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 16 Documents
 1   2 
Search results for , issue "Vol. 14 No. 1 (2025)" : 16 Documents clear
Optimizing Sentiment Analysis of Electric Vehicles Through Oversampling Techniques on YouTube Comments Lapendy, Jessica Crisfin; Resky, Andi Aulia Cahyana; Tenriola, Andi; Surianto, Dewi Fatmarani; Sidin, Udin Sidik
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.88205

Abstract

Air pollution from motorized fuel vehicles causes adverse impacts on the environment and human health, driving the need for more sustainable alternatives such as electric vehicles. However, the transition to electric vehicles is often met with mixed responses from the public, reflected by sentiments that are split between positive and negative. This research investigates such sentiments through analyzing comments on the YouTube platform, which are classified using two algorithms, SVM and Naïve Bayes, and three oversampling techniques: Random Oversampling, SMOTE, and ADASYN. A comparative evaluation is conducted to determine the most effective algorithm and oversampling strategy for handling imbalanced sentiment data, where negative comments dominate. Initial experiments showed that Naïve Bayes with SMOTE achieved the best result among baseline models, with 64% accuracy. However, traditional oversampling methods alone were not sufficient to significantly improve classification quality. To address this, the study proposes a hybrid method that combines Easy Data Augmentation (EDA), specifically Synonym Replacement (SR), with oversampling techniques. The proposed method substantially improved performance. Naïve Bayes combined with SR and SMOTE or Random Oversampling achieved 88% accuracy, with F1-scores of 0.84–0.85 for the positive class. The best result was obtained using SVM with SR and Random Oversampling, reaching 97% accuracy and F1-scores of 0.97 (negative) and 0.96 (positive). These findings demonstrate the effectiveness of combining augmentation and oversampling in improving sentiment classification and provide insights for stakeholders in promoting EV adoption.
Virtual Smart School: A Blended Learning Approach for Schools in Papua’s 3T Regions Sampebua, Mingsep Rante; Supiyanto, Supiyanto; Kmurawak, Remuz Maurenz
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.90329

Abstract

Traditional classroom-based teaching methods are still used in schools, particularly in Papua’s 3T (frontier, outermost, undeveloped) areas. This highly relies on the teacher-centered method and limits the completion of the curriculum due to time constraints imposed by the schedule. This research aims to design a web-based virtual smart school as a blended learning solution for schools in Papua’s 3T areas. The virtual smart school learning media application is developed using the ADDIE model, a five-step process encompassing analysis, design, development, implementation, and evaluation. This research results in a virtual smart school application that can increase student motivation, enable independent learning, evaluate student learning progress, provide quick access to learning materials, and facilitate interactions between teachers and students at any time or location. The research concludes that virtual smart schools can become a blended learning solution to improve the quality and equity of education in underdeveloped areas of Papua.
Service Management Audit of SIKUAT Using The ITIL 4 Framework Darmawan, I Gede Hadi; Gunantara, Nyoman; Sudarma, Made
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.91093

Abstract

The Balinese Traditional Village of Financial Information Management System (SIKUAT) is a web-based information technology service used to manage the financial administration of 1,493 Traditional Villages in Bali. To ensure service quality, user convenience, and improved service performance aligned with user needs, it is necessary to conduct a service management audit on SIKUAT. This research focuses on auditing the service management of SIKUAT by adopting the ITIL 4 framework, particularly within the domains of continual improvement, service continuity management, and infrastructure and platform management. The assessment was carried out using the Capability Maturity Model (CMM) method through interviews and document analysis. The results of the audit indicate that the maturity level of the SIKUAT service is at level 3 (defined) with an average score of 3,86, while the capability level is at level 2 (managed). The continual improvement domain has the highest maturity level, reaching level 4, which indicates that the improvement processes are relatively well-directed. However, the service continuity management domain and the infrastructure and platform management domain still require serious attention to improve their maturity levels, which are currently still at level 3. This condition indicates the need for further improvements in service sustainability and infrastructure management. Based on the audit results, it is recommended to establish a comprehensive infrastructure maintenance policy, define standards for incident handling, and conduct regular evaluations of features and data security. The implementation of these recommendations is expected to enhance the efficiency and sustainability of the SIKUAT service, thereby supporting more transparent and accountable financial governance in Traditional Villages. In addition, this study may serve as a reference for the Provincial Government of Bali in improving the SIKUAT service.
The Influence of Online Visual Merchandising and Customized Cross-Selling on Traveloka Mobile Apps Intention to Reuse: With Mediation of Visual Cues and Dynamic Personalization Ariawan, Nathania Putri; Ariadi, Gede
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.91443

Abstract

This study examined the impact of Online Visual Merchandising (OVM) and Customized Cross Selling (CCS) on the Intention to Reuse (ItR) Traveloka’s mobile app, mediated by Visual Cues (VC) and Dynamic Personalization (DP). With the increasing competition in the online travel industry and the need for platforms to retain users, understanding the factors that drive repurchase intentions is crucial. A survey of 135 app users aged 25-40 was conducted, and data were analyzed using PLS-SEM. Results indicate that while OVM alone did not significantly affect ItR, CCS had a positive impact. VC and DP significantly mediated the relationships between OVM, CCS, and ItR. The findings suggest that aesthetic elements alone are insufficient for driving repetitive behavior; instead, a strategic integration of visual, personalized, and cross selling strategies is crucial. The study supports nudge theory and offers practical insights for optimizing digital commerce applications to enhance repurchase intentions.
Enhancing Diesel Backup Power Forecasting With LSTM, GRU, and Autoencoder-based Input Encoding Dewi, Ni Putu Novita Puspa; Leu, Yungho; Mustofa, Khabib; Riasetiawan, Mardhani
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.92079

Abstract

Ensuring a reliable electricity supply is crucial for Indonesia's development. This study applies deep learning to forecast diesel backup power output. One challenge in such predictions is balancing the input sequence length and the number of features to avoid overly long input sequences, which may degrade model performance. To address this, we utilized an autoencoder to compress the input sequence, improving prediction accuracy. Additionally, given the time-consuming nature of hyper-parameter optimization in deep learning, we employed Bayesian optimization to streamline the process and achieve optimal hyper-parameter settings.The study compares a General Regression Neural Network (GRNN) optimized by FOA with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models optimized by Gaussian Process (GP). Results show that LSTM and GRU with encoded inputs outperform their non-encoded counterparts. The GRU, combined with an autoencoder and Bayesian-optimized hyper-parameters, achieves the lowest prediction error, demonstrating superior forecasting capability.The dataset, obtained from evaluated feeders in Kapuas District, Central Kalimantan, covers hourly power generation and distribution from October 2017 to September 2018. Data was split into 11 months for training and 1 month for testing, with the training set further divided into 70% training and 30% validation. The best performing model achieved RMSE and MAE values of 27.5824 and 14.9804, respectively. Future research may explore further optimization, feature selection techniques, and extended dataset variations.
Analyzing User Experience and Satisfaction in the B-Block Game-Based Assessment Husniah, Lailatul; Kholimi, Ali Sofyan; Yuhana, Umi Laili; Yuniarno, Eko Mulyanto; Purnomo, Mauridhi Hery
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 1 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i1.92784

Abstract

Game-based assessment (GBA) has developed as an innovative education method, including learning basic arithmetic operations. This study aims to analyze user experience and satisfaction using B-Block, an assessment-based game for basic arithmetic operations. The study involved 94 junior high school students with an age distribution of 12-13 years old and varying levels of gaming experience. The research used descriptive statistical analysis, validity and reliability test, Pearson correlation test, and multiple linear regression to identify factors influencing user satisfaction and continuance usage intention. The analysis showed that B-Block has good usability and educational benefits, with user satisfaction being the most dominant aspect. Validity and reliability tests confirmed that most variables were valid and reliable (Cronbach's Alpha > 0.7), except Errors, which had lower reliability (α = 0.632). Pearson correlation shows that Perceived Usefulness has a strong relationship with satisfaction (r = 0.784), while user satisfaction contributes significantly to continuance intention (r = 0.694). Multiple linear regression revealed that perceived usability and perceived usefulness were the main factors influencing user satisfaction, while confirmation and satisfaction had the most effect on continuance intention. The findings confirm that the gameplay's usability and perceived usefulness are key in increasing user satisfaction while matching the experience with initial expectations, and user satisfaction contributes to continued use.

Page 2 of 2 | Total Record : 16

 1   2 

Filter by Year

2025 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