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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.

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

Congestive heart failure (CHF) is a cardiovascular disease that frequently causes shortness of breath (dyspnea) and negatively impacts patients’ quality of life. The management of dyspnea involves not only pharmacological approaches but also nonpharmacological interventions, one of which is handheld fan therapy, which works by stimulating sensory receptors in the facial area. This study aims to describe the effect of handheld fan therapy on reducing shortness of breath in patients with CHF. This study employed a descriptive design using a case report method on a single 63-year-old female patient diagnosed with CHF. The intervention was conducted over four days, involving the use of a handheld fan for 10 minutes, held at a distance of 15–30 cm from the face and directed toward the nose and mouth. Measurements were taken before and after the intervention using respiratory rate and oxygen saturation as parameters. The results showed a gradual decrease in respiratory rate from 24 breaths/minute to 18 breaths/minute, as well as an increase in oxygen saturation from 91% to 96% during the intervention period. These findings indicate an improvement in breathing patterns and increased respiratory efficiency in the patient. Handheld fan therapy is effective as a nonpharmacological intervention for reducing shortness of breath and improving oxygenation in patients with CHF. This intervention is safe, easy to use, and can be implemented as a complementary therapy in nursing practice.

Background: Carpal Tunnel Syndrome (CTS) is a condition caused by compression of the median nerve at the wrist, resulting in pain, paresthesia, and decreased hand function. This condition is commonly experienced by individuals who perform repetitive wrist activities. Objective: To determine the effectiveness of a combination of neural mobilization exercises and electrotherapy modalities in improving hand function, increasing muscle strength, and reducing pain in a patient with Carpal Tunnel Syndrome. Methods: This study used a case report design involving a 57-year-old female patient (Mrs. Q) who presented with pain and sensory disturbances in the right hand. The intervention was administered for four weeks and consisted of ultrasound therapy, Transcutaneous Electrical Nerve Stimulation (TENS), grip strengthening exercises, and nerve gliding exercises. Outcome measures included pain intensity assessed using the Numeric Rating Scale (NRS), muscle strength evaluated using Manual Muscle Testing (MMT), and functional ability measured using the Wrist Hand Disability Index (WHDI). Results: The evaluation showed a reduction in pain intensity, with resting pain at 0/10, tenderness at 4/10, and movement pain at 4/10. Muscle strength improved from grade 3 to grade 4 based on MMT. Functional ability also improved, as indicated by a 20% reduction in the WHDI score. The combination of these interventions proved effective as a conservative management approach for Carpal Tunnel Syndrome. Conclusion: The administration of ultrasound, TENS, grip strengthening exercises, and nerve gliding exercises over four therapy sessions in Mrs. Q resulted in decreased pain, increased muscle strength, and improved hand functional ability.

The implementation of predictive maintenance supported by SAP Plant Maintenance (SAP PM) at PT Xyz has proven to be effective in reducing machine downtime, lowering maintenance costs, and improving asset reliability. The integration of SAP PM with Industry 4.0 technologies such as IoT sensors, AI-based analytics, and real-time notification systems strengthens operational efficiency and ensures continuous performance. Empirical results show improvements in key performance indicators, including a 20-25% reduction in downtime, a 30% reduction in maintenance costs, an increase in asset availability to 97%, an MTBF extension of up to 511 hours, and an OEE rate of 92.1%. These findings highlight the strategic role of digital predictive maintenance in increasing competitiveness and supporting long-term sustainability in manufacturing operations.

Predictive maintenance (PdM) plays a crucial role in modern industrial systems by minimizing downtime, reducing maintenance costs, and optimizing asset performance. However, many predictive models operate as “black box” systems, limiting transparency and making it difficult for operators to interpret their outputs. This study aims to integrate Explainable Artificial Intelligence (XAI) techniques with Remaining Useful Life (RUL) prediction models to improve both accuracy and interpretability. Various machine learning and deep learning approaches, including Support Vector Machines (SVM), Random Forest (RF), XGBoost, Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN), are employed to predict RUL using real-time sensor data from rotating machinery. XAI methods such as SHAP, LIME, and attention mechanisms are applied to provide human-understandable explanations of model predictions. The models are evaluated based on accuracy, Root Mean Square Error (RMSE), and interpretability scores. The results show that XAI-enhanced models outperform traditional approaches in predictive performance while offering greater transparency. These explanations help maintenance engineers better understand the factors influencing predictions, thereby improving decision-making and trust in the system. Nevertheless, the integration of XAI introduces additional computational complexity, which may pose challenges for large-scale industrial implementation. Overall, this study highlights the potential of combining XAI with RUL prediction to develop more reliable, transparent, and effective predictive maintenance solutions.

Proprioceptive sensor data, including inertial measurement units (IMU), joint encoders, and torque sensors, plays a critical role in state estimation for quadruped robots operating in dynamic and unstructured environments. However, these signals are often degraded by various sources of error, such as high-frequency noise, bias, drift, and contact-induced disturbances, which directly affect estimation accuracy and stability. This study presents a systematic analysis of sensor-specific noise characteristics and evaluates the effectiveness of preprocessing methods tailored to each sensor modality. Specifically, moving average filtering is applied to encoder signals to mitigate noise amplification during differentiation, while first-order low-pass filtering is employed for IMU and torque signals to suppress high-frequency noise. Experimental results on a publicly available quadruped dataset demonstrate that encoder velocity RMSE is reduced by 12.09%, high-frequency energy decreases by 59.63%, and signal-to-noise ratio (SNR) improves by 145.6%. However, variance reductions remain limited (3.39% for IMU and 4.05% for torque), indicating the persistence of impulsive, non-Gaussian noise caused by contact events. These findings highlight that linear preprocessing methods are effective for attenuating high-frequency noise but insufficient for handling non-Gaussian disturbances. The study provides practical insights into the effectiveness and limitations of preprocessing strategies, serving as a foundation for developing more robust signal processing and state estimation frameworks in quadruped robotics.

Abstract. Nutritional problems and low levels of healthy food literacy remain significant challenges in rural communities. The utilization of functional foods derived from locally available ingredients represents a strategic approach to improving community health quality. This community engagement program aimed to enhance the knowledge and skills of residents—particularly housewives and adolescents—through education and hands-on training in the production of banana–sappan wood yogurt as a nutrient-dense functional food alternative. The program was conducted on January 10, 2026, in Pabuaran Village, Serang Regency, using an educational and participatory approach. Activities included the delivery of educational materials on functional foods and the health benefits of probiotics, as well as a practical demonstration of yogurt preparation. Program evaluation was carried out through observation of participant engagement and interactive discussions. The results indicated that participants were able to successfully follow all stages of yogurt production and demonstrated high enthusiasm for the use of local ingredients as healthy food alternatives. The resulting product exhibited acceptable sensory characteristics and an appealing appearance. This activity contributed to improved nutritional literacy and food processing skills and demonstrated potential to support household-level food self-reliance.  

Sweet bread is one of the bakery products that is popular among consumers, but is generally low in dietary fiber. The addition of fiber in bread can improve the health benefits and nutritional quality of the product. High-fiber sweet bread with the addition of corn flour has been formulated and characterized to increase its fiber content. This study aims to determine the sensory characteristics and dietary fiber content of sweet bread products with the addition of corn flour. In this study, using a completely randomized design (CRD) research method, bread was made with several formulations containing a ratio of corn flour and wheat flour, namely (1) 0: 100; (2) 20: 80; (3) 30: 70; (4) 40: 60; (5) 50: 50 (%) with 3 repetitions. The results of the color sensory test on sweet corn flour bread ranged from 1.57-3.29 (brownish yellow) with a P value = 0.000. The taste of sweet corn flour bread ranged from 3.14-3.69 (very sweet) with a P value = 0.037. The aroma of sweet corn flour bread ranges from 2.23-2.17 (fragrant) with a P value of 0.175. The texture of sweet corn flour bread ranges from 2.40-3.06 (soft) with a P value of 0.014. The dietary fiber content of sweet corn flour bread ranges from 19.26%-53.68% with a P value of 0.021. The proportion of corn flour and wheat flour does not affect the aroma of sweet bread. The proportion of corn flour and wheat flour significantly affects the color, taste, texture, and dietary fiber content.

This study aimed to analyze the effect of infant massage on growth and development among infants attending Puskesmas Bongo II. Infant massage is recognized as a form of sensory stimulation that enhances neural function, improves blood circulation, and strengthens maternal–infant bonding, thereby potentially supporting optimal physical growth and developmental progress. This research employed an analytic cross-sectional design involving infants aged 0–12 months, with a total sample of 50 infants selected using purposive sampling based on predefined inclusion criteria. Information regarding infant massage practices was collected through structured maternal interviews and categorized into routine massage (≥3 times per week) and non-routine massage. Infant growth was assessed using the weight-for-age (W/A) indicator based on WHO growth standards, while development was measured using the Developmental Pre-Screening Questionnaire (KPSP). Data were analyzed using the chi-square test with a 95% confidence level (p < 0.05). The results showed that infants who received routine massage demonstrated significantly better growth status and developmental outcomes compared to those who did not receive massage routinely. These findings suggest that infant massage is a simple, safe, and practical intervention that can be recommended to support growth and development and may be integrated into maternal and child health services at Puskesmas Bongo II.

Stroke is a leading cause of disability that requires long-term rehabilitation. Herbal-based therapies, such as Shengmai San, may complement conventional medical treatments in aiding post-stroke recovery. This quasi-experimental study involved 10 post-stroke patients who received Shengmai San therapy for four weeks, with one session per week. Key parameters measured included blood pressure, muscle strength, motor function, sensory complaints (e.g., tingling, numbness), sleep quality, and Traditional Chinese Medicine diagnostic findings (pulse and tongue). The results showed clinical improvements across all patients, including stabilized blood pressure, enhanced muscle strength and mobility, reduced sensory complaints, better sleep quality, and increased physical stamina. Pulse and tongue diagnostics suggested improved Qi and Xue circulation. No significant side effects were reported. The study concludes that Shengmai San is a promising adjunct therapy for post-stroke rehabilitation, especially for patients with Qi deficiency and impaired blood circulation. However, the study suggests that Shengmai San should not replace conventional treatments but be used as a complementary therapy to support recovery.

Hallucinations are one of the symptoms of mental disorders in individuals which are characterized by sensory perception changes, namely feeling false sensations in the form of sounds, sight, tasting, touching or smelling. The application of drawing therapy in patients with auditory hallucination disorder may reduce hallucinogenic stimuli. The goal is to apply and analyze Nursing Care in Patients with Mental Disorders with the implementation of the application of drawing therapy to control auditory hallucinations. The method used in this is descriptive analysis with a case study approach. This study describes the application of drawing therapy to reduce the signs and symptoms of auditory hallucinations. It was also carried out by providing an intervention to apply drawing therapy for 15 minutes every day to three respondents for 7 consecutive days. The application of drawing therapy to the three respondents obtained results in the reduction of hallucinations from a moderate hallucinatory level score (22) to a mild level with a score (9). Brother B experienced a decrease in hallucinations from a moderate hallucination level score (20) to no hallucinations on days 6 and 7 with a score of (0). Brother JS decreased from a moderate hallucination level of score (20) to no hallucination on day 7 with a score of (0). It is hoped that the results of this study can provide an understanding of the application of drawing therapy to control auditory hallucinations.

Peningkatan kasus gangguan kardiovaskular menuntut adanya sistem pemantauan detak jantung yang tidak hanya akurat, tetapi juga mampu memberikan respons cepat terhadap kondisi abnormal. Penelitian ini bertujuan mengembangkan sistem pemantauan detak jantung berbasis Internet of Things (IoT) yang terintegrasi dengan algoritma Extreme Gradient Boosting (XGBoost) untuk mendeteksi pola detak jantung abnormal secara real-time serta memicu respons otomatis melalui Miniature Medical Car. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan metode simulasi, di mana data denyut jantung dikumpulkan menggunakan Pulse Armband berbasis ESP32-C3 Mini dan sensor MAX30102, kemudian dikirim ke server untuk diproses melalui pipeline data mining. Dataset penelitian terdiri dari 800 sampel yang dibagi menjadi kelas normal dan abnormal, kemudian diolah menjadi 14 fitur statistik dan variabilitas detak jantung untuk proses pelatihan model. Hasil penelitian menunjukkan bahwa model XGBoost mencapai akurasi 94%, precision 93,3%, recall 93,3%, F1-score 0,933, serta ROC-AUC 0,96, yang mengindikasikan kinerja tinggi dalam membedakan pola detak jantung normal dan abnormal. Integrasi model dengan miniature car memungkinkan sistem memberikan respons fisik secara otomatis saat mendeteksi kondisi berisiko. Kontribusi penelitian ini mencakup pengembangan sistem IoT–ML real-time yang efisien, penggunaan fitur statistik ringkas untuk data fisiologis, serta implementasi respons berbasis robotik. Implikasi penelitian membuka peluang penerapan pada sistem monitoring medis jarak jauh, lingkungan publik, maupun perangkat asistif berbiaya rendah.

Diabetic foot ulcer is a disease of the feet of DM sufferers with the characteristics of sensory, motor, autonomic neuropathy as well as macrovascular and microvascular disorders. Diabetic foot injuries are one of the complications that DM sufferers fear because they can result in amputation. Modern Dressing wound treatment with the Moist Wound Healing method is effective in healing ulcer wounds in DM patients. The wound healing method aims to maintain the moisture of the wound by using a moisture-retaining bandage so that wound healing and tissue growth can occur naturally. To determine nursing care in dm patients with leg injuries the application of Modern Dressing wound care using metcovazin and foam in diabetic ulcer patients. This study presents a descriptive study describing the treatment of ulcer wounds in DM patients with Modern Dressing wound treatment using a case study approach. Based on the results of the application of Evidence Based Practice (EBP) dapart, it is concluded that the application of Modern Dressing wound care is more effective than conventional wound treatment. as evidenced by the change in the decreased score in Mrs. N with 3 intervention processes, namely by decreasing the initial score of 30 down to 22 after Modern Dressing wound treatment. Modern dressing is more effective for diabetic foot ulcer care because it accelerates new tissue growth, reduces pain, and lowers the risk of infection.

The elderly are a vulnerable group to experience decreased physical and cognitive function, such as hypertension and dementia, which can affect their quality of life. The Activity Therapy Program aims to improve the well-being of the elderly through laughter therapy, listening to music, and playing guess the word. The method used is group dynamics, which involves fun activities to stimulate the cognitive and social of the elderly. This activity is expected to increase social interaction, sensory stimulation, and improve the cognitive function of the elderly. The implementation of therapy was carried out involving 60 elderly people, with stages that included orientation, work, and termination. Evaluations showed that 60% of participants actively participated in laughter and guess therapy, as well as being able to express their feelings. This program has shown success in improving the quality of life of the elderly by encouraging them to be more active and social. In conclusion, TAK can be an effective solution to improve the quality of life of the elderly through physical and cognitive stimulation. It is recommended that this program be carried out regularly to maintain the memory and social health of the elderly.

Hallucinations are false sensory perceptions unrelated to real external stimuli. Patients will have difficulty distinguishing whether the stimuli they experience originate internally (thoughts or feelings) or externally. This condition may affect any of the five senses. The most common type of hallucination is auditory hallucinations. One way to reduce the signs and symptoms of auditory hallucinations is through Art Therapy: freehand painting. To determine nursing care with the application of free painting therapy in patients with auditory hallucinations at the Mitra Mulia Husada Foundation, Palembang. The design used was a case study describing the cases of four patients with auditory hallucinations. Subjects were selected according to inclusion and exclusion criteria. The intervention provided was free-drawing therapy for four days, each lasting 30 minutes.After the intervention of applying free painting therapy for 4 days with a time of 30 minutes per visit, it was found that there was a decrease in signs and symptoms of hallucinations as shown through the results of the observation sheet in each patient. Mr. A. originally 9 became 3 signs of symptoms, Mr. S originally 7 became 3 signs of symptoms, Mr. AJ originally 9 became 3 signs of symptoms and Mr. M originally 10 became 5 signs of symptoms of auditory hallucinations. There was a decrease in auditory hallucination scores in each patient after being given Art Therapy: free painting. For future researchers, it is hoped that they can conduct research on the application of free painting therapy so that it can be carried out more frequently so that the therapy carried out is more effective in reducing the signs and symptoms of hallucinations and also add respondents so that the application of the therapy given is more effective in reducing the signs and symptoms experienced by patients.

This study aims to design and develop a functionally efficient and operationally effective Internet of Things (IoT)-based air quality monitoring system for radiology departments. The system utilises a DHT22 sensor integrated with an ESP32 microcontroller to monitor the temperature and humidity of diagnostic rooms in real time, and to display the data via the UdaraKu mobile application. The research method employed a quantitative experimental approach focused on measuring system performance, specifically the accuracy of the temperature and humidity sensors. The research model used was the Research and Development (R&D) method, aimed at transforming conventional air quality monitoring in radiology into a real-time digital system based on IoT. The research results indicate that the IoT-based monitoring system is capable of maintaining room temperature and humidity stability within the ideal range, namely 22–24°C and 50–60% RH, in accordance with international standards. This improvement in environmental stability has a direct impact on reducing noise in digital radiography images, as evidenced by an increase in the Signal-to-Noise Ratio (SNR). Instrument validation demonstrated a high level of reliability with a Cronbach’s Alpha value of 0.848, reinforcing the reliability of the data and the system. Overall, the IoT-based air quality monitoring system has proven effective in controlling noise in digital radiography images, improving the quality of diagnostic services, and supporting patient safety principles and operational efficiency within radiology departments.

Comparing gas flow measurement results using Ultrasonic Sensor Meters and Kelton software is very important because the objective is to determine whether the errors that occur are in accordance with applicable standards or not. This study aims to compare the simulation results from the Ultrasonic Flow Meter (USM) with Kelton software based on AGA 8, AGA 9, and ISO 6976 regulations. From measurements with the USM, an error value of 0.01% was obtained, while from Kelton software, an error value of 0.01% was also obtained. Thus, it can be concluded that the readings from both methods are still within the specified error tolerance range of 0.1%, so they do not cause excessive cost losses during the gas delivery process. This proves that the Ultrasonic Sensor Meter used has the ability to measure accurately, making it suitable for use as a measuring device in gas metering systems.  

The cosmetic industry continues to grow rapidly along with the increasing demand for natural-based body care products, one of which is massage oil. Essential oils such as lavender, citronella, and chamomile are known to have synergistic effects as relaxation agents, anxiety reducers, and anti-inflammatory agents. To support the safety and effectiveness of their use, the selection of appropriate carrier oils, such as olive oil, almond oil, and virgin coconut oil (VCO), is required due to their good penetration ability and moisturizing properties. This study aimed to determine the effect of variations in carrier oils on the physical and sensory characteristics of aromatherapy massage oil preparations and to identify the most optimal formulation. The research was conducted experimentally by formulating three massage oil formulations using a combination of lavender, citronella, and chamomile essential oils with different carrier oil compositions. The evaluations included organoleptic tests, pH, viscosity, specific gravity, stability, irritation tests, and hedonic tests. The results showed that all formulations were liquid, homogeneous, stable for 28 days, had pH values within the normal skin pH range, met the required viscosity and specific gravity standards, and did not cause skin irritation. Based on the hedonic test, formulation F2 was the most preferred by respondents and was determined to be the best formulation due to its most favorable aroma, texture, and comfort during use. Therefore, variations in carrier oils influence the characteristics of massage oil preparations and enable the determination of the optimal formulation

Gluten-free flour-based cookie products face a major challenge in producing physicochemical and sensory characteristics equivalent to wheat-based products due to the absence of gluten as a structural component. One common approach to address this issue is the addition of hydrocolloids, such as glucomannan and xanthan gum. This study aims to systematically examine the effect of the ratio of glucomannan and xanthan gum on the texture characteristics, spreadability, and sensory properties of gluten-free flour-based chocolate cookies using the Systematic Literature Review (SLR) method. The literature search process was carried out on several scientific databases using keywords related to gluten-free cookies, glucomannan, xanthan gum, texture, spreadability, and sensory properties. Selected articles were selected based on inclusion and exclusion criteria, then analyzed and synthesized narratively with reference to the PRISMA guidelines. The results of the study indicate that xanthan gum tends to increase the hardness and structural stability of cookies, but can decrease spreadability and crispiness at high concentrations. Conversely, glucomannan plays a role in enhancing softness and mouthfeel through its high water-binding capacity, although it can potentially limit spreadability if used excessively. The combination of glucomannan and xanthan gum exhibits a synergistic effect in balancing textural characteristics and enhancing sensory acceptability. In conclusion, optimizing the ratio of glucomannan to xanthan gum is a key factor in developing gluten-free chocolate cookies with optimal physicochemical and sensory characteristics.