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PT. Tirta Fresindo Jaya, specifically its Pasuruan plant as the producer of Pucuk Harum Tea beverage, requires a large supply of steam to support various production processes. This steam is used in the process of heating tea leaves, heating water through a heat exchanger, and heating chemicals and water in the cleaning in place (CIP) process. Steam pressure of 5 bar that is flowed to the process equipment will undergo condensation to produce condensate. To separate steam and condensate, steam traps are used, consisting of several types, namely mechanical, thermostatic, and thermodynamic. However, in operational practice, steam trap malfunctions often occur, either in the form of steam leaks that are wasted with condensate or failure to drain condensate from the system. This condition causes a decrease in the efficiency of the steam piping system and increases the workload of the boiler. As a result, fuel consumption and boiler feed water requirements become greater than ideal conditions. Therefore, this study aims to analyze the energy and operational losses caused by steam trap malfunctions, as well as evaluate their impact on boiler system performance and steam utilization efficiency at PT. Tirta Fresindo Jaya Pasuruan plant.      

The digital economy and e-commerce are rapidly transforming global markets, driving efficiency, inclusivity, and innovation. However, these developments also produce unintended consequences, particularly regarding environmental sustainability. This study aims to examine the relationship between digital transformation, the expansion of e-commerce, and their impact on carbon emissions and socio-economic outcomes. Using bibliometric analysis and VOS Viewer to map and analyze research trends from leading academic databases, this paper identifies key themes, knowledge clusters, and research gaps in the intersection of digital economy, logistics, and sustainability. The findings indicate that technological advances foster economic growth and greater accessibility but simultaneously contribute to rising energy consumption, logistics intensity, and carbon footprints. These results highlight the dual nature of digitalization as both a catalyst for inclusive development and a driver of environmental pressures. The study argues that an integrated policy framework is crucial to leverage the benefits of digital transformation while mitigating its environmental costs. It emphasizes the importance of green innovation, sustainable infrastructure investment, and inclusive e-commerce practices as key strategies for ensuring long-term socio-economic resilience. Ultimately, the paper contributes to the policy discourse by positioning innovation, inclusivity, and environmental stewardship as complementary rather than competing forces, thereby offering a pathway for future digital economy development that is both equitable and sustainable.

Physical fitness is a fundamental determinant of athletic performance and is strongly influenced by dietary intake and lifestyle behaviors. Adequate protein consumption is essential for muscle development and energy metabolism, whereas smoking has detrimental effects on lung function and aerobic capacity. This study aimed to explore the relationship between protein intake and smoking habits with physical fitness, measured by maximal oxygen uptake, among athletes of Persela Football Academy under-eighteen. A quantitative approach with a cross-sectional design was applied, involving adolescent male athletes. Protein intake was assessed using a semi-quantitative food frequency questionnaire, smoking habits were obtained through structured interviews, and maximal oxygen uptake was measured using the multistage fitness test. Findings revealed that the average daily protein intake of athletes was relatively high, while the mean maximal oxygen uptake score fell within the good category. Correlation analysis demonstrated a significant association between protein intake and aerobic fitness, as well as between smoking habits and aerobic fitness. The results indicate that lower protein intake and higher smoking frequency are linked to reduced physical fitness capacity. This study highlights the importance of nutritional interventions and healthy lifestyle promotion as integral components in the development of youth athletes to optimize performance and prevent decline in fitness.

Digital transformation through adoption cloud technology has become catalyst in effort efficiency energy and reduction greenhouse gas emissions glass (GHG). Research This aim for analyze contribution cloud technology against efficiency operational and impact the environment in framework economy green. With use approach studies literature and secondary data analysis from report institution international and journals scientific, research This find that migration to cloud computing can reduce consumption energy up to 84% and emissions carbon up to 88% compared to with traditional IT infrastructure. These results show that cloud computing is not only solution technology, but also important strategy in support development sustainable.

This study discusses the phenomenon of digital entrepreneurship in the era of global climate awareness, focusing on the integration of artificial intelligence (AI) ethics, sustainable technology, and green innovation. The main issues raised are the fragmentation of analysis between digital business ethics, green economic opportunities, and technological challenges such as greenwashing, high AI energy consumption, and the digital divide. The purpose of this study is to formulate an interdisciplinary framework that combines ethical, technological, and sustainability dimensions to strengthen the role of digital entrepreneurs in achieving low-carbon development. The methods used include critical literature analysis, bibliometrics of 200 publications (2018-2025) using VOSviewer, and fuzzy logic-based simulations using the UNESCO AI ethics framework (2021) and the sustainable business model of Bocken et al. (2014). The results show four main research clusters: AI for Sustainable Innovation, Ethical Digital Business, Blockchain for Green Supply Chain, and Circular Digital Economy. The application of AI ethics increases the efficiency of green business decisions by up to 20%, consumer trust by 17%, and MSME participation by 14%. The synthesis of findings confirms that AI ethics acts as a conceptual mediator that strengthens the link between technological innovation and sustainability. In conclusion, ethical digital entrepreneurship has great potential as a driving force for Indonesia's green economy, but it requires digital ethics audit policies and the adoption of low-carbon technologies to address ethical and environmental risks in the AI era.

The oil and gas industry plays a crucial role in meeting global energy needs, with crude oil from production wells being the primary product of upstream operations. Prior to further processing, crude oil requires pretreatment at the production site, one of the key stages being phase separation using a flash separator. This study examines the effect of variations in cooling temperature on the performance of liquid phase separation and energy requirements in the flash separation process of light hydrocarbons. The analysis was conducted through process simulation using Aspen HYSYS version 14.2 with the Peng Robinson property package. The feed stream had a mass rate of 10,000 kg per hour, a temperature of 50°F, and atmospheric pressure, with compositions of ethane, propane, isobutane, and normal butane. The process configuration included compression, cooling, and phase separation in a flash separator at a constant pressure of 50 psia. Variations in cooling temperature were applied at 20, 10, and 0°C. The simulation results indicated a thermodynamic critical point at 10°C. At 20°C, no liquid phase was formed, while at 10°C, significant liquid yield was obtained with moderate energy consumption. Lowering the temperature to 0°C dramatically increases liquid recovery, but the cooling energy requirement also increases sharply. Sensitivity analysis confirms a strong inverse relationship between temperature and condensation yield, as well as a surge in energy consumption at low temperatures. The optimal operating condition is set at 10°C, providing a balance between separation efficiency and energy efficiency in accordance with sustainable manufacturing principles.

Given the great benefits of electrical energy, the availability of electrical energy sources is limited. Currently, the availability of electrical energy sources is not able to meet the increasing demand for electricity in Indonesia. The high use of electrical energy in daily life will have a negative impact on the environment. Therefore, to maintain the sustainability of energy sources, it is necessary to pursue strategic steps that can support the provision of electrical energy optimally and affordably, This study aims to find out how much total energy is used by the Energy Consumption Index (IKE) on electrical energy from the influence of electrical power and the length of time of use of electrical energy at SMK Negeri 2 Lubuk Basung, Lubuk Basung District, Agam Regency. This study aims to determine the value of energy consumption used or Energy Consumption Index (IKE) and energy saving opportunities at SMK Negeri 2 Lubuk Basung, Lubuk Basung District, Agam Regency. The results of this study are for the IKE value of the first floor which is 1.71 kWh/m2, for the IKE value of the second floor which is 0.03 kWh/m2, for the IKE value of one building, which is with a value of 1.74 kWh/m2, for the annual IKE of 0.022 kWh/m2/year and for the value of energy-saving opportunities of IDR 651 646/month IDR 7 819 755/year.

Nutritional problems during the growth phase of adolescent are mostly caused by consumption patterns. The most commonly used eating patterns during adolescent are foods that are high in calories, fat, sugar and salt. The habits of an unhealthy eating pattern can affect nutritional status. The foods most consumed by adolescent are often junk food and caffeinated beverages. All kinds of food and drinks are easily found around campuses surrounded by student. The purpose of this study was to determine the relationship between junk food consumption and caffeinated beverages to the nutritional status of students of the Faculty of Technology and Food Industry at Slamet Riyadi University, Surakarta. The respondents involved were students aged 18-24 years. Data was collected using a questionnaire and interview to the student. Data were analyzed using Chi-Square test. The results showed that factor affecting the nutritional status of student was mother’s education (p=0,000) and father’s education (p=0.000). Factors that do not affect nutritional status were energy intake (p=0.545), protein (p=0.085), fat (p=0.204) and carbohydrate (p=0.112), the amount of pocket money (p=0.310), the consumption level of junk food (p=0.671) and caffeinated drinks (p=0.535). The results showed that there was no significant relationship between the consumption patterns of junk food and caffeinated drinks on the nutritional status of students of the Faculty of Food Technology and Industry at Slamet Riyadi University, Surakarta. Permasalahan gizi yang terjadi saat pertumbuhan fase remaja lebih banyak disebabkan karena pola konsumsi.  Pola makan yang sering diterapkan pada masa remaja adalah makanan tinggi kalori, lemak, gula, dan garam. Pola makan yang tidak sehat dapat mempengaruhi status gizi seseorang. Makanan yang paling banyak dikonsumsi oleh kalangan remaja masuk dalam kategori junk food dan juga minuman berkafein. Makanan dan minuman kategori ini mudah ditemukan di sekitar kampus yang dikelilingi mahasiswa. Tujuan pada penelitian ini ialah menentukan hubungan pola konsumsi junk food dan minuman berkafein terhadap status gizi mahasiswa Fakultas Teknologi dan Industri Pangan di Universitas Slamet Riyadi, Surakarta. Responden yang terlibat ialah mahasiswa berusia 18-24 tahun. Pengumpulan data menggunakan kuesioner dan wawancara kepada mahasiswa. Analisis data menggunakan uji Chi-Square. Hasil penelitian menunjukkan bahwa faktor yang mempengaruhi status gizi mahasiswa adalah pendidikan ibu (p=0.000) dan pendidikan ayah (p=0.000). faktor yang tidak mempengaruhi status gizi ialah asupan energi (p=0.545), protein (p=0.085), lemak (p=0.204) and karbohidrat (p=0.112), jumlah uang saku (p=0.310), tingkat konsumsi junk food (p=0.671) dan minuman berkafein (p=0.535). Hasil penelitian menunjukkan tidak terdapat hubungan signifikan antara pola konsumsi junk food dan minuman berkafein terhadap status gizi mahasiswa Fakultas Teknologi dan Industri Pangan Universitas Slamet Riyadi, Surakarta.

The increase in the population of Medan City has a direct impact on the increasing demand for housing and settlements, which is not always in line with environmental carrying capacity and the fulfillment of livable housing standards. Residential buildings contribute significantly to energy and water consumption, as well as environmental degradation, thus requiring a sustainable design approach. This study aims to formulate criteria and principles for the design of simple, livable houses by applying the concept of green buildings. The research method used is descriptive qualitative with a focus on the design of class 1a residential buildings. The study was conducted through a review of relevant regulations and standards, including the Ministry of Public Works and Public Housing's Green Building principles, the GREENSHIP Homes assessment system by the Green Building Council Indonesia, and livable housing indicators from the North Sumatra II Housing Provision Implementation Center. The results of the study show that the application of green building concepts in Small Houses can be realized through proper site management, optimization of natural lighting and ventilation, efficient use of energy and water, sustainable waste and wastewater management, and the selection of environmentally friendly building materials. The application of these principles can produce Small Houses that not only meet livable standards but also contribute to environmental sustainability.

This experiment investigates the heat transfer characteristics of an ice bag gel phase change material (PCM) incorporated within bricks. The study seeks to investigate the performance of ice bag gel as PCM in improving thermal behavior of building material. The experiment consisted of subjecting brick samples with and without ice bag gel PCM to thermal cycles in a semi-automated laboratory setup. The results indicate that ice bag gel PCM incorporated in bricks exhibited minimal changes and better heat transfer as compared to the dry bricks. It was observed that the ice bag gel PCM registered lower peak temperature and slower rates of temperature drop which means their heat storage and release characteristics were efficient. Furthermore, the ice bag gel system produced a steady radiation flux, indicating that it was able to minimize the effects of temperature variations. These results imply that ice bag gel PCM has the potential to be a green and economical option for enhancing thermal comfort and decrease energy consumption in buildings.

Power transformer theft, a pervasive issue disrupting critical infrastructure, necessitates the development of cost-effective and energy-autonomous security solutions. This paper presents the design and implementation of a detection-focused anti-theft framework that integrates a Raspberry Pi Zero W, camera module, and passive infrared (PIR) motion sensors powered by a solar system for continuous monitoring. The system is designed for remote, off-grid deployment, utilizing a headless Raspberry Pi powered by a 5V solar panel and power bank to ensure energy autonomy. Upon motion detection, captured images are processed on the edge device using OpenCV’s Haar Cascade classifier, optimized for upper-body detection to minimize false positives and verify human presence. Captured images are processed locally on the edge device using OpenCV’s Haar Cascade classifier to confirm human presence before an alert is sent to the mobile application, emphasizing real-time operation and low latency. Once an intrusion is confirmed, the images are saved locally and uploaded via the Secure File Transfer Protocol to a custom-developed Android application. The app provides a dedicated remote monitoring interface, enabling secure file transfer and system access, while providing users with immediate notifications and image management capabilities. The system emphasizes low power consumption, real-time operation, and low deployment cost. Tests over 200 triggered events under varied environmental conditions achieved 90% detection accuracy with an average latency of 4.5 s. Solar autonomy was maintained for approximately 24 h under normal operation. It is concluded that the integration of solar power, edge computing of images, and mobile monitoring provides a feasible, scalable, and financially viable framework for securing transformers, especially in resource-constrained environments.

Food waste generated from the household sector is one of the largest contributors to environmental degradation in Indonesia. Food waste generated from the household sector is one of the main contributors to the increasing volume of organic waste in Indonesia. This issue not only creates social and economic problems but also poses a serious threat to environmental sustainability. This study aims to analyze the contribution of household food waste to environmental degradation and to review sustainable management strategies. This study employs a Systematic Literature Review (SLR) method guided by the PRISMA 2020 Statement to review relevant national research conducted during the period 2018-2025. The results of the literature selection show that the impacts of household food waste on environmental sustainability can be categorized into three main dimensions: (1) ecological impacts, including pollution and the increase of greenhouse gas emissions; (2) resource impacts, such as the wastage of energy, water, and land; and (3) social-environmental impacts, including the increasing burden of regional waste management and the declining quality of life for communities living near landfills. The findings emphasize that the management of household food waste plays a crucial role in achieving environmental sustainability, particularly in supporting the attainment of Sustainable Development Goal (SDG) 12, which focuses on responsible consumption and production. Therefore, it is necessary to implement strategies of reduction, reuse, and recycling of food waste at the household level to minimize the negative impacts on environmental sustainability in Indonesia.

This research focuses on analyzing the performance of a vacuum pan automation sistem using solenoid valves at PT. Duta Sugar International as an effort to improve the efficiency and quality of refined sugar production. The vacuum pan is the main tool in the sugar crystallization process that functions to evaporate the sugar solution under low pressure. Problems faced in the manual sistem are temperature instability and high dependence on operators, which impact time inefficiency and decrease product quality. The purpose of this research is to design and analyze the implementation of an automatic control system based on a Distributed Control Sistem (DCS) with the integration of solenoid valve actuators to optimize temperature stability and cooking process efficiency. The research method was carried out using qualitative and quantitative approaches through direct observation, technical interviews with the automation team, and supporting literature studies. The results showed that the automatic system was able to maintain a stable cooking temperature in the range of 78°C–85°C, lower and more efficient than the manual system which fluctuates between 90°C–100°C. In addition, cooking time was reduced by 10–15 minutes per cycle, and the crystallization process became more uniform with more efficient energy consumption. The results showed that the implementation of DCS-based automatic control with solenoid valves significantly improved operational stability, productivity, and energy efficiency. Thus, this automation sistem proved to be an effective solution for optimizing vacuum pan performance in the modern sugar industry.

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

The use of fossil-fueled vehicles has long been a major cause of exhaust emissions that pollute the air and exacerbate global climate change. In an effort to address this problem, Indonesia has begun developing electric vehicles as a more environmentally friendly alternative solution. Electric vehicles (EVs) are considered capable of reducing dependence on fossil fuels while simultaneously reducing air pollution levels. The Indonesian government has demonstrated its commitment to supporting electric vehicle development by issuing several strategic policies, including Presidential Regulation (Perpres) Number 55 of 2019 concerning the Acceleration of the Battery-Based Electric Motor Vehicle Program for Road Transportation, and Presidential Instruction (Inpres) Number 7 of 2022 concerning the Use of Battery-Based Electric Motor Vehicles as official vehicles for central and regional government agencies. In line with these policies, research was conducted to assess the power consumption efficiency of the Ken Dedes electric vehicle prototype, designed using a 250-watt DC motor and a mid-drive system. The main focus of this research was to analyze the effect of variations in module input voltage and gear size on the vehicle's power consumption level. The method used was an experimental approach with a quantitative approach, where a series of tests were conducted on several gear combinations and input voltage levels. The results of the study indicate that variations in these two parameters—gear size and input voltage—significantly affect motor power consumption. The most optimal combination in this study achieved a power consumption efficiency of 6 Wh/km. This figure demonstrates the most energy-efficient performance in vehicle operation and can serve as a benchmark for further development of similar electric vehicles. This research provides an important contribution to efforts to encourage the use of more efficient and sustainable electric vehicles in Indonesia.

High-rise buildings such as the World Trade Center Jakarta generally have high inductive electrical loads, so that their reactive power consumption is large and the power factor decreases below the SPLN standard (≤0.85), resulting in increased power losses and operational costs. This study aims to measure the power factor value before and after repairing the detuned reactor and capacitor on the capacitor bank panel, compare the results of field measurements with ETAP simulations, and assess the feasibility of the installed capacitor bank and determine the difference in the results of the ETAP simulation between measurements and load calculations on the World Trade Center building. The methods used include literature review, field observations on the LVMDP panel, MCC and capacitor bank, discussions with supervisors, data collection of current, voltage, kW, kVAR, kVA and cos φ using Lovato DCRG8 and ampere clamp, and load simulation using ETAP software. The results show that the cosφ value increased from 0.70 to 0.95 (an increase of 35.71%), the compensated reactive power reached 204 kVAR (Lovato), 282.6 kVAR (tang ampere), and 415 kVAR (ETAP simulation), with a power factor or cosφ = 0.95. In conclusion, the replacement of detuned reactors and capacitors effectively improves the power factor in the WTC Jakarta Building, reduces reactive loads, and the ETAP simulation results are consistent with field measurements, so that the capacitor bank installed in the WTC building is declared effective in reducing reactive currents, thereby reducing kVAR, kVA loads and improving the efficiency of the electrical system distribution for better energy management

The increasing demand for cloud computing services has led to the rapid expansion of cloud data centers, which consume significant amounts of energy and contribute substantially to global CO2 emissions. As the IT industry grows, the environmental impact of these data centers becomes an urgent concern. Green Cloud Computing (GCC) has emerged as a solution to mitigate this impact by focusing on energy efficiency and reducing carbon footprints while maintaining the necessary functionality and performance of cloud infrastructures. However, traditional blockchain consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) face limitations regarding energy consumption and scalability, which exacerbates the environmental burden. This study proposes a quantum-inspired blockchain consensus algorithm designed to optimize energy consumption and reduce latency in cloud data centers. By integrating quantum principles such as superposition and entanglement, the algorithm enhances task scheduling and resource utilization, enabling more energy-efficient operations without sacrificing performance. Simulations in a green cloud environment showed that the quantum-inspired algorithm resulted in up to a 30% reduction in energy usage compared to traditional consensus methods, with a 40% improvement in consensus processing time. These results suggest that quantum-inspired algorithms hold significant potential for enhancing the sustainability of cloud infrastructures by improving energy efficiency and scalability. Furthermore, this study discusses the feasibility of implementing quantum-inspired algorithms on classical hardware, addressing challenges in scalability and integration into existing blockchain frameworks. The findings provide valuable insights into the potential of quantum-inspired technologies to drive energy-efficient solutions in cloud computing.

The DH Building of the Electrical Engineering Study Program at Udayana University faces significant challenges in energy efficiency, as it still relies on conventional electrical systems. User negligence, such as forgetting to switch off lights and air conditioners (AC) after use, often results in unnecessary energy waste and increased operational costs. This issue highlights the urgent need for smart solutions capable of automating energy management, reducing waste caused by human error, and supporting the creation of a more efficient and sustainable campus environment. To address this problem, this study designs and implements a smart building system based on the Internet of Things (IoT). The system employs a NodeMCU ESP32 microcontroller as the main processing unit, integrated with a series of sensors including a DHT22 sensor for monitoring temperature and humidity, an MQ2 sensor for smoke detection, a PIR sensor for motion detection, and a PZEM-004T sensor for monitoring energy consumption. Control of electronic devices such as lights and AC units is carried out both automatically and manually through relay modules connected to the system. All sensor data and control functions are accessed via a web interface developed using the Laravel framework and a MySQL database. The testing results indicate that the designed system was successfully implemented and functions as expected. Sensor testing demonstrated high accuracy compared to standard measuring instruments, while the electronic device control system achieved an average response time of approximately 3.6 seconds, proving its reliability. Overall, the system provides a comprehensive solution for energy consumption monitoring and control, while also enhancing comfort and safety in the DH Building, in line with the goals of energy efficiency and facility modernization.

Biomass is one of the materials that can be utilized as fuel. To ensure optimal quality, effective management of biomass is required to maximize its potential. One possible approach is the application of a biomass stove fueled by rubber wood pellets. By integrating a thermoelectric generator, data can be obtained to determine whether all aspects meet the established standards. This system is designed to generate electrical energy from combustion heat, supported by components such as a buck-boost converter and a 3V DC lamp. Testing was carried out using proximate and ultimate analyses on the fuel as well as the Water Boiling Test (WBT) on the stove, referring to SNI 8021:2020 and SNI 8021:2014 standards. The results showed that rubber wood pellets contained 7.64% moisture and had a calorific value of 4050 kcal/kg. The stove demonstrated an efficiency of 23.53%–37.28% and a fuel consumption rate of 0.61–0.77 kg/hour, both of which meet the requirements. In addition, the thermoelectric generator produced a voltage of 3.6 V and an electric current of 0.05 A, which are higher than those reported in previous studies (2.06 V and 0.01 A, respectively). Therefore, this thermoelectric biomass stove system is considered successful and feasible for further development as an alternative energy application.

The integration of Internet of Things (IoT) with cloud computing has revolutionized healthcare systems, offering scalable and real-time patient monitoring. However, optimizing response times and energy consumption remains crucial for efficient healthcare delivery. This research evaluates various algorithmic approaches for workload migration and resource management within IoT cloud-based healthcare systems. The performance of the implemented algorithm in this research, Hybrid Dynamic Programming and Long Short-Term Memory (Hybrid DP+LSTM), was analyzed against other six key algorithms, namely Gradient Optimization with Back Propagation to Input (GOBI), Deep Reinforcement Learning (DRL), improved GOBI (GOBI2), Predictive Offloading for Network Devices (POND), Mixed Integer Linear Programming (MILP), and Genetic Algorithm (GA) based on their average response time and energy consumption. Hybrid DP+LSTM achieves the lowest response time (82.91ms) with an energy consumption of 2,835,048 joules per container. The outcome of the analysis showed that Hybrid DP+LSTM have significant response times improvement, with percentage increases of 89.3%, 79.0%, 83.8%, 97.0%, 99.8%, and 99.94% against GOBI, GOBI2, DRL, POND, MILP, and GA, respectively. In terms of energy consumption, Hybrid DP+LSTM outperforms other approaches, with GOBI2 (3,664,337 joules) consuming 29.3% more energy, DRL (2,973,238 joules) consuming 4.9% more, GOBI (4,463,010 joules) consuming 57.4% more, POND (3,310,966 joules) consuming 16.8% more, MILP (3,005,498 joules) consuming 6.0% more, and the GA (3,959,935 joules) consuming 39.7% more. The result of ablation of the Hybrid DP+LSTM model achieves a 47.05% improvement over DP-only (156.57ms) and a 70.64% improvement over LSTM-only (282.41ms) in response time. On the energy efficiency side, Hybrid DP+LSTM shows 22.80% improvement over LSTM-only (3,671,51 joules), but 7.34% underperformance compared to DP-only (2,640,93). These research findings indicate that the Hybrid DP+LSTM technique provides the best trade-off between response time and energy efficiency. Future research should further explore hybrid approaches to optimize these metrics in IoT cloud-based healthcare systems.