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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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Wheelchair Control Using Bluetooth-Based Electromyography Signals Yoga Eko Prasetyo; Hindarto Hindarto; Syamsudduha Syahrorini; Arief Wisaksono
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2063

Abstract

In modern times like this, many wheelchairs have been developed with various controls, ranging from manual ones, namely by being pushed by other people or using their hands to turn the wheel, to automatic ones, such as electric wheelchairs that use joysticks and Electromyography control. The control of the electromyography signal utilizes muscles that can still be used to move the wheelchair, in this case, using the hand muscles. The use of a Bluetooth wireless system in sending electromyography signals aims to facilitate the use of a wheelchair without interference from the many connected cables so that users are more flexible in placing the electromyography sensor on the user's hand muscles. By placing the electromyography sensor on the user's arm, the electromyography sensor detects a contraction or relaxation, which is indicated by the LED flame. The output value of the sensor will be compared with a predetermined limit value. When the value is greater than the limit value, it will produce a logic low; when the value is less than the limit value, it will build a logic high. The Arduino microcontroller will calculate every low logic. The results of these calculations will be processed into serial data. The serial data will be sent to the HC-05 enslaved person via the HC-05 master wirelessly. The motor driver will execute the data so that it produces motion forward, backward, turn right, turn left and stop. It is hoped that this tool can help individuals with limited movement so that they do not have difficulty in mobility.
The Implementation of Fuzzy Logic Algorithm In Android-Based Typhoid Fever Diagnostic Application Suryani; Ahyuna; Magfirah; Michael Oktavianus; Erni Marlina; Asrul Syam; Faizal
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2064

Abstract

Typhoid fever is an infectious disease that causes death in Indonesia. This endemic disease has a high incidence rate and is a health problem related to the environment and sanitation. Problems due to limited time to consult directly with specialist doctors, it is not easy to consult with doctors at any time, and limited medical knowledge and experience, so it is difficult for the community to know and make an early diagnosis of the disease with symptoms of typhoid fever. This study created an Android-based application using a fuzzy logic algorithm for diagnosing typhoid fever. The application was built by adopting expert knowledge related to general and clinical symptoms that are often experienced by patients with typhoid fever, and data on the level of typhoid disease. Data collection was carried out through direct observation at the hospital and direct interviews with doctors. The data was processed to produce output in the form of diagnostic results and solution data recommended by the system. The application consists of 3 user levels, namely Admin who can process user data, Users who can diagnose their disease by inputting answers to questions in the application, and Experts who can process symptom data, disease level, and solution data. The research results are in the form of an application that can be used anytime as an alternative consultant that helps the community in diagnosing typhoid fever with output in the form of diagnostic results (negative typhoid, positive typhoid, or strong positive typhoid).
Expert System Using Certainty Factor Method For Adjustment Of Learning Styles With Students I Putu Aris Sanjaya; I Gede Aris Gunadi; Gede Indrawan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2068

Abstract

Alignment of students with learning styles greatly affects the quality of learning of students in educational units. With good learning quality, the passing rate of students in an educational unit will also increase and can produce quality graduates. So far, the learning process implemented in this school has been going well when viewed based on the number of students graduating with the number of students present, but so far no further research has been conducted regarding this suitability so that the effectiveness of student learning is still not optimal. Based on this, the research objective is to build an Expert System with the Certainty Factor method to adjust the learning styles of students at SMK PGRI 5 Denpasar. Based on the results that will be obtained through the system designed and built in this research, it is hoped that it will make it easier for educators to prepare learning models and strategies that will be given to students from the results of determining student learning styles. The research results obtained from the test results show 100% suitability in giving dominant results to students' learning styles. In this study the students who were used as the test sample had different learning style percentage accuracy so that it could be used to determine the right learning style for each student.
Implementation of Bot Telegram as Broadcasting Media Classification Results of Convolutional Neural Network (CNN) Images of Rice Plant Leaves Adi Fajaryanto; Fauzan Masykur; Mohammad Rizqi Rosyadi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1976

Abstract

Rice plants play an important role in the life of the Indonesian people because rice is the raw material for rice as a staple food. The rice production process does not rule out the possibility of interference by pests and diseases resulting in losses that cause crop failure. Meanwhile, pests on rice plants can be caused by various types, namely types of fungi (leafblast, hispa, brownspot) and types of nuisance animals. In this research, it will be carried out how to classify the image of rice plant leaves using the deep learning Convolutional Neural Network (CNN) algorithm, then the results of the classification are sent to users by utilizing the telegram chat application. The rice plant leaf image dataset is grouped into 4 groups (leafblast, brownspot, hispa and healthy). From several experiments it can be seen the results of system performance, namely the classification speed takes 30-60 seconds.
Researchers Productivity Level Clustering Based On H-Index and Citation Using The Fuzzy C-Means Algorithm Mira Orisa; Ahmad Faisol
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1984

Abstract

The fuzzy C-Means algorithm is a partition-based clustering algorithm.Fuzzy C-Means is very helpful in modeling data whose distribution has outliers. Outliers are where there is a data object that is far apart from the existing clusters. Fuzzy C-Means groups data by minimizing the membership function of a data set. so that each piece of data can be a member of more than one group. In this study, the dataset used was the paper citation vs. H-index dataset in the Kaggle.com repository. This dataset is known to have outliers in fuzzy C-Means and has better performance compared to the K-Means and K-Medoid algorithms in modeling datasets that have outliers.
Classification of Banana Ripeness Based on Color and Texture Characteristics Ahmad Hafidzul Kahfi; Muhamad Hasan; Riyan Latifahul Hasanah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1985

Abstract

Banana is one of the most consumed fruits globally and is a rich source of vitamins, minerals and carbohydrates. With the many benefits that bananas have, many farmers cultivate this fruit. The problem that occurs when the harvest is produced on a large scale is the process of selecting bananas that are still unripe or ripe. Usually farmers carry out the selection process manually by visually identifying ripeness based on the color of the fruit skin. However, direct observation has several drawbacks such as subjectivity, takes a long time and is inaccurate. For this reason, we need a system that can help determine the maturity level of bananas automatically through a series of banana image processing processes. One way that can be used to determine the maturity level of bananas is by looking at the color and texture of the bananas. This study aims to classify the maturity level of bananas based on the color and texture characteristics of the banana image using the Gray Level Co-occurrence Matrix and K-Nearest Neighbor methods for the classification process. Based on the results of the research analysis that has been carried out, using the parameter k which has a value of 3 obtains very high accuracy.
Telemedicine Development for Health Center Services Using Agile Methods Darmawan Lahru Riatma; Masbahah; Anis Laela Megasari; Rizka Adela Fatsena
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1987

Abstract

Puskesmas are the spearhead of health services throughout Indonesia, puskesmas are at the forefront in breaking the chain of transmission of COVID-19 because they are located in every sub-district and have a regional concept. Being at the forefront in handling COVID19 and continuing to provide other primary health services to the community is a tough task for puskesmas throughout Indonesia. In urgent situations and rapidly changing regulations regarding the handling of COVID19 and non-COVID19 patients, telemedicine application development researchers are required to work quickly and precisely according to the needs of the Puskesmas. This study discusses the development of telemedicine applications using the Agile development method, with the Scrum framework. Based on the problems above, researchers will develop telemedicine applications with several health service features, namely; COVID19 independent health checks, village doctor and midwife consultations, medicine orders, maternity services, and dental consultation services, the features in the telemedicine application were developed using the agile scrum method. Telemedicine development begins with system design analysis, UI/UX design, develop, functional testing, usability testing and launching. From the system design analysis, it produces output use case diagrams and class diagrams, according to the needs of the puskesmas business process. UI/UX design is carried out using figma tools, then application development is carried out focusing on the frontend and backend, after the application has been developed, functional testing is carried out three times and usability testing. The results of the usability test conducted on 35 respondents obtained an average score through the SUS questionnaire with a score of 79. In terms of the Acceptability Range, this application program is in the Acceptable category, while on the Grade Scale it is in Grade C position and on the Adjective Rating it is in a Good position . The results show that the telemedicine application for Pusline is good and can be accepted by users.
Vulnerability Assessment with Network-Based Scanner Method for Improving Website Security Dewi Laksmiati
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1991

Abstract

The digital world has seen a significant increase in security threats in recent years, with hacker attacks on websites being a major concern in cybersecurity. One platform that is particularly vulnerable is WordPress, which is widely used and therefore a popular target for hackers. About 95.62% hacked website in 2021 is WordPress based site. Therefore, to improve website security we conducted a vulnerability assessment on a WordPress based website, in order to identify vulnerabilities that may be exploited by hackers. To do the vulnerability assessment, we used the network-based scanner based to detect vulnerabilities on the WordPress website. Our results showed that the website had several vulnerabilities that needed to be addressed and fixed immediately. The conclusion of our research highlights the importance of conducting regular vulnerability assessments on WordPress-based websites to reduce the risk of vulnerabilities being exploited. By taking proactive measures to identify and fix vulnerabilities, website owners can better protect their sites from potential hacker attacks. It is crucial for website owners to be aware of the risks posed by security threats in the digital world and to take steps to mitigate these risks to protect their businesses and their customers.
Simulation Modeling System in Determining the Amount of Oil Inventory Okta Veza; Larisang; Albertus L. Setyabudhi; Nofri Yudi Arifin; Sherly Agustini
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2009

Abstract

Currently, XYZ Gas Stations, in carrying out fuel sales activities, have not yet used a simulation of calculating fuel supply needs at gas stations which functions to support decision making by the leadership, this causes frequent stock shortages at each XYZ gas station branch. because of that the authors are interested in creating a modeling system for calculating fuel inventory simulations using the Monte Carlo method and the LCM pattern. The purpose of this research is to produce a simulated calculation of the supply of purchased fuel so that management knows how much stock of fuel must be provided at each gas station and also to prevent empty fuel stocks at each gas station in the XYZ branch. The data collection methods used in this study were interviews, observations, and literature studies. The system is designed using the JAVA Programming Language. The data processed in this study is transaction activity data for January and February 2022 to determine the amount of inventory that must be provided in March 2022. The final results of the data processing that has been carried out with the trial purchase data transactions for the two current months, namely January and February 2022 to get the simulation results of fuel oil (BBM) supplies in March whose activation has been running with simulation predictions using the Monte Carlo Algorithm.
Comparison of Machine Learning Techniques in the Classification of Parkinson’s Desease Sufferers Titik Khotiah; David Fahmi Abdillah; Ilham Basri K; Fery Arianto; Abdul Rohman
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.2035

Abstract

Parkinson's disease is a progressive and relatively common neurodegenerative  disorder in the central nervous system where sufferers can have difficulty moving. This disease has a high mortality rate in the world of around 9.3 million in 2021. Meanwhile, in Indonesia, it is estimated that as many as 12,980 people die every year due to Parkinson's cases. This increase in cases of death is due to the lack of information about the initial symptoms and dangers of the disease, besides it is important to know how to prevent it early.  Early detection of Parkinson's disease can prevent symptoms of a certain age thereby increasing life expectancy. The existence of a computer-based system for diagnosing Parkinson's disease is called a classification system where the system applies the Machine Learning method. This study aims to compare the performance of algorithms in the classification system of people with computer diseases. In this study, it used methods in  Machine Learning such as K-NN, Multi Layer Percepteron (MLP), Linear Regression and Support Vector Machine (SVM).  The data set in this study was obtained using the Weka application.  The dataset used was Parkinson's Disease data  totaling 195 rows of data taken from the UCI Machine Learning Repository Datasets.  The results  of the experiment based on the four algorithms showed that  the poor performance was the Multi Layer Percepteron approach  to regression data with an RSME value of 0.459.  Meanwhile, the k-Neural Network Algorithm  is a good classification technique forParkinson's problem with an RMSE value of 0.1895.

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