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This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

Typhoid fever is a febrile illness that commonly occurs in urban areas with poor sanitation. It is usually caused by the consumption of untreated water and contaminated food. Because the S. typhi bacterium can survive in water for days, contamination of surface water—such as wastewater, freshwater, and groundwater—serves as the primary cause of typhoid fever. The patient presented to the Emergency Department of Cut Meutia General Hospital with complaints of high fever for approximately 4 days prior to admission, which had worsened over the past 2 days. The fever fluctuated and was accompanied by chills. It worsened at night and was not influenced by weather or temperature. These symptoms were accompanied by vomiting every time the patient tried to eat, nausea, abdominal pain, headache, and weakness. The patient reported vomiting the contents of their meal every time they ate, leading to a loss of appetite. These symptoms began when the patient first developed a fever. The patient also experienced abdominal pain. Spontaneous bleeding was denied. On physical examination, the patient appeared weak but was alert and oriented. On neck examination, palpable enlargement of the thyroid glands was found on the right and left sides of the neck, measuring 2x2 cm, mobile, and soft. On abdominal examination, increased bowel sounds were noted. Vital signs were normal except for the patient’s febrile temperature. Laboratory tests revealed a Tubex blood test result of scale 4 and a positive dengue IgG serology result.

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.

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 was conducted based on the crucial role of diesel generator engines as the primary source of electrical power on board ships, making their operational reliability essential. One of the factors influencing generator engine performance is lubricating oil temperature. Excessive lubricating oil temperature may reduce lubrication effectiveness, increase friction between moving components, and lower engine efficiency. Therefore, this research aimed to identify the causes of high lubricating oil temperature in diesel generator engines and determine appropriate corrective actions. The study employed a descriptive quantitative approach. Data were collected through direct observation, interviews, and documentation during sea practice aboard MV. CL FLANDERS from 4 July 2024 to 5 July 2025. The data were analyzed using simple linear regression to examine the relationship between generator load and lubricating oil temperature. The findings revealed that generator load had a significant effect on the increase in lubricating oil temperature. Under normal operating conditions, the lubricating oil temperature ranged from 60°C to 72°C, while under abnormal conditions it increased to between 68°C and 81°C. The abnormal rise in temperature was mainly caused by cooling system problems, particularly a dirty LO cooler, scale deposits on the sea water pump impeller, and blockage in the cooling capillary pipes. The regression equation under normal conditions was Y = 45 + 0.30X, whereas under abnormal conditions it was Y = 53.5 + 0.30X. Elevated lubricating oil temperature resulted in lower oil viscosity, higher fuel consumption, and reduced diesel generator engine performance. Therefore, regular maintenance of the LO cooler, sea water pump, and continuous temperature monitoring are necessary to maintain optimum engine performance.

Nile tilapia (Oreochromis niloticus) culture requires an efficient and low-cost feeding strategy that can support fry growth and survival. This study aimed to analyze the effects of three types of natural feed, namely silk worms, earthworms, and snails, on absolute length growth, absolute weight growth, and survival of Nile tilapia fry. The study was conducted at the Aquaculture Laboratory, Faculty of Science and Computer Science, Universitas Muhammadiyah Gorontalo, from January 31 to March 2, 2026. An experimental method was applied using a Completely Randomized Design consisting of three treatments and three replications. A total of 45 Nile tilapia fry were reared in 9 plastic containers filled with 10 L of water, with 5 fish in each container. Growth and survival data were analyzed using ANOVA at the 5% significance level, while water quality was analyzed descriptively. The results showed that the type of natural feed had no significant effect on absolute length growth, absolute weight growth, and survival. Descriptively, silk worms produced the highest length and weight growth, with values of 2.99 cm and 6.37 g, respectively. Snails produced the highest survival rate of 86.66%. Water quality remained stable, with temperature ranging from 26.3 to 26.8°C, pH from 7.6 to 7.9, and dissolved oxygen from 5.2 to 5.6 mg/L. These findings indicate that silk worms are potential natural feed for improving growth, while snails support the survival of Nile tilapia fry.

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.

Travertine is a non-marine carbonate rock precipitated from calcium- and bicarbonate-rich waters, commonly associated with hot springs, streams, and lakes in tectonically active regions. This study presents a systematic literature review of travertine deposit characteristics, encompassing mineralogical composition, geochemical signatures, petrographic textures, morphological types, isotopic properties, biotic–abiotic controls on formation, early diagenesis, and petrophysical implications. The synthesis indicates that travertine is predominantly composed of calcite, with aragonite forming under conditions of elevated temperature, high Mg/Ca ratios, and rapid CO₂ degassing. Travertines display exceptional textural diversity, ranging from abiotic crystalline crusts to microbially mediated fabrics such as shrub, peloidal, and stromatolitic structures. Major morphologies include fissure ridges, mounds, terraces, cascades, and slopes, strongly governed by tectonic setting, topography, hydrology, and substrate geology. Stable isotopes (δ¹³C and δ¹⁸O), strontium isotopes, trace elements, and REE patterns effectively constrain fluid provenance and distinguish thermogene from meteogene travertines. Microbial activity plays a crucial role in biomineralization, influencing precipitation rates, crystal morphology, and lamination patterns. Early diagenetic processes occurring during active deposition may significantly modify primary fabrics and geochemical signals. Travertine petrophysical properties exhibit distinctive porosity–velocity relationships, making them valuable analogues for subsurface carbonate reservoirs. This review highlights that travertines record complex interactions among physical, chemical, biological, and geological processes and hold significant value for paleoenvironmental reconstruction and carbonate reservoir studies.

The oil and gas industry requires efficient initial processing to separate reservoir fluids into oil, gas, and water phases. The Separator Unit is the main facility that plays a vital role in the surface facility production stage. This study aims to evaluate the type of separator used, identify control components, and understand the working principles and operational procedures of separators in the Main Production Facility (MPF) area. The methodology used is direct observation and literature studies during the implementation of practical work in July 2024 at PT. Citic Seram Energy Limited, Seram Non Bula Block, Maluku. The observation results show that the type of separator used is a Horizontal Three Phase Separator with tag codes 03-V-001A and 03-V-001B operating alternately. The separation process is carried out based on differences in fluid density utilizing gravity, supported by internal components such as deflector plates, mist extractors, weirs, and straightening vanes. Separator operation is maintained at an operating pressure of around 55 psig to ensure optimal separation efficiency and work safety. The conclusion of this study indicates that effective separator operation requires stable pressure and temperature control as well as routine maintenance to prevent sediment buildup and maintain product quality.

This study aims to design and develop an Augmented Reality (AR)-based application for real-time data monitoring of an automatic weather station at PT. XYZ. The system was developed using a prototyping method, involving five key stages: sensor data acquisition via CBOX devices and the Modbus RTU protocol, data transmission through a Flask-based Web API, storage in a MySQL database, QR code-based target image creation using the Vuforia Engine, and a 3D visualization interface developed with Unity integrated with the Vuforia SDK on Android devices. The system successfully received and stored weather data—such as temperature, humidity, and wind speed—into the MySQL database. The AR application also displayed a stable 3D interface panel over QR code markers, providing real-time data updates through an HTTP-based mechanism. This research demonstrates the successful integration of SCADA, Flask, MySQL, and Unity, enhancing both the functionality and commercial appeal of PT. XYZ’s weather station products. Future research should focus on field testing, cloud network integration, and device compatibility.

Modern infrastructure development often involves the use of mass concrete in large structural elements such as pile caps and foundations. However, massive concrete volumes trigger a significant temperature increase due to the heat of hydration that is difficult to dissipate, posing a risk of thermal stress and structural cracking. This study aims to analyze the temperature rise behavior of mass concrete and evaluate the effectiveness of combining chilled water and fly ash substitution in minimizing these thermal cracking risks.The research method employs a quantitative approach through laboratory testing at PT Adhimix RMC Plant Kaligawe. Specimen blocks measuring 40 x 40 x 100 cm were divided into three variations: normal concrete (BN), concrete with chilled water and 15% fly ash (BAF), and concrete with 25% fly ash (BF). Temperature was monitored using thermocouples at the core and surface for 14 days, then validated using the Portland Cement Association (PCA) formula. The results indicate that the integration of chilled water with 15% fly ash and the use of 25% fly ash significantly controlled extreme temperature surges at the 5th hour. The combination of chilled water and 15% fly ash produced the lowest core temperature of 37.3°C, far below the control concrete which reached 62.4°C. This proves that the combination of precooling methods and fly ash substitution is effective in reducing the heat of hydration during the early hardening period, although the use of 25% fly ash was found to be more stable in maintaining mass concrete temperature.

Sea Surface Temperature (SST) is an important parameter in oceanographic studies because it influences climate dynamics, ocean circulation, and marine ecosystems. Continuous monitoring of SST in open sea areas requires a reliable system capable of operating autonomously. This study develops a solar-powered ocean buoy designed to measure sea surface temperature while simultaneously evaluating the performance of a solar panel as the main energy source. The system uses a DS18B20 sensor to measure SST and an INA219 sensor to monitor the voltage, current, and power of the solar panel, while an ESP32 microcontroller functions as the central data processing unit. The results show that sea surface temperature tends to remain relatively stable with small daily variations, whereas the temperature and performance of the solar panel exhibit larger fluctuations due to direct exposure to solar radiation and changing weather conditions. Solar panel performance also shows significant variations in current and power depending on the intensity of sunlight. To analyze the influence of SST variations on solar panel performance, a statistical analysis using Analysis of Variance (ANOVA) was conducted. The ANOVA results, based on the calculated F-value and the significance value (p-value) at a confidence level of α = 0.05, indicate that SST variations have a significant effect on solar panel performance, demonstrating that the proposed solar-powered buoy system can operate autonomously and has potential for long-term SST monitoring in offshore areas.

Generators are one of the important auxiliary aircraft needed on ships for power generation. During the operation of a diesel generator, continuous rotation occurs resulting in friction and erosion of the moving parts. The supporting factor for the smooth running of a diesel engine is a lubrication system that is supported by good lubricating oil quality, besides that it also needs to be supported by an adequate and good cooling system. The use of lubricants is one of the most important factors to ensure the performance of diesel engines. The lubricant is in charge of maintaining the condition of the engine so that it remains stable. This study aims to analyze the effect of using lubricating oil beyond the operating hours limit on engine heat. Furthermore, it also discusses steps to ensure diesel engine temperatures remain normal. This research was carried out during the practice of sailing on a ship for approximately one year. This study uses a descriptive quantitative research method. The primary data obtained directly utilizes observation methods, and documentation. Secondary data was obtained from existing articles and journals. The data analysis techniques used are descriptive analysis and inferential analysis. The results of this study show that the working hours of lubricating oil use have a significant influence on the increase in the temperature of diesel generator engines as evidenced by hypothesis tests on two engine units, namely AE1 and AE2. In the AE1 unit, a t-value of 18.467 with a significance of 0.000 was obtained, while in AE2 the t-value was 14.289 with a significance of 0.000. The significance value in both units is less than 0.05 so it can be concluded that the working hours of lubricated oil have a significant influence on the temperature of the genarato diesel engine on the ship.

This research aims to analyze the influence of thermal conditions; specifically the temperature difference between the test object and the environment; on the characteristics of air flow and heat transfer around it. The object of this study is a test piece subjected to free air flow under various temperature conditions; focusing on the convection heat transfer phenomenon. The main problem addressed is how temperature variations affect the convection heat transfer coefficient; heat transfer rate; and heat flux; as well as changes in air velocity and pressure profiles. Therefore; the objective of this research is to quantitatively compare and assess these thermal and fluid parameters through an experimental study approach and Computational Fluid Dynamics (CFD) simulation. The methodology involves direct measurement of temperature and pressure parameters under low and high-temperature conditions; which are then processed to determine the convection coefficient (); heat transfer rate (); and heat flux (). The main findings indicate that at low-temperature conditions; the heat transfer coefficient () was found to be 53.26 ; the heat transfer rate () was 24.99 W; and the heat flux () was 537.87 ; with a pressure drop of 0.86 Pa. In conclusion; thermal conditions play a crucial role in determining the dynamics of air flow and the efficiency of heat transfer; the greater the temperature difference (); the higher the potential heat transfer rate; establishing a strong correlation between thermal conditions and the convection phenomenon.

Heating, Ventilating, and Air Conditioning (HVAC) systems often suffer from significant energy wastage due to their inability to adapt to real-time environmental changes, leading to high operational costs. Although Proportional-Integral-Derivative (PID) controllers are widely used for their simplicity and reliability, they struggle to handle the complex dynamics of modern environments, requiring advanced optimization to enhance efficiency. This study aims to optimize PID controllers by integrating the Queen Honey Bee Migration (QHBM) algorithm to improve HVAC performance, energy efficiency, and adaptability. The research method employs an experimental approach that compares the performance of conventional PID controllers with PID controllers optimized using the QHBM algorithm under dynamic environmental conditions. The results show that the PID-QHBM system significantly outperforms the conventional PID system, achieving a rise time of 0.2649 seconds and a settling time of 1.6874 seconds with an almost negligible steady-state error of 9.4991e-08. Although it experiences a slight overshoot of 16.3810%, the system stabilizes quickly and maintains the target temperature efficiently. In contrast, the conventional PID controller exhibits slower response characteristics, with a rise time of 1.3730 seconds, a settling time of 2.5144 seconds, and a larger steady-state error of 0.0361. This study demonstrates that integrating the QHBM algorithm into PID controllers provides a more effective solution for real-time temperature control, offering substantial improvements in energy efficiency and system performance. The findings contribute to advancing intelligent HVAC control systems that can better adapt to environmental variations while minimizing operational costs.

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.

The steering gear is a vital component in ship operations, functioning to control the ship’s direction accurately. The reliability of this system highly depends on the performance of the hydraulic system, where the mechanical seal plays a key role in maintaining system pressure and preventing oil leakage. This study aims to identify the main factors causing mechanical seal damage and analyze its impact on the performance efficiency of the steering gear AHTS Logindo Stamina. Qualitative data were obtained through participatory observation and in-depth interviews with the second engineer. Meanwhile, quantitative data were gathered by measuring technical parameters such as oil pressure, operating temperature, and rudder movement time, which were then compared with SOLAS standards. This damage results in oil leakage through the mechanical seal gap, abnormal noise in the hydraulic system, and a significant decrease in working pressure of -25,86%. The operational impacts include the occurrence of steering gear failure alarms, decreased hydraulic efficiency of 25.87%, and the risk of system failure that could endanger ship maneuverability. This study recommends preventive maintenance through oil quality monitoring, environmental condition control in the steering gear room, and periodic mechanical seal replacement in accordance with operational standards to maintaining optimal steering system performance.

Vannamei shrimp (Litopenaeus vannamei) is one of the most important aquaculture commodities with high economic value and strong market demand. The transportation of broodstock shrimp is a critical stage that may affect survival due to decreased oxygen levels and water quality deterioration. High stocking density during transportation can accelerate oxygen depletion and increase metabolic waste, leading to higher mortality. This study aimed to determine the effect of different packing densities on the survival rate of broodstock shrimp during 12 hours of transportation. The experiment used four treatments with densities of 6, 8, 10, and 12 shrimp per bag, each with six replications. Observed parameters included temperature, dissolved oxygen (DO), and survival rate. The results showed that lower stocking density produced higher survival rates, with the best result obtained at 6 shrimp per bag. Water quality remained within acceptable limits, although oxygen levels decreased with increasing density. Therefore, proper stocking density is essential to maintain shrimp survival during transportation.  

The performance of asphalt mixtures is strongly influenced by the composition of their constituent materials, particularly aggregate size and mixing temperature during production. In many tropical and subtropical regions, asphalt pavements frequently experience rutting, reduced stability, and changes in viscoelastic properties due to high environmental temperatures and heavy traffic loads. These conditions can significantly affect pavement durability, making it essential to produce asphalt mixtures that meet established technical standards. This study aims to analyze the effect of variations in aggregate size distribution and mixing temperature on the Marshall characteristics of Asphalt Concrete Wearing Course (AC-WC) mixtures. The research employs the Marshall test method to evaluate the load-bearing capacity and stability of hot asphalt mixtures and to assess their compliance with ASTM/SNI standards. The results indicate that mixtures with standard aggregate gradation achieve stability values of 985 kg at 120°C, 1055 kg at 140°C, and 1107 kg at 160°C. As mixing temperature increases, flow values decrease, while the Marshall Quotient (MQ) increases, indicating improved stiffness. Higher temperatures also enhance compaction, reducing VIM and VMA while increasing VFA. Conversely, non-standard aggregate gradations result in several parameters failing to meet ASTM/SNI requirements, confirming that standard gradation produces superior asphalt performance.

Rice plants (Oryza Sativa L.) are the main staple food commodity in Indonesia, as most of the Indonesian population relies on rice as their primary food. One of the causes of low rice production in Indonesia is that farmers generally cultivate rice improperly, such as in land preparation or land selection. Land suitability in rice cultivation greatly affects crop productivity. A process that can support decisions regarding rice land suitability is the development of a Decision Support System (DSS) website using a combination of the Simple Additive Weighting (SAW) method and the Technique for Order Performance of Similarity to Ideal Solution (TOPSIS). This combination is performed by taking the average (µ) of the final results from the SAW and TOPSIS methods. The final scores of each method are calculated separately, and then the average (µ) of these two results is taken to obtain the final ranking of the alternatives. The data used to determine the suitability of rice land is based on five criteria: soil type, soil pH, rainfall, temperature, irrigation and water supply. The alternative data used in the study includes six alternatives: Sungai Kunjang, Sambutan, Samarinda Utara, Palaran, Loa Janan Ilir, and Samarinda Seberang. The aim of this research is to provide information on alternative solutions to farmers or farmer groups in determining rice land suitability. The results of the combination of the SAW and TOPSIS methods show that the alternative with the highest final score is Samarinda Utara (A3), with a final score of 0.7337. Meanwhile, the alternative with the lowest final score is Sambutan (A2), with a final score of 0.4402.