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Intelligent IOT Service Recommendation System Based on Deep Learning
Get PDFThe rapid increase in interconnected devices, commonly known as the Internet of Things (IoT), has significantly impacted various sectors, enhancing services in energy, transport, health, and more. Unfortunately, that means consumers are facing increasing challenges in choice of quality IoT devices and services alike. Importantly, traditional methods of recommendation are largely reliant on collaborative or content-based filtering, which suffer from problems such as sparsity of data and the cold start problem that all result in potentially large inaccuracies. In this regard, this study supplies a unique QoS prediction approach with Generative Adversarial Network (GAN) and Gated Recurrent Unit (GRU), i.e., GRU-GAN is proposed to address these challenges. This approach maps the QoS matrix on service call records, involving user attributes and historical QoS records as a time series to train GRU-GAN model. In the GAN, the generator is trained to predict realistic QoS values and then discriminator evaluates classifying these predictions. We experimentally show the efficiency of our model. Our GRU-GAN model consistently outperforms traditional QoS prediction methods showing lower RMSE and MAE with regards to different data densities. More concretely, it had an RMSE of 0.16 and MAE of.05 with data density at 5%, and performed best across all the model as your increased data availability beyond that scale. In conclusion, the GRU-GAN model offers a robust solution for QoS prediction in IoT ser- vice recommendations, effectively handling data sparsity and enhancing prediction accuracy
The Influence of Material Control Systems on Remaining Materials in Structural Work
Get PDFDigital transformation has increased operational efficiency infrastructure critical, but at the same time also open new loophole against attack increasingly complex and destructive cyberspace. This study aims to identify spectrum threat cyber targeting infrastructure critical, analyzing vulnerability accompanying systemic, as well evaluate strategy multi-level protection used in mitigation risk cyber. Using approach qualitative through review methods systematically, this study examines 20 primary sources in the form of scientific journals, policy reports, and studies. case international published 2015–2024. The research results revealed that threats such as ransomware, Advanced Persistent Threats (APT), attacks AI -based, and zero-day exploits are becoming a form of attack dominant, with energy, health, and communications sectors as the main targets. Vulnerabilities systemic found in aspects of old technology that is not updated, governance weaknesse, as well as low awareness cyber at the level operational. Strategy effective protection nature layered, including perimeter security, access management, data encryption, training awareness, to response incidents and system recovery. This study recommends integration strategy adaptive, data -based protection risk, and supported by policies strong national to strengthen resilience cyber sector infrastructure critical
Food and Beverage Product Review Sentiment Analysis on E-Commerce with Word Embedding and LSTM
Get PDFSentiment analysis is a widely used method to understand customer opinions about a product. This study aims to analyze the sentiment of food and beverage product reviews on the Tokopedia marketplace using the Long Short-Term Memory (LSTM) approach and word embedding. The data used consisted of customer reviews that were categorized into three sentiment classes, namely positive, neutral, and negative. The model was developed through a series of stages of preprocessing, embedding, training with LSTM, as well as performance evaluation using accuracy and F1-score metrics. The results show that the developed model is able to classify sentiment with a fairly high level of accuracy. Based on the results of the final test on 5,000 data, the model managed to classify 122 data as negative, 130 data as neutral, and 4,871 data as positive, although it still showed an imbalance in class classification. Further analysis through word cloud visualization showed that words like "delicious", "steady", and "good" dominated the positive sentiment, while words like "disappointed", "broken", and "slow" often appeared in negative sentiment. This study provides valuable insights for businesses in understanding customer opinions and improving the quality of products and services
Academic Productivity of Private University Lecturers: Analysis of the Impact of Workload, Motivation, and Institutional Support
Get PDFThis study examines the relationship between workload, motivation, institutional support, and academic productivity among lecturers in private universities. Despite the growing emphasis on research output and academic productivity in higher education institutions, private university lecturers face unique challenges that may impact their productivity. Using a quantitative approach with a cross-sectional survey design, this study collected data from 217 full-time lecturers from 7 private universities across Brebes Regency, Tegal City, and Tegal Regency. The research employed stratified random sampling and utilized validated questionnaires measuring workload dimensions, academic motivation, perceived institutional support, and academic productivity indicators. Multiple regression analysis revealed that workload has a significant negative effect on academic productivity (β = -0.342, p < 0.01), while motivation (β = 0.418, p < 0.001) and institutional support (β = 0.376, p < 0.001) both demonstrated significant positive effects. Institutional support was found to moderate the relationship between workload and productivity, suggesting that strong institutional support can mitigate the negative effects of high workload. Path analysis indicated that motivation partially mediates the relationship between institutional support and academic productivity. The findings highlight the importance of balanced workload allocation, motivational strategies, and institutional support systems in enhancing academic productivity. This research contributes to the growing literature on academic productivity determinants in private higher education institutions in Indonesia and provides practical implications for institutional policy development aimed at fostering productive academic environments
Environmental Sustainability of Nickel Waste Utilization in Porous Asphalt: Toward Green and Circular Road Infrastructure
Get PDFThe rapid growth of road infrastructure in Indonesia has increased the demand of construction materials and at the same time, intensified environmental issues. The study explores the potential application of nickel waste- which is a byproduct readily available to Indonesia in the smelting of nickel- as a partial replacement to coarse aggregate in porous asphalt mixtures. The research not only assesses the technical performance but also the environmental impact of the nickel waste substitution which can be regarded as a contribution to the literature on sustainable management of the construction process and the circular economy. Key parameters such as stability, flow, void content and the Marshall Quotient were tested in the laboratory and were evaluated as per the Bina Marga and SNI requirements. The results refer to the fact that nickel waste may meet a number of technical requirements, reaching an ideal concentration of asphalt into 5.5 0-100 that, at the same time, can provide waste minimization and possible cost-saving benefits. However, due to the fact that nickel slag contains heavy metals, it requires the use of strong environmental risk management, such as leaching control and stabilization technologies. These findings indicate that the use of nickel waste is more than a technical innovation; it is a strategic direction of the ability to become resource-efficient, symbiotic in the industrial industry, and to govern the operation of infrastructure in a sustainable manner. Placing industrial waste in a new category as productive input, this research sheds some light on how policy can be changed, how to innovate in procurements, and how government, industry, and academia can collaborate. The study concludes that the addition of nickel waste to the porous asphalt mixtures could help improve the performance of roads, reduce environmental ecological impacts, and promote the green infrastructure agenda in Indonesia, assuming that there are regulatory protections and a systematic environmental check-up
Analysis of the Adherence to the Time of Doctor Visits in the Inpatient Installation
Get PDFOne of the national indicators of hospital quality is compliance with doctor's visit time, the achievement of the National Quality Index (INM) at the inpatient installation of Tk. III dr. Reksodiwiryo Padang Hospital in 2023 is 67%. This value is below the quality indicator standards that have been regulated by the Minister of Health Regulation No. 30 of 2022. This study is aimed at analyzing the adherence to doctor's visit time at the inpatient installation of Tk. III Dr. Reksodiwiryo Padang Hospital. The research used the mixed method method, the first stage was quantitative research with stratified random sampling techniques, then qualitative research was carried out with in-depth interviews with 14 informants, field observation and document review. Compliance with the doctor's visit time at the inpatient installation of Tk. III dr. Reksodiwiryo Padang Hospital based on research was obtained at 40%. The causes of non-compliance with doctor's visit time are the lack of the number of organic/permanent specialist doctors and the absence of an alarm to remind the doctor's visit time, the absence of clear regulations related to decrees, SOPs, and doctor's visit policies, the absence of a clear doctor's visit schedule, in addition to the DPJP's lack of understanding of the Regulation of the Minister of Health on visit time and the lack of optimal follow-up from monitoring and evaluating the compliance of doctor's visit time in inpatient installations
Analysis of Prostate Cancer Incidence Based on Body Mass Index and Blood Pressure Factors
Get PDFProstate cancer is one of the most common cancers in men worldwide and ranks fourth according to GLOBOCAN 2022. Its incidence in Asia, including Indonesia, continues to increase each year. Prostate cancer risk factors include both modifiable variables like blood pressure and body mass index (BMI) and non-modifiable variables like age and family history. This study aimed to determine the association between BMI and blood pressure with the incidence of prostate cancer. This study employed an analytical observational design using a retrospective hospital-based case-control approach. A total of 68 samples were collected, comprising 22 patients with benign prostatic hyperplasia (BPH) as the control group and 46 patients with prostate cancer as the case group. BMI and blood pressure data were collected from medical records and categorized based on the classifications from the WHO and PERHI (2019). The chi-square test was employed for the bivariate analysis with a significance level of p < 0.05. There was no significant associationfound between blood pressure and the incidence of prostate cancer (p = 0.304), while there was a significant association between BMI and the risk of prostate cancer (p = 0.023). The OR value of 0.581 with a 95% CI (0.205–1.645) indicated that blood pressure was not a statistically significant factor. These findings imply that hormonal alterations, persistent inflammation, and elevated insulin-like growth factor 1 (IGF-1) activity may raise the risk of prostate cancer in overweight individuals. In conclusion, BMI shows a significant association with prostate cancer incidence, whereas blood pressure does not demonstrate a significant association
Psychosocial Interventions and Social Support for Maternal Mental Health and the Prevention of Postpartum Depression: A Literature Review
Get PDFPostpartum depression is a significant public health issue that adversely affects maternal well-being and infant development. Psychological, hormonal, and social changes during pregnancy and the postpartum period increase women’s vulnerability to depressive symptoms, particularly when psychosocial support is inadequate. This study aimed to systematically review the evidence on psychosocial interventions for the prevention and reduction of postpartum depression among pregnant women in the third trimester and women in the postpartum period. A systematic literature review was conducted following the PRISMA guidelines. Articles were retrieved from Scopus, PubMed, and Garuda databases, limited to publications between 2020 and 2025. Ten studies met the inclusion criteria, encompassing randomized controlled trials, quasi-experimental studies, systematic reviews, meta-analyses, and qualitative meta-syntheses. The reviewed studies examined various psychosocial approaches, including digital and app-based interventions, psychoeducation and psychological self-help programs, as well as social and family support–based interventions. Overall, the findings indicate that psychosocial interventions are effective in reducing postpartum depressive symptoms and improving secondary mental health outcomes such as anxiety, stress, emotional well-being, and self-efficacy. Social support from partners, family members, and supportive healthcare environments emerged as a key protective factor that enhances intervention effectiveness. Digital interventions showed moderate but significant effects and offer advantages in accessibility and scalability. In conclusion, preventing postpartum depression requires a multidimensional and culturally sensitive approach that integrates psychosocial interventions with strengthened social support systems to promote sustainable maternal mental health outcomes
Analysis of Indonesian Social Security Administrator Policy Implementation in Improving Service Quality
Get PDFThis study analyzes the implementation of the National Health Insurance (JKN) policy administered by the Badan Penyelenggara Jaminan Sosial in enhancing service quality at Royal Prima Marelan General Hospital. The primary issues identified include insufficient dissemination of policy guidelines to medical personnel and patients, complex administrative procedures, and limited service facilities available to JKN participants. Using a descriptive-analytic approach, the research applies the SERVQUAL (Service Quality) model and the Expectancy–Disconfirmation Theory (EDT) to evaluate the gap between patient expectations and perceived service quality. Data were obtained through observations, interviews, and questionnaires involving medical staff, administrative officers, and JKN patient participants. The findings reveal that the Tangibles and Reliability dimensions are relatively satisfactory; however, Responsiveness and Empathy remain low due to limited human resources and heavy workloads. The implementation of JKN policies by the Badan Penyelenggara Jaminan Sosial has not been fully optimized, primarily due to inadequate training, the absence of integrated digital information systems, and limited managerial support for systematic service quality monitoring and evaluation. Based on the EDT assessment, a notable mismatch exists between patient expectations and actual service experiences, resulting in dissatisfaction. Integrating the JKN policy framework with SERVQUAL and EDT highlights the need to strengthen policy dissemination, enhance human resource capacity, and reform management systems through digitalization and a human-centered approach to ensure equitable, efficient, and sustainable health services at Royal Prima Marelan General Hospital
The Influence of Employee Engagement and Organizational Citizenship Behavior on Employee Performance Laboratory Division: JEL Classification: J24, M12, M51, M54, D23
No full textThe nickel mining industry faces significant challenges in maintaining employee performance amidst high work demands and a complex work environment. One strategy that can be implemented is to enhance employee engagement and organizational citizenship behavior (OCB). This study aims to analyze the influence of employee engagement and OCB on the performance of employees in the Laboratory Division of PT Obsidian Stainless Steel. This research was conducted in 2025 using a quantitative approach with multiple linear regression analysis techniques. The sample consisted of 134 employees selected through random sampling. Data were collected through questionnaires and documentation. The results show that employee engagement has a significant partial effect on performance (p = 0.000), as does OCB (p = 0.002). Simultaneously, employee engagement and OCB have a positive and significant effect on employee performance (p = 0.001 < 0.05). The adjusted R² value of 0.593 indicates that 59.4% of the variation in performance can be explained by these two variables, while the remaining 40.6% is influenced by other factors outside this study