Publication Search

The integration of cloud computing and data security systems is vital for the operational success and competitiveness of fintech startups. Cloud computing enables these startups to scale quickly, manage resources efficiently, and reduce infrastructure costs, making it an indispensable tool for businesses in the rapidly evolving fintech sector. However, with the benefits come significant challenges, particularly in data protection and cybersecurity. As fintech services handle sensitive financial data, ensuring robust security measures such as encryption, access controls, and continuous monitoring is crucial to maintaining user trust. Furthermore, regulatory compliance, both local and global, adds complexity to the data protection strategies of fintech companies. This research explores the key factors that drive cloud adoption in fintech, the security challenges associated with cloud environments, and the strategies implemented by startups to address these challenges. Interviews with IT managers from Indonesian fintech startups reveal that while cloud computing offers scalability and cost-effectiveness, issues like compliance with local regulations and the protection of sensitive data remain major concerns. The research suggests that fintech startups should invest in both cloud infrastructure and advanced cybersecurity measures to protect their operations and customer data. Additionally, creating a comprehensive roadmap for regulatory compliance and fostering partnerships with cybersecurity firms will help mitigate risks and ensure long-term success. The findings highlight the importance of integrating cloud computing with effective security strategies to navigate the complex regulatory and security landscape of the fintech industry.

The disparity in the quality of rehabilitation services across regional work units presents a significant challenge to effective public management. This study aims to bridge the gap between problem diagnosis and policy prediction by proposing a hybrid, data-driven approach. We integrate K-Means Clustering to map the current state of service quality and Stochastic Simulation to predict the impact of strategic interventions. Using the 2024 Public Satisfaction Index (IKM) dataset from the National Narcotics Agency (BNN), the K-Means algorithm initially identified 26 work units (15.7%) in the "Red Zone" (critical performance), highlighting urgent areas for improvement. Next, a stochastic simulation modeling a "Directed Priority Intervention" scenario was run. The results predicted a significant structural shift in the distribution of service quality, characterized by an 80.8% decrease in critical units (down to 5 units) and a 71.8% increase in excellent performing units (up to 67 units). These findings validate that the integration of clustering and simulation provides a comprehensive framework for evidence-based decision-making, enabling policymakers to optimize resource allocation and efficiently accelerate national service standardization.

Beef cattle are a strategic commodity in supporting animal food security and strengthening the regional economy.West Kutai Regency has significant potential for beef cattle development, but is not yet supported by targeted, data-driven livestock planning. This study aims to identify base and non-base areas for beef cattle and map priority zoning for beef cattle center development through the integration of Location Quotient (LQ) and Geographic Information Sistem (GIS) analysis. The study was conducted from April to October 2025 using primary data from field observations and secondary data from relevant agencies. LQ analysis was employed to assess the level of specialization within the beef cattle population at the sub-district level, while GIS spatial analysis was utilized to integrate the LQ results with information on land use and regional accessibility networks. The results showed that of the 16 sub-districts, five are base areas (LQ > 1): Long Iram, Sekolaq Darat, Linggang Bigung, Nyuatan, and Penyinggahan, with Long Iram having the highest LQ value (2.79). The integration of LQ results and spatial modeling resulted in a priority zoning map that highlighted the primary concentration of beef cattle development in areas with high livestock populations, adequate accessibility, and available cultivation space. This study emphasizes the significance of quantitative and spatial approaches in livestock spatial planning, thereby supporting the development of sustainable beef cattle centers in West Kutai Regency.

This study aims to analyze the integration of the Pancasila Student Profile (PSP) within Civics Education (PPKn) learning in elementary schools through a descriptive qualitative library research approach. The research draws on 15 national journal articles published between 2020 and 2025 that discuss strategies, challenges, and outcomes of implementing the PSP in learning practices. The findings show that PSP values—such as mutual cooperation, independence, critical thinking, creativity, and noble character—are primarily integrated through classroom activities, project-based learning, and habituation programs aligned with the Merdeka Curriculum. However, several challenges persist, including limited teacher understanding, inconsistent school support, inadequate learning media, and insufficient alignment between curriculum expectations and classroom practices. The analysis also reveals that effective implementation requires strong teacher leadership, contextual learning strategies, and sustained school commitment to character development. The study contributes theoretically by deepening understanding of value-based learning and practically by offering recommendations for teachers and schools to optimize character-based PPKn instruction. Overall, the integration of PSP values strengthens students’ character formation and supports the development of a holistic learning environment consistent with Pancasila principles.  

The quality of education is a crucial issue that continues to receive attention in facing the challenges of globalization, digitalization, and the demands of 21st century competencies. Quality improvement efforts are not only related to the quality of students' learning outcomes, but also concern the role of leadership, management effectiveness, and the implementation of a quality assurance system. This study aims to identify strategies to improve the quality of education that have been studied in the literature for the last five years (2020-2025) and answer two research questions, namely: (1) what quality strategies are predominantly discussed in the literature, and (2) how the role of leadership, strategy management, and quality assurance in supporting the quality of education. The method used is literature review with a qualitative approach. Data was obtained from Google Scholar and Publish or Perish (PoP) databases using the keyword "quality strategy" with a publication year limit of 2020–2025. The search yielded 30 articles, which then through a screening and selection process obtained 5 relevant articles for analysis. The results of the analysis show three main trends: (1) the strategic role of school principals in building a quality culture, (2) the importance of evaluation and implementation of quality management in a sustainable manner, and (3) the synergy of visionary leadership with the quality assurance system  as the basis for sustainable quality. This study concludes that the education quality strategy requires the integration of these three aspects. Going forward, further research is needed to develop integrative models across approaches and broader educational contexts.

This study aims to analyze the effect of service quality, store atmosphere, and word of mouth on repurchase intention of Batik Lochatara Kediri consumers. This research employs a quantitative approach with a causal associative design. Data were collected through questionnaires distributed to 96 respondents who are customers of Batik Lochatara Kediri, selected using accidental sampling. The research instrument was measured using a five-point Likert scale. Data analysis was conducted using multiple linear regression with the assistance of SPSS software, preceded by validity, reliability, and classical assumption tests. The results reveal that partially, word of mouth has a positive and significant effect on repurchase intention, while service quality and store atmosphere do not show a significant effect. However, simultaneously, service quality, store atmosphere, and word of mouth have a significant influence on repurchase intention. These findings indicate that positive consumer recommendations and shared experiences play a more dominant role in encouraging repurchase intention in the context of local batik MSMEs. Therefore, strengthening word-of-mouth strategies is essential to enhance customer loyalty and business sustainability.

This study aims to analyze the effect of asset growth, capital structure, and asset structure on the profitability of PT Astra Graphia Tbk during the period 2016–2023. The research employs a quantitative approach with a causal research design using secondary data derived from the company’s quarterly financial statements. A total of 32 quarterly observations were selected through purposive sampling. Profitability is measured using Return on Equity (ROE), while data analysis is conducted using multiple linear regression. Prior to hypothesis testing, classical assumption tests including normality, multicollinearity, heteroskedasticity, and autocorrelation tests were performed to ensure the robustness of the regression model. The results indicate that asset growth, capital structure, and asset structure simultaneously have a significant effect on firm profitability. However, partially, only asset structure has a significant effect on profitability, while asset growth and capital structure show no significant influence. These findings suggest that efficient asset composition plays a more critical role in improving profitability than mere asset expansion or increased leverage. The managerial implication of this study highlights the importance of optimizing asset structure to enhance the firm’s ability to generate sustainable profits.

This research examines the implementation of green building principles in the design of the Multipurpose Building at SMP–SMA Islam Hidayatullah Semarang, focusing on energy-efficient strategies and spatial comfort based on the GREENSHIP GBCI certification criteria. The study employs a qualitative descriptive method through interviews with the architect, analysis of architectural drawings, interpretation of interior design visualizations produced by Falana Studio, and literature review on sustainable building design. The findings indicate that the building consistently applies passive design strategies, including the optimization of natural lighting through large openings and a central void, the application of cross-ventilation on each floor, and the integration of façade vegetation that reduces surface temperature and improves microclimate performance. Material selection such as GRC panels, HPL, and modular plywood supports long-term durability, while the interior design demonstrates strong visual comfort and ergonomic quality through indirect lighting, neutral color schemes, and activity-based furniture layout. According to the GREENSHIP assessment categories, the building fulfills Energy Efficiency and Conservation (EEC), Indoor Health and Comfort (IHC), Material Resources and Cycle (MRC), and Appropriate Site Development (ASD) criteria. In conclusion, the Multipurpose Building successfully integrates green building principles as an effective approach to energy efficiency and the enhancement of the educational environment.

Relational databases store information in interconnected tables and are widely used for data management and retrieval. However, in certain environments, the original values stored in a relational database cannot be exposed during data retrieval. This limitation creates a challenge because common encryption methods only transform data for storage and do not support mathematical operations needed for value matching. Partially Homomorphic Encryption is a cryptographic approach that allows specific mathematical operations to be performed directly on transformed data without restoring it to its original form. This study proposes the use of Partially Homomorphic Encryption to enable value-based data retrieval while keeping all stored values in their transformed form throughout the entire process. The method relies on homomorphic properties that allow mathematical comparison to be conducted on encrypted data, making the retrieval process possible without revealing the original values. The results show that this approach can perform data retrieval operations in a relational database while preserving the transformed structure of the stored data. The proposed method offers an alternative for environments that require data retrieval without exposing original values and demonstrates the potential of homomorphic techniques in supporting secure and functional data processing in relational database contexts.

Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.

Suhu dan kelembaban merupakan parameter lingkungan yang harus dijaga pada ruang kubikel untuk memastikan peralatan distribusi listrik tetap bekerja secara optimal. Pada multi-kubikel, perbedaan fungsi dan beban menyebabkan karakteristik suhu dan kelembaban pada tiap ruang kubikel tidak sama, sehingga pemantauan secara manual menjadi kurang efektif dan efisien. Penelitian ini bertujuan untuk merancang dan membangun prototype sistem monitoring dan kontrol suhu-kelembaban pada multi-kubikel berbasis Internet of Things (IoT) yang terdiri dari tiga buah kubikel. Sistem ini menggunakan ESP8266 sebagai mikrokontroler utama dan sensor DHT20 sebagai sensor suhu dan kelembaban yang masing-masing dipasang pada kubikel dengan kondisi lingkungan berbeda. Sistem dilengkapi dengan aktuator kipas dan lampu, serta notifikasi real-time melalui LCD dan Telegram. Meskipun kontrol dan monitoring dilakukan secara terpisah pada tiap kubikel, notifikasi kondisi seluruh kubikel terintegrasi pada satu kanal Telegram yang sama. Pengujian kinerja sistem dengan memberikan variasi suhu dan kelembaban yang berbeda untuk tiap kubikel. Kubikel 1 diberi kondisi normal (suhu 35°C-40°C dan kelembaban 50%-70%), kubikel 2 diberi kondisi overheat (suhu di atas 40°C), sedangkan kubikel 3 diberi kondisi overhumidity (kelembaban > 70%). Hasil pengujian menunjukkan sistem mampu melakukan kontrol suhu dan kelembaban dalam ruang multi-kubikel serta mengirimkan notifikasi melalui Telegram dengan tingkat keberhasilan 100% dan rata-rata delay 5,6 detik.

The increasing global energy demand drives the search for efficient and sustainable renewable energy solutions. Solar panels have become one of the most widely used technologies; however, their efficiency remains limited when installed in a static position. This research aims to analyze the performance of a single-axis auto tracking system on a 10WP solar panel integrated with the Internet of Things (IoT) for real-time monitoring, specifically in powering a portable powerbank. The research method employed was a quantitative experimental design with three testing scenarios: powerbank charging using an auto-tracking solar panel, a static solar panel, and conventional household electricity as a comparison. Charging data were collected via an IoT system integrated with the Blynk application in real-time. The results indicate that the auto-tracking system increased charging efficiency by around 10%, compared to only 6% with a static panel in one hour. This performance is nearly equal to household electricity charging, which reached approximately 10–11%. The study concludes that the single-axis IoT-based auto-tracking system significantly enhances the performance of small-scale solar panels and holds strong potential for portable energy solutions in remote areas.

This study aims to examine the effect of profitability ratios, namely Earnings per Share (EPS), Net Profit Margin (NPM), Return on Assets (ROA), and Return on Equity (ROE), on the stock price of PT Ciputra Development Tbk during the 2016–2023 period. The research employs a quantitative approach with a causal research design using secondary data derived from quarterly financial statements and stock closing prices published by the Indonesia Stock Exchange. The data were analyzed using multiple linear regression, supported by classical assumption tests, partial hypothesis testing (t-test), simultaneous testing (F-test), and the coefficient of determination (R²). The results show that EPS, NPM, and ROA do not have a significant effect on stock prices, while ROE has a positive and significant effect. Simultaneously, all profitability variables do not significantly influence stock prices. The coefficient of determination indicates that profitability ratios explain a relatively small proportion of stock price variation, suggesting that stock prices in the property sector are influenced more by external and market-related factors than by short-term profitability indicators. These findings imply that ROE is the most relevant profitability indicator for investors in assessing property sector stocks, while other profitability ratios play a limited role.

This study aims to analyze and evaluate the health level of PT Bank Mega Tbk during the 2016–2023 period using the Risk-Based Bank Rating (RGEC) method. This research employs a quantitative descriptive approach with an evaluative design. The data used are secondary data obtained from audited annual financial statements published by PT Bank Mega Tbk and the Indonesia Stock Exchange. The analytical method refers to regulatory provisions by Bank Indonesia and the Financial Services Authority, covering four assessment factors: Risk Profile (measured by Non-Performing Loan and Loan to Deposit Ratio), Good Corporate Governance (based on self-assessment reports), Earnings (measured by Return on Assets, Return on Equity, BOPO, and Net Interest Margin), and Capital (measured by Capital Adequacy Ratio). Each indicator is assessed according to regulatory criteria and integrated to determine the Composite Rating (PK). The results show that PT Bank Mega Tbk consistently achieved Composite Rating 1 (PK-1), categorized as “Very Healthy,” throughout the observation period. The Risk Profile, Capital, and most Earnings indicators demonstrate strong and stable performance, while Good Corporate Governance remains consistently in the “Healthy” category. However, the Return on Equity indicator shows relatively lower performance compared to other profitability ratios, indicating the need for more optimal utilization of equity. Overall, the findings confirm the bank’s strong financial resilience while highlighting managerial implications related to capital efficiency.

This study aims to analyze the quality control of white crystal sugar production at ABC Sugar Factory using the Statistical Quality Control (SQC) method. The research employed a descriptive quantitative approach with a case study design. The primary data consisted of production volume and defective product data during the 2024 production period, while supporting data were obtained through observation and interviews with the Quality Control department. The analytical tools applied included check sheets, histograms, Pareto diagrams, p control charts, and fishbone diagrams. The results show that from a total production of 190,745.89 tons, defective products amounted to 66.70 tons, representing 0.33 percent of total output. The identified defects consisted of wet sugar at 45 percent, brownish sugar color at 30 percent, and oversized sugar crystals at 25 percent. Defective products occurred only during the first to third production periods, while no defects were observed from the fourth to seventh periods. The p chart analysis indicates that the production process was statistically out of control in the early periods but became stable and controlled in the subsequent periods. From a managerial perspective, these findings provide practical guidance for improving manufacturing quality through enhanced process control, equipment maintenance, and workforce capability development.

This study aims to analyze inventory control of catfish seeds at ABC Company by comparing the conventional inventory method represented by the Economic Order Quantity (EOQ) approach and the Just In Time (JIT) system in order to improve cost efficiency. This research employed a descriptive quantitative approach using a case study design. Data were collected through direct observation, semi-structured interviews with company management, and documentation of inventory and cost records for the 2024 operational period. The analysis method involved calculating optimal order quantities, ordering frequency, delivery frequency, and total inventory costs using EOQ and JIT formulas, followed by a comparative cost efficiency analysis. The results show that the conventional method resulted in a total inventory cost of Rp 75,050,000 per year with high ordering frequency. In contrast, the implementation of the JIT system reduced inventory costs to Rp 18,762,500 per year, achieving a cost efficiency of 72%. These findings indicate that the JIT system is more cost-efficient than the conventional method; however, its implementation requires careful consideration of supplier capacity, logistics readiness, and biological risks associated with live inventory. This study contributes empirical evidence on the applicability of JIT in the aquaculture sector, which has different characteristics from manufacturing industries.

Diabetes mellitus is the second leading cause of death worldwide after cardiovascular disease. This condition causes physical and psychological burdens. Quality of life is influenced by various aspects, including the ongoing special needs of diabetes mellitus patients. Family support is a form of assistance provided by family members to provide physical and psychological comfort when someone is ill. This study aims to determine the relationship between family support and quality of life of diabetes mellitus patients at Santa Elisabeth Hospital Medan in 2024. This type of research is quantitative with a correlational design and a cross-sectional approach. The sampling technique used purposive sampling with a sample size of 80 respondents. Inclusion criteria included patients who had been diagnosed with diabetes mellitus for more than one year, were accompanied by their family, and were able to communicate in Indonesian. Data collection was conducted using the HDFSS questionnaire and the DQOL questionnaire. The results showed high family support and a high quality of life for diabetes mellitus patients. The Spearman statistical test produced a p-value of 0.048 and a correlation of 0.222. Thus, there is a positive relationship between family support and quality of life for diabetes mellitus patients. This means that the higher the family support, the better the patient's quality of life. Based on the results of this study, hospitals are advised to provide education regarding the importance of family support in influencing the quality of life of diabetes mellitus patients.

Cough self-medication was a common practice among the community because it was perceived as quick and practical; however, it posed a risk of irrational drug use when not supported by adequate knowledge. The phenomenon of many customers at Gracia Pharmacy Mengwi Badung purchasing cough medicines without consulting a pharmacist prompted the need for research on the relationship between knowledge level and self-medication behavior. This study aimed to analyze the relationship between the level of knowledge and cough self-medication behavior at Gracia Pharmacy Mengwi Badung. The study used a quantitative descriptive method with a cross-sectional approach. The research population consisted of all customers who purchased cough medicine without a doctor’s prescription, with a total sample of 30 respondents meeting the inclusion criteria through purposive sampling. The research instrument used a questionnaire. Data were collected through direct interviews and observations. Data analysis was conducted using quantitative descriptive techniques. The results showed that most respondents had a good level of knowledge (60%) and demonstrated good self-medication behavior (56.7%). Statistical analysis revealed a positive and significant relationship between knowledge level and self-medication behavior for cough (r = 0.612; p = 0.004).

This community service program is designed to address the problem of low understanding of MA Taruna Islam Kraksaan students regarding the process of psychological development and self-potential. Many students do not understand the rhythm of development, abilities, and past experiences as important components in the formation of identity, which causes a lack of self-confidence, learning motivation, and ability adaptation. The main objective of this activity is to help students understand the laws of developmental rhythm, the law of survival, and the law of self-development so that they can gradually optimize their potential. Using qualitative methods, mentoring is carried out through lectures, group discussions, observations, interviews, and documentation. This ensures that students not only get theory but also engage in a reflective and participatory process. This program really helps improve students' understanding of self-development, as shown by increased self-confidence, motivation to learn, self-reflection skills, and readiness to face academic and social challenges. In addition, students show a more positive and adaptive attitude towards their potential in academic, emotional, and social terms.