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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 646 Documents
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Evaluating the Acceptance of Blockchain Technology in the Supply Chain of Lombok Traditional Weaving Industry Using Extended Technology Acceptance Model Kurrotaa'yun, Baiq Dwi Zulianti; Wijayanto, Heri; Widiartha, Ida Bagus Ketut; Afwani, Royana; Agitha, Nadiyasari; Murpratiwi, Santi Ika
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.92595

Abstract

Traditional Sasak weaving in Lombok faces major challenges such as counterfeit products, lack of supply chain transparency, and price disparities, all of which undermine sustainability and consumer trust. Blockchain technology offers potential solutions by improving transparency, security, and data integrity. However, adoption among weaving MSMEs (Micro, Small, and Medium Enterprises) remains limited due to low digital literacy and limited awareness of blockchain’s benefits. This study evaluates the acceptance of blockchain technology among traditional weaving MSMEs in Lombok using an Extended Technology Acceptance Model (TAM). Beyond the standard constructs Perceived Usefulness (PU) and Perceived Ease of Use (PEU) the model integrates Perceived Trust (PT), Perceived Privacy (PP), Perceived Security (PS), Social Influence (SI), and Customer Satisfaction (CS). A quantitative survey was conducted with 50 MSME actors in Sukarara, Lombok. Findings show that PEU significantly influences PU (path coefficient = 0.798; t = 11.520; p < 0.001), while Attitude Toward Using (ATU) strongly affects Behavioral Intention to Use (BITU) (path coefficient = 0.775; t = 5.147; p < 0.001). Both PS and PP significantly impact PT, with path coefficients of 0.410 and 0.380, respectively. Conversely, SI and CS have no significant effect on BITU. The model demonstrates strong explanatory power, with R² values of 81.7% for ATU and 80.7% for BITU. These results highlight that technical factors particularly usability and trust are more influential than social factors in determining blockchain adoption. The study recommends simplifying technology, improving digital literacy, and ensuring policy support to drive wider adoption among traditional MSMEs.
IoT-Based Automatic Control and Monitoring System for Reverse Osmosis Storage Tanks Wijaya, Merta; I Putu Trisna Hady Permana S.; Putra, Made Adi Paramartha
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.92943

Abstract

Reverse Osmosis (RO) is a system designed to purify drinking water, making it safe for consumption. This system uses a semipermeable membrane filter to carry out the purification process. The advantage of the RO system is its ability to produce cleaner water. However, the purified water must be stored first due to the relatively slow production process of RO. Tirta Utama Drinking Water Depot (DAMIU) is one of the depots that provides RO water, but the RO water supply at Tirta Utama DAMIU often runs out due to poor management. This research aims to develop a water storage management tool to be integrated with the RO system at Tirta Utama DAMIU, with the goal of assisting the depot owner in managing water storage. This tool is designed using an ESP32, equipped with ultrasonic sensors to detect water levels, relays to control water pumps, an LCD to display water level information, and a buzzer as an alarm. The tool also has the capability to connect to the Blynk app, allowing the depot owner to monitor water levels via smartphone. To enhance decision-making in water level control, the system incorporates fuzzy logic as a method to interpret sensor readings and control the RO machine and pumps more intelligently, especially under uncertain or fluctuating water conditions.
Examining the Role of Augmented Reality Interactivity on Student Performance: Mediating Effects of Visuospatial and Auditory Knowledge Wahyuni, Dessy Seri; Koehler, Thomas; Saari, Erni Marlina; Sindu, I Gede Partha
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.93234

Abstract

Augmented Reality (AR) has been widely used to support collaborative learning and provide students with facilities to complete tasks during the learning process. This study examines the impact of Augmented Reality on the interactivity, including controllability, responsiveness, and playfulness, of student performance through visuospatial and auditory Knowledge concerning Cognitive Load Theory (CLT). These elements must be processed simultaneously (both visually and audibly), resulting in a higher cognitive load. The CLT posits that learning is optimized when intrinsic, extraneous, and germane cognitive loads are balanced. This study employs the PLS-SEM approach to examine the conceptual model, as completed by 94 students in a vocational high school in Gianyar Regency who filled out the questionnaire. The findings of this study are novel, with visuospatial and auditory Knowledge that mediates AR interactivity on student performance in vocational high schools in Bali. These two forms of knowledge act as cognitive bridges, combining visuospatial and auditory knowledge between interactivity and achievement. When these modalities are well-integrated, they distribute cognitive load across channels (dual-channel processing), enhancing student performance. Antecedents of perceived AR interactivity, such as controllability and responsiveness, have a more significant influence on the mediator variables than playfulness, which enhances and enhances students’ achievement in vocational high schools. Visuospatial Knowledge helps learners mentally simulate spatial relationships, which is crucial in tasks like shaping ring components, whereas auditory Knowledge supports sequencing and procedural memory. The interactivity of AR can boost engagement and motivation, which translates into enhanced student performance, especially in vocational tasks like crafting a ring, which require precision, tactile feedback, and procedural mastery.
Enhancing Renewable Energy Utilization in Remote Areas Through an Accessible IoT Monitoring Framework: A Case Study on Tidung Island Dwiyaniti, Murie; Isdawimah, Isdawimah; Nadhiroh, Nuha; Setiana, Hatib; Muchlishah; Monika, Dezetty; Wardhani, Rika Novita; Tahazen, Tahazen
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.93685

Abstract

This research addresses the lack of an accurate and efficient monitoring system for renewable energy utilization in Tidung Island. Despite its high solar and wind energy potential, the absence of real-time environmental data hinders optimal energy management. Existing IoT-based monitoring systems are costly and complex, making them unsuitable for remote areas. This research integrates Blynk IoT and Google Sheets database for real-time, cost-effective, and easily accessible data storage. This system enables real-time data acquisition to support efficient energy management and environmental monitoring in remote areas. Testing results show that the Telkomsel 4G modem provides a more stable connection with lower latency and minimal packet loss. Temperature remains between 25–30°C, while humidity fluctuates up to 100% at night. Wind speed is classified as low to moderate (1.0–6.1 m/s), and CO₂ levels range from 400–600 PPM, remaining within safe limits. These findings suggest the need for improved energy storage, system resilience against environmental changes, and adaptive energy management strategies for optimal hybrid renewable energy utilization.
Aspect-based Sentiment Analysis on Beauty Product Reviews using BERT and Long Short-Term Memory Al Aufar, Arya Prima; Romadhony, Ade
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.94392

Abstract

In e-commerce, product reviews play a crucial role in influencing potential buyers by sharing user experiences and assessing product quality. This is especially important for beauty products, where poor quality can lead to physical harm. Reviews also help increase consumer interest in purchasing. Previous research has shown that product reviews differ in various aspects and content, making it challenging for consumers to quickly analyze them from multiple perspectives. This study applies aspect-based sentiment analysis to beauty product reviews on the Female Daily Network using a combination of BERT and LSTM. The goal is to provide more precise sentiment classification across different aspects, aiding consumers in selecting the best products. Several evaluation scenarios were conducted to assess different aspects of product reviews, including price, packaging, staying power, moisture, and aroma. The F-1 score revealed that the price aspect achieved the highest performance, reaching 100% in a 90%:10% test data scenario. However, the aroma aspect proved the most challenging to analyze, indicating that the model struggles to capture features related to scent effectively under the given evaluation setup.
Graph-Structured Network Traffic Modelling for Anomaly-Based Intrusion Detection Pratomo, Baskoro Adi; Haykal, Muhammad Farhan; Studiawan, Hudan; Purwitasari, Diana
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.94959

Abstract

The increasing complexity of cyber threats demands more advanced network intrusion detection systems (NIDS) capable of identifying both known and emerging attack patterns. In this study, we propose a graph-based anomaly detection approach for network intrusion detection, where network traffic is modeled as graph structures capturing both attribute and topological information. Five graph anomaly detection models—DOMINANT, OCGNN, AnomalyDAE, GAE, and CONAD—are implemented and evaluated on the UNSW-NB15 dataset. The constructed graphs use info_message attributes as nodes, with edges representing sequential traffic relationships. Experimental results show that the Graph Autoencoder (GAE) and Dual Autoencoder (AnomalyDAE) models outperform other methods, achieving F1-scores of 0.8728 and 0.7939, respectively. These findings demonstrate that reconstruction-based approaches effectively capture complex network behaviors, highlighting the potential of graph-based methods to enhance the robustness and accuracy of modern NIDS. Future work will explore dynamic graph modeling, attention mechanisms, and optimization techniques to further improve detection capabilities.
A Tag-Constrained Top-k Shortest Path for Finding Diverse Routes Santoso, Bagus Jati; Tamtama Adi, Ibrahim; Ijtihadie, Royyana Muslim
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.95815

Abstract

The top-k shortest path problem is a fundamental topic in graph theory and pathfinding applications. Traditional approaches focus solely on finding k paths with the least total cost or distance, often resulting in highly similar paths that offer limited flexibility for user selection. Moreover, real-world navigation demands often involve additional user preferences, such as specific points of interest or required amenities along the route. Motivated by this observation, this paper proposes an efficient framework for answering top-k diverse path search queries incorporating user-specified tag preferences. Specifically, given a source and destination node, a set of user-defined tags, and a similarity threshold, our method retrieves k shortest paths that not only satisfy the user's tag constraints but also maintain diversity by ensuring that the similarity among the retrieved paths remains below a given threshold. The proposed solution employs a two-phase approach: (1) preprocessing the graph structure to generate a tag-based matrix and shortest path data for efficient query processing, and (2) a hybrid search strategy that combines a modified Dijkstra’s algorithm and depth-first search with pruning based on tag satisfaction and diversity checking. Extensive experiments on synthetic road network datasets demonstrate that our method achieves significant improvements in query processing efficiency and provides a higher degree of path diversity compared to conventional approaches. Our contributions include the formal definition of the top-k diverse path search with tag preferences, the development of an efficient search framework, and comprehensive experimental validations. The results suggest that the proposed framework effectively balances path optimality, tag satisfaction, and diversity, enabling a more flexible and user-centric pathfinding system.
Attention-Driven U-Net with Ensemble Strategy for Inferior Alveolar Nerve Segmentation on 2.5D CBCT Data Arsy Bilahi Tama; Suciati, Nanik
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.96058

Abstract

Image segmentation plays a crucial role in medical analysis, particularly in accurately identifying anatomical structures. In dental implant planning, the identification of the Inferior Alveolar Nerve (IAN) is critical to avoid complications resulting from nerve injury. However, the manual annotation process on CBCT images is time-consuming and labor-intensive. Recent studies utilizing deep learning for IAN segmentation in 3D images often face two main challenges: limited availability of annotated data and high computational requirements.To address these challenges, this study proposes a more efficient segmentation approach based on 2.5D images. We implemented a U-Net architecture enhanced with attention gates to improve the model's focus on relevant nerve structures and increase segmentation accuracy. Furthermore, to maximize performance, predictions from multiple models were combined using ensemble learning techniques, which enhance robustness and final accuracy by leveraging the predictive strengths of diverse training samples.Experimental results demonstrate that the proposed approach achieves an average Dice score of 87.7%. These findings indicate that the combination of an attention-enhanced U-Net, the use of 2.5D imaging, and ensemble learning effectively yields accurate IAN segmentation while providing a practical solution to the challenges of data scarcity and computational complexity.
Vector-Borne Disease Detection Using Random Forest and BPSO Raharja, Made Agung; Pradyto, Kadek Dwitya Adhi; Wibawa, I Gede Arta; Astawa, I Gede Santi
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.96722

Abstract

Vector-borne diseases such as malaria, dengue fever and yellow fever still pose a serious threat to public health. To distinguish between these diseases, an accurate classification process is required. In this study, Random Forest algorithm is used as a classification method due to its ability to overcome overfitting and provide good accuracy results. However, the large number of features in the data can cause redundancy and decrease the accuracy of the model. Therefore, the Binary Particle Swarm Optimization (BPSO) method is used as a feature selection technique to optimize the performance of Random Forest. The optimization process is also complemented by finding the best parameters using Random Search and Grid Search. Evaluation was conducted on a vector-borne disease dataset with 64 features and 11 disease classes. The results showed that the accuracy of the model increased from 90.48% to 100% after feature selection by BPSO which selected 37 best features, and Random Search proved to be more efficient in computation time than Grid Search. This research shows that the combination of Random Forest and BPSO can improve classification accuracy and efficiency in detecting vector-borne diseases.
Ambidextrous IoT Governance Framework for SmartCo’s Digital Transformation Aligned with COBIT 2019 Traditional and DevOps Rahayu, Indah Sari; Mulyana, Rahmat; Fakhrurroja, Hanif
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 2 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i2.98135

Abstract

SmartCo, a digital infrastructure provider, faces IoT governance challenges (security, privacy, regulation) despite leveraging IoT for digital transformation. To address this, this research proposes an ambidextrous IoT governance framework that balances exploration (innovation and adaptation) and exploitation (efficiency of existing resources). The framework integrates COBIT 2019 with agile DevOps practices to optimize IT resource value and performance. Employing the Design Science Research (DSR) methodology an approach in Information Systems that provides structured guidance for designing, evaluating, and validating technological solutions, the study assessed the current governance environment, identified design factors, and prioritized Governance and Management Objectives (GMOs). Data were collected through semi-structured interviews with key stakeholders, guided by structured questions, and validated using internal documents in iterative analysis cycles until saturation was reached. DSS05 (Managed Security Services) emerged as the most critical domain. In COBIT 2019, DSS05 includes coordination and execution of IT operational procedures, such as SOPs and monitoring. The governance capability was found at level 3. Gaps included the lack of IoT unit test documentation with a security focus and unclear responsibilities of Testing and Release Managers. Recommendations include defining clearer responsibilities to the testing and release manager roles and mandating security-based unit testing before release. These improvements are projected to raise the DSS05 maturity level from 3.71 to 3.85. This study contributes by offering a tailored IoT governance solution for SmartCo and demonstrating the practical use of ambidextrous COBIT 2019 to manage innovation in dynamic technology environments.

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