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Inductive loads on ships are loads that cause the power factor value to move away from 1.00, especially if the addition of this type of load exceeds the standard and the load is installed unbalanced, it can worsen the power factor value. A low power factor value results in soaring current values and reactive power, which often results in cable insulation burning and reduced efficiency. The aim of this research is to create a tool that can automatically correct low power factor values using a Capacitor Bank, PZEM-004T sensor and ESP32 controller at certain inductive loads and can monitor and record electrical load parameter data from various areas on the ship online and offline. This research uses a trial and error method. Based on the test results, this tool can automatically improve the power factor value of inductive loads in the form of TL lamps and electro motors to above 0.90 and the working current value of TL lamps can be reduced from 0.30-0.31 A to 0.17-0.18 A. Electro motors experience a decrease in current from 0.74-0.76 A to 0.66-0.68 A. This tool is also equipped with a system for monitoring and recording load parameter data using Google Spreadsheet when an internet connection is available. If an internet connection is not available, the recording will be transferred using Micro-SD.

Indonesia is a country located between active earth plates, namely the Eurasian Plate, the Indo- Australian Plate, and the Pacific Plate. These plates are very active plates that move and pose a high risk of earthquake disasters. Therefore, the author wrote an Applied Scientific Work with the title Earthquake Disaster Detection System Using Arduino at the SMI Shipyard port. Earthquake Detection System is made in order to detect earthquake disasters and minimize casualties due to the earthquake disaster. The use of these tools in the world of transportation to detect earthquakes used in coastal areas and port ports located in earthquake-prone areas. The method used is system design to determine the occurrence of an earthquake or vibration detected by the ADXL 355 sensor to reach the output, namely the buzzer and LCD. From that the author makes a tool that can provide warnings to the community or workers in the area to avoid casualties. Earthquake Detection System Using Arduino gives output commands to the buzzer and 220 V lamp. If the vibration is from 2.0 SR, the buzzer and light output will not be active. This system has an accuracy rate of 77.6% and has the largest error rate of 22.4%.

In the midst of job competition between countries in Asia, people with disabilities must also fight for their place in the job market. People with disabilities, who may face physical, mental, intellectual, motor and sensory barriers, face the additional challenge of finding employment commensurate with their abilities and barriers. Although the Indonesian government has made efforts to provide equal rights to people with disabilities through laws and policies, many challenges remain. Many people with disabilities are forced to work in the informal sector with low wages, and low participation. Therefore, research on the career prospects and experiences of individuals with disabilities is important in identifying the obstacles faced and exploring solutions that can improve disability inclusion in the world of work. Literature studies can provide valuable insights into the potential and problems experienced by people with disabilities in finding and maintaining employment, and provide a basis for the development of more inclusive policies and more effective support. By encouraging better accessibility and providing appropriate support services, communities and governments can help people with disabilities develop their potential and achieve success in their careers, while ensuring that work environments become more inclusive for all individuals, regardless of background or physical condition.

The position of humans in the eyes of God is considered equal, but often it is humans themselves who create differences in treatment towards fellow humans. This differential treatment is particularly felt by individuals with physical, mental, or intellectual limitations, known as people with disabilities. Disability is defined as a condition in which someone experiences long-term physical, intellectual, mental, and/or sensory limitations, resulting in obstacles and difficulties in social interaction. This article discusses the challenges and opportunities faced by people with disabilities in the workplace, as well as the government's role in creating inclusive employment opportunities and laws that protect their rights in the workplace. Despite the existence of many laws regulating this matter, people with disabilities often still face discrimination in the workplace. The method used in writing this article is through literature review, involving understanding and learning theories relevant to the topic.

Design and Development of an Internet of Things (IoT)-Based Fish Freshness Detection Device. Guided by Mrs. Henna Nurdiansari, S.T., M.T., M.Sc. and Mrs.  Monika Retno Gunarti, S.Si.T., M.Pd. Indonesia has a great potential in fish production, reaching 12 million tons annually, accompanied by an increase in fish consumption. However, significant challenges arise regarding food safety, especially concerning the sale of non-fresh fish and the presence of formalin. As an innovative solution, a fish freshness and formalin detector based on IoT was developed. This device utilizes the TCS3200 sensor to detect color intensity and the HCHO sensor to detect formalin. This research employed the Research and Development (R&D) method to produce an effective detection device. When the LED is green without a buzzer sound and the LCD displays "Fresh Fish" or "Formalin Free," the fish can be confirmed to be fresh and free of formalin. However, if the LED is red, the buzzer turns on, and the LCD displays "Non-Fresh Fish" or "Fish with Formalin," the fish is considered to be below standard or contains formalin. The device categorizes fish condition into three groups: green (fresh), yellow (less fresh), and red (not fresh), reflecting the fluctuating freshness level. When the HCHO sensor reads a value above 0.5 ppm, the fish is considered to contain formalin, while below 0.5 ppm is considered safe and free from formalin. Therefore, this device can be an effective solution in detecting fish freshness and formalin content, ensuring food safety for consumers.

This study proposes an approach for human fall classification utilizing a combination of Weighted Moving Average (WMA) and Convolutional Neural Networks (CNN) on the SisFall dataset. Falls among elderly individuals pose a significant public health concern, necessitating effective automated detection systems for timely intervention and assistance. The SisFall dataset, comprising accelerometer data collected during simulated falls and activities of daily living, serves as the basis for training and evaluating the proposed classification system. The proposed method begins by preprocessing accelerometer data using a WMA technique to enhance signal quality and reduce noise. Subsequently, the preprocessed data are fed into a CNN architecture optimized for feature extraction and fall classification. The CNN leverages its ability to automatically learn discriminative features from raw sensor data, enabling robust and accurate classification of fall and non-fall events. Experimental results demonstrate the efficacy of the proposed approach in accurately distinguishing between fall and non-fall activities, achieving high classification performance metrics such as accuracy, precision, recall, and F1-score. Comparative analysis with existing methods showcases the WMA-CNN hybrid approach's superiority in classification accuracy and robustness. Overall, the proposed methodology presents a promising framework for real-time human fall classification using sensor data, offering potential applications in wearable devices, ambient assisted living systems, and healthcare monitoring technologies to enhance safety and well-being among elderly individuals.

In the context of the industrial revolution 4.0 and the introduction of new technology, workplace safety has become a crucial aspect, especially in the manufacturing sector. In facing these challenges, it is important for the manufacturing industry to integrate proactive and integrated safety strategies. Employee safety and welfare is not only a moral responsibility, but also reflects the company's commitment to protecting human assets, in accordance with the values and principles of the 1945 Constitution. This research aims to provide a systematic, factual and accurate picture of strategy implementation safety management at PT Denso Indonesia in achieving Zero Accident, in line with Law of the Republic of Indonesia Number 1 of 1970 concerning Work Safety. The research results highlight that most work processes at PT Denso Indonesia have a high level of risk, however, the company has adopted safety management strategies to prevent accidents that are detrimental to employees and the company. In implementing this strategy, PT Denso Indonesia prioritizes national values by considering the principles of the 1945 Constitution. Efforts such as Safety Dojo and SCW are used to improve safety, while technology such as PIR sensors are also applied to prevent accidents. Success in achieving Zero Accident is influenced by consistency, employee participation, and strategy integration into a company culture that is based on national values. Thus, safety in the workplace is not only a goal, but also reflects the spirit of harmony between the interests of the company, employees and the nation, in accordance with the principles of the 1945 Constitution.

Penelitian ini bertujuan untuk mendeskripsikan aspek niali moral pada tokoh-tokoh dan nilai pendidikan karakter dalam cerita rakyat. Penelitian ini merupakan penelitian deskriptif kualitatif dengan metode content analysis (analisis isi). Pendekatan yang digunakan dalam penelitian ini pendekatan psikologi sastra melalui teori psikologi David Krech. Sumber data penelitian adalah: (1) teks cerita rakyat Malin Kundang dan Danau Toba Karya Nuairi dan Rosmilan Pulungan; (2) panduan wawancara; (3) buku literatur yang relevan. Teknik pengumpulan data dengan analisis dokumen dan wawancara. Teknik validasi data dengan triangulasi data dan sumber. Teknik analisis data dengan model analisis interaktif. Berdasarkan hasil analisis dapat disimpulkan bahwa : (1) terdapat empat tingkatan emosi yang mempengaruhi tokoh-tokoh dalam cerita rakyat Malin Kundang dan Danau Toba yaitu: emosi dasar,Emosi yang berhubungan dengan stimulasi sensor, Emosi yang berhubungan dengan penilaian diri sendiri, Emosi yang berhubungan dengan orang lain; (2) terdapat nilai moral yang menonjol berdasarkan karakter pelajar pancasila dalam cerita rakyat Malin Kundang dan Danau Toba yaitu; mandiri, gotong royong,beriman dan bernalar kritis.

Children with visual and hearing impairments experience barriers to communication, and tactile cueing systems present a more effective communication solution for people with multiple sensory disabilities. Researchers used the literature study research method and found references related to the title which were then reviewed as a whole. Tactile sign systems combine sign language and hand touch. As a communication method, tactile sign systems have their own advantages and challenges.

Background: Mental disorders are conditions in which mental functions, thought processes, emotions, feelings, psychomotor and verbal behavior are disrupted which becomes a group of clinical symptoms accompanied by suffering and results in disruption of an individual's humanistic function (Ramadani et al, 2020). One type of mental disorder is schizophrenia, where the main perception disorder in schizophrenic patients is hallucinations. Hallucinations are changes or perceptions that there is unfavorable stimulation from within the individual or from outside the individual accompanied by a reduced, excessive or distorted response (Rustika, 2020). One non-pharmacological implementation strategy for patients with hallucinations is by providing music therapy (Alfionita, 2016). Method: Giving therapy to listen to dangdut music to patients for 4 days is carried out 1 day once therapy for 10-15 minutes. Results: After the intervention of giving menmusic therapy for 4 days, it was found that the patient experienced a decrease in signs and symptoms of hallucinations from initially a score of 8 to 2. Conclusion: Providing dangdut music therapy can help reduce the frequency of hallucinations. This is due to the diversion of the patient's attention from the hallucinatory sounds to the dangdut music he hears. rebuking and music to reduce the symptoms of the hallucinations he was suffering from.

Coffee is one of the leading commodities in the plantation subsector in Indonesia which can compete in quality globally, so coffee has a strategic role in the national economy. Until now, coffee demand shows a positive trend, not only domestic demand but also global demand, which is increasing at a rate of 14% increase in coffee consumption every year. Coffee is an agricultural product that relies on quality and taste aspects. The quality and taste of coffee is influenced by many factors, one of which is the level of ripeness of the fruit at harvest time. Improper harvesting will affect the quality and taste of the coffee, for this reason it is necessary to test the sensory characteristics of Robusta Coffee based on the level of fruit ripeness. The research used a Completely Randomized Design (CRD) with three (3) treatments based on the composition of fruit maturity levels, namely 95% red fruit + 5% green fruit (M1); 85% red fruit + 15% green fruit (M2); and 75% red fruit + 25% green fruit (M3). The testing method used is a cupping test which follows SCA (Specialty Coffee Association) rules with 20 semi-trained panelists. Based on the Robusta coffee cupping test, the highest total score of 78.86 was obtained from a composition of 95% red fruit + 5% green fruit (M1), followed by a composition of 85% red fruit + 15% green fruit (M2) with a total score of 77.57. , and the lowest in the composition of 75% red fruit + 25% green fruit (M3) with a total score of 71.38. The results of the panelists' assessment of Robusta coffee at various maturity level compositions are still not included in specialty coffee.

Background: Mental disorders are a description of a syndrome with a variety of causes, many of which are not yet known with certainty and the course of the disease is not always chronic, in general it is characterized by fundamental deviations, characteristics of thoughts and perceptions, as well as the presence of unnatural or blunted affect. One of the mental disorders that occurs is sensory perception disorder: hallucinations. Hallucinations are a loss of human ability to differentiate between internal stimuli (thoughts) and external stimuli (outer world). How to treat hallucinations can be done in pharmacological and non-pharmacological forms. One non-pharmacological therapy that is effective in reducing hallucinations is music therapy. Method: Giving classical music listening therapy to patients for 4 days is carried out 1 day once therapy for 10-15 minutes. Results: Classical music activity therapy nursing intervention greatly influenced the level of hallucinations in patients with hallucinatory auditory sensory disorders. Conclusion: Providing classic music therapy can help reduce the frequency of hallucinations. This is due to the diversion of the patient's attention from the hallucinatory sounds to the classic music he hears. rebuking and music to reduce the symptoms of the hallucinations he was suffering from.

Thermohygrometer is a tool that functions to measure room temperature and humidity. The temperature and humidity in the operating room are set in the temperature range of 19˚C - 24˚C and humidity of 45% - 65%. Therefore, the operating room requires a good temperature and humidity control system to avoid damage to electronic components due to temperatures that are too low and humidity that is too high which causes corrosion. In addition, the influence of high concentrations of medical gas accelerates the rate of corrosion. Because medical gas consisting of CO and CO₂ gas contains oxygen as an oxidant gas. Therefore, a tool such as a Thermohygrometer is needed but equipped with a medical gas reading. This tool aims to read the conditions of temperature, humidity, and medical gas (CO & CO₂) so that it can be analyzed by Electromedics to regulate the air conditioning system. In addition, a Thermohygrometer system is made to allow data access from outside the operating room. The Thermhygrometer tool is made using two sensors, namely DHT22 and MQ-135. DHT22 is used to read temperature and humidity parameters, while the MQ-135 sensor is used to read the concentration of CO and CO₂ gases. The reading results are displayed on the I2C LCD screen. The components are integrated with ESP32 for data processing and as hardware that can be used to create a WiFi connection system. WiFi connectivity is needed to send data to the Blynk application. Testing by calibrating the DHT22 sensor and testing the suitability of the MQ-135 sensor with the gas analyzer. Based on the tests carried out, the temperature error value was obtained at -0.02% and humidity at -0.02%. While the error value was 0.32% for CO gas and -0.16% for CO₂ gas. The error value is still within the tolerance limit

This study presents an advanced structural health monitoring (SHM) system for steel bridges based on wireless sensor networks (WSN) integrated with machine learning algorithms. The proposed system monitors and predicts structural integrity under various load conditions. The research focuses on developing a machine learning model capable of real-time anomaly detection, allowing for early warnings of potential failures. Experimental results from both simulation and field tests demonstrate the system’s effectiveness in prolonging bridge lifespan while reducing maintenance costs.

The Covid-19 virus emerged in late 2019 in Wuhan, China, rapidly spreading to over 190 countries worldwide. Governments implemented various measures, including body temperature checks as an initial step in detecting Covid-19 symptoms. However, manual body temperature measurement using a thermogun has limitations due to direct contact. Therefore, this research develops an automatic, contactless body temperature monitoring system based on Arduino Uno to improve efficiency and reduce physical contact. The system uses an HC-SR04 ultrasonic sensor as a distance limiter for temperature measurement, an MLX-90614 infrared temperature sensor for detecting body temperature, and an Arduino Uno to process data displayed on an LCD in degrees Celsius, with a buzzer as a notification indicator. The test results show that this system achieves a body temperature measurement accuracy of 99.53%, producing results close to the reference device when the object and sensor are within a 1–5 cm range and aligned in a parallel position.

Industrial robotics has transformed the field of mechanical engineering, enhancing precision, productivity, and safety in various industrial applications. This article examines the key challenges and opportunities that industrial robotics presents within mechanical engineering, alongside an exploration of emerging technologies like AI-enhanced robotics, collaborative robots (cobots), and advanced sensor integration. By addressing the complex issues surrounding robotics and highlighting potential advancements, this paper provides insights into the future of robotics in industrial settings.

In the digital age, public road lighting (PJU) monitoring efficiency is becoming essential for effective infrastructure management. The research developed a PJU monitoring system based on LoRa technology and an Arduino microcontroller to monitor the operating conditions of PJU solar panels in real time. The system uses the LoRa 433 MHz module for remote data communication and is equipped with a voltage sensor to monitor batteries and solar panels as well as an ACS712 current sensor to measure current consumption on LED lights. The data is displayed on an I2C 16x2 LCD screen, making monitoring easy. LoRa technology offers the advantages of broad communication range and low power consumption. The development method used is prototyping, including needs analysis, system design, implementation, testing, and maintenance. Test results show that the system works well, with sensors providing adequate accuracy and LoRa communication enabling remote data access. The system improves the efficiency and accuracy of PJU monitoring, as well as reduces time and effort in the monitoring process. Overall, the system is an effective solution for PJU management in the digital age.

The obesity rate among adolescents in Indonesia is increasingly worrying. Obesity in adolescents is affected by a variety of factors, including lifestyle changes that tend to lead to an unhealthy diet and lack of physical activity. To overcome this problem, early prevention efforts are very important, one of which is by measuring Body Mass Index (BMI) as an early indicator of obesity. This research uses a Research and Development (RnD) approach, which aims to develop or improve existing tools to obtain new data and insights into the use of these tools in various contexts. This tool is a development of the previous tool with the HC SR04 sensor to measure height, the Load Cell sensor to measure weight, and the Atmega328p microcontroller to calculate BMI. The main innovation of the tool is the use of a 433 MHz Radio Frequency module that allows wireless communication between height and weight data, increasing the mobility of the tool as it does not require cables and poles as a support. With the result of an error value in the IMT measurement of 1,28%. With an error value of 1.28% in BMI measurements and 93.40% in BMI measurement validity. So from the results of the above percentage, it can be stated that this tool is suitable for use.

Urban workers are increasingly vulnerable to heat stress due to rising global temperatures, especially in cities affected by the Urban Heat Island (UHI) effect. This heat stress poses significant risks to worker health and productivity, exacerbating health issues such as dehydration, heat exhaustion, and heat stroke, while also reducing work efficiency. The study aims to assess the effectiveness of green rooftop designs as a mitigation strategy for heat stress in urban workplace environments. Green rooftops are increasingly seen as a sustainable solution for urban heat management, offering benefits in temperature regulation, energy efficiency, and overall worker well-being. This study examines various heat stress mitigation strategies, including green roofs, industrial fans, and shading systems, focusing on their comparative effectiveness in reducing temperatures and improving worker comfort. The research involved environmental temperature measurements inside and outside urban workplaces, the use of wearable heat sensors to monitor workers’ heat stress levels, and building energy simulations to predict the impact of green rooftops on indoor climate control. Results indicate that green rooftops reduced workplace temperatures by an average of 3.8°C and decreased heat-stress-related complaints by 35%. In comparison to industrial fans and shading systems, green rooftops provided superior long-term relief, reducing heat stress and improving both worker productivity and environmental quality. The findings support the integration of green rooftops into urban workplace designs as a viable climate adaptation strategy. Future research should explore optimizing green rooftop designs for different climates and assessing their long-term benefits for worker health and urban resilience.

Applying ergonomic principles in work tool design for manufacturing industries is a crucial factor in improving productivity while maintaining worker health. This research aims to analyze the effectiveness of adaptive work tool design models based on cognitive and physiological ergonomic principles, identify interaction patterns between workstation design and operational performance, and develop a conceptual framework for integrating ergonomic principles into production cycles. The research method adopts a cognitive-physiological approach with qualitative analysis of human-machine interactions, biomechanical simulations using digital human modeling, and muscle load measurements through electromyography. Implementation was conducted using a participatory ergonomics approach and IMU sensor-based real-time monitoring systems. Results show that using materials with controlled deformation capabilities (15-20%) in work tools reduces muscle work by up to 27%, while adaptive automation system integration improves assembly accuracy by 18%. Workstations with ergonomic adjustments increase assembly speed by an average of 12%, and low-cost ergonomic interventions effectively improve productivity by 11-15% in resource-limited environments. Longitudinal analysis reveals that evidence-based ergonomic investments yield a 230% ROI through increased productivity, reduced injury compensation costs, and decreased employee turnover. IMU-based posture monitoring systems integrated with adaptive feedback loops reduced musculoskeletal disorder incidents by up to 41%. In conclusion, ergonomic optimization based on cognitive-physiological principles creates synergy between production efficiency and worker well-being, making it an essential component in achieving sustainable productivity.