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Jurnal Komputer Indonesia
Published by Universitas Dehasen Bengkulu
ISSN : -     EISSN : 29623626     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Komputer Indonesia (JKI) diterbitkan oleh Universitas dehasen Bengkulu. JKI memuat naskah hasil-hasil penelitian di bidang Ilmu Komputer. JKI berkomitmen untuk memuat artikel berbahasa Indonesia yang berkualitas dan dapat menjadi rujukan utama para peneliti dalam bidang Ilmu Komputer. Ruang lingkup JKI adalah sebagai berikut: Domain Specific Frameworks and Applications IT Management dan IT Governance e-Government e-Healthcare, e-Learning, e-Manufacturing, e-Commerce ERP dan Supply Chain Management Business Process Management Smart Systems Smart City Smart Cloud Technology Smart Appliances & Wearable Computing Devices Robotic Systems Smart Sensor Networks Information Infrastructure for Smart Living Spaces Intelligent Transportation Systems Models, Methods and Techniques Conceptual Modeling, Languages and design Software Engineering Information-centric Networking Human Computer Interaction Media, Game and Mobile Technologies Data Mining Information Retrievel Information Security Image Processing and Pattern Recognition Remote Sensing Natural Language Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 50 Documents
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Utilization Of Artificial Intelligence In Image-Based Medical Diagnosis Febriani, Rizki Annisa
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.567

Abstract

Artificial Intelligence (AI) has become one of the most revolutionary technologies in the medical field, especially in image-based diagnostics. This research aims to explore the utilization of AI, particularly through deep learning and Convolutional Neural Networks (CNN), in improving the accuracy and efficiency of medical diagnosis systems. This research uses a literature study approach and prototype implementation to analyze how AI can support doctors in making faster and more informed clinical decisions. The results show that AI is able to improve the accuracy of diagnoses as well as reduce human errors in medical image analysis.
Cyber Security In 2023: The Latest Challenges And Solutions Wiratama, Ahmad Doni
Jurnal Komputer Indonesia Vol. 2 No. 1 (2023): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v2i1.569

Abstract

Cybersecurity has become a crucial issue in the digital age, especially in 2023 where technology continues to evolve rapidly. This article discusses the challenges faced in maintaining cybersecurity, such as the rise of increasingly sophisticated cyberattacks, and the latest solutions offered to deal with them. The research was conducted through literature analysis as well as relevant case studies. The results show that new approaches such as Zero Trust, artificial intelligence in threat detection, and collaboration between entities are key to strengthening cybersecurity in 2023.
Development Of Machine Learning Algorithms For Fraud Detection In Digital Transactions Tarigan, Heskyel Pranata
Jurnal Komputer Indonesia Vol. 3 No. 1 (2024): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i1.571

Abstract

This article discusses the development of machine learning algorithms to detect fraud in digital transactions. With the increasing use of online transactions, fraud detection becomes crucial to maintain security. The proposed algorithm uses deep learning techniques to identify anomalous patterns in transaction data. The results show that the algorithm is able to improve the accuracy of fraud detection compared to conventional methods.
Study On The Effect Of Edge Computing On Latency In Iot Applications Saputri , Vettyca Diana; Febriani , Rizki Annisa
Jurnal Komputer Indonesia Vol. 3 No. 1 (2024): Juni
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i1.572

Abstract

This article examines the effect of implementing edge computing on latency in Internet of Things (IoT) applications. Edge computing moves data processing closer to the data source to reduce latency and improve efficiency. This research compares the performance of IoT applications with and without edge computing. The results show a significant reduction in latency and an increase in application response speed.
The Application Of Google Sites In Student Learning Outcomes At Sman 09 Bengkulu Selatan Agustina , Esi; Asnawati, Asnawati; Fitria, Yenni
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.575

Abstract

This research aims to explain the application of Google Sites in learning outcomes in the Informatics subject in learning outcomes for the integration of Ms-Word office applications in class XA students at SMAN 9 Bengkulu Selatan. The approach method used in the research is a qualitative descriptive method. The focus of the research carried out was to explain the application of Google Sites in learning outcomes in Informatics subjects. The results of the research were validation of material experts in the feasible category with an average assessment of 3.22 and validation of media experts in the Very Appropriate category with an average assessment of 3.52. The results of observations regarding the implementation of Google Sites obtained a percentage of Very Good at 19%, Good at 56%, Fairly Good at 13%, Poor at 2% and Very Poor at 2%. The results of the student questionnaire regarding the implementation of Google Sites obtained results in the Strongly Agree category of 25%, the Agree category of 70%, the Disagree category of 6% and the Strongly Disagree category of 0%. Based on these results, it can be concluded that the application of Google Sites in learning outcomes in the Informatics subject in the MS-Word office application integration learning outcomes of class XA students at SMAN 9 South Bengkulu is included in the good category.
Application of the Group Investigation (Gi) Learning Model to Improve Learning Outcomes in Informatics Subjects Students Class Xi Sma Negeri 5 Seluma Monica, Monica; Fitria, Yenni; Amdhi Yul, Fadlul
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.582

Abstract

This research aims to determine the application of the group investigation (GI) learning model to improve learning outcomes in the informatics subject for class XI students at SMA Negeri 5 Seluma. This research method is a descriptive quantitative experiment. The design used is a one group pretest-posttest design. The subjects of this research were 31 students in class XI A of SMA Negeri 5 Seluma. The instrument used is 10 posttest questions and 5 pretest questions. The instrument has been tested for validity and reliability. The analysis techniques used are normality test, homogeneity test and hypothesis test. The results of the pretest with an average of 29 were in the very poor category, while the posttest with an average of 84 was very good and the results of student responses using a questionnaire with a validity test with a percentage of agreement or valid. The results of research using the paired sample test showed that the value was Sig.( 2-tailed) of 0.000 < 0.05 where t count > t table 12.449 > 2.042 so Ho is rejected Ha is accepted which means the group investigation (GI) learning model has a significant effect on the learning outcomes of class XI A students at SMA Negeri 5 Seluma
Decision Support System For Choosing Food Menus In Patients With Gout Using The Simple Additive Weighting (Saw) Method At Harapan Doa Hospital, Bengkulu City Fadhilah, Abyyu; Supardi, Reno; Elfianty, Lena
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.598

Abstract

A Decision Support System is generally defined as a system that is able to provide problem-solving skills and communication skills for semi-structured problems. This research uses the Simple Additive Weighting method made using a scope-based application, namely Visual Studio Code using MySql as the database. The data collection methods carried out in this study are observation, interviews and literature studies. The purpose of this study is to create a decision support system for choosing food menus for gout patients at Harapan Doa Hospital, Bengkulu City, so that in the selection of food menus researchers use the Simple Additive Weighting method with a computerized system. The SAW method is often known as the weighted addition method. The basic concept of the SAW (Simple Additive Weighting) method is to find the weighted sum of the performance ratings on each alternative on all attributes. Application of meto
Implementation Of The Assossian Rule Mining (ARM) Method In The Sales Pattern Of Goods To Consumers In Stores Agung Bengkulu Herrianto, David; Khairil, Khairil; Kanedi, Indra
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.632

Abstract

Management of product sales data at Toko Agung Bengkulu is still done manually. There is no system that helps predict sales patterns for products that are in high demand and the problem that is often faced is the scarcity of supply of products that are in demand at Toko Agung. To make decisions in determining the amount of product inventory that can be adjusted to market demand, Toko Agung does not yet use a system and is still calculating manually. Therefore, this research was carried out with the aim of implementing the Association Rule Mining (ARM) method in grouping sales data at the Agung Store. So you can easily determine and classify high product sales. The system implementation uses the PHP programming language and MySQL database and the method used in this research is the waterfall method. After carrying out the Association Rule Mining (ARM) process at Toko Agung with data testing, the results obtained were the highest level of product sales at Toko Agung Bengkulu. This can be used as a reference by Toko Agung for product inventory for the following month.
Application Of Text Mining In Grouping Thesis Topics Using TF-IDF Method Based On Thesis Abstract Andreswari, Delsy; Suranti, Dewi; Trianggara, Dimas Aulia
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.634

Abstract

UPT (Technical Service Unit) Dehasen University Bengkulu Library documents student theses based on study programmes using the Slims 9 (Bulian) application. One of them is the Informatics Study Programme, Faculty of Computer Science, where there is a specialisation in software engineering and networking that distinguishes one thesis from another. This sometimes makes it difficult for the library to provide information to students who are looking for references, due to the large amount of thesis data that is managed and the difficulty in obtaining information on the percentage of the number of thesis topics from each thesis document. The application of text mining in grouping thesis topics using the TF-IDF Method based on thesis abstracts at the Dehasen University Library Bengkulu can help library staff in grouping theses in more detail for the same topic or theme, help library staff quickly find theses that are relevant to user needs, and can find out information on the percentage of the number of thesis topics from each title and abstract that has been submitted, especially in students of the Informatics Study Program, Faculty of Computer Science. The system has uploaded training data as much as 25 data which is used as the basis for the calculation of the TF-IDF Method. In the TF-IDF Method there are several processes that occur, namely Tokenizing, Filtering, Stemming and the final value of tf-idf. Based on testing that has been done on testing data as much as 3 thesis data, the results show that 2 theses belong to the data mining thesis topic group with a percentage of 66.77% and 1 thesis belongs to the decision support system thesis topic group with a percentage of 33.33%.
Classification Of Brain Tumors Using The VGG19 Method Syah, Maulidya Prastita; Kristanaya, Mirechelin; Nariswari, Naura Ulayya; Azzahra, Melinda Putri; Pratama, Alfan Rizaldy; Saputra, Wahyu S.J.
Jurnal Komputer Indonesia Vol. 3 No. 2 (2024): Desember
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jki.v3i2.677

Abstract

Brain tumor is one of the diseases that has a high mortality rate and requires early detection to increase the chance of cure. In recent years, artificial intelligence-based methods, especially Deep Learning, have shown promising performance in brain tumor classification using Magnetic Resonance Imaging (MRI) images. This study applies the VGG19 architecture, one of the Convolutional Neural Network (CNN) models, to classify brain tumor types based on MRI images. The model is trained with data that has gone through augmentation and contrast enhancement processes to improve image quality before classification. The experimental results show that the VGG19 method is able to achieve high accuracy in brain tumor classification. These findings confirm the effectiveness of VGG19 in automatically detecting brain tumors and can be a supporting solution for medical personnel in performing early diagnosis.

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