Publication Search

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 Family Welfare Empowerment (PKK) is a community organization that plays a strategic role in improving the quality of family life through various programs covering education, health, economy, and social aspects. However, in practice, the recording and management of member data as well as PKK activities are still carried out manually. This condition creates several challenges, including difficulties in archiving, limited access to information retrieval, and delays in preparing reports required by administrators and stakeholders. This study aims to design and develop a web-based information system for PKK member activity services that can manage member data, record activities, track attendance, and generate reports quickly, accurately, and efficiently. The system development method employed an object-oriented approach, consisting of requirement analysis, system design, implementation, and testing stages. The implementation results show that the developed information system can improve organizational service efficiency, assist administrators in monitoring member activeness, and reduce potential errors in data recording. Furthermore, the system provides better support for data-driven decision-making, thereby enabling PKK to become more modern, transparent, and adaptive to technological developments. Thus, this system has the potential to serve as an innovative solution to sustainably enhance the performance of PKK organizations.  

The automotive sector continues to demonstrate significant progress in line with innovations in various supporting components of motor vehicles. Motorcycles, which initially served only as a practical means of transportation, have now evolved into a lifestyle element and a popular activity among many communities. Along with the increasing demand from consumers for performance and efficiency, the development of transmission technology, particularly the Continuously Variable Transmission (CVT) system, has become an important aspect that requires serious attention. One of the key components in the CVT system is the double clutch lining and the clutch housing, which play a vital role in transferring torque and power from the engine to the driving wheel. The performance of these components directly affects acceleration, efficiency, and engine durability. Therefore, research on the design and modification patterns of the double clutch lining and clutch housing is essential to determine an optimal configuration. This study applies an experimental method using a 110 cc motorcycle as the test object. Several modification patterns were applied to the double clutch lining and clutch housing to examine their influence on vehicle performance. The testing process was carried out using a dynotest, which enables precise measurement of torque and power across different engine speeds. The data obtained from these tests are expected to provide a clear overview of the effect of modification patterns on the transmission performance of motorcycles. The findings of this research are expected to contribute significantly to the development of more efficient and optimal designs for double clutch linings and clutch housings. Furthermore, this study may serve as a valuable reference for the automotive industry as well as motorcycle modification communities in enhancing vehicle performance while maintaining efficiency and component durability. In this regard, innovations in CVT components hold great potential to support the advancement of two-wheeled transportation technology in the future.

Employee performance appraisal is a crucial aspect of human resource management and development, as the evaluation results serve as the basis for managerial decision-making, including promotions, incentives, and career development. However, unstructured assessment sistems often hinder the objectivity, transparency, and accuracy of performance evaluations. This study aims to design and develop a web-based Decision Support Sistem (DSS) to assess the performance of Biller employees at the ULP PLN Kuala office by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS was selected because it effectively addresses multi-criteria decision-making problems by comparing each alternative to both positive and negative ideal solutions. The evaluation criteria include invoice achievement, account return balance, and PAL balance. The sistem was developed using PHP as the programming language and MySQL as the database, ensuring integration and accessibility. The test results indicate that the sistem is capable of providing employee rankings in an objective and measurable manner. Based on the calculation, Tri Widodo achieved the highest score (0.8027), demonstrating the best performance among the evaluated employees. The implementation of this TOPSIS-based DSS makes the performance appraisal process more sistematic, efficient, transparent, and accurate, thereby contributing to the improvement of human resource management quality within the organization.  

The current advancements in information technology have brought significant benefits to the industrial world, particularly in the automotive sector. Website development in business and computer- based academic information system development are among the utilization of information technology. With information technology, Carsentro dealer data can be processed quickly and easily, enabling the presentation of accurate, fast, transparent, and efficient administrative information reports. The purpose of developing this system is to address existing issues in the old system by creating an administration information system for Carsentro dealer rental payment data. The implementation of a new system for Carsentro dealer data can improve record-keeping accountability, thus avoiding manual input recording errors that cannot be monitored by dealers renting space at Carsentro. In the development of this administrative information system, the data to be inputted includes information on when dealers joined the Carsentro ecosystem, the amount of monthly rental fee invoices, payment data, and dealer debt or receivables data. The software used is DBMS (Database Management System) MySql as the data storage medium, while programming languages such as PHP, CSS, JavaScript, and HTML are used for interface development. This aims to facilitate both users and administrators in managing data.

This study discusses the effect of valve weight and clearance on the efficiency of a hydraulic ram pump, with a focus on optimizing water discharge efficiency in the Sumberingin Tourism Area, Wringinsongo Village, Tumpang, Malang Regency. The method used in this study is an experiment with variations in valve weight consisting of 10 kg, 11 kg, and 12 kg, as well as valve clearances varying between 16.5 mm, 24.5 mm, and 32.5 mm. The results showed that the combination of a valve weight of 10 kg and a clearance of 16.5 mm produced the highest water discharge efficiency, namely 69.7 liters per minute, with an optimal efficiency of around 33%. In the optimization process, the application of Design of Experiment (DOE) revealed that a valve weight of 11 kg and a clearance of 16.5 mm can produce a maximum discharge efficiency of 63.155 with a desirability value reaching 0.7671. These findings indicate that proper settings on valve weight and clearance can contribute significantly to increasing the efficiency of a hydraulic ram pump. This research provides valuable insights into improving the performance and reliability of hydraulic ram pumps in rural water distribution systems. Understanding the influence of these variables is expected to yield more effective solutions for water resource management, particularly in areas requiring efficient irrigation systems. Furthermore, this research also opens up opportunities for further research on hydraulic ram pump optimization by considering other factors that can influence the efficiency and performance of the overall water distribution system. It is hoped that the results of this research can serve as a reference for the development of more efficient and environmentally friendly hydraulic ram pump technology, as well as supporting the sustainability of water resource management in rural areas.

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.

Consistent and efficient concrete quality in each implementation is one of the main factors in the success of construction projects. Concrete as a structural material requires strict quality control in order to meet the technical standards that have been set. One way to improve the quality of concrete is to add certain additives to the job mix formula (JMF). This research is focused on the application of SG type additives known as chemical-based additives to improve the properties of fresh concrete and hard concrete. SG additives have an important function in increasing workability, speeding up or slowing down the binding time as needed, maintaining quality stability, and strengthening concrete finishes. In this study, a comparison was made between a concrete mixture with SG additives and a concrete mixture without additives. The tests included slump parameters, initial binding time, and compressive strength at 7 and 28 days of age. The test results showed a significant difference, especially in the improvement of the consistency and compressive strength of concrete with the use of additives. The results of the discussion showed a comparison of Trial Mix 1 and Trial Mix 2 that are different in terms of material composition, cost efficiency, and compressive strength of concrete. Trial Mix 2 with the composition of cement, admixture, water, and aggregate (sand and split) showed more optimal results. The compressive strength achieved was 821,396.00 kg/cm² at the age of 28 days. In terms of cost, Trial Mix 2 requires Rp. 351,582.00 per m³, with an efficiency difference of around Rp. 32,953.00 per m³ compared to the previous mix

The development of information technology has encouraged institutions, including hospitals, to adopt digital systems to improve operational efficiency. One important aspect is the employee attendance system, which previously relied on fingerprints. This method has limitations, such as difficulty detecting when fingers are not in ideal condition and causing queues during peak hours. This research aims to design and implement an Android-based attendance system using the Eigenface facial recognition method as a faster, safer, and more accurate alternative. Eigenface works by extracting facial features using Principal Component Analysis (PCA), thus being able to efficiently recognize individual identities. The system was developed with MySQL database integration and tested on employees of Khalishah General Hospital. The implementation results showed that the system can recognize faces with a good level of accuracy and increase the effectiveness of attendance recording. Furthermore, the use of facial-based attendance can minimize the potential for fraud and increase user comfort because it does not require physical contact. Thus, the Eigenface method has proven feasible to be implemented as a modern attendance solution to support employee attendance management in hospital work environments and other institutions.

Innovation in healthcare organization management in the digital era plays a crucial role in enhancing the efficiency, accessibility, and quality of healthcare services. As digital technologies continue to evolve, healthcare institutions are increasingly adopting systems such as Electronic Medical Records (EMR), Hospital Management Information Systems (HMIS or SIMRS), telemedicine platforms, mobile health applications, Big Data analytics, and Artificial Intelligence (AI) to streamline operations and improve patient outcomes. This literature review highlights how the implementation of these technologies can accelerate service delivery, reduce administrative burdens, support data-driven clinical and managerial decision-making, and enable remote healthcare access—particularly beneficial in rural or underserved areas. For instance, EMRs improve the accuracy and availability of patient data, while AI can assist in diagnostics and predictive analytics for disease prevention. However, despite these promising developments, several significant challenges persist. These include limited digital infrastructure in some regions, low levels of digital literacy among healthcare professionals, high implementation and maintenance costs, organizational resistance to technological change, and concerns over data privacy and cybersecurity. Therefore, successful digital transformation in healthcare is not solely dependent on technology itself. It also requires strong organizational readiness, supportive regulatory frameworks, investment in workforce training and development, and effective change management strategies. Collaborative efforts between government, private sector, and healthcare providers are essential to overcome these barriers. In conclusion, innovation in healthcare management must be holistic—integrating technological advancements with human, organizational, and policy-level adaptations—to ensure the delivery of high-quality, efficient, and sustainable healthcare services in the digital age.

This study aims to analyze the growth of tilapia (Oreochromis niloticus) cultivated in a concrete pond system in Dusun IV, Fadoro Lasara Village, Gunungsitoli City. The concrete pond system was chosen for its advantages in land efficiency, ease of management, and ability to maintain stable water quality. The research method employed a quantitative experimental approach over 60 days, with 200 Nile tilapia as the study subjects. The parameters observed included absolute weight and length gain, specific growth rate (SGR), feed conversion ratio (FCR), and survival rate (SR). The results showed that the average weight of the fish increased from 5.12 grams to 98.46 grams, with a length increase of 12.5 cm. The SGR was recorded at 4.29% per day, FCR at 1.38, and SR at 96.5%. These results indicate that the concrete pond system can support optimal tilapia growth. This study recommends the application of concrete ponds as an efficient aquaculture alternative, particularly in areas with limited land and resources. This system has proven to be adaptive to local conditions and contributes to increased productivity and income for aquaculture farmers.

This study aimed to evaluate the effect of broiler concentrate-based rations combined with corn and rice bran on the performance of native chickens. A total of four dietary treatments were formulated, namely P1 (100% broiler concentrate), P2 (75% broiler concentrate, 10% corn, 15% rice bran), P3 (50% broiler concentrate, 30% corn, 20% rice bran), and P4 (25% broiler concentrate, 55% corn, 20% rice bran). The parameters observed included feed intake, body weight gain, and feed conversion ratio (FCR). Data were analyzed using analysis of variance (ANOVA), and significant differences among treatments were further tested with Duncan’s New Multiple Range Test (DMRT). The results showed that dietary treatments significantly affected the growth performance of native chickens (P<0.05). Chickens fed diets with higher proportions of broiler concentrate (P1 and P2) exhibited better body weight gain and more efficient feed conversion compared to those receiving lower concentrate levels (P3 and P4). In contrast, increasing corn and rice bran levels tended to increase feed intake but did not proportionally improve body weight gain, resulting in poorer FCR. It can be concluded that native chickens perform optimally when fed rations containing at least 75% broiler concentrate, which provides a balance between growth and feed efficiency.

Salem District is one of the largest coffee commodities in Brebes Regency. This significant potential has yet to provide a meaningful contribution to the income of coffee farmers, especially in Gunung Jaya village, Salem District. The low income of coffee farmers is due to the fact that they still sell their coffee products in the form of cherry. Over time, in 2018, farmers began to develop small-scale and simple coffee processing from green beans to roasted beans and coffee powder, pioneered by the SME "Lulumpang Kopi". They still use simple tools and often have to travel out of town to obtain the desired coffee powder. Lulumpang Kopi can produce 100-150 packages of coffee weighing 100 grams. Seeing this potential, the Community Partnership Empowerment team (PKM) from the University of Civilisation and UNSOED, funded by DIKTISAINTEK, is conducting community service this year 2025 using training methods, workshops, and appropriate technology grants. Thus, technology has been granted in the form of 1 Huller machine with a capacity of 150kg/batch, 1 BBM Grinding machine with a capacity of 10kg/batch, and scales. This assistance aims to enhance farmers' capabilities to achieve greater economic independence and improve their competitiveness in the market. As a result of this activity, partners were able to increase the capacity and quality of coffee farmers' production through the grant of equipment such as huller, BBM grinder, and digital scales, making the processing faster, more efficient, and yielding better coffee compared to traditional methods. In addition, the training participants also demonstrated an increase in knowledge through pre-tests and post-tests, rising from 66.5% to 77.3%, an increase of 13.8% from the 40 participants who attended.

Tomato crop yields face significant threats from plant diseases, with existing deep learning solutions often computationally prohibitive for resource-constrained agricultural settings; to address this gap, we propose Efficient Disease Attention Network (EDANet), a novel lightweight architecture combining depthwise separable convolutions with hybrid attention mechanisms for efficient Tomato disease recognition. Our approach integrates channel and spatial attention within hierarchical blocks to prioritize symptomatic regions while utilizing depthwise decomposition to reduce parameters to only 104,043 (multiple times smaller than MobileNet and EfficientNet). Evaluated on ten tomato disease classes from PlantVillage, EDANet achieves 97.32% accuracy and exceptional (~1.00) micro-AUC, with perfect recognition of Mosaic virus (100% F1-score) and robust performance on challenging cases like Early blight (93.2% F1) and Target Spot (93.6% F1). The architecture processes 128×128 RGB images in ~23ms on standard CPUs, enabling real-time field diagnostics without GPU dependencies. This work bridges laboratory AI and practical farm deployment by optimizing the accuracy-efficiency tradeoff, providing farmers with an accessible tool for early disease intervention in resource-limited environments.

This study aims to examine and analyze the effect of labor costs and feed costs on the income of broiler chicken farming businesses in Sikka Regency. The background of this research is based on the fact that labor costs and feed costs are the largest expense components in broiler chicken farming, thus it is necessary to investigate their contribution to farmers’ income. This research applies a quantitative approach with a causal design to identify cause-and-effect relationships between variables. The population of the study consisted of 78 broiler chicken farming businesses in Sikka Regency, with the purposive sampling technique applied to determine the sample. Data were collected through documentation techniques within the observation period of 2022–2024. Data analysis was conducted using multiple linear regression with the aid of the Statistical Package for the Social Sciences (SPSS) software. The results show that partially, labor costs have a significant effect on business income, indicating that the more efficient the management of labor, the higher the income generated. Feed costs also have a significant effect on business income, as feed is the main factor determining the growth quality of broiler chickens. Simultaneously, labor costs and feed costs significantly influence the income of broiler chicken farming businesses in Sikka Regency. These findings emphasize the importance of cost efficiency in the management of broiler chicken farming businesses to increase income and strengthen the competitiveness of local farmers amid the increasingly competitive poultry industry.

The research aims to develop a system for Zhafirah Cosmetics Store to address operational issues such as manual transaction recording, lack of transaction receipts, and time-consuming documentation processes. A desktop-based sales and purchase information system was developed using a descriptive research method, with data collected through observation and interviews, system analysis conducted using the PIECES framework, and system development following the waterfall model. The implementation results show that the system effectively accelerates transaction recording, minimizes input errors, and generates accurate and efficient reports. It also simplifies the management of product, supplier, and transaction data, thereby supporting managerial decision-making. System testing was conducted using Black Box Testing and User Acceptance Testing (UAT), with UAT results showing an average score of 88.67%, categorized as “Very Good,” indicating strong user acceptance. The implication of this research is an improvement in operational effectiveness and a reduction in data loss risk through the digitization of the store’s business processes.

Profitability is a key indicator in assessing a company’s financial performance, particularly in the personal care industry listed on the Indonesia Stock Exchange (IDX). This study aims to analyze the effect of Return on Assets (ROA), Return on Equity (ROE), and Debt to Equity Ratio (DER) on profitability as measured by Net Profit Margin (NPM). The research employed a quantitative approach using multiple linear regression analysis based on the financial statements of personal care companies for the 2021–2024 period. The findings reveal that ROA has a positive and significant effect on NPM, indicating that the more efficiently a company manages its assets, the higher the net profit margin achieved. Meanwhile, ROE and DER show no significant effect on NPM, implying that shareholder equity returns and debt utilization in the capital structure have not directly enhanced net profitability. These results suggest that optimal asset management is a crucial factor in improving the financial performance of personal care companies.

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.

This study aims to analyze various sustainable food processing innovations that contribute to improving public health in Indonesia. The research was conducted through a literature review of 13 scientific articles published between 2015 and 2025 that discussed aspects of nutritional innovation, environmentally friendly processing technology, social empowerment, and food waste management. The analysis results indicate that the use of local food ingredients such as moringa leaves, snakehead fish, and soybeans plays a significant role in improving nutritional literacy, preventing stunting, and strengthening family food security. Meanwhile, the application of appropriate technologies such as oil draining machines, energy-efficient dryers, and waste processing into organic fertilizer contributes to production efficiency and reduced environmental impact. Furthermore, social innovation through the empowerment of MSMEs and women's groups can strengthen the local economy and foster environmental awareness. Thus, the synergy between nutritional, technological, and social innovations forms the basis for developing a healthy and sustainable food system to support the achievement of SDGs 2 and 3 in Indonesia.  

The integration of blockchain technology with Multi-Agent Reinforcement Learning (MARL) presents a promising solution for optimizing resource allocation and ensuring security in decentralized network environments, particularly in 5G and 6G network slicing. This research proposes a model that combines the security features of blockchain with the adaptive, decentralized decision-making capabilities of MARL. Blockchain ensures the integrity and transparency of resource allocation by providing a secure, tamper-proof ledger for transaction validation, while MARL allows agents to dynamically allocate resources based on real-time network conditions. The simulation results demonstrate significant improvements in resource allocation efficiency, fairness among users, and resilience to cyberattacks. By combining these two technologies, the proposed model overcomes many of the challenges posed by traditional centralized systems and offers an enhanced, secure, and fair solution for resource distribution in future mobile networks. However, scalability remains a challenge, especially in large-scale networks where transaction processing and consensus overhead can create bottlenecks. Additionally, training complexity in MARL models presents computational challenges, particularly in highly dynamic network environments. The model's performance trade-offs, including the balance between high security and system overhead, are also discussed. Future research should focus on optimizing blockchain consensus mechanisms to improve scalability and enhancing MARL model training techniques to reduce computational costs and improve real-time decision-making. This integration holds significant potential for revolutionizing resource allocation in 5G and 6G networks, enabling more efficient, secure, and fair management of network resources in the increasingly complex and decentralized digital ecosystem