Journal of Information Systems and Informatics (Journal-ISI)
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Evaluating User Experience and Usability of the USEPT Website Using User Experience Questionnaire and System Usability Scale Method
Get PDFIn recent years, assessing the quality of the Sriwijaya University English Proficiency Test (USEPT) website and its user experience has become increasingly important due to the globalization of higher education and the need for students to develop international communication skills. This study aims to evaluate the UX and usability of the USEPT website by using the User Experience Questionnaire (UEQ) and System Usability Scale (SUS) to provide a comprehensive analysis. The results showed that all aspects of the UEQ scored with an average value ranging from -0.88 to 0.48 making it in the “bad” category especially on attractiveness, stimulation and novelty. While the average SUS score is 50 which categorizes usability at the “Not Acceptable” level, with a grade of “F” and adjective rating at the “poor” level. These findings illustrate the poor functionality of the website due to unsatisfactory user experience, thus requiring holistic improvements across all dimensions of UEQ. Recommendations for improvement include optimizing website navigation, increasing visual appeal by creating an attractive design, integrating interactive features to increase user engagement and satisfaction. This research makes a positive contribution to the development of the USEPT website in user satisfaction and can be a reference for website evaluation
Strategic Information Systems Planning Analysis Using the Ward and Peppard Method: A Case Study
Get PDFThis paper aims to develop a strategic information systems (IS) plan using the Ward and Peppard methodology, employing a qualitative approach with data collected through direct observations, interviews with key stakeholders, and a comprehensive literature review. The study integrates analytical tools such as SWOT, Value Chain, Porter’s Five Forces, PEST, and McFarlan’s Strategic Grid to evaluate internal and external environments. Findings reveal strengths in operational efficiency and customer engagement, alongside challenges like reliance on manual reservation systems and limited product diversification. Based on these insights, a strategic IS application portfolio and phased implementation plan were proposed to align IT investments with strategic objectives. The proposed solutions are expected to improve reservation handling, enhance customer engagement, and increase operational efficiency. This study highlights the innovative application of the Ward and Peppard methodology in the recreational sports industry, offering a scalable framework for other businesses to address similar operational challenges. Future research could extend this approach to real-world implementations or explore its adaptability across diverse sectors
Low-Cost LoRaWAN Solution for Groundwater Monitoring in Peatlands
Get PDFSome efforts made in restoring peatlands include moisture restoration, replanting, hydrological restoration, monitoring, and evaluation using technology to obtain periodic condition data. The implementation of the Water Level Logger (WLL) for monitoring groundwater levels in peatlands still faces issues because the sensor installation points are not served by cellular communication networks for data transmission. This research aims to implement a Low Power Wide Area Network (LPWAN) as a low-cost infrastructure used in applications for monitoring water levels in peatland. The method in this research is an approach to develop LoRaWAN gateway devices and servers using ChirpStack, equipped up to the application layer as supporting infrastructure for self-hosted groundwater level monitoring tools integrated with a time-series database and displaying measurement data on a dashboard periodically. Based on the tests, the average measurement of the Received Signal Strength Indicator (RSSI) obtained at the farthest distance of 3 km was -116 dBm, where the RSSI value also decreased with each additional distance, and the Line-of-Sight (LOS) condition significantly affected the RSSI value. This research shows that a real-time peat groundwater monitoring system has been successfully built at a low cost using self-hosted LoRaWAN gateways and servers, while maintaining reliability
Sentiment Analysis and Trend Mapping of Hotel Reviews Using LSTM and GRU
Get PDFThis study explores applying Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models for sentiment analysis and trend mapping of hotel reviews, specifically focusing on customer feedback from Hotel Vila Ombak in Lombok, Indonesia. The primary objective was to leverage these advanced deep learning models to capture nuanced sentiment patterns in unstructured textual data, enhancing insights into guest satisfaction. The analysis was conducted on a dataset of 326 reviews, achieving an overall model accuracy of 91% (0.91). The results showed that while the models excelled in identifying positive sentiments, with a precision of 0.94, recall of 0.98, and F1-score of 0.96, they struggled with minority classes. Both negative and neutral sentiments exhibited 0% accuracy, primarily due to the dataset’s imbalance, where positive reviews constituted 92.3% of the total entries. The macro average metrics (precision 0.31, recall 0.33, F1-score 0.32) highlighted the model's limitations in classifying sentiments less frequently despite high weighted averages driven by the dominant positive class. This research underscores the need to address data imbalance and suggests that future studies incorporate techniques like data augmentation or hybrid models to improve performance across all sentiment categories. By optimizing sentiment analysis models, hospitality businesses can gain deeper insights into customer feedback, ultimately enhancing service quality and customer satisfaction
Clustering Sugar Content in Children's Snacks for Diabetes Prevention Using Unsupervised Learning
Get PDFDiabetes is a chronic health problem with increasing prevalence, especially among children, due to the consumption of sugary foods/beverages. This study aims to cluster children's snack products based on sugar content using unsupervised learning by combining Hierarchical Clustering and K-Means algorithms optimized using Silhouette Score. This combined approach utilizes Hierarchical Clustering to determine the optimal value (????) of K-Means, ensuring the efficiency and accuracy of data clustering. A total of 157 sample data were effectively clustered with K-means. The test results with Silhouette Score yielded the highest value of 0.380 for 2 clusters, while 3 clusters scored 0.350 and 0.277 for 4 clusters. For this reason, 2 clusters better represent the homogeneity of the data in the cluster, although it has not reached the ideal condition. Further analysis showed that high sugar and calorie content in sugary drinks, including milk, could increase blood glucose levels. These findings can be the basis for the development of consumer-friendly nutrition labels. However, support is needed from the government to create a labelling policy to ensure the sustainability of implementation in the community as an educational effort to prevent the risk of diabetes in children
Development of a Digital Village Concept based on Information Technology Infrastructure and Strategy Management to Facilitate SPBE Ogan Ilir Regency
Get PDFTechnology in the digital era is currently progressing very rapidly. This is marked by the increasingly massive number of social media users in everyday life. Survey results from the Indonesian Internet Service Providers Association (APJII) in 2022 recorded that the number of internet users in Indonesia reached 196.7 million people. This number increased by 23.5 million or 8.9% compared to 2018. With information technology and the internet, information is now becoming more easily spread and can be accessed by all levels of society thanks to the internet, not just people in urban areas, but people living there. in rural areas too. The Ogan Ilir Regency Government initiated information technology infrastructure including village internet or Digital Village to solve the problem of inequality in digitalization of society in rural and urban areas. Development and implementation of a digital village is a program that implements electronic-based government system (SPBE) services to the community and empowers the community based on the use of technology. This research aims to conduct a survey of information technology infrastructure to identify village potential, marketing and accelerating access and public services. Apart from that, this research also identifies digital-based life patterns of people in rural and urban areas, as well as to advance economic development in rural areas to improve SPBE services in Ogan Ilir Regency. The method used is a quantitative method for surveying and mapping the use of information technology in villages and ultimately producing the concept of an independent digital village. Research data was obtained from surveys and FGDs with the Ogan Ilir district government, village heads, village communities and micro, small and medium enterprises. Meanwhile, secondary data will be obtained through the results of MSME and village profiles from the Central Statistics Agency
Hotel Guest Length of Stay Prediction Using Random Forest Regressor
Get PDFThis research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry. This research investigates the application of the Random Forest Regression model to predict the Length of Stay (LoS) of hotel guests, leveraging key features such as country, guest type, room type, and rating. The study addresses the need for precise forecasting to optimize resource allocation, improve operational efficiency, and support data-driven decision-making in the hospitality sector. The methodology involves data collection from a structured dataset of guest reviews, preprocessing through encoding categorical variables, converting target values into numeric forms, and standardizing features to ensure consistency and uniformity. The dataset is split into training (80%) and testing (20%) subsets, with hyperparameters such as n_estimators=100 and random_state=42 set to ensure stability and reproducibility during model training. The Random Forest Regression model demonstrated strong predictive performance, achieving an R-squared value of 0.85 and a Mean Absolute Error (MAE) of 1.06. Feature importance analysis identified "country" as the most significant variable (importance score: 0.5), followed by guest type (0.2), room type (0.15), and rating (0.15). The Predicted vs. Actual Plot and Error Distribution evaluation reveals that most errors cluster near zero, indicating high accuracy with minor deviations in extreme cases. These findings emphasize the model’s potential to enhance marketing strategies, optimize resource allocation, and improve guest satisfaction. This research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry
Challenges in IoMT Adoption in Healthcare: Focus on Ethics, Security, and Privacy
Get PDFThis study highlights ethical, security, and privacy barriers to IoMT adoption in developing countries and proposes strategies like regulatory frameworks, data encryption, AI transparency, and professional training to address these challenges. The Internet of Medical Things (IoMT) has the potential to revolutionize healthcare by enabling real-time patient monitoring, enhancing diagnostic accuracy, and supporting personalized treatments. However, significant privacy, security, and ethical challenges hinder its widespread adoption, particularly in underdeveloped nations. This study employs the PRISMA methodology to systematically review existing literature and identify key barriers to IoMT implementation in healthcare systems, with a focus on developing countries. Through a rigorous selection process, 80 studies were included in the analysis, revealing critical challenges such as inadequate data protection frameworks, ethical concerns around artificial intelligence (AI) in decision-making, and risks of patient data exploitation. The findings provide actionable recommendations for policymakers, including the establishment of robust ethical guidelines, implementation of strong security measures, and use of advanced encryption techniques. Addressing these challenges is crucial to fostering the ethical and secure adoption of IoMT, ultimately improving healthcare outcomes globally Key recommendations for IoMT adoption include the implementation of advanced encryption techniques to safeguard patient data, the establishment of clear informed consent protocols, and the development of ethical guidelines to manage AI’s role in medical decision-making, ensuring transparency and patient autonomy
Employee Performance Evaluation Using ANP and TOPSIS
Get PDFIn the era of competitive globalization, employee performance evaluation is crucial for ensuring productivity and quality in human resources. This research addresses the challenge of subjectivity in performance evaluation by integrating the Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The study identifies relevant evaluation criteria, assigns weights using ANP, and prioritizes employee performance objectively through TOPSIS. Using a Research and Development (RnD) approach, data were collected via observations, interviews, and documentation. Results demonstrate that the combination of ANP and TOPSIS significantly improves the accuracy and fairness of evaluations, reducing bias by 20% and enhancing transparency by 15% compared to traditional methods. Employees with a preference score of 1.00, such as Sumadin, Siti, and Ardianto, were deemed to have optimal performance across the criteria: Responsibility, Attendance, Service, Cleanliness, and Loyalty. The system also categorized employees with medium preference values (0.6–0.9) and low scores (<0.4), providing actionable insights for employee development. This research highlights the efficacy of technology-based evaluation systems in strategic HR decision-making, contributing to increased job satisfaction and productivity. The system developed has proven to be efficient, able to reduce bias, and increase job satisfaction and productivity
Leveraging MANETs for Healthcare Improvement in Rural Botswana
Get PDFRural health facilities in Botswana face significant challenges, including limited infrastructure, poor communication networks, and inadequate access to medical resources, which hinder quality healthcare delivery. This study investigates the feasibility and benefits of implementing Mobile Ad hoc Networks (MANETs) in these underserved areas. A MANET is a decentralized wireless network where devices communicate directly with each other without relying on fixed infrastructure, allowing dynamic, self-configuring connections. Key solutions proposed include integrating MANETs with solar-powered systems to ensure continuous operation, developing localized health information systems to enhance data accessibility, and implementing community training programs to build local technical capacity. Additionally, designing resilient network architectures and collaborating with local telecom providers for hybrid solutions can improve reliability and coverage. Utilizing MANETs for real-time health monitoring and emergency alerts can enhance patient outcomes and response capabilities. The real-world implementation of MANETs is expected to improve emergency response times, reduce healthcare delivery delays, and facilitate faster decision-making in critical situations. This paper highlights the potential of MANETs to address healthcare disparities between rural and urban areas by providing sustainable, scalable, and reliable communication infrastructure. Future research should focus on extensive pilot programs, empirical data collection, and exploring the integration of advanced technologies to further enhance healthcare delivery in rural Botswana. These findings aim to inform policymakers and healthcare providers on adopting MANET technology to improve rural healthcare systems