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Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Published by Universitas Pendidikan Ganesha
ISSN : 20898673     EISSN : 25484265     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Education Engineering
Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) is a collection of scientific articles in the field of Informatics / ICT Education widely and the field of Information Technology, published and managed by Jurusan Pendidikan Teknik Informatika, Fakultas Teknik dan Kejuruan, Universitas Pendidikan Ganesha. JANAPATI first published in 2012 and will be published three times a year in March, July, and December. This journal is expected to bridge the gap between understanding the latest research Informatika. In addition, this journal can be a place to communicate and enhance cooperation among researchers and practitioners.
Arjuna Subject : -
Articles 14 Documents
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Search results for , issue "Vol. 12 No. 3 (2023)" : 14 Documents clear
Accuracy Analysis of WP, AHP-WP, Entropy-Topsis Methods in Determining Majors Saiful Bahri; Maria Ulfah Siregar
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.57718

Abstract

Determination of majors at SMK AR Rahma is still manual and Excel is only used to find average scores. On the other hand, the number of students is around 140 students, so the majors can cause inaccuracies. In this study, the accuracy of the WP, AHP-WP, and ENTROPY-TOPSIS methods was analyzed in determining the majors of SMK AR Rahma’s students. So that it will be known which method is more accurate in producing student majors. In the process of student majors, data are needed in the form of report cards, academic test scores, majors test scores and health scores. The result is that the majors produced by the AHP-WP method are more accurate than the majors produced by the other two methods, respectively by 70.71%, 64.29%, and 62.86%.
Web-Based Online Exhibition by Implementing Virtual and Augmented Reality to Visualize Architecture Building Design Ketut Nova Wirya Dinata Dinata; I Gede Partha Sindu Sindu; Dessy Seri Wahyuni Wahyuni
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.61609

Abstract

Web-based online exhibition using immersive technology, namely Virtual Reality & Augmented Reality, has a major effect on the efficiency of time, place, and cost in providing visitors with an understanding of building architecture. Interaction in understanding architectural modeling is also assisted by a technology called Avatar Mediated Communication (AMC) which is the scope of interaction with other visitors in a Virtual Environment created by Virtual Reality technology. Technology that is able to support all website-based reality activities is made with the Laravel & Express Js framework (Website), Spoke Mozilla Hubs (Virtual Reality Environment), and Library AR Js (Augmented Reality Marker Based).  The technology is selected, built, and combined in the stages of the Research & Development (R&D) method, the Multimedia Development Life Cycle (MDLC) model in examining the development stages and user responses to web-based Virtual & Augmented Reality development products. The results of the responses obtained are based on 6 categories in the UEQ (User Experience Questionnaire) instrument. The result showed that the three largest categories that give a positive response are stimulation, attractiveness, and novelty. Meanwhile, the three categories below are efficiency, perspicuity, and dependability. This indicates that the online exhibition in the support of immersive visualization is able to increase user curiosity in trying to enter the virtual reality room presented in web-based Virtual & Augmented Reality.
YOLOV4 Deepsort ANN for Traffic Collision Detection Arliyanti Nurdin; Bernadus Seno Aji; Yupit Sudianto; Mardhiyyah Rafrin
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.62923

Abstract

Every collision must be handled right away to prevent further harm, damage, and traffic bottlenecks. Hence, the implementation of a systematic approach for accident detection becomes imperative to expedite response mechanisms. Our proposed accident detection system operates in three stages, encompassing vehicle object detection, multiple object tracking, and vehicle interaction analysis. YOLOv4 is employed for object detection, while DeepSort is utilized to the tracking of multiple vehicle objects. Subsequently, the positional and interactional data of each object within the video frame undergo thorough analysis to identify collisions, utilizing an Artificial Neural Network (ANN). Notably, collisions involving a single vehicle and not affecting other road users are excluded from the scope of this study. The evaluation of our approach reveals that the ANN model achieves a commendable F-Measure of 0.97 for detecting objects without collisions and 0.88 for objects involved in collisions, based on the conducted tests.
Balinese Shadow Puppet Characters Detection In The Wayang Peteng Performance Using The Yolov5 Algorithm I Gusti Ngurah Bagus Putra Asmara; Made Windu Antara Kesiman; Gede Indrawan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.65906

Abstract

To generate greater public interest in Balinese shadow puppet performances, it is crucial to explore novel ways of educating viewers about the characters showcased in the plays, as many individuals may need to become more familiar with them. In Object Detection, an algorithm is called You Only Look Once (YOLO). This research utilizes the YOLOv5 algorithm to detect Balinese shadow puppet characters in the "wayang peteng" performances. The dataset consists of 5040 images, divided into training, validation, and test data, with a ratio of 7:2:1 (This ratio helps in effectively training and evaluating the YOLOv5 model on a diverse set of data). Four YOLO models are trained, each with a different number of epochs (a single iteration of training when the entire dataset has been passed forward and backward through the neural network), resulting in 12 models. All models are tested using the test data images to obtain precision, recall, and mean Average Precision (mAP) metrics. Additionally, three videos measure the average frames processed per second. The research findings reveal that the YOLOv5n model with 200 epochs achieves the best results, with a precision value of 1, recall of 1, mAP@0.5 of 0.995, mAP@0.5-0.95 of 0.985, and 128.20 frames per second.
Date Palm Identification using DenseNet-201 Transfer Learning Method Kusnadi Bin Raman; Agus Subekti
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.65932

Abstract

There are more than 400 types of dates in the world that are similar in size, shape, colour, fruit texture, taste and maturity, making it difficult for people to memorise them. Identification with artificial intelligence can make labelling dates easier. This research proposes the DenseNet-201 transfer learning method with freeze all the pre-trained layers, re-train all the pre-trained layers, and hyperparameter models for date variety identification. The date dataset was collected from the market with a total of 3,300 images of 11 types of dates, including Ajwa, Bam, Golden, Khalas, Khenaizi, Lulu, Mabroum, Medjool, Safawi, Sukari and Tunisian. The purpose of the research is to identify, analyse the test images and compare and recommend the best performance model to identify the type of dates. The experimental results have resulted in the recommendation that the DenseNet-201 method with the hyperparameter model shows the best performance with an accuracy value of 99.39%.
Document Validation for Cooperation Agreement Documents at The Undiksha Cooperation and Public Relations Agency (Badan Kerja Sama dan Kehumasan) using Local Binary Pattern (LBP) and YOLOv5 Methods Komang Jepri Kusuma Jaya; Made Windu Antara Kesiman; I Made Dendi Maysanjaya
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.66070

Abstract

A cooperation agreement document managed by BKK Undiksha is a conventionally managed document. With the implementation of the Kampus Merdeka - Merdeka Belajar curriculum in 2021, the number of incoming cooperation agreement documents has increased rapidly, making the collection of document data much longer and inefficient. Therefore, there is a need for a scheme that can automatically validate collaboration documents. The document validation scheme was developed using the Local Binary Patterns and YOLOv5 methods. The data used in the development is primary data from BKK Undiksha in 2021, where two agencies collaborate. The development result is the document validation model collaboration using the Local Binary Pattern and YOLOv5 methods with the best accuracy results of 95.36%, and the ability of the model to detect the number of seal, stamp and signature components is 90.73%.
Development of Interactive Media on The Root Material of Numerical Nonlinear Equations Using Geogebra and Ethercalc Cahya Kamila Maulida; R. Ati Sukmawati; Mitra Pramita
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.67125

Abstract

This study aims to develop web-based interactive learning media by utilizing geogebra and ethercalc on the topic of determining the roots of non-linear equations numerically and evaluating their validity through material and media validity tests. The development method used is Research and Development (R&D) with the limited ADDIE development model. The data was collected through material and media validation sheets filled out by two experts. The results of the data analysis show that interactive web-based learning media for the topic of roots of nonlinear equations are developed with technologies such as HTML, CSS, Bootstrap, JavaScript, JQuery, Geogebra, Ethercalc, MathJax, Firebase, Figma, Adobe Illustrator, Canva, CapCut, and Netlify. The results of the material validity reached 84% with a high level of validity, while the media validity was 82% with a fairly high level of validity. There are several suggestions from media and material validators, namely improving the instructions for carrying out exercises and evaluations. With these results, after being repaired the learning media is ready to be tested.
Improving the Performance of the General Course Scheduling System at UPN Veteran Jawa Timur through the Application of the IWCFPSO Algorithm Made Hanindia Prami Swari; Chrystia Aji Putra; I Putu Susila Handika; Dwi Wahyuningtyas
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.68128

Abstract

Algorithm selection is the main key in producing a system, especially an artificial intelligence-based system, for example, a course scheduling system that involves many constraints in producing an optimal schedule. This research develops a scheduling system using the ICWFPSO algorithm which is a development from previous research, namely the development of a scheduling system using the MIPSO algorithm. The use of inertia weight in the MIPSO algorithm which is used as a scheduling algorithm in previous research can be optimized by using a combination of inertia weight and constriction factor. Scheduling system development is carried out using the waterfall method with research steps namely problem and needs analysis, data collection and literature study, system design, system implementation, and ends with testing the performance of the algorithms that are applied to the scheduling system that is built. Based on the tests carried out, it can be concluded that the ICWFPSO algorithm provides 2 times better performance compared to the MIPSO algorithm in terms of optimal schedule generation time. Meanwhile, tests carried out on CPU and RAM usage showed that there was no significant impact on these two parameters through the implementation of MIPSO and ICWFPSO in the course scheduling system created. Keywords: best scheduling, ICWFPSO, number of iterations
Application of Lung Diseases Detection based on CSLNet Panji Bintoro; Zulkifli Zulkifli; Fitriana Fitriana; Sukarni Sukarni; Abdullah Abdullah
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.68815

Abstract

Lung diseases caused by fungal or bacterial infections can lead to inflammation in lung and even death when not detected early. A standard method for diagnosing lung diseases is the use of chest X-ray, which require careful examination of X-ray images by a radiology expert. Therefore, this study proposes several new architecture models, namely CSLNet, to classify chest X-ray images for diagnosing whether patients suffer from COVID-19, viral pneumonia, bacterial pneumonia, tuberculosis, and normal. The experimental results show that the model has an 0.99 average Accuracy, 0.98 Precision, 0.98 Recall, and 0.98 f1-score. Meanwhile, the Receiver Operating Characteristic (ROC) for bacterial pneumonia, COVID-19, normal, tuberculosis, and viral pneumonia are 0.97, 0.99, 0.99, 0.94, and 0.97 respectively. This study is based on a deep learning with a new model, CSLNet, which can work well on the dataset of chest X-ray images used for diagnosing lung diseases.
Usability Testing on The Mobile Gras (Green Trash System) Application Using The Usability Scale System Method I Gusti Made Ngurah Desnanjaya; I Kadek Budi Sandika; Ida Bagus Gede Sarasvananda; Putu Wirayudi Aditama; I Komang Arya Ganda Wiguna
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 3 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i3.68930

Abstract

This study focuses on the GRAS (Green Trash System) mobile application, developed under the KEDAIREKA program to enhance waste management efficiency. The application is an integral part of the GRAS smart waste system, designed to facilitate real-time monitoring and reporting of waste capacity issues. The primary objective is to streamline waste sorting processes and educate users, particularly students, about sustainable waste management practices. The system features innovative sensor technology that provides audio feedback for correctly sorted waste, thus reinforcing correct behaviors. To assess the application's effectiveness, we conducted a usability test using the System Usability Scale (SUS) method. Data were collected through questionnaires to evaluate the application's ease of use, efficiency, and user satisfaction. The results indicated a high level of usability, with most users experiencing seamless interaction with the application, affirming its potential as a tool for effective waste management education and practice.

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