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Law enforcement holds a central role in shaping social order and ensuring the effective implementation of legal functions in Indonesia. The law is not merely a normative reference but must be strategically positioned as the fundamental basis for resolving disputes and conflicts that emerge within society. In this regard, Law No. 16 of 2004 concerning the Indonesian Prosecutor’s Office, particularly Article 2 paragraph (1), clearly stipulates that the Prosecutor’s Office is a state institution entrusted with exercising governmental authority in the field of prosecution, along with other responsibilities mandated by law. Within the framework of criminal justice, the Prosecutor’s Office assumes a pivotal role as Dominus Litis—the ultimate controller of criminal cases. This authority signifies that the Prosecutor’s Office is the only institution empowered to decide whether a particular case, supported by sufficient evidence in line with the Criminal Procedure Code, is eligible to be brought before the court. The prosecutor’s discretionary power in this context highlights its critical position in upholding justice and maintaining the integrity of legal proceedings. Beyond its prosecutorial function, the Prosecutor’s Office also bears the exclusive responsibility for executing criminal judgments, ensuring that court decisions are implemented properly and consistently with the rule of law. This dual function—both as Dominus Litis and executor of judicial decisions—underlines the institutional indispensability of the Prosecutor’s Office in the Indonesian legal system. The institution’s authority is therefore not limited to initiating prosecutions but also extends to safeguarding the finality and enforcement of criminal verdicts, which makes it a cornerstone in the broader architecture of law enforcement. Consequently, strengthening the role and capacity of the Prosecutor’s Office is essential for advancing justice, protecting the rights of citizens, and reinforcing the legitimacy of Indonesia’s legal order.

Environmental education plays a crucial role in modern curricula, emphasizing sustainability and ecological responsibility to address global challenges. This study compares faith-based and secular environmental education strategies, focusing on how theological reflection and ecological consciousness are integrated into teaching frameworks. Faith-based schools, particularly those rooted in Christianity and Islam, incorporate ecological ethics within religious teachings, framing environmental stewardship as a moral and spiritual duty. In contrast, secular models prioritize scientific literacy and environmental problem-solving. The study reveals that faith-based models promote both scientific understanding and moral engagement with environmental issues through religious values like Imago Dei (in Christian schools) and khalifah (in Islamic schools). These values instill a sense of moral accountability, motivating students to act sustainably. The research also highlights how curriculum design, teacher involvement, and experiential learning contribute to the effectiveness of both models in fostering ecological responsibility. By comparing these approaches, the study proposes an integrative eco-theological pedagogical framework that combines the strengths of both methods to promote long-term commitment to sustainability. The findings have implications for educational policy, curriculum development, and teacher training, especially in pluralistic school settings where diverse perspectives must be considered. Integrating ecological ethics into education can cultivate a generation committed to sustainability and ethical responsibility.

The major work of the Cijurey Dam Project Package III is located in Bogor Regency, West Java Province, which is a spillway structure consisting of iron structures and concrete structures. To achieve the right quality, on time, on cost, and zero accidents, concrete casting calculations and appropriate work implementation methods are required. This research method uses descriptive with quantitative and qualitative approaches. The stages of concrete casting work for the Cijurey Dam spillway structure's launch channel consist of preparation, measuring the launch channel block boundaries, lean concrete work, reinforcement work, formwork panel preparation, formwork panel installation, waterstop and dowel bar work, concrete sampling and slump test, concrete casting, concrete curing/maintenance, formwork dismantling, and finishing of tierod holes. The results of the study showed that the calculations for casting the concrete channel were a large volume of concrete channel casting of 135,000 m3, concrete material requirements (in the form of: 1,115,100 sacks of cement, 58,050 m3 of sand, 1,020,600 m3 of gravel, and 29,025,000 liters of water), channel formwork (surface area) of 27,675 m2, productivity of casting the concrete channel launcher of 24 m3/hour or 193 m3/day, and the efficiency of casting the concrete channel launcher time of around 125% (25% faster than planned). Meanwhile, the stages of work implementation for channel concrete casting include preparation work, measurement work for the boundaries of the launcher channel blocks, lean concrete work, reinforcement work, formwork panel preparation work, formwork lubrication work, formwork panel installation work, waterstop and dowel bar work, concrete sampling and slump test work, channel concrete casting work, concrete curing/maintenance work, formwork dismantling work, and finishing work for tierod holes. In addition, an inter-segment locking system with a shear key is used to overcome problems with the concrete pump, joint inspections are carried out during mobilization, routine inspections, repairs and replacement of the concrete pump.

Fire incidents in Indonesia remain relatively high, with a total of 2,286 cases recorded. In 2022, the frequency of fires in Jakarta reached 1,691 cases, marking a 10% increase compared to the previous year, which had successfully reduced fire frequency by 23%. The high fire risk in high-rise buildings can lead to both material losses and casualties. This study aims to design the layout and determine the requirements for portable fire extinguishers  in a hospital project in Jakarta. The design of the fire extinguisher layout and requirements is intended for the operational phase of the building, ensuring optimal applicability. The location, area, and/or environment with various work activities and risk levels ranging from low to high indicate that safety is of paramount importance and must be prioritized, and that any form of accident should be addressed as early as possible. This research employed a qualitative descriptive method to describe and illustrate existing phenomena, both natural and human-engineered, through observation, interviews, and documentation. The findings show that the design of the fire extinguisher layout and requirements amounted to 61 units across the 4th to 7th floors, with the fire extinguisher layout plan attached. The type of fire extinguisher used on each floor is a 6-kg dry powder extinguisher. The conducted fire risk assessment indicates that each floor presents a moderate hazard, while some rooms exhibit a high hazard level. This study provides recommendations for the placement and requirements of fire extinguisher in accordance with standards and is expected to contribute to fire prevention efforts in the hospital project in Jakarta once it becomes operational.

Compensation is an effort to reduce the pollution load from other sectors to replace the wastewater load that will be discharged by businesses and/or activities due to river water quality being exceeded. Currently, most large rivers in Indonesia have exceeded the water quality standards set by the government. The one of the hospitals in Jember plans to discharge wastewater into the Bedadung River. However, the Biochemical Oxygen Demand (BOD) quality standard for the Bedadung River has been exceeded. Therefore, alternative compensation activities are needed to reduce the BOD levels of the Bedadung River. Bathing, Washing, and Toilet (MCK) facilities with biofilter septic tanks were chosen. This technology is considered to be able to effectively reduce the BOD concentration of domestic waste before being discharged into the environment. This study aims to calculate the potential for reducing the BOD pollutant load in Bedadung River water if compensation is carried out through the construction of MCK with a biofilter septic tank system, so that it is expected to provide a significant contribution to improving river water quality while supporting the sustainability of hospital activities.

Adoption of melon (Cucumis Melo L.) cultivation innovation plays an important role in increasing productivity and efficiency. This study discusses the application of innovation adoption in melon plants with greenhouse technology, hydroponics, modern irrigation technology, post-harvest processing mechanisms for breeding. This literature review uses the Systematic Literature Review (SLR) method to compare National Journals and International Journals that are relevant to Innovation Adoption. The use of the Internet of Things (IoT) allows automatic monitoring of environmental conditions. Technology in melon cultivation has a significant impact on agricultural productivity and efficiency. In the hydroponic system of soilless cultivation in limited land conditions, each innovation has challenges in its implementation, such as high investment costs, the need for training for farmers, and limited access to certain technologies  

Candikusuma Beach in Bali has experienced significant erosion since 2009, threatening public facilities, including a mosque in Candikusuma village. This issue is critical as it affects a coastal fishing community. To mitigate the erosion, a revetment structure using concrete block armor is proposed. This revetment aims to protect the coastal cliff from wave forces and prevent further erosion. The planning process begins with analyzing bathymetric and topographic data to assess land and sea conditions. Tidal analysis determines key water elevations, while wind data is used to calculate maximum and average wind speeds and directions. Wave hindcasting, based on wind data and effective fetch length, provides estimates of wave height and period. Shoreline changes are evaluated by comparing satellite imagery from 2003 and bathymetric surveys from 2012, revealing an average shoreline retreat of 21.70 meters over nine years. The design of the revetment includes a crest elevation of +3.70 meters MSL, constructed on a base at -0.5 meters MSL. The concrete foundation extends to a depth of -1.5 meters MSL. Hindcasting results show maximum wave heights of 1.21 to 1.50 meters from the southwest, with an average wave height of 0.01 to 0.30 meters from the south. The design wave height for a 25-year return period is 1.37 meters with a period of 4.58 seconds, resulting in a wave height of 1.31 meters at a depth of 2 meters. The estimated budget for the 200-meter-long revetment is Rp. 7,778,174,000.

Eco riding/driving is an approach to driving that aims to optimize fuel efficiency and reduce environmental impact. This technique guides drivers to avoid sudden acceleration and braking in order to maintain a stable speed, maintain optimal tire pressure and carry out regular vehicle maintenance. This technique helps save fuel, reduces greenhouse gas emissions, and extends vehicle life. The aim of this research is to determine the level of understanding of students in the automotive engineering education study program regarding Eco Riding. This research is a survey research carried out from July - December 2024 to 56 students in the automotive engineering education study program at Muhammdiyah University, Purworejo. The research data were analyzed using quantitative descriptive analysis. The research results showed that the level of students' understanding of Eco Riding was in the high category at 50%, followed by the medium category (32.1%), rendang category (14.3%) and very high category at 3.6%.

The transformation of Human Resource Development (HRD) through a data-driven decision-making system has become a strategic necessity for organizations aiming to improve performance and competitiveness. This study employs a qualitative descriptive approach by reviewing several relevant journals that discuss the integration of data analytics into HRD functions. The findings indicate that data-driven decision systems enable organizations to accurately identify training needs, predict employee performance, and design development programs that align with evolving organizational demands. Furthermore, the use of data reduces subjective bias in evaluation processes and enhances the objectivity of performance assessments. This transformation also strengthens the strategic role of HRD by providing timely and evidence-based recommendations that support organizational goals. However, successful implementation requires technological readiness, digital competencies among HR personnel, and an organizational culture that encourages data utilization. Overall, the literature review shows that adopting data-driven decision approaches significantly contributes to improving HRD effectiveness and organizational performance.

The development of vocational education requires Vocational High Schools (SMK) to align their competencies with student interests and industry needs. However, a mismatch between student interests and the competencies offered can result in low enrollment, requiring schools to consider closing certain programs. This study proposes the application of Artificial Neural Networks (ANNs) as a predictive method to determine the potential closure of vocational competencies based on an analysis of student interest patterns. The data used includes interest history, academic grades, and other preference indicators, which are then subjected to a preprocessing stage to ensure the quality of the model’s input. The ANN is trained to accurately recognize interest patterns, thus generating objective and adaptive decision-making recommendations. The results show that the ANN implementation provides high accuracy in predicting student interest trends and provides more precise The development of vocational education in Vocational High Schools (SMK) requires the ability to align skill competencies with students' interests and industry needs. A mismatch between students' interests and the competencies offered can lead to low interest in certain programs, which in turn may result in the decision to close those programs. This study proposes the application of Artificial Neural Networks (ANN) as a predictive method to determine the potential closure of skill competencies based on the analysis of students' interest patterns. The data used includes interest history, academic grades, and other preference indicators. This data is processed through a preprocessing stage to ensure the quality of input for the model. The ANN is trained to accurately recognize students' interest patterns, allowing it to generate more objective and adaptive decision recommendations. The results of the study show that the application of ANN has high accuracy in predicting students' interest trends and provides more precise recommendations compared to traditional methods. Therefore, this system can be an effective tool for schools to plan curriculum policies more strategically and sustainably, as well as support decisions regarding skill programs that align with students' interests and industry needs.  

Madrasas and Islamic boarding schools are Islamic educational institutions that have a strategic role in shaping the character, morals, and competencies of students. In addition to carrying out the formal learning process, these two institutions are also centers for moral, spiritual, and social development. In their operations, madrasas and pesantren manage various administrative activities, such as student data collection, attendance recording, grade processing, teacher data management, lesson schedule preparation, and delivery of academic information to related parties. However, many institutions still use manual systems that rely on notebooks or separate applications that are not integrated. This condition poses a number of obstacles, including the high risk of recording errors, duplicate data that is difficult to track, the slow process of recapitulation of grades and attendance, and delays in the delivery of academic information. In addition, manual processes cause administrative management to be less efficient and prone to data loss. As the need for fast, accurate, and accurate information increases, technological solutions are needed that are able to integrate all administrative and academic processes in one centralized system. Web-based information systems are an effective alternative to improve work efficiency, minimize errors, and facilitate access to information for teachers, students, and guardians. With the implementation of a well-managed system, madrasas and Islamic boarding schools are expected to improve the quality of services and support a more modern, structured, and sustainable learning process.

Liver disease is an increasingly prevalent health problem among the productive-age population, primarily driven by unhealthy lifestyles, alcohol consumption, obesity, and the risk of hepatitis infection. Liver dysfunction often presents no specific symptoms in its early stages, making early detection challenging. The Community Service Program (PKM) conducted in Grogol Village aimed to raise public awareness about the importance of early liver function screening through SGOT and SGPT enzyme assessments. This activity included education on risk factors as well as on-site liver enzyme testing for participants. Among the 71 participants, 18 individuals (25.35%) had elevated SGOT levels, and 17 individuals (23.94%) showed SGPT levels exceeding normal limits. These findings highlight the importance of early liver function screening in preventing the progression to chronic liver diseases such as NAFLD or hepatitis, and in serving as an indicator of cardiometabolic risk. Therefore, routine liver enzyme testing can serve as a foundation for increasing public awareness about the importance of maintaining liver and metabolic health in a sustainable manner.

Anemia is a hematological disorder that is often not recognized in the adult age group. One lifestyle factor that can affect hemoglobin and hematocrit levels is the consumption of tea or coffee with meals, because the tannin and polyphenol content inhibits the absorption of non-heme iron. Early detection of hemoglobin and hematocrit levels accompanied by education about eating and drinking habits is an important strategy in preventing anemia. This screening activity is carried out using the Plan-Do-Check-Act (PDCA) approach. Examination of hemoglobin and hematocrit levels is carried out using Point-of-Care Testing (POCT) from capillary blood. Education is provided to all participants through leaflets and group counseling regarding the effect of tea and coffee consumption on iron absorption. A total of 91 participants took part in this activity, consisting of 39.6% men and 60.4% women, with an average age of 47.4 years. The average hemoglobin was recorded at 11.2 ± 1.6 g/dL and hematocrit at 33.0 ± 4.7%. As many as 42.9% of participants experienced anemia based on hemoglobin levels below normal values ​​according to gender. Hemoglobin and hematocrit examinations successfully identified a significant proportion of individuals at risk of anemia. Education on the right time to consume tea or coffee and increasing consumption of foods rich in iron and vitamin C are preventive interventions that can be applied to maintain optimal hematological status.   Keywords: Hemoglobin, Hematocrit, Anemia, Iron, Tea, Coffee, Diet

The development of electric propulsion systems has become a major focus in efforts to provide energy-efficient and environmentally friendly air propulsion technology. One emerging innovation is the electric motor-based turbojet fan, which is expected to replace conventional fossil-fueled systems. As the need for energy efficiency increases, studies on electrical power consumption and airflow performance are crucial in supporting the development of new-generation propulsion systems. This study aims to evaluate the relationship between nozzle angle and the characteristics of electrical power consumption and airflow velocity in a double-spool turbojet fan. The method used is an experimental test with an ESP32-based control system. The duty cycle is set at 80% to maintain operational stability. Research data is obtained through measurements of electrical current, voltage, and airflow velocity. The nozzle angle variations tested include 13°, 19°, and 25°. The test results show a significant difference between nozzle angle variations on electrical power consumption and wind speed performance. The 13° nozzle angle produces the highest electrical power consumption, indicating a greater energy requirement to maintain airflow. Conversely, the optimal wind speed was found at an angle of 19°, indicating a balance between energy efficiency and aerodynamic performance. Meanwhile, an angle of 25° showed a decrease in performance in terms of both power and speed, making it less effective. In conclusion, the nozzle configuration has a direct influence on energy consumption and fluid dynamics in electric turbojet fan systems. This research provides an important contribution to the design of electric-based propulsion systems by emphasizing efficiency and performance aspects, while supporting the transition to environmentally friendly technologies.

Wireless communication, in its infrastructure nature, faces many challenges such as fading, data coverage, and interference issues. Therefore, High-Fidelity or (Li-Fi) is utilized due to its ability to naturally provide high-density wireless data coverage in closure’s particularly helpful for application(s) in some areas while the radio interference conditions are concern. This article illustrates an advanced Li-Fi approach performing high-speed data transmission between two Personal Computers (PCs) utilizing the Arduino Nano-based technique. In the experimental phase, data is mainly used to be transmitted over red laser diode (630 nm) through (30 cm) in distance, a distance of 30 cm, achieving a high peak speed reach to about (512Bps). The proposed approach performance is computed by evaluating the most important and related metrics like Signal-to-Noise Ratio (SNR), Bit-Error-Rate (BER), and influence of throughput on input data over various light circumstance. The proposed approach mainly utilizes a keypad as a user input and two related detection models for both a solar cell and a photodetector in order to make a powerful comparison in terms of performance. the results showed that when the photodetector applies a higher-detection efficiency (via BER enhancement which reaches to 20% over solar-cell), the solar-cell clarify outstanding power and cost-activity. The mentioned findings are propped by elaborated statistical-analyses and MATLAB simulation to design, simulate and visualize the validate functionalities of the robustness and scalability properties of the proposed Li-Fi approach.

Image classification is a key field in digital image processing with broad applications, such as object recognition and disease detection. The use of artificial neural network architectures, such as MobileNetV2, has significantly advanced pattern recognition in large datasets. However, in small datasets, challenges related to accuracy and generalization are often encountered. This study explores an RGB-based approach utilizing MobileNetV2 for image feature extraction and Support Vector Machine (SVM) as the classifier. MobileNetV2 is applied to extract features from RGB images, which are then further processed by SVM to determine image classes. The results indicate that this model achieves an accuracy of 91.67%, precision of 0.9163, recall of 0.9167, and F1-score of 0.9161. Based on the confusion matrix analysis, the model effectively distinguishes between classes, despite slight overlaps. This research contributes to the development of intelligent image classification systems that can be applied in various fields, including the food industry. With these achievements, the RGB approach integrating MobileNetV2 and SVM has proven effective in enhancing image classification accuracy, even with relatively small datasets. These findings open opportunities for applying similar methods in other image processing tasks that require high accuracy in object or disease detection and classification.

Developing research and community service (P2M) applications is crucial in enhancing efficiency and accuracy in managing related data at higher education institutions. This research aims to design a web-based application that simplifies the data management process for research, community service, and associated activities at Universitas Informatika dan Bisnis Indonesia (UNIBI). The research engaged the Rapid Application Development (RAD) methodology to actively incorporate stakeholders throughout the application development lifecycle, thereby guaranteeing alignment with their requirements. The results showed that the developed Application effectively resolved inaccurate data displays, manual data collection, and inefficient validation processes. Key features include a more accurate dashboard, an automated article validation tool integrated with Google Scholar, and streamlined submission community service activities. The activity submission process enhances operational efficiency and improves transparency and accountability in managing academic data. This research contributes to the broader adoption of digital solutions in educational administration, offering significant improvements in data accuracy and management at UNIBI.

The performance of pencak silat athletes is influenced by several important factors including physical condition, technique, tactics and psychology. This study aims to determine the body composition, level of nutritional knowledge, and endurance of pencak silat athletes. The type of quantitative research uses a non-experimental observational research design, the participants of this study were 20 Lumajang pencak silat athletes, consisting of 9 male athletes and 11 female athletes. The data in this study were obtained from body composition measurements using the Onemed 825 scan body fat scale, nutritional knowledge level tests from the adoption of the Nutrition for Young and Adult Athlete (NUKYA) questionnaire, and endurance tests using the Beep test. The results of the study showed differences in body composition in male and female athletes in terms of body weight indicators, Fat Free Mass (FFM), Skeletal Muscular Mass (SMM) and Body Mass Index (BMI). The athlete's body composition must be improved in the upper extremity muscle mass of the left and right arms and left and right fitness for female and male athletes and reduce fat mass for female athletes. The level of nutritional knowledge is higher for male athletes with fairly good scores and good endurance levels for both female and male athletes. For coaches, it is recommended to provide weight training programs for athletes with Circuit Training and for athletes to be more active in reading and understanding athlete nutritional knowledge.

Nonlinear dynamical systems represent a fundamental area of study in applied mathematics due to their relevance across various disciplines, including physics, biology, and engineering. Their inherent complexity, characterized by phenomena such as bifurcation, chaos, and sensitivity to parameter variations, often limits the effectiveness of traditional manual analysis, particularly when addressing high-dimensional or computationally intensive models. This study aims to address these challenges by applying computational modeling and numerical simulation techniques to analyze the stability of nonlinear dynamical systems. The research employs analytical methods, including equilibrium point identification and linearization, which are then validated and extended through the fourth-order Runge-Kutta numerical method. Simulations were conducted to visualize equilibrium points, phase portraits, and parameter-driven bifurcation phenomena. The findings demonstrate a strong correspondence between analytical and numerical approaches, with minimal error margins (≤1%) observed in equilibrium point estimation, thus confirming the reliability of computational methods. Moreover, the bifurcation analysis revealed critical transitions such as pitchfork and Hopf bifurcations, which indicate sudden shifts from stability to instability behaviors that are difficult to capture through manual calculations alone. The integration of computational approaches provides clear advantages, offering systematic exploration of parameter spaces and detailed visualizations of system dynamics, thereby expanding the scope of stability analysis. In conclusion, this study emphasizes that computational modeling is not only an effective complement to analytical methods but also a necessary strategy for advancing the understanding of nonlinear dynamical systems in applied mathematics.  

Nonlinear eigenvalue problems (NEPs) pose significant challenges in mathematical physics and other computational applications due to their nonlinear nature, which makes analytical solutions difficult to obtain. NEPs are encountered in various scientific and engineering fields, including signal processing, electronic structure calculations, and structural optimization. This study aims to explore the application of adaptive algorithms in solving nonlinear eigenvalue problems, with a primary focus on improving accuracy and computational efficiency. The proposed method combines an iterative solver with adaptive step-size adjustment, where the step size is dynamically adjusted during the iteration based on error estimates calculated at each step. This approach enables faster convergence and significant reductions in computational time without compromising accuracy. In experiments conducted on large-scale problems, the adaptive algorithm reduced computational time by 40% faster compared to fixed-step iterative methods. The comparison between the adaptive algorithm and traditional methods showed that the adaptive algorithm is not only more efficient but also more robust when dealing with high-complexity problems. Additionally, the adaptive algorithm provides more accurate error estimates, allowing better error control throughout the iteration process. Overall, this study concludes that adaptive algorithms offer a more effective and efficient solution for complex nonlinear eigenvalue problems and can be adapted to various types of problems in scientific and engineering applications. Further research could focus on optimizing the implementation of this algorithm for larger and more complex scales.