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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.

The optimal therapeutic impact of local vaginal drug delivery systems is strongly influenced by the physical characteristics balance of Solid Vaginal Suppositories. A comprehensive review regarding the comparison of mechanical profiles, specifically melting time and crushing strength parameters, from various base classifications constitutes the primary objective of this literature research. The implementation of a Literature Review study design was executed through the extraction of empirical data from twelve experimental journals published within the last ten years. Excessively rapid phase transformation characteristics at physiological basal temperatures and low compression resistance were consistently demonstrated by lipophilic bases such as Oleum Cacao. The risk of structural deformation during the distribution process is highly susceptible to unmodified lipid preparations. High surface elasticity accompanied by a delay in molecular hydration duration reaching 120 minutes was recorded in the utilization of Glycerinated Gelatin Base. Structural rigidity exceeding 4 kgF and disintegration time efficiency under 60 minutes were optimally demonstrated by Polyethylene Glycol (PEG) Base. An enhancement in mechanical resistance against external shocks during the storage period is offered by the thorough modification of the synthetic polymer ratios. Therefore, the determination of the PEG base as the most optimal material is recommended to maintain the quality stability of pharmaceutical products. Compendial regulation standards regarding the physical strength testing of pharmaceutical preparations must be obeyed by every institution to ensure long-term treatment effectiveness. Thus, the alignment between active substance release duration and physical preparation endurance can be realized for absolute patient comfort.

Background: Anxiety can affect physiological functions in patients prior to surgery, including increased heart rate and respiration, changes in blood pressure and temperature, relaxation of smooth muscles in the bladder, cold and clammy skin, and dry mouth, which may reduce the patient’s energy level. Psychologically, anxiety can lead to increased postoperative pain, delayed wound healing, increased physical disability, and decreased quality of life. One effective non-pharmacological intervention to reduce anxiety is Benson relaxation therapy. Objective: This study aimed to determine the effect of benson relaxation therapy on reducing anxiety levels in pre operative. Methods: This study used a case study design involving one preoperative patient with anxiety symptoms in the Teratai Ward of Prof. Dr. Margono Soekarjo Hospital, Purwokerto. Benson relaxation therapy was administered for 3 days, twice daily, with a duration of 15 minutes per session. Anxiety levels were measured using the Zung Self-Rating Anxiety Scale (ZSAS) before and after the intervention. Results: The patient showed a decrease in anxiety score from 55 (moderate anxiety) to 40 (mild anxiety) after receiving Benson relaxation therapy. Subjectively, the patient reported feeling calmer, more accepting, and motivated. Objectively, there was a reduction in heart rate and physical signs of anxiety. Conclusion: Benson relaxation therapy is effective in reducing anxiety levels in preoperative patients. This intervention can be used as a non-pharmacological alternative to support psychological recovery of pre-operative patients.

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.

Low productivity and high sick leave in the weaving division of PT XYZ in Yogyakarta are caused by excessive physical and mental workload on Shuttle Loom Unit 2 operators. The productivity of the weaving division of PT XYZ was recorded at only 61.96% (target 75%) with sick leave of 4.17%, indicating operator fatigue. This study measured physical workload using the Cardiovascular Load (CVL) method based on heart rate and mental workload using NASA-TLX, and analyzed the correlation with age and length of service. The results showed a moderate physical workload category (40% light CVL <30, 60% moderate 30-60) at a temperature of 30.5°C, and high-very high mental workload (45% high 50-79, 55% very high ≥80, average EF 79.3) due to strict quality targets (0.5% defects). There is a correlation between CVL and NASA-TLX with age. Recommendations include reducing the daily production target from 100 to 85-88 yards, optimizing ergonomics, and training to reduce EF to 65 and defects to 0.3, to increase effective productivity.

Natural fiber based composite materials are increasingly being developed as an environmentally friendly alternative to synthetic fiber-based composites. This study aims to characterize the thermal and mechanical properties of natural fiber composite materials and evaluate their potential use as sustainable materials. Composites are made using natural fibers as reinforcement and a polymer matrix through a specific molding method. Mechanical property characterization includes tensile tests, flexural tests, and impact tests, while thermal property characterization is carried out using thermal analysis to determine the thermal stability of the material. The test results show that the addition of natural fibers has a significant effect on improving the mechanical properties of the composite, especially tensile strength and elastic modulus, compared to the unreinforced matrix. In addition, natural fiber composites show quite good thermal stability over a certain temperature range, making them suitable for non-structural applications. Based on these results, natural fiber composite materials have the potential to be developed as environmentally friendly materials that have competitive mechanical and thermal performance.

Starfruit (Averrhoa bilimbi L.), commonly known in Indonesia as belimbing wuluh, is widely used as a natural acid in traditional cuisine. It is often processed into dried sour starfruit (asam sunti), which can last 1–1.5 years. However, traditional sun-drying methods are inefficient due to weather dependency, long processing times, and inconsistent product quality and color. This study aims to design and develop a tunnel-type starfruit dryer equipped with a blower system and heat control based on the Arduino Mega 2560. The research employs a quantitative method to evaluate tool performance. The dryer is cylindrical and supported by key components, including LPG gas as a heat source, a blower for air circulation, and a drum holder. Drying is conducted in six stages, each lasting 120 minutes, totaling 12 hours to achieve optimal dryness. Temperature monitoring at three points (T1, T2, T3) uses a MAX6675 sensor with a thermocouple connected to the Arduino Mega 2560, while weight measurement is done manually. Results indicate the tool functions effectively. A denser drying chamber and proper blower installation are recommended to ensure even heat distribution and improved drying efficiency for community use.

Starfruit (Averrhoa bilimbi L.), commonly known in Indonesia as belimbing wuluh, is widely used as a natural acid in traditional cuisine. It is often processed into dried sour starfruit (asam sunti), which can last 1–1.5 years. However, traditional sun-drying methods are inefficient due to weather dependency, long processing times, and inconsistent product quality and color. This study aims to design and develop a tunnel-type starfruit dryer equipped with a blower system and heat control based on the Arduino Mega 2560. The research employs a quantitative method to evaluate tool performance. The dryer is cylindrical and supported by key components, including LPG gas as a heat source, a blower for air circulation, and a drum holder. Drying is conducted in six stages, each lasting 120 minutes, totaling 12 hours to achieve optimal dryness. Temperature monitoring at three points (T1, T2, T3) uses a MAX6675 sensor with a thermocouple connected to the Arduino Mega 2560, while weight measurement is done manually. Results indicate the tool functions effectively. A denser drying chamber and proper blower installation are recommended to ensure even heat distribution and improved drying efficiency for community use.

The computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

The computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

Whiteleg shrimp (Litopenaeus vannamei) is one of the species that is a national superior commodity. The traffic of shrimp between provinces in Indonesia showed a significant increase in the period 2014-2017 with an average growth of 74.48% per year. Things that need to be considered in distribution activities are determining the number of seeds to be transported, providing oxygen in the packaging container, optimizing the use of low temperatures to suppress metabolic activity. This study was conducted with the aim of determining different densities on survival and determining the optimal density for the survival of whiteleg shrimp (Litopenaeus vannamei) in closed transportation for 36 hours. The method in this study used an experimental method with data collection carried out through direct observation. The experimental design used in this study was a Completely Randomized Design (CRD) with 5 treatment combinations. Density consisted of 1500 individuals/2 liters, 2000/2 liters, 2500 individuals/2 liters, 3000/2 liters and 3500 individuals/2 liters. The main parameters observed were survival and the test parameters measured were DO, temperature, salinity, and pH. The results showed that the best performer was in Treatment (B) with a density of 2,000 individuals with a survival rate of 86.02%. The results of the air quality observation study showed that almost all were still at optimal levels to support the survival of whiteleg shrimp (Litopenaeus vannamei) with an average temperature of 26.22°C. pH 7.18 – 8.08. Dissolved oxygen 3.87 – 8.06 ppm.

The white shrimp (Litopenaeus vannamei) is one of the popular marine shrimp species in aquaculture due to its adaptability to various environmental conditions, including a wide range of salinity, and its omnivorous feeding behavior. This study aims to determine the effect of different combinations of stocking density and salinity on the growth rate and post larval survival of vaname shrimp (Litopenaeus vannamei). The research was conducted using factorial planning based on two factors namely stocking density (3, 6, and 9ekor/L) and salinity (15 ppt and 25 ppt). Parameters measured included daily growth rate, absolute weight, survival rate, feed utilization efficiency, and feed conversion ratio (FCR). Water quality observations were also made during the study period including temperature, pH, dissolved oxygen, salinity, and total ammonia. The results showed that the combination of stocking density of 3 fish/L with salinity of 25 ppt gave the best results with a daily growth rate of 0,00664 gram and a survival rate of 86%. This treatment also produced the best feed utilization efficiency of 0.87 and the best FCR value of 1.27, indicating the most efficient use of feed. Water quality parameters during the study were within the appropriate range to support the growth of vanamei shrimp.

Vaname shrimp (Litopenaeus vannamei) has a fast growth rate, good tolerance to a wide range of salinity and temperature, and resistance to several common shrimp diseases. Vaname shrimp has an efficient feed conversion making it more economical to cultivate, and its international market demand is high. The research method used four treatments of fermented soybean meal doses, namely 0% (control), 15%, 25%, and 35%, each with 3 replications. The feed was formulated using Pearson’s Square method targeting 35% protein, and the soybean meal was fermented using tempe yeast method. The observed parameters included daily growth rate (%), absolute weight gain (grams), survival rate (%), feed utilization efficiency (FUE), and feed conversion ratio (FCR). The results showed that the treatment with 25% fermented soybean meal dose gave the best results with a daily growth rate of 6.42%, absolute weight gain of 0.22 grams, survival rate of 90.66%, and the highest feed utilization efficiency of 0.66.

This research investigates intelligent cooling system design for main ship engines operating in tropical waters, integrating advanced machinery engineering with human factors to address thermal management challenges affecting engine performance, reliability, and crew operational effectiveness. Tropical maritime environments impose severe cooling demands through elevated seawater temperatures (28-32°C), high ambient conditions (28-35°C), and accelerated biofouling, reducing conventional cooling system effectiveness by 15-25% while increasing maintenance burdens and operational risks. Through qualitative analysis involving marine engineers, chief engineers with tropical operational experience, cooling system manufacturers, naval architects, automation specialists, and maritime training institutions, this study examines how intelligent cooling systems incorporating variable-speed pumps, adaptive control algorithms, predictive maintenance, and crew-centered interfaces can optimize thermal management while supporting effective human-machine collaboration. Results demonstrate that intelligent systems can reduce cooling energy consumption by 20-35%, improve temperature stability by 50-65%, extend maintenance intervals by 40-80%, and enhance crew situational awareness through intuitive monitoring interfaces, while requiring comprehensive training programs developing technical understanding and operational competencies. Key implementation challenges include control system complexity, sensor reliability in harsh marine environments, integration with existing engine management platforms, crew competency development requirements, and lifecycle cost justification. Findings reveal that successful intelligent cooling system implementation requires holistic sociotechnical approach addressing machinery engineering optimization, automation technology deployment, and human capability development through coordinated design and training strategies. This research contributes to marine engineering literature by providing integrated frameworks for intelligent system design incorporating machinery performance, automation capabilities, and human factors supporting operational excellence in tropical maritime operations.

This research investigates thermal material properties and performance characteristics for high-speed vessel components subjected to extreme thermal stress during sustained high-speed operations. High-speed vessels including patrol boats, fast ferries, and naval craft experience elevated thermal loads from high-power density propulsion systems, aerodynamic heating, and sustained operational intensities creating demanding conditions for structural and mechanical components. Through qualitative analysis involving naval architects, materials engineers, high-speed vessel operators, and component manufacturers, this study examines how material thermal properties affect component durability, performance, and safety while identifying optimal material selections for critical applications. Results demonstrate that advanced thermal materials including high-temperature aluminum alloys, titanium alloys, ceramic composites, and thermal barrier coatings can extend component service life by 40-70%, improve thermal management effectiveness by 25-45%, and enhance operational reliability compared to conventional materials. Key implementation challenges include material cost premiums of 150-300%, manufacturing complexity, limited operating experience, qualification testing requirements, and supply chain constraints. Findings reveal that strategic thermal material selection for critical components represents essential enabling technology for high-speed vessel performance, reliability, and operational availability supporting defense, commercial, and emergency response applications requiring sustained high-speed capabilities. This research contributes to marine materials engineering literature by providing evidence-based frameworks for thermal material selection applicable to diverse high-speed vessel applications.

Pyrolysis is a biomass conversion method into fuel through heating at high temperatures under oxygen-limited conditions. The main factors influencing the pyrolysis process include temperature, residence time, pressure, particle size, reactor design, and the type of pyrolysis employed. This study aims to design an auger-type fast pyrolysis system based on previous research. The design and modeling of the fast pyrolysis equipment were carried out using Autodesk Inventor 2021 software. Based on the calculation and design results, a fast pyrolysis reactor with a multi-stage configuration and a capacity of 5.2 kg was developed. The system consists of a three-stage reactor made of Stainless Steel 304. The reactor is equipped with a screw conveyor for material transport, which is driven by an electric motor. Biomass heating inside the reactor is provided by a clamp heater with an electrical power requirement of 611 W, while biomass cooling is performed using a condenser with a cooling water capacity of 15.586 liters. Based on the structural simulation results, the maximum von Mises stress obtained was 35.4 MPa, the maximum displacement was 0.0528 mm, and the safety factor was 6.07 under loading conditions including an internal reactor pressure of 0.32 MPa, a torsional moment of 1,130 kg·mm, and an operating temperature of 700 °C. These values are within the allowable limits of the material, indicating that the designed reactor is structurally safe and feasible for use.

Coffee husk is an agro-industrial waste with significant potential to be utilized as a renewable energy source through the fast pyrolysis process. This study aims to analyze and optimize gas production from the fast pyrolysis of coffee husk biomass using a screw reactor through single-particle-based Computational Fluid Dynamics (CFD) simulations. The simulations were conducted by varying the operating temperature at 500°C, 600°C, and 700°C to examine pressure distribution, heat transfer, particle temperature, and the formation of pyrolysis products, namely bio-oil, biogas, and biochar. The modeling was performed using COMSOL Multiphysics 6.2 with a numerical approach to represent thermal phenomena and biomass decomposition reactions during the pyrolysis process. The simulation results indicate that increasing temperature significantly affects the rate of heat transfer and the temperature distribution of coffee husk particles. At 600°C, heat transfer and temperature distribution are more uniform compared to 500°C, although heating at the particle core is not yet fully optimal. The pressure distribution shows a stable flow of pyrolysis gas from the bottom to the top of the reactor. In terms of products, increasing temperature leads to a reduction in biochar and bio-oil formation due to the occurrence of secondary reactions, while biogas production increases. The highest gas production is achieved at 700°C, indicating the most optimal condition for maximizing gas yield from fast pyrolysis. Therefore, single-particle-based CFD simulation can be used as an effective tool to understand pyrolysis mechanisms and optimize process parameters in a screw reactor.

This study investigates biomass-derived surface engineering of AISI 1020 steel for electromedical applications using galam wood charcoal and chicken bone waste as carburizing media. Surface modification is required to improve the mechanical performance of low-carbon steel, particularly in applications that demand high wear resistance and long-term durability. A pack carburizing approach was applied using various ratios of biomass-derived media at a treatment temperature of 800 °C for 2 hours. Chemical composition was analyzed using Optical Emission Spectroscopy (OES), surface hardness was evaluated using Micro Vickers hardness testing, and microstructural characteristics were observed using optical microscopy. The results show a significant increase in surface carbon content with increasing fractions of chicken bone powder, indicating its effectiveness as a carbon donor and diffusion promoter. The surface hardness increased from approximately 150 HV in the untreated condition to a maximum of about 860 HV in the treated specimen. Microstructural observations revealed the formation of a distinct carburized layer with increasing thickness and uniformity, consistent with enhanced carbon diffusion and surface strengthening. These findings demonstrate that biomass-derived surface engineering provides an effective and sustainable approach for improving the surface properties of low-carbon steel. The proposed method offers strong potential for environmentally friendly manufacturing of durable and reliable electromedical components.

Rainfall is a crucial factor in the stability of the Earth's ecosystem and has a significant impact on agriculture, forestry, energy, and water management. However, increasingly unstable climate change makes rainfall patterns difficult to predict accurately using traditional methods. The city of Medan, the capital of North Sumatra Province, has a tropical rainforest climate with an average annual rainfall of approximately ±2200 mm and an average temperature of 27°C. Significant weather fluctuations in this area can trigger flooding when rainfall increases and cause water shortages when rainfall decreases (BMKG, 2021). Therefore, a prediction approach that can manage non-linear and dynamic data is needed. Artificial Neural Networks (ANN) are one of the reliable machine learning methods for detecting data patterns. By using the backpropagation algorithm, the model can gradually reduce prediction errors, making it widely used in weather forecasting applications. In this regard, this study uses ANN with the backpropagation method to forecast monthly rainfall in Medan City by utilizing data from 2022–2024 as training and testing data.

This research aims to determine the growth of Rhizophora apiculata mangroves based on height, number of leaves and stem diameter in mangrove nurseries in the Segara Ayu Group, Kedonganan, Bali. The research was conducted for six months, from March to August 2025, using quantitative descriptive methods. Observations were made on 40 plants spread across four demonstration plots, with data collected every two weeks. The environmental parameters measured include temperature and salinity. The results showed that the absolute growth in plant height ranged between 27–31 cm, with relative growth of 27.4–33.7%. The average number of leaves reaches 11 to 18 pieces, while the stem diameter ranges from 1.7–2.7 cm. Environmental conditions at the research location are classified as supporting optimal growth, with salinity of 24–28 ppt and temperature of 28–31°C, In general, Rhizophora apiculata plants show good growth during the nursery period, which indicates that the Segara Ayu location has ecological conditions that are suitable for mangrove rehabilitation activities.