box testing. The results of the research indicated that the developed system could help the company schedule production more efficiently, reduce delays, and improve operational efficiency.
Android Based Sports Infrastructure E-Booking Application at Provincial Youth and Sports Office Using Waterfall Method Rahma, Firda Aulia; Samsudin
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4804

Abstract

Booking is an agreement process in the form of ordering goods or services. The Youth and Sports Service (DISPORASU) is a government agency under the auspices of the Governor of North Sumatra. DISPORASU provides sports infrastructure that can be used by the general public by rental method. In the rental process, DISPORASU still applies the direct rental method, by coming to the DISPORASU office in Medan City, so this results in a large number of tenants piling up at the same time. Therefore, a system is needed that helps tenants in carrying out the infrastructure rental process. The concept is an Android-based Sports Infrastructure E-Booking application. This application was built and designed using the waterfall model and UML (Unified Modeling Language) with several diagrams, namely Use Case Diagrams, Activity Diagrams and Class Diagrams. The programming language used is Dart, Flutter Framework and Firebase as the database. By building this sports infrastructure E-Booking application, it is hoped that it can help improve performance in future business processes and become a reference for employees/staff in this agency itself.
Analysis of Drug Sales Patterns in the Belawan Naval Hospital Pharmacy Using Apriori Algorithm Bahari, Mhd Raja Doly; Kurniawan, Rakhmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4805

Abstract

Hospital pharmacy plays an important role in ensuring drug availability and effective stock management. With the increasing number of drug redemptions, manual data management becomes inefficient and can lead to understocking or overstocking. Therefore, a method is needed that is able to automatically analyze drug sales patterns to improve stock management efficiency. One approach that can be used is the Apriori algorithm, an effective data mining technique for finding patterns in drug redemptions. This study aims to analyze drug redemption patterns at the Belawan Navy Hospital Pharmacy using the Apriori algorithm. The data used is drug redemption data. The Apriori algorithm is applied to find relationships between drug items that are often purchased together, so that it can provide useful insights in drug stock management. The results of the study showed that the Apriori algorithm successfully identified several significant drug redemption patterns. These patterns can be used to improve the efficiency of drug stock management and ensure timely drug availability, as well as reduce the risk of understocking or overstocking. The results of the study used logistic regression to predict discrete (binary) values from a column based on values from other columns and the accuracy obtained was 1.0 or 100%. This study concludes that the application of data mining with the Apriori algorithm can provide significant benefits in optimizing the management of drug stock redemption in hospital pharmacies.
Optimizing SMS Spam Detection Using Machine Learning: A Comparative Analysis of Ensemble and Traditional Classifiers Airlangga, Gregorius
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4822

Abstract

With the rapid rise of mobile communication, Short Message Service (SMS) has become an essential platform for transmitting information. However, the growing volume of unsolicited and harmful spam messages presents significant challenges for both users and mobile network operators. This study explores the effectiveness of various machine learning models, including Random Forest, Gradient Boosting, AdaBoost, Support Vector Machine (SVM), Logistic Regression, and an Ensemble Voting Classifier, in detecting SMS spam. A dataset containing 5,572 SMS messages, labeled as either spam or ham (legitimate), was used to evaluate these models. Hyperparameter tuning was performed on each model to optimize accuracy, and the models were assessed using metrics such as precision, recall, F1-score, and accuracy. The results indicated that the SVM and Ensemble Voting Classifier achieved the highest performance, with accuracies of 0.9857 and 0.9848, respectively. Both models demonstrated superior recall for spam messages, making them highly effective for real-world spam detection systems. While Random Forest, Gradient Boosting, and AdaBoost also performed well, their slightly lower recall for spam suggests that they may misclassify some spam as legitimate messages. The study highlights the effectiveness of machine learning models in addressing the SMS spam problem, particularly when using ensemble methods. Future research should focus on addressing class imbalance and exploring deep learning approaches to further enhance model performance. These findings offer valuable insights for developing more accurate and scalable SMS spam detection systems.
Implementing Dynamic Systems Development Method for a Web-Based System to Evaluate Child Health and Growth Aisah, Nurkosrina; Ikhwan, Ali
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4824

Abstract

The Simpang Gambir UPTD Community Health Center has developed an innovative digital system to monitor the growth of toddlers. Previously, the recording of toddler growth data was done manually, often leading to data loss or damage. This new system is designed to address these issues and provide a more efficient and accurate solution. The system not only facilitates health center staff and posyandu cadres in monitoring toddler development but also assists them in creating digital growth reports. With this system, toddler growth data can be accessed quickly and easily, facilitating decision-making regarding child health management. One of the key features of this system is its ability to track toddler growth based on weight-for-age charts. This feature allows health workers to easily identify toddlers with nutritional problems and promptly provide necessary interventions. Additionally, the system is equipped with a fast data search feature, enabling staff to easily find specific toddler growth data. The development of this system utilizes the Dynamic System Development Method (DSDM), allowing for a structured and efficient development process. With this method, the system can be developed rapidly and in accordance with user needs.
A Comparative Analysis of Deep Learning Models for SMS Spam Detection: CNN-LSTM, CNN-GRU, and ResNet Approaches Airlangga, Gregorius
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4827

Abstract

Spam messages have become a growing challenge in mobile communication, threatening user security and data privacy. Traditional spam detection methods, including rule-based and machine learning techniques, are increasingly insufficient due to the evolving sophistication of spam tactics. This research evaluates the effectiveness of advanced deep learning models such as CNN-LSTM, CNN-GRU, and ResNet for SMS spam detection. The dataset used consists of diverse SMS messages labeled as either spam or legitimate (ham), ensuring broad coverage of real-world spam patterns. The study employs a robust ten-fold cross-validation approach to assess the generalization capabilities of the models, measuring performance based on accuracy, precision, recall, and F1 score. The results indicate that ResNet outperformed the other models, achieving an average accuracy of 99.08% and an F1 score of 0.9646, making it the most reliable model for spam detection. CNN-GRU demonstrated competitive performance with a balance between accuracy (98.97%) and computational efficiency, making it suitable for real-time applications. CNN-LSTM, while highly accurate (98.92%), showed a slightly lower recall compared to the other models, indicating a more cautious approach to detecting spam. These findings highlight the potential of hybrid deep learning models in addressing the complexities of SMS spam detection. Future research could focus on optimizing these models for deployment in resource-constrained environments, such as mobile devices, and further exploring the integration of residual connections for more effective spam filtering.
Application of the Naive Bayes Method for Determining the Quality of Crude Palm Oil (CPO) at PTPN 2 Sawit Seberang Prananda, Dimas Raka; Mhd. Furqan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4832

Abstract

The palm oil industry is a vital pillar of Indonesia's economy, with Crude Palm Oil (CPO) as one of its leading commodities. The quality of CPO significantly impacts its competitiveness and market price internationally. PTPN 2 Sawit Seberang, as a prominent CPO processing company, faces challenges in consistently maintaining product quality. Key factors affecting CPO quality include moisture content, free fatty acids, and impurity levels, which are difficult to manage manually. To address these challenges, this study applies the Naive Bayes method as an efficient and fast classification tool for determining CPO quality. Naive Bayes was chosen for its simplicity in probability calculations and its ability to handle data classification with reasonable accuracy. The data used in this study include moisture content, free fatty acids, and impurity levels measured between February and June 2024. The data was split into training data (80%) and testing data (20%) and analyzed using RapidMiner software. The results show that the Naive Bayes method achieved an accuracy rate of 66.6%, with precision and recall values of 50% each. Although the accuracy could be improved, the application of this method has significantly enhanced the efficiency of determining CPO quality. Thus, the implementation of the Naive Bayes method in determining CPO quality at PTPN 2 Sawit Seberang is an effective step towards improving operational efficiency, classification accuracy, and decision-making quality related to product standards, ultimately supporting the company's competitiveness in the global market.
Optimizing Transportation Costs for Distribution of Food Products Using the Modified Distribution (Modi) Method in Medan City (Case Study: Pt. Indomarco Adi Prima) Farhan, Luthfi; Rakhmawati, Fibri
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4836

Abstract

Every company in the world always hopes for the maximum possible profit so that the company's life cycle runs well. For this reason, the company must be able to manage the costs used in such a way so that there is a gap between the company's expenses and income. PT. Indomarco Adi Prima is one of the companies operating in the food products sector which still finds it difficult to determine the right method for optimizing transportation costs. Therefore, this research aims to obtain optimal transportation costs at PT. Indomarco Adi Prima in the city of Palu using the Modified Distribution (MODI) method. The results of this research show that before implementing the Modified Distribution (MODI) method the transportation costs incurred by PT. Indomarco Adi Prima, which is IDR. 61,510,000 and the resulting transportation costs after using the Modified Distribution (MODI) method are IDR. 55,565,000. This shows that PT. Indomarco Adi Prima can optimize transportation costs for the distribution of food products in December 2023 with distribution cost savings of IDR. 5,945,000 or around 10.7%.
Naive Bayes Algorithm for Sentiment Analysis on Spider-Man Movie: No Way Home: Data Mining Makarim, Ziddan; Nawangsih, Ismasari; Sanudin, Sanudin
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4845

Abstract

The rapid development of streaming platforms has significantly changed the landscape of movie consumption. The ease of access and social interaction in online communities has led to the creation of a new pop culture around movies. One interesting phenomenon is the movie Spider-Man: No Way Home, which sparked heated and viral conversations on various social media platforms. This research aims to analyze audience sentiment towards the movie Spider-Man: No Way Home using Naïve Bayes algorithm. Review data collected from online platforms was processed to identify positive and negative sentiments. The choice of Naïve Bayes algorithm is based on its efficiency and ability to classify text. The results showed that the model built was able to classify sentiment with an accuracy of 72.34%. The model is more effective in identifying positive reviews than negative, indicating a positive response from the majority of viewers. However, the model still needs to improve its performance in classifying negative sentiments. This research makes an important contribution in understanding audience preferences and evaluating the success of a movie, especially in the context of the digital era. The results can be utilized by the film industry to improve production quality, marketing strategies, and content development that is more relevant to audience preferences. In addition, this research also opens up opportunities for further development, such as the use of more complex algorithms or combining with other sentiment analysis techniques, as well as application to various types of social media content.
Mudik Assistance Application Using Android-Based Scrum Method Ardhana, Muhammad Reza; Alda, Muhamad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.4863

Abstract

Homecoming is an activity undertaken by nomads and migrant workers to return to their hometowns. In Indonesia, going home is synonymous with annual traditions starting from religious and national holidays such as Eid al-Fitr, Eid al-Adha, Christmas and New Year. However, going home is often accompanied by traffic jams and confusion, which can be a nuisance for travelers. Therefore, a possible solution to overcome this problem is to develop a mobile application to support homecoming. This research focuses on developing an Android-based homecoming assistance application using the Scrum methodology. The aim is to create technological solutions that make it easier for Indonesian people to return home every year. The development process is divided into sprints, and each sprint lasts two weeks. Each sprint includes planning, developing, and evaluating features such as real-time maps, traffic information, stop locations, and emergency response systems. The development team works closely with stakeholders to ensure that the application meets user needs. The research results show that the use of the Scrum methodology increases development efficiency and improves the quality of the final product. The resulting application prototype received a positive response in user testing. 90% of participants found the app useful when returning home. In conclusion, the development of homecoming assistance applications using the Scrum methodology has produced an effective and user-friendly solution to help travelers. This research opens up opportunities for further development and large-scale implementation in the future.

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