cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Nurul Khairina
Contact Email
nurulkhairina27@gmail.com
Phone
+6282167350925
Journal Mail Official
nurul@itscience.org
Editorial Address
Jl. Setia Luhur Lk V No 18 A Medan Helvetia Tel / fax : +62 822-5158-3783 / +62 822-5158-3783
Location
Kota medan,
Sumatera utara
INDONESIA
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
 56   57   58   59   60 
Application of Google cloud computing for web-based library information systems at Bahayangkara University Surabaya Irsyadi, Muhammad Haidir; Alam, Fajar Indra Nur; Sari, Anggraini Puspita; Agussalim, Agussalim
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.6955

Abstract

Libraries are essential in academic work as they expose people to structured, easily procurable information.  However, the majority of schools, including Bhayangkara University Surabaya, still face challenges in managing and storing library information because local or manual systems are substandard. The goal of this project is to deploy and test the effectiveness of Google Cloud Computing technologies, such as Google Cloud Storage, Google Cloud SQL, and Google Compute Engine, on a website-based library information system.  We adopted a quantitative approach by performing experiments and system testing, i.e., black-box testing, access speed testing, and heavy load resistance testing. The result of the implementation is massive benefits, including a response time of 2 seconds on average, stability with 500 users at the same time, and storage efficiency at just 30% of the original size.  Other colleges can have an example that they can use to make a change to a cloud-based digital library from this research.  This also helps create digital library information systems that are technology-centered and dependable.
Design and Development of a Web-Based E-Learning System at SMA Tri Dharma Palembang Ayu, Niken; Supratman, Edi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.6965

Abstract

The rapid advancement of information and communication technology has transformed learning practices globally, yet teaching activities at SMA Tri Dharma Palembang remain predominantly conventional and do not fully align with the requirements of the Merdeka Curriculum. This study was conducted to design and develop a web-based e-learning system that integrates learning material management, assignment submission, automated and manual assessments, discussion forums, and real-time student activity monitoring. The research applied a Research and Development (R&D) approach consisting of needs analysis, system design using Unified Modeling Language (UML), implementation with PHP, MySQL, and Bootstrap, and evaluation through black box testing and a Likert-scale user satisfaction survey. The system was tested by two teachers and ten students, and expert validation was conducted to assess the research instrument. Results show that all modules performed as expected during functional testing, and the user satisfaction survey yielded an overall score of 85.33%, categorized as very good. The findings were analyzed using the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the DeLone & McLean IS Success Model, confirming that system quality, ease of use, usefulness, and user satisfaction significantly influence e-learning adoption in secondary education. This study contributes theoretically by extending the application of established information systems success models in the Indonesian school context and practically by providing a digital platform that supports the implementation of the Merdeka Curriculum. Keywords: activity monitoring; e-learning; Merdeka Curriculum; TAM; UTAUT
Implementation of the K-Means Clustering Algorithm for Segmenting Employee Mental Health Profiles Based on Work Productivity Indicators Rahman, Maulia; Leman, Dedi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.6974

Abstract

This study aims to identify mental health profile segmentation among employees based on work productivity indicators in the context of working from home (WFH) using the K-Means clustering algorithm. This study uniquely integrates mental health and productivity indicators into an unsupervised clustering framework. A cross-sectional method was conducted on 100 employee respondents with 10 main variables, analysed using K-Means with four optimal cluster evaluation methods. The results identified four distinct segments: Low WFH Adaptation (25%), High WFH Enthusiasts (30%), Mixed Preference (25%), and Office Preference (20%), with Silhouette Score validation of 0.623 and Davies-Bouldin Index of 0.967. The main findings reveal the paradox of High WFH Enthusiasts, who have the highest productivity (93%) but the highest mental health risk (1.90). This segmentation provides a practical framework for developing personalised mental health intervention strategies in employee management in the remote working era.
Analysis of Predicting the Number of Rejected Chips Using Random Forest at PT. Wahyu Kartumasindo Internasional Supriyadi, Agus; Sunge, Aswan Supriyadi; Tedi, Nanang
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 4 (2025): Articles Research October 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i4.7028

Abstract

Manufacturing industries face significant challenges in maintaining consistent product quality, particularly in minimizing reject rates across production machines, as high reject levels not only increase operational costs but also reduce overall efficiency and competitiveness. This study aims to develop a predictive approach using the Random Forest algorithm to forecast monthly chip rejects across different production machines, with historical reject data consisting of 1,820 records from June 2023 to September 2024 analyzed based on four primary reject categories and five production machines (DCL1, DCL2, CMI200, CMI200+, and YMJ400). The Random Forest model was applied to classify and predict reject patterns, and its performance was evaluated based on prediction accuracy and error rates, showing that the algorithm is effective in predicting reject counts with an absolute error of 0.640 ± 0.183, especially for lower reject values under 300, although accuracy decreases when handling higher reject levels above 500. Machine-level analysis further reveals that DCL1 and DCL2 consistently contribute the highest reject counts with high variability, while CMI200 and CMI200+ demonstrate stable performance with most rejects below 300, and YMJ400 generally records lower rejects but occasionally exhibits spikes, suggesting inconsistent performance. In conclusion, the Random Forest model provides a reliable predictive framework for monitoring reject trends, identifying DCL1 and DCL2 as priority targets for improvement, and supporting proactive maintenance strategies to enhance overall production quality.
Copyright Protection of Scientific Works using Digital Watermarking by Embedding DOI QR Code Harahap, Muhammad Khoiruddin; Khairina, Nurul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1064

Abstract

Digital identifier is a technology used to prove ownership of a work. At this time, the Digital Object Identifier is a form of implementation of the digital identifier used in every scientific work. Not infrequently there are several cases of theft of ownership or copyright of a work, both scientific works, and certain other works. Watermarking is a technique created to protect the ownership of works. Watermarking techniques can be applied to several media such as audio, video, and also documents, one of which is the Portable Document Format document file. In this study, researchers want to build copyright protection for scientific works. Researchers offer research concepts using a Digital Object Identifier which is always installed on scientific papers to be published. The Digital Object Identifier will later become the basic data in building the Quick Response Code. The Digital Object Identifier of each scientific work will not be the same as each other, this will certainly make the Quick Response Code more unique. The results show that the watermarking process in building copyright protection of scientific works can be very successful Quick Response Code can be read and detected properly without experiencing lag time. Quick Response Code readings from several variations of motion are also not very influential, so it can be concluded that distance does not limit the detection of Quick Response Codes. From this research, researchers can deduce that the watermark is performed on the scientific work not only serves as the copyright protection of that scientific paper but can also be an alternative for other researchers to access the scientific work.
Information Technology Governance Analysis Of Stmik Palcomtech In The New Normal Era Using Cobit 2019 Method Ajismanto, Fahmi; Surahmat, Surahmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1097

Abstract

The pandemic conditions experienced by the world today inevitably force us to practice social distance so that gatherings involving large numbers of people must be avoided first. In universities, especially in the city of Palembang, the use of information technology and learning media is mandatory due to the decision of the minister of education which requires universities to carry out online learning activities. So that information technology governance during a pandemic also has a major influence in the implementation of teaching and learning activities in universities to ensure the quality of the learning and teaching process carried out so that it must be known the shortcomings and advantages of governance which is carried out by conducting further analysis of technology governance in accordance with with the initial goal of education at the university. The method that can be used is to apply the Cobit 2019 where with this method the current maturity level can be known in the application of information technology. The research method in this study uses a descriptive-quantitative method by describing the indicators used as the basis for measurement taken by the Cobit 2019 literature. This study discusses information technology governance form of Design Factor 1 (Enterprise Strategy) to Design Factor 10 (Technology Adoption Strategy) with the result that there are 13 important processes out of 40 total processes in the Cobit 2019 domain that must be considered at STMIK Palcomtech, namely EDM03, APO08, DSS05 EDM02, APO04, APO09, APO12, APO13, BAI01, BAI02, BAI03, BAI06 , MEA03
Application of the AHP Method for KIP Recommendation Applications -College Students Satria, Eri; Ilham, Dirja Nur; Budiansyah, Arie; Candra, Rudi Arif; Papuangan, Miswar
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1112

Abstract

The Smart Indonesia Card (KIP) is an assistance in the form of cash from the government given to students whose parents are less able to finance their education, as a continuation and expansion of the targets of the Poor Student Assistance (BSM) program. KIP has a goal, namely to increase access for children aged 6 (six) to 21 (twenty-one years) to obtain educational services until they graduate from high school to support the implementation of Universal Secondary Education / Pilot Compulsory Education 12 (twelve) years, prevent students from the possibility of dropping out of school or not continuing their education due to economic difficulties. The KIP-Kuliah, formerly known as Bidikmisi, is presently in service. They may find it difficult to determine who is a qualified candidate to become a recommendation for KIP-Kuliah recipients who will be presented to the system since many variables and assessments will be passed in determining the prospective KIP-Kuliah recipients. Therefore, from this problem, a system is needed that can quickly and accurately assess the eligibility of KIP-Lecture recipients without having to sort out the files that have been collected one by one. As a result, it is deemed necessary to develop a decision-making system to address the existing issues. The steps of research that will be carried out to create a decision support system will collect criteria and sub-criteria from the assessment and then enter them into the calculation formula or method employed, namely the AHP method.
Planning Model and Questionnaire for Measuring MSME Performance through (TOE) Technology Organization Environment Indonesia Siagian, Ade Onny; Riesmiyantiningtias, Ninuk; Amalia, Rizky
Journal of Computer Networks, Architecture and High Performance Computing Vol. 4 No. 1 (2022): Article Research Volume 4 Number 1, Januay 2022
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v4i1.1213

Abstract

MSMEs (Micro, Small and Medium Enterprises) as one of the factors driving the economy in Indonesia are experiencing the Covid-19 pandemic crisis which has led to the activities of the Indonesian people. This will indirectly affect the activities of human life, including the buying and selling process. Buying and selling activities that are usually carried out face-to-face can not be carried out normally due to activities from the government so that it indirectly affects the sales results of business actors, including MSME actors. During this pandemic, there was a very significant decline and caused deep anxiety for MSME actors such as payment of employee salaries, daily operational costs, and others. The existence of this phenomenon or incident has resulted in MSMEs having to rack their brains in order to survive in the midst of the ongoing crisis. In order to continue to survive, MSMEs use social media to promote sales, or make sales online with social media. The purpose of this study was to determine the effect of social media adoption on the performance of MSMEs. This research method is carried out in several stages which include problems, literature review about the research model, research design, making instruments that produce questionnaires. The result of this study is produces a research model related to the adoption of social media on the performance of MSMEs which is supported by the dependent variable of the Technology-Organization-Environment (TOE) framework, as well as a questionnaire.
Implementation Of The Data Mining Cart Algorithm In The Characteristic Pattern Of New Student Admissions Siregar, Ahmad Syahban Rifandy; Siregar, Yunita Sari; Khairani, Mufida
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.v5i1.1975

Abstract

University of Harapan Medan is one of the private universities in North Sumatra which has an Informatics Engineering Study Program with Good Accreditation. With better accreditation, the number of students who register is also increasing. At the admission of new students, the committee has a huge pile of data, making it difficult in the process of whether the student passed or did not pass. Therefore, in this study, we will implement data mining with the CART (Classification And Regression Tree) algorithm. Data mining is a technique to determine the characteristic pattern of a variable or data criteria with a large amount. In the CART method, the data is first converted into testing data, which will then be used to form a classification tree by calculating the value of information gain, Gini index and goodness of split. From the results obtained, it will be re-determined terminal nodes, marking class labels and finally pruning the classification tree which produces a decision tree. In this study, the number of testing data was 75 with 3 criteria, namely the average value of report cards, CAT test scores, and interview scores. The results of testing data testing using RapisMiner 5.3 software produce 23 number of characteristic pattern rules, where node 1 is the CAT test score, level 1 branch node is the interview score criteria and level 2 branch node is the average report card value.
Implementation of Bot Telegram as Broadcasting Media Classification Results of Convolutional Neural Network (CNN) Images of Rice Plant Leaves Cobantoro, Adi Fajaryanto; Fauzan Masykur; Rizqi Rosyadi, Mohammad
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.

Page 58 of 80 | Total Record : 795

 56   57   58   59   60 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol. 7 No. 2 (2025): Research Article, Volume 7 Issue 2 April, 2025 Vol. 7 No. 2 (2025): Forthcoming: Research Article, Volume 7 Issue 2 April, 2025 Vol. 7 No. 4 (2025): Articles Research October 2025 Vol. 7 No. 3 (2025): Articles Research July 2025 Vol. 7 No. 1 (2025): Article Research January 2025 Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024 Vol. 6 No. 2 (2024): Articles Research Volume 6 Issue 2, April 2024 Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024 Vol. 6 No. 4 (2024): Articles Research October 2024 Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023 Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023 Vol. 4 No. 2 (2022): Article Research Volume 4 Number 2, July 2022 Vol. 4 No. 1 (2022): Article Research Volume 4 Number 1, Januay 2022 Vol. 3 No. 1 (2021): Computer Networks, Architecture and High Performance Computing, January 2021 Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing Vol. 2 No. 1 (2020): Computer Networks, Architecture and High Performance Computing Vol. 1 No. 2 (2019): Computer Networks, Architecture and High Performance Computing Vol. 1 No. 1 (2019): Computer Networks, Architecture and High Performance Computing More Issue