cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota denpasar,
Bali
INDONESIA
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 646 Documents
 55   56   57   58   59 
Comparative Analysis of CNN Methods for Periapical Radiograph Classification Sumantara, I Gusti Lanang Trisna; Kesiman, Made Windu Antara; Sunarya, I Made Gede
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.71664

Abstract

Periapical radiographs are commonly used by dentists to diagnose dental problems and overall dental health conditions. The varying abilities of dentists to diagnose may be limited by their visual acuity and individual skills. To address this issue, there is a need for an application capable of computationally recognizing and classifying periapical radiographs. The commonly used computational method for image processing, specifically image recognition, is the Convolutional Neural Network (CNN) method. This study aims to create an application that can classify periapical radiographs and analyze the capabilities of the Convolutional Neural Network (CNN) method in this classification process. In general, periapical classification is divided into five types: Primary Endo with Secondary Perio, Primary Endodontic Lesion, Primary Perio with Secondary Endo, Primary Periodontal Lesion, and True Combined Lesions. The periapical radiograph classification process was tested using four CNN models: ResNet50v2, EfficientNetB1, MobileNet, and Shalow CNN. The evaluation of the CNN method utilized a confusion matrix-based technique to generate accuracy, precision, recall, F1-score and Weighted Average F1-score values. Based on the evaluation results, the highest accuracy value was achieved by EfficientNetB1 with 82%, followed by ResNet50v2 with 76%, MobileNet with 75%, and Shallow CNN with 71%.
Pneumonia Diagnosis Through Deep Learning: ResNet50v2 Model Implementation Yufis Azhar; Zamah Sari; Wahyu Priyo Wicaksono
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.72068

Abstract

Pneumonia is a significant global health concern, particularly affecting young children and the elderly. It is a lung infection caused by bacteria, viruses, fungi, or parasites, leading to the alveoli filling with pus or fluid. This study addresses the challenge of accurately diagnosing pneumonia using chest X-ray images, a process traditionally dependent on the expertise of radiologists. The reliance on radiologists results in lengthy diagnosis times and high costs, particularly in regions with a shortage of medical professionals. This research presents a deep-learning approach to automate the classification of pneumonia using the ResNet50v2 model, which has been pre-trained on the ImageNet dataset. The dataset used in this study, obtained from the Guangzhou Women and Children’s Medical Center, comprises 5,856 images, with 1,583 normal and 4,273 pneumonia cases. The images were preprocessed and augmented to enhance the model's robustness. The proposed model achieved an accuracy of 94%, demonstrating its potential in clinical settings to assist in the rapid and reliable diagnosis of pneumonia. This study contributes to the growing body of research in medical image analysis by employing a pre-trained ResNet50v2 model. It highlights the importance of leveraging advanced machine-learning techniques to improve diagnostic accuracy and efficiency.
Classification of Dog Emotions Using Convolutional Neural Network Method Hermawan, Slamet; Siregar, Amril Mutoi; Faisal, Sutan; Mudzakir, Tohirin Al
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.74340

Abstract

The utilization of neural networks in dog emotion classification has great potential to improve the understanding of pet emotions. The goal is to develop a dog emotion classification system. This is important due to the lack of public ability to recognize and understand dog emotions. Neural networks able to create learning models can be used for decision-making, thus helping to reduce the risk of dangerous dog attacks. CNN itself is part of neural networks, where the CNN model has a higher accuracy rate of 74.75% compared to ResNet 65.10% and VGG 68.67%. Modeling using ROC-AUC shows the model's ability to distinguish emotion classes well. Angry has the highest AUC of 0.97, happy 0.93 and sad 0.96. While relaxed has the lowest AUC of 0.92. Classification report results show model has the highest precision and F1-Score values in angry class, while the highest recall value is in sad class.
The Effectiveness of Augmented Reality Technology in Mathematics: A Case Study of SMP Al Azhar Plus Bogor Siti, Ragil Siti Sholehah; Nuur Wachid Abdul Majid
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.74582

Abstract

The field of mathematics education is rapidly advancing, particularly with the introduction of augmented reality (AR) technology as one of the tools used as an innovative learning medium. This research seeks to assess how the incorporation of AR influences students' grasp of mathematical concepts. This study is an experimental quantitative research using the experimental design method, with a population of 37 students from class IX of SMP Al Azhar Plus Bogor. The researcher obtained 30 students as samples based on purposive sampling technique, which were then divided into 2 groups: 15 students as the experimental group and 15 students as the control group. The experimental group underwent mathematics learning utilizing AR technology with 3D teaching materials that were prepared and accessible via smartphones through a barcode, covering topics such as congruent, similar, and spatial figures. Meanwhile, the control group followed conventional teaching methods using books as teaching materials with the same subject coverage. The study's results emphasize the substantial improvement in students' understanding of mathematical concepts through the effective utilization of AR. This improvement encompasses students' abilities to solve mathematical problems, retain conceptual memory, and actively participate in the learning process. Based on the statistical test results conducted, the experimental group obtained an average of 68.4153 or 68%, which falls into the category of moderately effective, while the control group obtained an average of 16.1508 or 16%, classified as ineffective. The Independent Sample Test yielded a Sig. (2-tailed) value of 0.000 < 0.05, indicating a significant difference in effectiveness between the experimental and control groups. Further data analysis indicates that the learning experience through AR not only provides a better understanding but also offers additional motivation to students, thereby increasing their interest in the subject of mathematics. Moreover, the study observes that a well-integrated instructional design within the curriculum, considering the context of AR usage, can contribute significantly to improved learning outcomes. The consequences of these discoveries strengthen the perspective that augmented reality (AR) is not just a successful educational instrument but can also offer a pleasurable learning encounter within the realm of mathematics education. The outcomes of this study play a substantial role in advancing more interactive approaches to teaching mathematics, with a specific emphasis on enhancing students' conceptual understanding. It is hoped that these findings can serve as a foundation for the implementation of AR in educational curricula as a strategic effort to enhance the quality of mathematics education and enrich students' learning experiences.
Analyzing Technology Acceptance Model for Lombok Traditional Food Restaurant in GoFood Application Bimantari, Joselina Rizki; Alamsyah, Noor; Murpratiwi, Santi Ika
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.74816

Abstract

During the COVID-19 pandemic, Lombok Island, known for its stunning natural beauty, faced significant challenges in its culinary industry, resulting in a drastic decline in revenue and tourist visits. Embracing technological solutions, particularly through food delivery apps like GoFood, became pivotal in overcoming these obstacles. These apps not only sustained local restaurants during the pandemic but also preserved Lombok's distinctive cuisine, such as Sate Rembiga. Beyond pandemic resilience, GoFood played a crucial role in balancing global technological advancements and supporting daily activities. The aim of this research is to employ the Technology Acceptance Model (TAM) using Partial Least Square (PLS) approach to analyze the adoption of the GoFood application among owners of traditional Lombok cuisine restaurants, particularly focusing on the impact of the COVID-19 pandemic. This research method is designed to assess the extent of acceptance and adoption of GoFood among these restaurant owners during the pandemic, identifying key factors influencing their technological acceptance. The results of this research offer insights into the dynamics of technology acceptance within Lombok's culinary sector amid external changes such as the pandemic. In conclusion, understanding these dynamics can inform strategies to enhance the utilization of food delivery apps in traditional culinary businesses, ensuring resilience and adaptation in the face of unforeseen challenges.
Improving Image Retrieval Performance with SCS and MCS Clustering Techniques Fikri, Ulul; Prakoso, Rahmat; Azhar, Yufis
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.75643

Abstract

This paper presents two methods, Single Cluster Search (SCS) and Multiple Cluster Search (MCS), aimed at enhancing image retrieval performance on the Corel1k, Corel5k, and Corel10k datasets, which has a wide variation of images. The Multi Texton Co-Occurrence Descriptor (MTCD) method is used for feature extraction, and the K-Medoids and DBSCAN methods are used for dataset clustering. The clusters are then ranked based on the distance of their medoids to the query image. The most relevant images are retrieved from the highest-ranking clusters. SCS selects the cluster with the highest ranking as the search area and expands the search area to the next ranking cluster if the number of images is less than 6, which is the desired number of retrieval results. MCS merges several clusters with the highest ranking and combines clusters as the search area. Both methods are evaluated using several metrics, such as AP, MRR, and retrieval time. The results are also compared with the original method, which does not use clustering (the query image and the dataset are only extracted with MTCD, and their distance is calculated). The findings indicate that both methods improve the retrieval time. In Corel1k, the SCS method reduces the time complexity by 0.001s, while the MCS method, although not surpassing the original method, still shows potential. In Corel5k, both methods reduce the time complexity by 0.052s in the SCS method and 0.015s in the MCS method. In Corel10k, both methods reduce the time complexity by 0.122s in the SCS method and 0.058s in the MCS method, compared to the original method. These results have practical implications for improving image retrieval efficiency. The paper discusses the reasons behind these results and suggests possible directions for future research.
IoT-Based Humidity Control System for Electrospinning Hikamiah, Luluk Arifatul; Ariyanto, Dewa Pascal; Widayani, Della Astri; Nugroho, Panji Setyo; Amaratirta, Jasmine Cupid; Harjunowibowo, Dewanto; Rezeki, Yulianto Agung
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.75896

Abstract

In recent years, electrospinning has become the most common and most widely used nanofiber manufacturing method. One parameter affecting the manufacturing process is the humidity parameter, which affects the morphology. The control tools that have been developed have not been equipped with a remote control and monitoring system. This research aims to develop a humidity control system that can be controlled and monitored remotely and is equipped with data recapitulation. This research used methods from literature studies on humidity control systems, manufacture and assembly of hardware and software, calibration, and performance tests. A humidity control device is produced using a NodeMCU microcontroller connected to the IoT-based Blynk application. This can be controlled and monitored manually with an LCD and Keypad or by using a handphone through the Blynk application, and the humidity value can be recapitulated with Google Sheets in real-time. The sensor used for reading this humidity value is a DHT 22 sensor which has an accuracy value of 99.72% and a precision of 98.81% for 45%-95% humidity. This IoT-based humidity control system device can automate the process of controlling, monitoring, and recapitulating humidity data in real-time.
Analyzing Hotel Owners Acceptance of Tiket.com Using Technology Acceptance Model Baiq Dwi Zulianti Kurrotaa'yun; Noor Alamsyah; Helmina Andriani; Santi Ika Murpratiwi
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.76188

Abstract

Lombok, a captivating island in West Nusa Tenggara, faces tourism challenges due to the COVID-19 pandemic, causing a decline in visits and revenue. Senggigi, known for its picturesque beaches, experienced a drastic drop in hotel occupancy. Focusing on post-pandemic recovery, the aim of this research is to investigate the adoption of Tiket.com applications by hotel owners in Senggigi, utilizing the Technology Acceptance Model (TAM) with a Partial Least Squares (PLS) approach. This research method is using a quantitative methodology, the study involves 50 respondents from 20 hotels, distributing questionnaires to explore perceptions of Online Travel Agent technology adoption based on TAM variables. The result of this research is the Partial Least Squares analysis indicates that perceived ease of use significantly influences perceived usefulness, emphasizing the importance of a user-friendly platform. While perceived usefulness alone may not directly impact usage intention, positive attitudes toward the system play a crucial role. The study recommends collaborative efforts between Tiket.com service providers and Senggigi hotel owners to enhance system adjustments, aligning with user needs and expectations. This research contributes valuable insights into technology's role in post-pandemic tourism recovery, providing a nuanced understanding of factors influencing the acceptance of Tiket.com within the Senggigi hospitality sector.
Analysis of User Complaints for Telecommunication Brands on X (Twitter) using IndoBERT and Deep Learning Hakim, Valianda Farradillah; Riana, Dwiza
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.76497

Abstract

Tweeting on different official accounts is what users of Twitter (X) do most frequently. These tweets ranging from compliments to critiques. One of the official accounts that gets a lot of tweets from its customers is Telkomsel, an Indonesian telecom company. This study aims to find the maximum accuracy that can be obtained by combining CNN and Bi-LSTM algorithms with IndoBERT embeddings. A considerable accuracy level above 90% is demonstrated by the study, with CNN obtaining the greatest accuracy of 99% at a learning rate of 6*10^-5, along with scores of 98%, 97%, and 97% for precision, recall, and F1 correspondingly.
Electronic Payment Threats and Security: A Systematic Literature Review Amelia Citra Dewi; Erik Iman Heri Ujianto; Rianto, Rianto
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 2 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i2.76635

Abstract

In the emerging field of electronic payment systems, security challenges have become a major concern. This research addresses a comprehensive understanding of mitigation strategies for these threats. Through systematic literature analysis, we investigated the security vulnerabilities in electronic payment processes and discovered the latest blockchain technology as a strengthened security framework. Our findings reveal that while encryption and authentication provide the foundation of security, the integration of blockchain technology offers an unprecedented level of transaction integrity and transparency. This research not only highlights the urgent need for electronic payment security measures but also highlights the potential of blockchain and machine learning as transformative solutions. The implications of our research indicate an important shift in payment systems towards more secure and resilient electronic systems, paving the way for future research to explore the integration of cutting-edge technologies in combating ever-evolving cyber threats by leveraging blockchain technology, quantum computing and machine learning.

Page 57 of 65 | Total Record : 646

 55   56   57   58   59 

Filter by Year

2012 2025


Reset
Filter By Issues
All Issue Vol. 14 No. 2 (2025) Vol. 14 No. 1 (2025) Vol. 13 No. 3 (2024) Vol. 13 No. 2 (2024) Vol. 13 No. 1 (2024) Vol. 12 No. 3 (2023) Vol. 12 No. 2 (2023) Vol. 12 No. 1 (2023) Vol. 11 No. 3 (2022) Vol. 11 No. 2 (2022) Vol. 11 No. 1 (2022) Vol 11, No 1 (2022) Vol. 10 No. 3 (2021) Vol. 10 No. 2 (2021) Vol 10, No 2 (2021) Vol 10, No 1 (2021) Vol. 10 No. 1 (2021) Vol 9, No 3 (2020) Vol. 9 No. 3 (2020) Vol 9, No 2 (2020) Vol. 9 No. 2 (2020) Vol. 9 No. 1 (2020) Vol 9, No 1 (2020) Vol. 8 No. 3 (2019) Vol 8, No 3 (2019) Vol 8, No 2 (2019) Vol. 8 No. 2 (2019) Vol. 8 No. 1 (2019) Vol 8, No 1 (2019) Vol 8, No 1 (2019) Vol 7, No 3 (2018) Vol. 7 No. 3 (2018) Vol 7, No 3 (2018) Vol. 7 No. 2 (2018) Vol 7, No 2 (2018) Vol. 7 No. 1 (2018) Vol 7, No 1 (2018) Vol 7, No 1 (2018) Vol 6, No 3 (2017) Vol 6, No 3 (2017) Vol. 6 No. 3 (2017) Vol 6, No 2 (2017) Vol. 6 No. 2 (2017) Vol 6, No 2 (2017) Vol. 6 No. 1 (2017) Vol 6, No 1 (2017) Vol 6, No 1 (2017) Vol 5, No 3 (2016) Vol. 5 No. 3 (2016) Vol 5, No 3 (2016) Vol. 5 No. 2 (2016) Vol 5, No 2 (2016) Vol 5, No 2 (2016) Vol 5, No 1 (2016) Vol 5, No 1 (2016) Vol. 5 No. 1 (2016) Vol 4, No 3 (2015) Vol. 4 No. 3 (2015) Vol 4, No 3 (2015) Vol 4, No 2 (2015) Vol 4, No 2 (2015) Vol. 4 No. 2 (2015) Vol 4, No 1 (2015) Vol. 4 No. 1 (2015) Vol 4, No 1 (2015) Vol 3, No 3 (2014) Vol. 3 No. 3 (2014) Vol 3, No 3 (2014) Vol. 3 No. 2 (2014) Vol 3, No 2 (2014) Vol 3, No 2 (2014) Vol 3, No 1 (2014) Vol. 3 No. 1 (2014) Vol 3, No 1 (2014) Vol 2, No 3 (2013) Vol. 2 No. 3 (2013) Vol 2, No 3 (2013) Vol. 2 No. 2 (2013) Vol 2, No 2 (2013) Vol 2, No 2 (2013) Vol 2, No 1 (2013) Vol 2, No 1 (2013) Vol. 2 No. 1 (2013) Vol 1, No 3 (2012) Vol 1, No 3 (2012) Vol. 1 No. 3 (2012) Vol. 1 No. 2 (2012) Vol 1, No 2 (2012) Vol 1, No 2 (2012) Vol 1, No 1 (2012) Vol 1, No 1 (2012) Vol. 1 No. 1 (2012) More Issue