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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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Sentiment Analysis of Reviews of Tourist Attractions in the Lake Toba Area Using the Naïve Bayes Method Wiranti, Yuke; Nasution, Yusuf Ramadhan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4287

Abstract

Lake Toba is one of the tourism destinations in Indonesia which is the main destination for domestic and foreign tourists. However, the natural beauty of Lake Toba is not enough to develop quality tourist destinations, so analysis needs to be carried out in order to develop tourist destinations that suit tourist needs with the aim of improving the economy from tourism, especially at Lake Toba. One aspect that must be analyzed is comments from tourists who have visited Lake Toba via various platforms. This is very influential for potential future tourists to have a reference for Lake Toba tourism. The analysis process can be carried out by analyzing comments using the Naive Bayes method so that managers of the Lake Toba tourist destination can improve tourist attractions and provide tourist satisfaction and develop various tourism innovations to meet various tourist needs in a sustainable manner. The results of the sentiment analysis of Lake Toba tourist reviews using Naive Bayes detected 31 positive labels, 378 neutral labels and 7 negative labels with an accuracy result of 77.49% from 1260 data, where training data was 1008 and test data was 252 data.
Design of Mask Detection Application Using Tensorflow Lite based on Android Mobile Effendi, M Makmun; Turmudi, Ahmad; Arwan, Asep
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4329

Abstract

A mask is a type of personal protective equipment (PPE) that is essential for protecting the nose and mouth from contamination by droplets or airborne particles. The use of masks became highly popular during the Covid-19 pandemic, which began in December 2019 in China and peaked in Indonesia in 2020. Despite the pandemic subsiding and vaccinations increasing immunity, some companies still require masks to prevent the spread of illnesses such as colds and flu, especially in work processes that produce smoke, such as soldering and welding. To ensure employees comply with mask usage, effective supervision is necessary. Manual supervision is less efficient, thus a digital detection method is needed. This study developed a mask detection application using deep learning algorithms and the TensorFlow Lite framework on an Android platform. The application can detect mask usage with 100% accuracy at a distance of 1 to 5 meters. The system was tested under various lighting conditions and environments to ensure reliability. Additionally, the implementation of this technology can be extended to other public areas to ensure compliance with health protocols. This tool helps companies easily monitor and enforce mask-wearing discipline among employees, thereby enhancing workplace safety and health. Future work could explore the integration of this system with other health monitoring tools to create a comprehensive safety solution.
Analysis of Vina Film Sentiment on Social Media X Using The Naïve Bayes Method Asti, Dini; Putri, Raissa Amanda
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4341

Abstract

The increasingly rapid development of technology and information, one of which is the internet. Where users can share opinions and discuss various topics or problems around them, namely social media One of the news items that frequently appears as a trending topic on X is the Vina film controversy. However, with the large amount of review data available, it will be difficult to process manually. Therefore, sentiment analysis is needed to see whether people's tendencies toward the Vina film case are positive or negative. The stages carried out were data collection taken via web scrapping with an initial amount of data of 833 and processed through the preprocessing stage, including cleaning, case folding, normalization, stopword removal, tokenization, and stemming, the data became 830. The application of the Naïve Bayes algorithm in this research uses the probability method to classify and predict 664 training data and 166 test data, with the help of the Python library. The accuracy calculation results show quite good performance with TF-IDF weighting producing an accuracy of 78%, precision of 80%, and recall of 90%, f1-score of 84%. Analysis from this research shows that the dominance of negative sentiment is 517 while positive sentiment is 313. The amount and quality of training data play an important role in system quality, where high data quality provides better accuracy in predicting sentiment classes.
Comparison of Deep Learning Methods for Detecting Tuberculosis Through Chest X-Rays Udayana, I Putu Agus Eka Darma; Indrawan, I Gusti Agung; Prawira, I Made Karang Satria
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4345

Abstract

Chronic diseases are the leading cause of death worldwide, accounting for 73% of deaths in 2020. Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis, is one of these diseases and has a significant impact on countries with a high TB burden due to a lack of radiologists and medical equipment. Early diagnosis of TB is crucial but challenging because of its similarity to lung cancer and the shortage of radiologists. A semi-automatic TB detection system is needed to support medical diagnosis and improve public health services. Deep learning technology, such as Convolutional Neural Networks (CNN), offers an effective solution for disease diagnosis with high accuracy. This study compares deep learning methods using an 8-layer CNN and VGG-19, both enhanced with Histogram Equalization (HE) for improved image quality. The study utilizes chest X-ray images of normal lungs and TB-affected lungs from Kaggle. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results indicate that the VGG-19 model outperforms the 8-layer CNN across all evaluation metrics, achieving an accuracy of 72.00% compared to 65.00% for the 8-layer CNN. VGG-19 also demonstrates better precision, recall, and F1-score, making it a more suitable choice for TB detection with enhanced image quality.
Designing a Web-Based Accounting Information System Using the Object Oriented Analysis and Design Method Hasibuan, Anisha Fhuza; Alda, Muhamad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4347

Abstract

The development of information technology in the digital era has created many new efficient applications. With the development of computer technology as a means of processing data into information which is then processed again in such a way in its presentation. Perum BULOG is one of the state-owned companies engaged in rice logistics and food security. As a company that continues to carry out public duties from the government, BULOG in carrying out activities that can stabilize the basic purchase price for grain, stabilize prices, especially basic prices, distribute rice for the poor (Raskin) and manage food stocks. This research aims to optimize the process of purchasing food and distributing computerized social assistance. The development method used in making this system is the Object Oriented Analysis and Design (OOAD) method which can model objects in the system, in the context of AIS, objects such as "accounts, transactions" can be represented as objects in the OOAD model. The results showed that the sales and distribution activities of social assistance are increasingly managed according to the needs equipped with a transaction process that can be stored.
Sentiment Analysis of Starlink on Twitter Using Support Vector Machine Algorithm Sardin, Sardin; Nugroho, Agung; Kurniadi, Nanang Tedi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4348

Abstract

Indonesia faces unique challenges in the provision of internet services. Cable and fiber optic infrastructure is often difficult and expensive to implement in many areas. Based on data from the Asosiasi Penyelenggara Jasa Internet Indonesia (APJII), by 2024 internet users will reach 221.5 million. Starlink, Elon Musk's satellite-based internet service through his SpaceX company, offers an innovative solution to fill the void in Indonesia's telecommunications infrastructure. However, Starlink's presence has raised concerns among local service providers, particularly regarding potential market disruption and existing regulations. Starlink could also pose a potential threat to Indonesia's security and sovereignty. Starlink has been a hot topic on various social media platforms, including Twitter. Twitter is a very popular social media platform with millions of active users who often share their opinions in real-time. The number of public responses in assessing the presence of Starlink in Indonesia, became a reference for a sentiment analysis. The Support Vector Machine algorithm is used to classify opinions into positive and negative categories. Based on testing that has been done using the Cross Validation technique with a K-Fold value with a total of 1976 tweets data. The results show that 1112 tweets contain positive sentiment and 864 tweets contain negative sentiment. This shows that 56.3% of people agree with the presence of starlink in Indonesia. While from the use of the Support Vertor Machine algorithm, the Accruracy value is 76.22%, Precision is 77.48%, and Recall is 81.38%.
Flood Prediction Using Support Vector Regression (Case Study of Floodgates in Jakarta) Azi, Amanda; Saleh, Robby Febrianur; Ardana, Wildan Muhammmad; Kusrini, Kusrini
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4360

Abstract

Flood can be interpreted as an event that occurs suddenly and quickly enough where the water discharge in the drainage channel cannot be accommodated, so that the blocked area causes the water discharge in the drainage channel in several surrounding areas to overflow and is one of the natural disasters that occurs at an unexpected time and cannot be prevented, because of this, a prediction must be made to detect floods for the next day. Flood prediction is a crucial aspect of disaster management and mitigation, particularly in flood-prone areas such as Jakarta, Indonesia. This study aims to leverage Support Vector Regression (SVR) to predict flood events by analyzing various environmental and hydrological factors that influence flooding. The primary data sources include historical wheater data, river water levels, floodgate positions in Jakarta. The data preprocessing involved cleaning, handling missing values, and normalizing the datasets to ensure compatibility with the SVR model. Feature selection was conducted to identify the most relevant predictors of flooding, such as wheater data, and river water levels. The dataset was then split into training and testing sets, maintaining an 80-20 ratio to ensure robust model validation. An SVR model with a radial basis function (RBF) kernel was trained on the standardized training data. The model's performance was evaluated using Root Mean Squared Error (RMSE) as the primary metric. The RMSE produced in this study was 0.112 with an R Square accuracy of 0.977. The results indicated that the SVR model could effectively predict flood events with a reasonable degree of accuracy, demonstrating its potential as a valuable tool in flood forecasting.
Comparison of Automation Testing On Card Printer Project Using Playwright And Selenium Tools Melyawati, Ni Luh Putu; Asana, I Made Dwi Putra; Putri, Ni Wayan Suardiati; Atmaja, Ketut Jaya; Sudipa, I Gede Iwan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4362

Abstract

The quality of the software is greatly determined by the testing phase, which involves various test cases that can be conducted through manual testing and automation testing. Manual testing is performed manually without using automation scripts, whereas automation testing is conducted using automation scripts. ABC is a company that operates globally in the field of access control, with the Card Printer being one of the menus used in access control. In the development process of this software, both manual and automation testing phases are carried out. The automation testing process employs the Selenium tool, which has proven to be time-consuming and poses challenges when running numerous test cases. This research aims to develop automation testing using Playwright to address the long execution time issue encountered with Selenium. The research utilizes the Card Printer project in the development of automation testing and adopts the Agile methodology. The result of developing automation testing using Playwright was successfully applied to 12 test cases. Additionally, the time analysis between Playwright and Selenium showed that Playwright has a total execution time of 4.9 minutes, which is faster compared to Selenium's total execution time of 8.3 minutes. With faster execution times, Playwright can be considered a tool in the development of automation testing.
Design and Development of a Mobile Application for Marriage Counseling and Divorce Mediation at KUA Medan Tuntungan Satria, Satria; Alda, Muhamad
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4364

Abstract

Marriage counseling is an effort that can be aimed at preparing prospective couples to establish a more serious relationship. Good communication involvement between the two prospective couples is one factor in building a solid foundation in marriage. Life after marriage has a big role and responsibility. Divorce can occur due to lack of readiness between the two prospective couples, so marriage counseling is very important so that prospective brides and grooms can prepare carefully for the relationship that will be carried out in the future. Therefore, this study builds a marriage counseling mobile application aimed at understanding the roles and responsibilities of marriage. This study itself uses a qualitative method by collecting, analyzing and reviewing valid data and information regarding marriage counseling for prospective couples. The waterfall method is used in this study as a system design where the waterfall is considered adaptable in the development of a marriage counseling mobile application accompanied by Unified Modeling Language (UML) modeling.
Customer Relationship Management Strategy in Mobile-Based E-Commerce Platform Development to Increase Purchase Interest Br Purba, Yunita Dana; Haraha, Aninda Muliani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4365

Abstract

The demands of technological developments trigger every company to be able to increase competitive advantages in order to create a smooth business process. Customer satisfaction in comparing expectations before making a transaction with the service directly felt by a customer is one of the elements that affect how succesful. Therefore, this study develops and implements a mobile-based e-commerce system equipped with a customer relationship management feature that aims to increase the involvement of interest and product purchases at the Tarigan Clothing Store so that it can provide very significant additional value in a product marketing process. This mobile-based e-commerce information system application also utilizes javascript technology as its interface design. The use of javascript is considered to facilitate access to the latest features in the e-commerce application that is built because of the high existence of javascript which continues to develop according to technological advances. This mobile-based e-commerce application is expected to provide wider reach, convenience and become a more effective marketing tool for customers and Tarigan Clothing Store so that it can provide significant benefits for both parties and create a more comfortable and efficient shopping process.

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