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The emergence of Internet of Things (IoT) technology has opened up considerable possibilities for automation systems aimed at enhancing energy efficiency in both home and office settings. This study focuses on the creation and deployment of an IoT-driven Smart Home system utilizing ESP32 for the automatic and manual supervision and regulation of electrical appliances within the Employee Dormitory of the Institute for Lecturer Performance Development (LPKD). The established system employs a Passive Infrared (PIR) sensor for detecting human presence and a Light Dependent Resistor (LDR) sensor to assess the intensity of light in the room. The data from these sensors is analyzed by the ESP32 microcontroller, which controls lights and fans automatically through relay modules based on the surrounding conditions. Furthermore, the system is linked to the Blynk application and the Telegram Bot API to enable remote operation and immediate notifications. The methodological approach taken in this research is Research and Development (R&D) employing a prototyping method. The assessment outcomes show that the system functions reliably, with success rates for sensor detection and appliance management exceeding 95%. The introduction of this system aims to boost electrical energy efficiency, improve user experience, and facilitate the adoption of IoT-centered smart facility management within the LPKD framework.

Dividend policy is one of the key indicators used by investors to assess the stability and financial performance of banking companies. This study aims to analyze the effect of financial performance on the Dividend Payout Ratio in conventional banks in Indonesia during the 2021–2024 period. Financial performance is proxied by liquidity, Leverage, and profitability. This research employs a quantitative approach with an associative research design. The population consists of 43 conventional commercial banks listed on the Indonesia Stock Exchange up to 2024. The sampling technique uses purposive sampling, resulting in 24 conventional banks with a total of 96 panel data observations. The data used are secondary data obtained from the companies’ annual financial statements and analyzed using multiple linear regression. The results show that liquidity, proxied by Loan to Deposit Ratio (LDR), has a positive and significant effect on the Dividend Payout Ratio; Leverage, proxied by Debt to Asset Ratio (DAR), has a negative and significant effect on the Dividend Payout Ratio; and profitability, proxied by Return on Assets (ROA), has a positive and significant effect on the Dividend Payout Ratio. Furthermore, liquidity, Leverage, and profitability simultaneously have a significant effect on the Dividend Payout Ratio in conventional banks in Indonesia. This study indicates that the company’s financial performance is a key factor in determining dividend policy in the banking sector.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

This study presents an innovation design for an Internet of Things (IoT)-based watering and liquid fertilizer control system for chili plants using a NodeMCU ESP32. The main problem addressed is the manual watering and fertilizing process, which makes it difficult for farmers to monitor soil moisture, temperature, air humidity, and light intensity in real time. The recommended method used in this draft is Research and Development (R&D) with a prototyping approach because the study focuses on designing, building, integrating, and testing an IoT device through iterative stages. The system is designed using a soil moisture sensor, DHT11, LDR sensor, two-channel relay, two 12 V DC pumps, 16x2 I2C LCD, and the Blynk Mobile application for remote monitoring and control. Sensor data are transmitted to Blynk as percentage values and plant condition statuses, while the water and fertilizer pumps can be controlled using virtual buttons. The control logic defines the optimal condition for chili plants based on soil moisture of 60-80%, temperature of 25-30°C, air humidity of 60-80%, and light intensity of 50-90%. Prototype documentation and functional testing data will be completed in the next stage.

This study aimed to analyze the effect of credit risk on profitability with liquidity as a mediating variable in banking companies listed on the Indonesia Stock Exchange (IDX) during 2022–2024. The study employed a quantitative approach with an explanatory research design. Secondary data were obtained from annual financial statements, and the sample consisted of 31 banking companies selected through purposive sampling from a total of 47 companies. The research variables included credit risk as the independent variable, profitability proxied by Return on Assets (ROA) as the dependent variable, and liquidity proxied by the Loan to Deposit Ratio (LDR) as the mediating variable. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) through the assessment of the measurement model and the structural model. The results indicated that credit risk did not affect profitability and did not affect liquidity, while liquidity affected profitability. The findings also demonstrated that liquidity did not mediate the relationship between credit risk and profitability. The study implied that liquidity management played an important role in supporting bank profitability, whereas the influence of credit risk on profitability during the study period was likely driven by other factors outside the proposed model. This study provided empirical evidence on banking performance dynamics in 2022–2024; however, generalization should have been made cautiously due to the limited observation period and the variables included.

Penelitian ini bertujuan menganalisis pengaruh Good Corporate Governance (GCG), Financial Risk, dan Capital terhadap Opini Audit, dengan Earning sebagai variabel intervening dan Reputasi Kantor Akuntan Publik (KAP) sebagai variabel moderasi, pada perusahaan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2020–2024. Penelitian menggunakan pendekatan kuantitatif kausal dengan data panel dari 15 bank yang dipilih secara purposive sampling, sehingga diperoleh 75 observasi bank-tahun. GCG diproksikan dengan jumlah Dewan Direksi dan Komite Audit; Financial Risk diproksikan dengan Non-Performing Loan (NPL) dan Loan to Deposit Ratio (LDR); Capital diproksikan dengan Debt to Equity Ratio (DER) dan Debt to Asset Ratio (DAR); Earning diproksikan dengan Return on Assets (ROA) dan Return on Equity (ROE); dan Opini Audit diukur dengan skor 1–5 berdasarkan jumlah catatan tambahan auditor. Data dianalisis menggunakan Partial Least Squares Structural Equation Modeling (PLS-SEM) berbantuan SmartPLS dengan konstruk formatif dan prosedur bootstrapping 5.000 resample. Hasil penelitian menunjukkan Financial Risk dan Capital berpengaruh negatif signifikan terhadap Earning, sedangkan GCG tidak berpengaruh signifikan. GCG dan Capital berpengaruh signifikan meskipun dengan arah negatif terhadap Opini Audit, sementara Financial Risk dan Earning tidak berpengaruh signifikan. Earning tidak terbukti memediasi pengaruh variabel eksogen terhadap Opini Audit, dan Reputasi KAP tidak terbukti memoderasi hubungan Earning-Opini Audit, meskipun berpengaruh positif secara langsung terhadap Opini Audit. Temuan ini mengindikasikan bahwa pada industri perbankan yang sangat teregulasi, opini audit lebih ditentukan oleh kewajaran penyajian laporan keuangan dan kredibilitas auditor dibandingkan kinerja profitabilitas semata.

This community service program was carried out to enhance the technological literacy of residents in Telang Sari Village through the introduction of an automated street lighting system based on sensor technology. The system presented to the community utilizes an Arduino microcontroller integrated with an LDR sensor to detect light intensity and an ultrasonic sensor to identify the presence of nearby objects. With this configuration, the street lights operate automatically: they turn on when the environment becomes dark and an object is detected, and turn off when the surroundings are bright or no activity is detected in the sensing area. The program activities included device installation, technical explanation, and a live demonstration to ensure that residents comprehended its functions and benefits. Additionally, the use of solar panels was introduced as an alternative power source to support sustainable operation without relying on grid electricity. The results of the program showed a positive response from the community, as the system was considered effective in improving nighttime safety, reducing energy consumption, and requiring minimal maintenance. Overall, this activity successfully increased public understanding of automation technology and renewable energy applications suitable for rural community development.

This study aims to design and test a Dual Axis Solar Tracker to improve the energy absorption efficiency of solar panels on ships. The system is designed with a two-axis movement mechanism (horizontal and vertical) using a linear actuator motor controlled by Arduino Nano and ESP32. Testing was conducted on a 20 WP solar panel in Surabaya for 30 days, divided into three methods: 10 days using an LDR sensor, 10 days using an RTC, and 10 days in static conditions without a sensor. Voltage, current, and power data were measured every 30 minutes at 07.00–17.00 WIB. The test results show that the RTC method provides the highest and most stable output power, according to the sun's movement patterns in tropical areas, while the LDR method responds quickly to changes in light intensity but is less stable in changing weather. Static installation produces the lowest power. This system is able to maintain the panel orientation perpendicular to the sun's rays, thus increasing energy efficiency compared to static systems. These findings prove that dual-axis solar tracker technology, especially with an RTC sensor, is effective in dynamic maritime environments and can be a practical solution for optimizing renewable energy on ships. The most effective results using RTC sensors demonstrated the most stable and high power output, especially since the sun in tropical areas like Surabaya moves fairly consistently following a cyclical pattern. The success of this system not only increases the energy output of solar panels but also provides a practical solution for renewable energy applications in tropical climates.

This community service program was carried out to enhance the technological literacy of residents in Telang Sari Village through the introduction of an automated street lighting system based on sensor technology. The system presented to the community utilizes an Arduino microcontroller integrated with an LDR sensor to detect light intensity and an ultrasonic sensor to identify the presence of nearby objects. With this configuration, the street lights operate automatically: they turn on when the environment becomes dark and an object is detected, and turn off when the surroundings are bright or no activity is detected in the sensing area. The program activities included device installation, technical explanation, and a live demonstration to ensure that residents comprehended its functions and benefits. Additionally, the use of solar panels was introduced as an alternative power source to support sustainable operation without relying on grid electricity. The results of the program showed a positive response from the community, as the system was considered effective in improving nighttime safety, reducing energy consumption, and requiring minimal maintenance. Overall, this activity successfully increased public understanding of automation technology and renewable energy applications suitable for rural community development.

Cracker drying process is considered inefficient because it still depends on weather factors and manual supervision, which can affect the quality of the production results. To overcome this, a smart shrimpcrackerdryingdevicebasedonan Arduino Uno microcontroller with an automatic closing mechanism and an automatic container has been designed and built. This system is equipped with a rain sensor and an LDR sensor to detect weather conditions around the device, as well as a DHT11 sensor to monitor humidity in the cracker storage container. In addition, an ultrasonic sensor is used to automatically regulate the movement of crackers into the storage container after the drying process is complete. A DC motor controlled by a BTS7960 driver functions to move the cover roof and the cracker transfer mechanism, while a limit switch is used to limit the motor movement.Based on the test results, this device can work automatically Shrimp crackers are one of the typical food products widely produced by the people of Bunga Karang Village, Tanjung Lago District, Banyuasin Regency. The traditional shrimp following changes in environmental conditions, thereby increasing the efficiency of the drying process and maintaining the quality of shrimp crackers produced by the residents of Bunga Karang Village.

This study aims to provide a comprehensive overview of the implementation of green finance and its relationship with the financial performance and profitability of banking institutions in Indonesia. Although sustainable finance policies have been continuously strengthened by regulators and stakeholders, the contribution of green financing to overall banking performance is still developing gradually, making it important to conduct a more focused and systematic analysis of its effectiveness. This research specifically aims to describe the application of green financing practices, assess financial performance conditions, and analyze bank profitability during the 2020–2024 period. The study employs a descriptive quantitative approach using secondary data on green financing distribution, financial performance indicators such as the Capital Adequacy Ratio (CAR), Non-Performing Loans (NPL), and Loan to Deposit Ratio (LDR), as well as profitability measured through Return on Assets (ROA). The findings indicate that the implementation of green finance has the potential to enhance long-term financial stability and improve profitability in the banking sector. This study implies that expanding green financing can serve as a relevant and sustainable business strategy for the banking industry while simultaneously supporting national sustainability and environmental development objectives.

The rapid advancement of the Internet of Things (IoT) has spurred the development of intelligent home systems that optimize energy use and enhance user convenience. One essential component of a smart home environment is an adaptive lighting system that can operate based on environmental conditions. This study aims to design and implement a microcontroller-based automatic lighting system that responds to variations in ambient light intensity and supports further integration with IoT-based monitoring. The system is built using an Arduino Atmega328P microcontroller, a Light Dependent Resistor (LDR) sensor for illumination detection, and a relay module to control the electrical load. This research employs an experimental design that includes system analysis, hardware assembly, software development, and performance testing. The LDR sensor was tested under bright and dark conditions, producing consistent readings, with an average threshold of 450–500 analog units for light and below 300 units for dark. The system successfully activated the lamp in 100% of dark-condition trials (n=10) and turned it off correctly in all bright-condition trials (n=10). Response time measurements showed that the system processed changes in light intensity in less than 1 second, ensuring real-time adaptability. The findings demonstrate that the proposed design operates reliably, optimizes electricity usage, and reduces the need for manual intervention. This study contributes to the development of affordable, energy-efficient, innovative lighting systems. It provides a practical foundation for future work, including full IoT integration with wireless modules for remote control and monitoring.

This study aims to examine the impact of credit risk, liquidity, and operational efficiency on the profitability of Regional Government Banks (BPD) in Indonesia, and to explore the moderating role of female commissioners on the relationship between credit risk and profitability. The research uses a quantitative approach with secondary data from 2020 to 2024, utilizing regression analysis. The findings indicate that liquidity (LDR) and operational efficiency (BOPO) have a significant positive impact on profitability (ROA), while credit risk (NPL) does not significantly affect profitability. The presence of female commissioners shows a negative effect in the direct model, but this becomes insignificant with moderation, suggesting that the influence of gender diversity in banking governance may differ depending on the context. The study contributes to the literature by highlighting the critical role of liquidity management and operational efficiency in enhancing profitability, and offers practical implications for improving governance and performance in Regional Government Bank.

This study aims to analyze the effect of Non-Performing Loans (NPLs) and the Loan-to-Deposit Ratio (LDR) on bank financial performance, as measured by Return on Assets (ROA), with Net Interest Margin (NIM) as an intervening variable in banking companies listed on the Indonesia Stock Exchange during the 2021-2023 period. The research method used is quantitative research with a causal-comparative approach. The data used in this study is secondary data sourced from the financial reports of banking companies accessible through the official IDX website. The population in this study is banking sector companies listed on the Indonesia Stock Exchange, with a sample of 35 companies selected using a purposive sampling method based on certain criteria. The independent variables in this study are Non-Performing Loans (X1) and Loan to Deposit Ratio (X2), while the dependent variable is Return on Assets (Y) and the intervening variable is Net Interest Margin (Z). Data analysis techniques in this study use panel data regression, classical assumption tests, t-tests, coefficients of determination, and Sobel tests. The results of this study indicate that NPL has no effect on NIM, while LDR has an effect on NIM, NPL has an effect on ROA, LDR has no effect on ROA, NIM has an effect on ROA, NIM does not mediate the relationship between NPL and ROA, and NIM mediates the relationship between LDR and ROA.

Solid financial performance is a crucial foundation for companies to achieve long-term success. In the banking context, financial health assessments are essential, as they directly relate to the stability of the national financial system. Therefore, the Financial Services Authority (OJK) has established standards for evaluating bank soundness using the RGEC method, which includes four key aspects: Risk Profile, Good Corporate Governance (GCG), Earnings, and Capital. This study aims to analyze the soundness level of PT Bank Central Asia Tbk (BCA) during the 2020–2024 period using the RGEC approach. The assessment is conducted by evaluating financial ratios such as Non-Performing Loan (NPL), Loan to Deposit Ratio (LDR), Good Corporate Governance (GCG), Return on Assets (ROA), Net Interest Margin (NIM), and Capital Adequacy Ratio (CAR). The analysis results show that BCA achieved a "very healthy" rating (PK-1) in all RGEC aspects. This reflects BCA's ability to effectively manage risk, implement sound corporate governance principles, and maintain strong profitability and capital. These findings strengthen BCA's position as one of the best-performing banks in Indonesia and demonstrate the company's commitment to maintaining financial stability and customer trust.

This study analyzes the dynamics of Non-Performing Loans (NPLs) in the Indonesian banking sector by examining both internal and external factors affecting financial stability. The variables included in the research are NPL, Loan to Deposit Ratio (LDR), lending interest rate, inflation, Household Debt to Income (HDTI), fintech lending, and Capital Adequacy Ratio (CAR). Using annual secondary data from 2005 to 2024, sourced from the World Bank and Statistics Indonesia (BPS), the study employs a Vector Autoregression (VAR) method. This method includes stationarity tests, optimal lag selection, cointegration tests, Impulse Response Function (IRF), and Forecast Error Variance Decomposition (FEVD). The results show that most variables demonstrate a dominant contribution from their own shocks, although interactions between variables remain significant. The IRF analysis reveals that CAR and HDTI are relatively stable and quickly return to equilibrium, while fintech lending, inflation, and NPLs show more volatile responses, making them more susceptible to external shocks. LDR and lending interest rates are sensitive in the short term but tend to stabilize over the long run. FEVD further indicates that inflation plays a significant role in driving NPL variations, while fintech lending is closely associated with CAR in the long term. The study concludes that the stability of Indonesia’s banking sector is influenced by both internal factors like CAR and LDR, as well as external factors such as inflation, fintech lending, and household debt. Thus, a coordinated approach involving monetary policy, macroprudential measures, and financial supervision is crucial to enhance the resilience of the banking sector against global and domestic economic shifts.

This study aims to analyze the health of the digital banking sector listed on the Indonesia Stock Exchange (IDX) for the period 2022-2024 using the Risk-Based Bank Rating (RGEC) approach, which involves four main aspects: risk profile, good corporate governance, earnings, and capital. The research method used is descriptive quantitative analysis with secondary data. The sampling method was purposive sampling, which includes four digital banks listed on the IDX: ARTO (Bank Jago Tbk), BBHI (Bank Harda Internasional Tbk), BBYB (Bank Neo Commerce Tbk), and AMAR (Bank Amar Indonesia Tbk). The results show that based on the composite value calculations, these digital banks have shown significant improvement, moving from a composite rating of 3 (PK-3) with a "fairly healthy" predicate in 2022 to a composite rating of 2 (PK-2) with a "healthy" predicate in 2023 and 2024. Although improvements have been made in several key areas, such as risk management and profitability, the main challenges still faced by digital banks are liquidity management and credit quality, reflected in the high Loan to Deposit Ratio (LDR) and significant Non-Performing Loans (NPL). This study also emphasizes the importance of strengthening good corporate governance (GCG) principles and more effective risk management to support the sustainability and growth of the digital banking sector in Indonesia. Therefore, digital banks need to focus more on improving liquidity management, credit quality, and enhancing the efficiency of margin and capital management to overcome future challenges and strengthen their position in the digital banking industry.

Banking is a key pillar of the financial system, playing a crucial role as an intermediary between those with excess funds and those in need of financing. In the context of post-pandemic economic recovery in the 2022–2024 period, bank sustainability and resilience, particularly in terms of profit-generating ability, are crucial aspects to consider. This study was conducted to analyze the extent to which capital structure and intermediation efficiency influence the profitability of banks listed on the Indonesia Stock Exchange. Capital structure in this study is proxied by the Capital Adequacy Ratio (CAR), while intermediation efficiency is measured by the Loan to Deposit Ratio (LDR). The profitability indicator used is Return on Assets (ROA), which reflects a bank's effectiveness in utilizing its assets to generate profits. This research methodology uses a quantitative approach through multiple linear regression analysis with secondary data in the form of annual financial reports from 111 banks for the 2022–2024 period. The analysis results show that simultaneously, CAR and LDR variables have a significant effect on ROA. Furthermore, both variables have been shown to contribute positively to increasing bank profitability. In other words, maintaining adequate capital and efficient credit management can strengthen overall financial performance. This finding offers strategic implications for bank management in formulating capital and liquidity management policies. Optimizing these two aspects not only impacts short-term profit achievement but also contributes to the stability and sustainability of banking profitability in the long term. Therefore, banks need to ensure a strong capital strategy coupled with efficient intermediation to be more resilient in facing future economic dynamics.

This study aims to evaluate the financial condition of four private banks, namely Bank Mega, Bank JTrust, Bank Danamon, and Bank Panin listed on the Indonesia Stock Exchange during the period 2015 to 2024. The analysis uses the Risk-Based Bank Rating (RBBR) approach with a quantitative method, where the data source is derived from published annual financial statements. The sampling technique was carried out by purposive sampling with the criteria of financial statements available for the last 10 years and the fluctuations in profits in the last three years. The bank's health assessment is carried out through four main aspects. First, the risk profile is measured using non-performing loan (NPL) ratios and liquidity levels through the Loan to Deposit Ratio (LDR). Second, Good Corporate Governance (GCG) is evaluated based on regulatory compliance and transparency reporting. Third, profitability which includes the return on asset ratio (ROA) and net interest margin (Net Interest Margin / NIM). Fourth, the capital aspect is analyzed through the Capital Adequacy Ratio (CAR). The results of the study show that in general, the four banks are in a healthy condition, especially in terms of capital and governance, which reflects the bank's ability to meet the minimum capital requirements and maintain management practices in accordance with banking industry standards. However, significant differences were found in the risk and profitability aspects. Banks that have less than optimal risk management tend to experience an increase in NPLs, while banks that are more efficient in managing operational costs are able to maintain ROA and NIM at a more stable level. In addition, external factors such as global economic conditions, monetary policy, interest rates, and interbank competition also affect financial performance.

This study aims to analyze the effect of liquidity and credit risk on the profitability of banks listed on the Indonesia Stock Exchange (IDX) during the period 2018–2022. Profitability is measured by Return on Assets (ROA), liquidity is proxied by the Loan to Deposit Ratio (LDR), while credit risk is measured using the Non-Performing Loan (NPL) ratio. The research employs a quantitative approach with multiple linear regression analysis to test the partial and simultaneous influence of the independent variables on profitability. Data were obtained from the annual financial reports of banks published on the IDX, covering a five-year observation period. The results of the analysis show that credit risk, as measured by NPL, has a significant negative effect on bank profitability. This finding reflects that the higher the NPL ratio, the lower the bank’s ability to generate returns on assets, emphasizing the importance of effective credit quality management. In contrast, the liquidity level measured by LDR demonstrates a positive but statistically insignificant effect on ROA. This suggests that although liquidity plays a role in supporting banking operations, its direct impact on profitability is relatively weak when considered independently. However, when examined simultaneously, both credit risk and liquidity significantly affect bank profitability. These findings imply that effective credit risk management is a crucial determinant of financial performance in the banking sector. High levels of non-performing loans can erode bank profits, while optimal liquidity management supports operational efficiency, even if its impact is not strongly significant in isolation. From a managerial perspective, banks need to strengthen monitoring of loan quality, implement more prudent credit policies, and adopt sustainable liquidity strategies to enhance profitability. For regulators, the results highlight the importance of supervising asset quality and ensuring adequate liquidity management in the banking system. This study contributes to the literature on banking performance by providing empirical evidence on the interaction between credit risk, liquidity, and profitability in the Indonesian banking sector.