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The consistent decline in cucumber production in Indonesia indicates limitations in conventional cultivation systems, particularly due to land scarcity and inefficient resource management. This condition has encouraged the development of hydroponic systems as a more controlled and productive cultivation alternative. This study aims to critically analyze the key factors determining the success of hydroponic cucumber cultivation and to identify the most influential management aspects in improving yield. The method employed is a literature review, examining various recent studies related to hydroponic systems, nutrient management, growing media, and environmental factors. The results show that the advantages of hydroponics lie not only in land and water efficiency but also in the ability to precisely control growth variables. However, optimal productivity highly depends on the proper integration of nutrient management, particularly the regulation of pH, electrical conductivity (EC), and nutrient balance, as well as the control of environmental factors such as temperature, humidity, and light intensity. Inaccuracy in a single component can significantly reduce plant performance, even when other factors are optimal. Therefore, an integrated approach combining nutrient and environmental management simultaneously is essential to enhance hydroponic cucumber productivity. This study confirms that hydroponics has strong potential as a strategic solution to support sustainable agriculture amid land limitations in Indonesia.

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 discusses the design and simulation of an automatic lighting system based on a photodiode sensor using an Arduino Uno microcontroller as the main controller. The system is designed to detect changes in ambient light intensity and automatically control the lamp without human intervention. The photodiode sensor is used as a light detector that converts light energy into an analog electrical signal, which is then processed by the Arduino to determine bright or dark conditions. The output from the Arduino subsequently controls a relay module that functions as an electronic switch to connect or disconnect the current to the light bulb. The research method employed is an experimental approach, which includes system planning, hardware design, software programming, simulation using Proteus, and system performance testing. The simulation results indicate that the system operates as expected, where the lamp automatically turns on when the light intensity decreases and turns off when the ambient brightness increases. This system is expected to improve electrical energy efficiency and provide ease of operation for lighting control, particularly in public facilitiesand workplace environments.

Nitrogen is an essential element for soybean growth, particularly in the formation of vegetative organs and seed protein. The nitrogen requirement of soybean plants varies according to their growth stages. This study aimed to quantify nitrogen levels in soil and plant tissues of Anjasmoro soybean variety over a 13-week cultivation period. Observations were conducted weekly by collecting soil and plant samples from three randomly selected polybags. Nitrogen analysis was performed using a colorimetric Kjeldahl method. The results showed that nitrogen supply was obtained not only from soil media and fertilizers, but also from biological nitrogen fixation facilitated by symbiotic microbes forming root nodules as well as non-symbiotic soil microbes. The lowest total soil nitrogen content was recorded at 0 weeks after planting (WAP) at 0.20%, while the highest was observed at 7 WAP at 0.82%. The lowest total nitrogen content in plant tissue occurred at 8 WAP at 1.80%, whereas the highest was recorded at 4 WAP at 8.07%. Soybean plants experienced etiolation due to suboptimal light intensity, resulting in a vegetative phase that was prolonged by two weeks. Nitrogen uptake during this extended vegetative period reached 4.6%. The average total nitrogen absorbed by the plants during cultivation was 2.881 g per plant, while total nitrogen accumulation in the system increased by 26.285 g per plant.

This study aims to analyze the influence of the work environment on employee productivity at PT Harmoni Reka Cipta. The research employs a descriptive c method using Spradley’s approach, which includes place, actor, and situation. Informants were selected based on inclusion and exclusion criteria, resulting in one key informant and four main informants relevant to the data requirements. Data were collected through in-depth interviews and field observations. The research findings, based on NVIVO analysis visualized through a word cloud, indicate that the most dominant aspect in discussions of the work environment is workplace facilities, followed by work relations, work atmosphere, and operational constraints. Interviews revealed that lighting and coworker relationships are generally in good condition; however, challenges remain, including limited workspace, insufficient facilities, and suboptimal air circulation, especially in the production area. These conditions affect employee comfort, focus, and work effectiveness. NVIVO results related to productivity show that quantity, quality, and timeliness are influenced by a work environment that is not yet fully supportive. Some delays occur due to high production intensity, heavy workloads, and inadequate facilities. This study concludes that improving facilities, reorganizing workspace layouts, and enhancing physical comfort are necessary to support optimal employee productivity

Chrysanthemum is an ornamental plant widely cultivated in Indonesia, with various varieties that have unique and attractive characteristics. Each variety responds differently to changes in light intensity. Providing shade can help regulate the light intensity received by chrysanthemum seedlings during the acclimatization stage. This study aimed to determine the best shade percentage for the acclimatization growth of three chrysanthemum varieties. The research was conducted in the screenhouse of the Faculty of Agriculture, Tanjungpura University, for three months, from October to December 2024. The experiment used a Split Plot Design (Split Plot) with a Randomized Block Design (RBD), consisting of two factors: shade percentage and variety. There were three levels of shade and three chrysanthemum varieties, resulting in nine treatment combinations. Each treatment was repeated three times, with each replication consisting of three sample plants, resulting in 81 experimental units. The shade percentages used were 25% (n1), 50% (n2), and 75% (n3), and the varieties tested were Xanne (v1), Suciyono (v2), and Pinka Pinky (v3). Observed variables included plant survival rate, plant height, stem diameter, internode length, number of internodes, number of flower primordia, leaf color changes, along with supporting data such as temperature, humidity, and light intensity. The results showed that 50% shade was effective in promoting plant height and the number of flower primordia in the three varieties: Xanne, Suciyono, and Pinka Pinky. The Suciyono variety exhibited good vegetative and generative growth under all shade percentages.

Vegetables are an important horticultural commodity in fulfilling community nutritional needs; however, their consumption level in Indonesia remains relatively low, necessitating efforts to increase production. Spinach (Amaranthus sp.) is a promising vegetable due to its short growth cycle, ease of cultivation, and high nutritional value. Limited agricultural land, particularly in urban areas, poses a major constraint to conventional cultivation, thereby encouraging the adoption of alternative technologies such as hydroponics. The hydroponic system, especially the Nutrient Film Technique (NFT), offers efficient use of land and water while enabling better control of plant growth. This review aims to identify hydroponic cultivation techniques for spinach in greenhouse conditions and to analyze factors influencing its success, including nutrient concentration, growing media, pH, temperature, and light intensity. The findings indicate that optimal nutrient concentration ranges from 410–900 ppm, supported by proper environmental and pH management to enhance vegetative growth. The implementation of the NFT system improves production efficiency, resulting in more uniform, cleaner, and higher-quality yields. Nevertheless, challenges remain, including nutrient management, environmental fluctuations, and pest and disease risks. Therefore, proper and sustainable system management is essential to ensure successful hydroponic spinach cultivation.

The commercial sector, especially the hospitality industry, is one of the largest consumers of electrical energy, with energy costs often ranking as the second highest operational expense. This study aims to conduct a specific Electrical Energy Audit in the Office Engineering unit of Aston Denpasar Hotel & Convention Center to optimize electricity usage and improve energy efficiency. The research applies a detailed audit approach with a focus on lighting systems and air conditioning (AC), which are major contributors to energy consumption. The initial stage involves calculating the actual Energy Consumption Intensity (IKE) in kWh/m²/month and comparing the results with ASEAN and SNI standards to determine the efficiency classification of the building. Data collection is carried out through direct field measurements as primary data, using instruments such as a Clamp Meter and Lux Meter. The expected outcome of this study is the identification of detailed Energy Saving Opportunities (ESO), along with the estimation of potential monthly energy cost savings and the calculation of the investment Payback Period.

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 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.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

Plastic waste detection in indoor environments is an essential challenge in the development of intelligent cleaning systems and robotic automation. Small and medium-sized plastic debris is often difficult to identify using conventional methods due to variations in color, shape, and reflectance. This study proposes an image-processing-based approach that combines thresholding and contour detection techniques to improve the accuracy of detecting plastic objects on floor surfaces. The initial stage involves converting the image into a color space that is more stable under varying illumination, such as HSV or grayscale, to reduce the influence of lighting intensity. Subsequently, adaptive thresholding is applied to separate plastic objects from the background by using dynamic threshold values tailored to the image’s conditions. The segmentation results are refined through morphological operations such as opening and closing, enabling the removal of small noise and enhancing the clarity of object boundaries. The core stage of the system employs contour detection to extract object shapes and areas, allowing the identification of plastic waste based on size, perimeter, and specific geometric characteristics. Experiments were conducted under different lighting conditions and various floor types, and the results demonstrate that the proposed approach successfully detects plastic debris with satisfactory accuracy and relatively fast processing time. Therefore, this method is suitable for implementation in robotic cleaning systems, indoor cleanliness monitoring devices, and other computer vision applications requiring real-time and efficient object detection.

The Indonesian Naval Academy (AAL) as a military educational institution requires a large electricity supply to support its operational activities, including in the Sapudi Building of the Engineering Department. This study aims to design a solar energy system to supply the electricity needs for lighting in the building. The method used is Research and Development (R&D) with the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Data collection was conducted through direct observation of building conditions, electrical equipment, and solar radiation intensity data in Surabaya. The research results show that the total electricity requirement for lighting in the Sapudi Building is 4.686 kW with a total of 143 lights (96 neon lights and 47 light bulbs). Based on calculations with an average solar radiation of 5.00 kWh/m²/day, the designed system requires 41 units of Solar PV Lesso HPM 550W panel type with 21.3% efficiency and 9 units of Panasonic LC-P12100NA batteries with a capacity of 100Ah arranged in 3 series and 3 parallel configurations. This study proves that the utilization of solar energy can be an efficient and sustainable alternative solution to reduce dependence on conventional electricity in the AAL environment, while supporting the implementation of renewable energy in Indonesian military institutions.

Reliable and sustainable lighting is crucial for supporting practical activities in a military educational environment, particularly in the Engineering Laboratory Workshop (Labtek) of the Naval Academy. The main problem faced is complete dependence on electricity supply from PLN, which is prone to disruptions and outages, thus impacting the safety and effectiveness of technical activities. Therefore, this research aims to design a solar-powered emergency lighting system as an environmentally friendly and efficient alternative lighting solution. This research uses the Research and Development (R&D) method with a case study approach at the Naval Technology Laboratory (Labtek) of the Naval Academy (AAL). The stages include power requirement analysis, direct observation of building and lighting conditions, selection of solar energy system components, and calculation of solar panel and battery capacity. Based on the analysis results, the total emergency power requirement of 1.96 kW can be met using 100 Wp monocrystalline solar panels and 12V 100Ah batteries for energy storage.The system design consists of solar panels, a solar charge controller, batteries, and LED lights that automatically turn on when the power goes out. Simulation results show that the system is capable of providing emergency lighting for 6–10 hours, depending on sunlight intensity and battery capacity. The implementation of this system not only improves the reliability of Labtek facilities but also supports nat ional clean energy policies and long-term operational cost efficiency.

Energy audits are an essential step in supporting the efficiency of electricity utilization, particularly in large-scale commercial buildings such as shopping malls. This study was conducted to measure and analyze electricity consumption at Pollux Malls Paragon Semarang using a direct measurement approach combined with historical monitoring of energy consumption. The main focus of the audit was on the lighting system and the Heating, Ventilation, and Air Conditioning (HVAC) system from the Basement to the 6th Floor. Measurement results showed that the Energy Consumption Intensity (ECI) ranged between 39.94–45.20 kWh/m²/month, far above the national efficiency standard (maximum 18.5 kWh/m²/month), indicating a highly wasteful energy usage condition. The two main systems contributing to the largest share of consumption were HVAC and lighting, with a combined estimated share exceeding 60% of the total monthly energy use. Based on the analysis, several energy-saving opportunities were identified, including the replacement of energy-efficient lighting (LED), installation of automatic control systems (light, temperature, and timer sensors), and regular maintenance of HVAC systems. With the implementation of technical, managerial, and operational efficiency strategies, it is estimated that energy consumption savings could reach 20–30%, or around 60,000 kWh per month, without compromising visitor comfort.

Enhancing the efficiency of renewable energy on ships is crucial for reducing dependency on fossil fuels. This research employs the Research and Development (R&D) method, aiming to design and implement a solar panel optimization system for battery charging, with a focus on increasing power efficiency and providing real-time performance monitoring. The system is designed using Maximum Power Point Tracking (MPPT) technology to maximize the solar panel's power output. A 200Wp solar panel with dimensions of 1290 x 760 x 30 mm was utilized. Static testing results show that the deployed sensors possess a high degree of accuracy, with an average error of 0.71% for the temperature sensor and only 1.81% for the light sensor used to monitor environmental conditions. Dynamic and system integration tests prove that the MPPT implementation significantly increases power output efficiency by 30.83% compared to a system without MPPT. Furthermore, the system with MPPT charges the battery approximately 27% faster. Additionally, the developed Modbus protocol-based monitoring system enables comprehensive and remote monitoring of key parameters such as voltage, current, temperature, and light intensity via a cloud database. Data communication reliability tests confirmed the system's capability to transmit entire data packets to a Google Sheets database at a periodic interval of 15 seconds without failure. Based on these results, the developed solar panel optimization system is feasible for implementation in maritime environments to enhance the utilization efficiency of renewable energy and the operational reliability of onboard systems.

This research presents the design and testing of an automatic color detection system using TCS3200 color sensor integrated with Arduino Uno microcontroller. The system was developed and tested using Wokwi virtual simulation platform before physical implementation. The TCS3200 sensor converts RGB light intensity reflected from objects into frequency signals, which are processed by Arduino Uno to classify colors into red, green, and blue categories. The system incorporates audio feedback using DFPlayer Mini module to provide sound notifications for detected colors. Testing results show that the system can accurately detect and classify primary colors with frequency-based thresholds: red (R<48 &R>37 & G<95 & G>85), blue (G<75 & G>65 & B<33 & B>23), and green (R<55 & R>40 & B<25 & B>5). The simulation validation demonstrates stable performance with consistent color recognition capabilities, making it suitable for industrial sorting applications and assistive technology for visually impaired individuals.

The availability of electrical energy is one of the important factors during learning activities. However, because the electrical system can be said to be very complicated, starting from the generator center all the way to the consumer, there will most likely be a disruption that causes the flow of power to the consumer to be cut off. One of the factors that affect includes environmental factors, maintenance and other factors, so that the learning process is slightly hampered. The purpose of this research is to maintain electricity supply by automatically switching sources and utilizing renewable energy as a reserve for lighting students' practice rooms. Therefore, a system is needed that automatically regulates the switching of primary sources to backup sources. Automatic Transfer Switch or ATS is a device that automatically switches the main power source from PLN to a backup source such as solar panels by setting the time using Time Delay Relay (TDR). TDR functions to regulate the duration of the power source change operation to meet load needs, especially on small loads such as student practice rooms with a voltage of 220 Volts in one language. The advantage of this system is that it is able to automatically switch electricity supply between PLN and Solar Panels with a controlled time lag. The research method involves the installation of electrical panels and Solar Panels using Solar Charger Controller or SCC, Inverter devices. At the time of the study, the adjustment of the TDR setting to set the time lag on the ATS. SCC settings are carried out to obtain Inputs and Outputs in the optimal battery charging process where the measurement results show that When the load of the incandescent lamp is increased from 50Watt to 300Watt, the current increases from 4.47A to 25.2A, while the voltage decreases from 11.7V to 9.8V. In conclusion, the greater the load, the solar panel voltage decreases and the current increases. The results of the study show that the implementation of the automatic transfer switch system is able to automatically switch the electricity supply between PLN and Solar Panels with a controlled time lag.

Non-Communicable Diseases (NCDs) remain the leading cause of global morbidity and mortality, and one of the chronic conditions included in this group is rheumatoid arthritis (RA). RA is an autoimmune disease that affects the synovial joints, resulting in persistent inflammation, chronic pain, stiffness, and eventual deformities if left untreated. In Indonesia, the burden of RA continues to grow; the prevalence reaches 11.9% based on clinical diagnosis and rises to 24.7% when measured using symptom-based diagnosis. This case study aimed to describe family nursing care for a client with RA through a structured nursing process approach to improve quality of life and family involvement. The study took place in Purwodadi Village, Tonjong Subdistrict, Brebes Regency, focusing on the family of Mr. AS with Mrs. W as the client diagnosed with RA. Data collection involved comprehensive interviews, direct observation, physical examination, and documentation review. Assessment findings included chronic pain with an intensity score of 4, limited mobility, and inadequate family knowledge regarding RA management. Nursing interventions implemented were family education on RA, simple rheumatic exercises tailored to the client’s ability, and the application of warm ginger compresses as a non-pharmacological pain relief method. Post-intervention evaluation showed pain reduction to a score of 2, improved independence in performing light daily activities, and enhanced family understanding and support. In conclusion, family-centered nursing care combined with non-pharmacological interventions can effectively reduce pain, improve mobility, and strengthen the family’s role in supporting RA management.