eJournal Komunitas Dosen Indonesia
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Evaluating the Success of the Mobile JKN Application through the DeLone & McLean Framework
Get PDFThe JKN mobile app is a digital platform developed by BPJS Kesehatan to help users access information and manage their membership independently. This research assesses the effectiveness of the application by employing the framework developed by DeLone and McLean, which includes aspects such as the quality of the system, the quality of information, the quality of service, and the intention to use, User Contentment, and Overall Gains. A quantitative approach was used, applying PLS-SEM for data analysis. Based on the Lemeshow formula, the minimum sample size was 384, and 400 active users of the latest app version participated. The analysis was conducted utilizing SmartPLS 4. Results show that the quality of the system and the quality of the information significantly influence user contentment and their inclination to participate. Thus, user contentment is essential in determining the perceived overall advantages. The study indicates that the app's success is more influenced by technical performance and user experience rather than service quality. This highlights the need to improve system reliability, interface usability, and information accuracy. Users tend to value fast access and functionality over support services. Continuous improvement in these areas can help increase satisfaction and long-term usage. The findings suggest that focusing on user-centered design and regular updates will strengthen digital health engagement. These insights can also serve as guidance for similar e-health initiatives in developing countries.The JKN mobile app is a digital platform developed by BPJS Kesehatan to help users access information and manage their membership independently. This research assesses the effectiveness of the application by employing the framework developed by DeLone and McLean, which includes aspects such as the quality of the system, the quality of information, the quality of service, and the intention to use, User Contentment, and Overall Gains. A quantitative approach was used, applying PLS-SEM for data analysis. Based on the Lemeshow formula, the minimum sample size was 384, and 400 active users of the latest app version participated. The analysis was conducted utilizing SmartPLS 4. Results show that the quality of the system and the quality of the information significantly influence user contentment and their inclination to participate. Thus, user contentment is essential in determining the perceived overall advantages. The study indicates that the app's success is more influenced by technical performance and user experience rather than service quality. This highlights the need to improve system reliability, interface usability, and information accuracy. Users tend to value fast access and functionality over support services. Continuous improvement in these areas can help increase satisfaction and long-term usage. The findings suggest that focusing on user-centered design and regular updates will strengthen digital health engagement. These insights can also serve as guidance for similar e-health initiatives in developing countries
Optimization of Earthquake B-Value Prediction in Java Using GRU and Particle Swarm Optimization
Get PDFAccurate prediction of earthquake parameters is essential for seismic risk assessment and disaster mitigation, particularly in tectonically active regions such as Java Island, Indonesia. This study presents a novel predictive model for estimating the earthquake b-value a fundamental seismological parameter representing the logarithmic relationship between earthquake frequency and magnitude by integrating a Gated Recurrent Unit (GRU) neural network with Particle Swarm Optimization (PSO). The model is trained using earthquake catalog data from 1962 to 2024, sourced from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG). The GRU architecture is selected for its effectiveness in modeling temporal dependencies in seismic time series data. PSO is employed to optimize essential hyperparameters, including the number of GRU units, learning rate, and dropout rate. The optimized model achieves notable improvements in predictive performance: Mean Squared Error (MSE) is reduced from 0.00435 to 0.00030, Root Mean Squared Error (RMSE) from 0.0509 to 0.0173, and Mean Absolute Percentage Error (MAPE) from 3.42% to 1.12%. Training time is also reduced from 57 seconds to 33 seconds, indicating greater computational efficiency. The optimal PSO settings include an inertia weight of 0.8, cognitive and social coefficients of 1.0, 40 particles, and 10 iterations. The primary novelty of this study lies in its targeted application of PSO-optimized GRU architecture for b-value prediction in a seismically complex region. These results demonstrate that evolutionary optimization significantly enhances deep learning performance, providing a robust and efficient framework to support earthquake forecasting and risk mitigation efforts in high-risk zones such as Java Island
Evaluate the Intentions and Behaviors of Live Streaming Feature Users with the UTAUT Model
Get PDFThe rapid advancement of digital innovation in Indonesia's e-commerce industry has encouraged the widespread adoption of live streaming features such as Shopee Live, which enable real-time interaction between sellers and buyers. Despite the growing popularity of this feature, limited research has investigated the behavioral factors that drive its sustained use, particularly by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the construct of trust. This study aims to evaluate users’ behavioral intentions and actual usage of Shopee Live by applying the UTAUT model, extended with the trust variable to better capture the dynamics of live streaming-based commerce. A quantitative approach was employed through an online survey distributed to Shopee users with prior experience using the live feature. Using purposive sampling, a total of 215 valid responses were collected, with a response rate of 86%. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results show that Effort Expectancy, Social Influence, Price Value, Habit, and Trust significantly affect behavioral intention, while Performance Expectancy, Facilitating Conditions, and Hedonic Motivation do not. Furthermore, Habit, Trust, and Behavioral Intention significantly influence actual usage behavior. This study contributes to the e-commerce literature by extending the UTAUT framework with trust in the specific context of live streaming. The findings emphasize the stronger role of trust and social factors over utilitarian and entertainment considerations. E-commerce platforms should focus on strengthening user trust, promoting ease of use, and encouraging habitual usage to increase engagement with live commerce features.The rapid advancement of digital innovation in Indonesia's e-commerce industry has encouraged the widespread adoption of live streaming features such as Shopee Live, which enable real-time interaction between sellers and buyers. Despite the growing popularity of this feature, limited research has investigated the behavioral factors that drive its sustained use, particularly by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the construct of trust. This study aims to evaluate users’ behavioral intentions and actual usage of Shopee Live by applying the UTAUT model, extended with the trust variable to better capture the dynamics of live streaming-based commerce. A quantitative approach was employed through an online survey distributed to Shopee users with prior experience using the live feature. Using purposive sampling, a total of 215 valid responses were collected, with a response rate of 86%. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results show that Effort Expectancy, Social Influence, Price Value, Habit, and Trust significantly affect behavioral intention, while Performance Expectancy, Facilitating Conditions, and Hedonic Motivation do not. Furthermore, Habit, Trust, and Behavioral Intention significantly influence actual usage behavior. This study contributes to the e-commerce literature by extending the UTAUT framework with trust in the specific context of live streaming. The findings emphasize the stronger role of trust and social factors over utilitarian and entertainment considerations. E-commerce platforms should focus on strengthening user trust, promoting ease of use, and encouraging habitual usage to increase engagement with live commerce features
User Centered Design Approach for Developing a Health Monitoring System for Posyandu
Get PDFIndonesia continues to report high maternal and infant mortality rates, underscoring the urgent need for effective community-based health information systems, particularly in rural areas served by Posyandu (Integrated Health Service Posts). Despite their crucial role in primary healthcare delivery, many Posyandu still rely on manual data recording, resulting in fragmented documentation, delayed health risk detection, and inefficient decision-making processes. This study adopts a design research approach, utilizing the User-Centered Design (UCD) methodology to develop a web-based health monitoring system tailored for non-technical users, specifically Posyandu cadres in Dukuh Village, Boyolali Regency. The UCD process involved four iterative stages: understanding the user context, specifying user requirements, designing high-fidelity interface prototypes using Figma, and conducting usability evaluation through the System Usability Scale (SUS). The developed prototype includes key features such as digital patient data entry, real-time health examination input, visual health monitoring graphs, and automatic report generation by category and period. Usability testing was conducted with five Posyandu cadres who participated in defined usage scenarios and completed the SUS questionnaire. The resulting average SUS score was 84, categorized as “Excellent,” indicating that the system is intuitive, accessible, and efficient for users with limited technological experience. These findings demonstrate that the UCD approach effectively aligns system functionality with user needs, enhancing usability and supporting timely, data-driven health service decisions. This model offers significant potential for scalability and adaptation in other Posyandu settings, contributing to more integrated and responsive public health interventions at the village level.Indonesia continues to report high maternal and infant mortality rates, underscoring the urgent need for effective community-based health information systems, particularly in rural areas served by Posyandu (Integrated Health Service Posts). Despite their crucial role in primary healthcare delivery, many Posyandu still rely on manual data recording, resulting in fragmented documentation, delayed health risk detection, and inefficient decision-making processes. This study adopts a design research approach, utilizing the User-Centered Design (UCD) methodology to develop a web-based health monitoring system tailored for non-technical users, specifically Posyandu cadres in Dukuh Village, Boyolali Regency. The UCD process involved four iterative stages: understanding the user context, specifying user requirements, designing high-fidelity interface prototypes using Figma, and conducting usability evaluation through the System Usability Scale (SUS). The developed prototype includes key features such as digital patient data entry, real-time health examination input, visual health monitoring graphs, and automatic report generation by category and period. Usability testing was conducted with five Posyandu cadres who participated in defined usage scenarios and completed the SUS questionnaire. The resulting average SUS score was 84, categorized as “Excellent,” indicating that the system is intuitive, accessible, and efficient for users with limited technological experience. These findings demonstrate that the UCD approach effectively aligns system functionality with user needs, enhancing usability and supporting timely, data-driven health service decisions. This model offers significant potential for scalability and adaptation in other Posyandu settings, contributing to more integrated and responsive public health interventions at the village level
Implementation of Web-Based Room Management System for Boarding House Operations
Get PDFThe rapid advancement of digital technologies has significantly impacted various sectors, including property management. However, boarding house management still relies heavily on manual processes, resulting in inefficiencies such as inaccurate tenant data, delayed payments, and difficulties in monitoring room occupancy. This study aims to design and develop a web-based room management information system for Pak Yadi Boarding House, aimed at automating and streamlining key administrative tasks. Using the Waterfall development model, the study follows five phases: requirements analysis, system design, implementation, testing, and maintenance. Data collection was performed through literature review, observation, and interviews with the boarding house owner. The system was implemented using the Laravel framework and MySQL, with system architecture designed using UML diagrams. Testing was conducted using the Black Box method, with user acceptance testing involving one administrator and ten tenants. Key features tested include room data entry, tenant registration, payment invoicing, and complaint management. Results showed that all features performed as intended, and 90% of users expressed satisfaction with the system’s functionality and interface. The system successfully reduced administrative workload, minimized data entry errors, and enhanced operational efficiency. This research demonstrates that web-based systems can improve boarding house management and offers a scalable model for similar small-scale accommodations. Future research could explore integrating mobile access and cloud storage to enhance flexibility and remote management capabilities.The rapid advancement of digital technologies has significantly impacted various sectors, including property management. However, boarding house management still relies heavily on manual processes, resulting in inefficiencies such as inaccurate tenant data, delayed payments, and difficulties in monitoring room occupancy. This study aims to design and develop a web-based room management information system for Pak Yadi Boarding House, aimed at automating and streamlining key administrative tasks. Using the Waterfall development model, the study follows five phases: requirements analysis, system design, implementation, testing, and maintenance. Data collection was performed through literature review, observation, and interviews with the boarding house owner. The system was implemented using the Laravel framework and MySQL, with system architecture designed using UML diagrams. Testing was conducted using the Black Box method, with user acceptance testing involving one administrator and ten tenants. Key features tested include room data entry, tenant registration, payment invoicing, and complaint management. Results showed that all features performed as intended, and 90% of users expressed satisfaction with the system’s functionality and interface. The system successfully reduced administrative workload, minimized data entry errors, and enhanced operational efficiency. This research demonstrates that web-based systems can improve boarding house management and offers a scalable model for similar small-scale accommodations. Future research could explore integrating mobile access and cloud storage to enhance flexibility and remote management capabilities
Development of a Web-Based Internship Registration System to Improve Administrative Efficiency
Get PDFThe rapid advancement of information technology in the era of globalization has significantly impacted sectors such as communication, education, economy, and culture. Information is now easily accessible, overcoming traditional barriers of distance and time. In computer science, computers have become essential tools for meeting information needs in personal, educational, business, and governmental settings due to their ability to process data rapidly and accurately. In education, particularly in vocational schools, there is a need for an information system to streamline access to data, especially related to internship (PKL) activities. This research focuses on developing a web-based internship registration system at SMK Persada Pasarkemis to address issues like document loss, delays in data entry, and errors in manual processes. The system aims to improve registration efficiency by allowing users to upload documents, track registration status in real-time, and enhance transparency and data access for teachers. This study seeks to implement a computer-based system that optimizes PKL data management, reducing administrative bottlenecks and ensuring accurate data processing. The expected outcome is a more organized and efficient PKL registration process. Future developments include integrating the system with other information systems and adding features based on user feedback. The software development process follows the Software Development Life Cycle (SDLC) using the Waterfall model, chosen for its structured, sequential approach. This methodology ensures that each phase design, requirements analysis, testing, implementation, and maintenance is thoroughly completed before moving to the next, ensuring a reliable, well-documented system that meets user needs
Measuring e-Filing Adoption as an e-Government Service Using the Technology Acceptance Model
Get PDFThe digital transformation of public services in Indonesia, as mandated by Presidential Regulation No. 95 of 2018 on SPBE (Electronic-Based Government System), has led to the development of e-Filing—an electronic tax return reporting system that allows taxpayers to submit their Annual Tax Return (SPT) online. However, adoption among individual taxpayers remains uneven. This study investigates the factors influencing the acceptance and use of e-Filing among individual taxpayers registered at KPP Pratama Banjarmasin using the Technology Acceptance Model (TAM). Employing a quantitative explanatory approach, data were collected from 100 purposively selected respondents through structured questionnaires and analyzed using PLS-SEM. The findings reveal that perceived ease of use significantly influences users’ attitudes, and positive attitudes, in turn, strongly predict the intention to continue using e-Filing. However, perceived usefulness shows no significant effect on either user attitudes or usage intentions, highlighting a key divergence from core TAM assumptions. Moreover, intentions to use the system significantly influence actual usage, while ease of use and usefulness do not directly drive usage intentions. This study contributes uniquely by identifying a gap between perceived system benefits and actual behavioral intent, especially in the context of infrequent or assisted use among taxpayers. It recommends broader research that includes varied demographic groups and adopts extended models like UTAUT to explore external influences such as digital literacy, policy enforcement, and user support
Comparative Analysis of Machine Learning Algorithms for Predicting LQ45 Stock Index Prices
Get PDFAn essential metric for assessing the success of the country's capital markets is the LQ45 index, which is made up of 45 stocks with the biggest market capitalization and liquidity on thb e Indonesia Stock Exchange. Stock price prediction, particularly in volatile markets, remains complex challenge that benefits from advanced analytical approaches. While machine learning (ML) techniques have demonstrated significant promise in financial forecasting, comprehensive comparative evaluations across multiple algorithms and preprocessing strategies remain limited. In order to evaluate the predictive performance of nine machine learning algorithms Random Forest, Decision Tree, AdaBoost, Support Vector Classifier (SVC), XGBoost, Naive Bayes, K-Nearest Neighbors (KNN), Logistic Regression, and Artificial Neural Networks (ANN) in predicting the direction of movements of the LQ45 index, this study presents a structured comparative framework. The models are trained using a 10-year historical dataset, incorporating both continuous and binary representations of technical indicators. Three data preprocessing approaches are explored: raw trading data, unsmoothed indicators, and smoothed indicators. Accuracy, precision, recall, F1-score, and ROC AUC are all important factors in model evaluation. The findings show that when applied to continuous data with smoothed technical indications, Random Forest and XGBoost produce the best prediction results. For binary classification tasks, Naive Bayes emerges as the most effective model. These results demonstrate how important data representation and preprocessing in particular, smoothing are to enhancing the accuracy and robustness of models. Research aids in the creation of trustworthy, data-driven stock prediction tools that are suited for developing markets. Financial analysts, portfolio managers, and algorithmic traders looking to improve investment strategies through well-informed model selection and preprocessing design can benefit from the findings
Design and Development of a Counseling Service System Using Extreme Programming Methodology
Get PDFThis study addresses the inefficiency and error-prone nature of manual counseling and student violation point recording processes in schools, which often result in delays and inaccuracies. To overcome these challenges, we propose the development of a digital guidance and counseling service system designed to improve data management and enhance service accessibility for school administrators and counselors. The innovation lies in the creation of an integrated, browser-accessible application built using the MERN (MongoDB, Express.js, React, Node.js) stack, which ensures robust functionality and scalability. By applying modern development and testing methodologies, the system is designed to be both reliable and user-friendly. The core objective of this system is to streamline processes such as counseling appointment scheduling, alumni tracking, certificate submission, and student behavior reporting. It was developed using the Extreme Programming (XP) methodology, which encourages flexibility and iterative planning through close collaboration with end users. White Box Testing techniques, including cyclomatic complexity analysis and independent path testing, were employed to validate the system's internal logic. The system’s usability was assessed using the System Usability Scale (SUS), achieving an excellent score of 93.25, indicating high user satisfaction. Furthermore, the Lighthouse performance test yielded a perfect score of 100, confirming the system's high responsiveness. These results demonstrate that the developed system significantly enhances the efficiency, accuracy, and accessibility of guidance services, reduces administrative burdens, and enables better monitoring of student development, making it ideal for deployment in real-world school environments
Tinjauan Kondisi Harga, Kualitas Produk, dan Promosi Implikasinya Terhadap Keputusan Pembelian Konsumen Sabun Lifebuoy di Cileungsi
Get PDFPenelitian ini ingin meninjau implikasi kondisi harga, kualitas produk dan promosi terhadap keputusan pembelian konsumen. sabun Lifebupy di Cileungsi Bogor. Sabun merek Lifebuoy merupakan produksi dari perusahaan raksasa consumer goods yakni PT. Unilever. Perusahaan ini menghasilkan berbagai merek sabun dengan karakter masing-masing. Lifebuoy dengan julukan sabun kesehatan, Lux dengan julukan sabun kecantiukan, Dove fokus pada perawatan kulit, Love Beauty and Planet dikenal dengan bahan-bahan alami yang berkelanjutan. Pembersih badan ini juga dijuluki sabun kesehatan keluarga di Indonesia seperti yang terlihat pada iklan-iklannya. Penelitian ini dilakukan di Cileungsi pada 11 Maret sampai 11 Mei 2025 dengan sampel sebanyak 196 responden ibu rumahtangga. Teknik penentuan sampel menggunakan rumus Lameshow dimana metode ini mengisyaratkan jika jumlah populasi tidak dapat ditentukan. Metode penelitian yang digunakan adalah deskriptif causal yang menggambarkan hubungan serta pengaruh suatu varibel independen dengan variabel terikat. Analisa data menggunakan regresi berganda linier dengan pengujian kualitas data dilakukan uji validitas, cek reliabilitas, serta uji asumsi klasik melalui uji normalitas, heterokastisitas dan multikolinieritas. Hasil penelitian disimpulkan secara parsial variabel harga (X1) berpengaruh 0.714 satuan, variabel kualitas produk (X2) berpengaruh 0.792 satuan, dan variabel promosi (X3) berpengaruh 0.690 satuan terhadap keputusan pembelian konsumen (Y). Secara simultan Fhitung sebesar 44.217 jauh melampaui dari Ftabel dengan signifikansi 0.00 jauh dibawah 0.05. Jadi semua variabel bebas berpengaruh berpengaruh