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This study investigates the influence of the Selena application’s service features on job satisfaction among sales personnel at PT Pegadaian Kanwil VII Denpasar, with the interest in using technology serving as a mediating variable. The research is motivated by the growing importance of digital applications in supporting operational performance and employee satisfaction, especially in the financial services sector. A quantitative causal research approach was employed to examine the relationships between the variables. Data were obtained through questionnaires distributed to respondents and supplemented with interviews to gain deeper insights. The sample consisted of 50 active sales personnel operating in the Bali region, selected using purposive sampling to ensure relevance to the research objectives. Data analysis was carried out using Structural Equation Modeling with the Partial Least Square (SEM-PLS) method through the WarpPLS 8.0 application. This analytical approach was chosen because it is effective in testing complex causal relationships and mediation effects, even with relatively small sample sizes. The findings reveal that the service features of the Selena application have a positive and significant effect on job satisfaction. Furthermore, the service features also exert a positive and significant influence on employees’ interest in using technology. The interest in using technology itself positively and significantly affects job satisfaction, confirming its role as an important factor in enhancing workplace outcomes. In addition, the mediation test results demonstrate that the interest in using technology significantly mediates the effect of service features on job satisfaction. These results highlight the importance of continuously improving application service features and fostering employees’ willingness to adopt technology to maximize job satisfaction and overall performance.

This study examines the implementation of the advertising tax policy and its role in supporting Regional Original Income (PAD) in Gresik Regency, and identifies barriers that affect its effectiveness. This research adopted a qualitative descriptive approach with data obtained from field studies involving key government officials and supported by relevant literature and regulatory documents. Data were analyzed using McNabb's (2002) framework, which includes grouping data based on constructs, identifying the basis for interpretation, developing generalizations, testing alternative interpretations, and refining theoretical insights. The results indicate that the implementation of the advertising tax policy in Gresik focuses more on intensification than extensification, as intensification is considered more practical and faces less resistance. The licensing and collection processes for advertising tax are carried out based on the legal framework of Regional Regulation No. 8 of 2023 concerning Regional Taxes and Levies and Regent Regulation No. 79 of 2023, which regulates the rental value of advertising as the basis for taxation. Despite significant revenue potential, significant challenges remain, such as inter-agency coordination issues, inadequate data collection, and technical and non-technical barriers in implementing this policy. Unclear legal sanctions and low public awareness and compliance are also inhibiting factors. Nevertheless, advertising tax revenue has generally reached its target, although certain periods were affected by unfavorable economic conditions. This study concludes that to maximize the contribution of advertising tax to local revenue (PAD), improved inter-agency coordination, strengthened institutional capacity, clarified regulatory sanctions, and enhanced public education and engagement are needed. This is expected to support regional fiscal independence in Gresik Regency.

Mindfulness or mindfulness is increasingly promoted in Western countries as a psychological strategy to improve emotional regulation and self-control, including in the context of reducing aggressive behavior, especially when individuals experience a state of exhaustion or ego depletion. However, the effectiveness of this approach in the context of non-Western cultures has not been widely explored. This study aims to replicate the study of Yusainy and Lawrence (2015) in Indonesia to test whether the induction of mindfulness can also moderate aggression after ego depletion in different cultural environments. This experimental research involved 119 Indonesian students as participants. Using a laboratory design, participants were divided into conditions of induction of mindfulness and control, and were asked to complete a reaction time competition task that had been modified to measure aggression (through the intensity of the sound explosions released against a fictitious opponent). In addition, an additional measure of the frequency of delayed maximum burst release was used to evaluate more subtle forms of aggression, particularly in female participants. The results showed that mindfulness significantly moderated the relationship between ego-depletion and aggression conditions, especially in low- to moderate-provoking situations. Mindfulness induction also showed improved self-control performance after participants completed aggression tasks. Another important finding is that the positive effect of mindfulness on aggression reduction is most visible in more subtle indicators of aggression, especially in groups of women who experience ego thinning. In conclusion, the results of this study reinforce the cross-cultural validity of the Western mindfulness approach and emphasize the importance of using more sensitive aggression measures, especially in assessing the effects of psychological interventions on female populations in non-Western cultures such as Indonesia.

This study aims to compare the effectiveness of the Deep Learning and Differentiated Instruction models in improving junior high school students’ mathematical problem-solving and reasoning abilities. The background of this research stems from the low level of mathematical literacy among Indonesian students, which demands innovative and reflective learning approaches. A quasi-experimental method was used with a Nonequivalent Control Group Design. The sample consisted of two eighth-grade classes at SMP Negeri Satu Atap 01 Ciseeng, each receiving different instructional treatments: one class was taught using the Deep Learning approach, and the other using the Differentiated Instruction approach. The instruments employed included mathematical problem-solving tests, observation sheets, and student perception questionnaires. The data analysis results indicated that the class taught with the Deep Learning model experienced a more significant improvement in mathematical reasoning ability compared to the class using Differentiated Instruction. These findings suggest that Deep Learning-based instruction is more effective in promoting students’ higher-order thinking skills. It encourages deeper engagement with mathematical concepts, fosters critical and analytical thinking, and allows students to construct knowledge through meaningful learning experiences. However, Differentiated Instruction remains relevant in providing learning comfort and addressing diverse student needs, making it beneficial in inclusive classroom settings. The theoretical and practical implications of this research highlight the importance of integrating both depth of thinking (Deep Learning) and flexibility in learning (Differentiation) within mathematics instruction. Such integration could offer a balanced learning environment that supports both cognitive development and emotional engagement, leading to more effective and equitable mathematics education. In conclusion, this study recommends educators and curriculum developers to consider incorporating Deep Learning strategies to enhance students’ mathematical reasoning while maintaining the adaptive and student-centered principles of Differentiated Instruction. Future research could explore hybrid learning models that combine the strengths of both approaches to maximize student outcomes in mathematics learning.

This study aims to examine the influence of independent variables—Social Media, Pricing, and Promotion—on the dependent variable, Repurchase Decision, at Kedai Kopi Bersahaja. A quantitative research method was employed, utilizing multiple linear regression analysis with the assistance of SPSS 25 software. The population of the study consisted of 226 consumers, and a sample of 107 respondents was selected using incidental sampling techniques. Data were collected through questionnaires distributed to visitors who had made at least one purchase at the coffee shop. The results of the analysis indicate that each independent variable—Social Media, Pricing, and Promotion—has a positive and statistically significant partial influence on the Repurchase Decision. Additionally, the variables collectively demonstrate a strong simultaneous influence, suggesting that an integrated marketing approach is crucial for fostering customer retention and encouraging repeat purchases. Among the three, Social Media showed the most dominant influence, emphasizing the growing role of digital presence and online engagement in shaping consumer preferences and purchasing patterns. Based on these findings, it is recommended that Kedai Kopi Bersahaja maximize the use of social media platforms such as Instagram, TikTok, and Facebook by creating engaging, relevant, and interactive content that resonates with the target audience. Content strategies may include customer testimonials, behind-the-scenes videos, product highlights, and limited-time offers. Pricing should be evaluated periodically to remain affordable yet profitable, considering both market competition and perceived customer value. Meanwhile, promotion efforts can be diversified through the use of loyalty programs, bundle offers, student discounts, and digital coupons. The synergy between these three marketing factors—if consistently and strategically applied—is expected to enhance customer loyalty, strengthen brand image, and significantly increase the likelihood of repurchase decisions. These efforts are essential for building sustainable business growth in the competitive food and beverage industry.

The increasing need for electrical energy in Indonesia encourages the development of new renewable energy (EBT), including hydroelectric power plants (PLTA) as an environmentally friendly solution. This research was conducted at the Mentawa Dam, West Toili District, Banggai Regency, Central Sulawesi, to analyze the potential of water energy that can be utilized as a source of micro-hydro power plants (PLTMH). This dam currently functions as irrigation and a tourist attraction, but has significant potential to generate sustainable electrical energy. The research methods include measuring water discharge using the float method, measuring the height of the water fall (head) with an altimeter and GPS, and analyzing the potential for electrical power using the formula P = η ⋅ ρ ⋅ g ⋅ Q ⋅ H. The measurement results show an average water discharge of 3.01 m³ / s and a water fall (head) of 6.56 meters. With a turbine efficiency of 80%, the potential electrical power that can be generated reaches 154.76 kW. This study recommends the use of Kaplan turbines in Mentawa Dam, which are ideal for large discharge conditions and low to medium heads, and can adapt to discharge fluctuations, making it an optimal choice to maximize energy potential. This research is expected to provide sustainable energy solutions for the people of Toili Barat District and support the development of the tourism sector.

The study presents a comprehensive framework for optimizing customer retention budget by integrating clustering, classification, and mathematical optimization techniques. The study begins with the IBM Telco dataset, which is prepared through data cleansing, encoding, and scaling.  In the preliminary phase, customer segmentation is performed using K-Means clustering, with k = 3 and k = 4 identified as optimal based on the elbow method and Silhouette score. The configurations produced three (Premium, Standard, Low) and four (Premium, Standard Plus, Standard, Low) customer segments based on purchase preferences, which served as input features for churn prediction. In the second phase, the dataset was divided into training and test sets in an 80:20 ratio, followed by data balancing using the Synthetic Minority Over-sampling Technique (SMOTE) and Edited Nearest Neighbors (ENN). Multiple classification algorithms were evaluated, including Naive Bayes (NB), Random Forest (RF), Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), Gradient Boosting (GB), Support Vector Machine (SVM), Logistic Regression (LR), K-Nearest Neighbors (KNN), and Multi-Layer Perceptron (MLP) using F1-score as the performance metric. CatBoost and LightGBM, with k values of 3 and 4, respectively, were the highest-performing classification models, with only minimal differences in performance.    Ultimately, customer segmentation established customer prioritization, whereas churn prediction assessed customer churn likelihood. Four distinct configurations were assessed utilizing mixed-integer linear programming (MILP) to optimise retention budget allocation within uniform budget constraints, discount amounts, and churn thresholds. In both the k=3 and k=4 scenarios, CatBoost surpassed LightGBM, with CatBoost at K=3 effectively discounting 66% of at-risk consumers across all three segments, hence improving the intervention's efficacy and budget allocation, making it the ideal choice for maximizing customer retention. The results demonstrate the importance of segmentation in enhancing retention budgeting and budget optimization, particularly concerning parameter sensitivity.

This study analyzes the influence of solar panel type and solar charging technology on the charging performance of lithium-ion batteries. Two types of solar panels, monocrystalline and polycrystalline, were tested alongside two charging technologies: Maximum Power Point Tracking (MPPT) and Pulse Width Modulation (PWM). Experiments measured voltage, current, and charging time parameters, and calculated the State of Charge (SoC) as a performance indicator. The results showed that the combination of monocrystalline panels with MPPT technology achieved the highest charging efficiency and shorter charging times compared to other combinations. These findings indicate that selecting the appropriate panel type and solar charging technology significantly affects lithium-ion battery charging performance, providing valuable considerations for portable solar energy system designs and renewable energy applications.

 The increasing use of electric vehicles in last-mile logistics distribution demands efficient and strategic charging infrastructure. This study aims to determine the optimal location for electric vehicle charging stations in Semarang City using the Set Covering Problem approach. A total of 17 last-mile distribution points operated by a logistics company were analyzed based on geographic data consisting of latitude and longitude coordinates, which were then processed into a distance matrix using the Euclidean formula. The optimization model was developed under the constraint of the electric vehicle’s maximum coverage radius and solved using binary linear programming. The analysis revealed that a single charging station located in Central Semarang is sufficient to cover all distribution points spread across the city. These findings reinforce the efficiency of the set covering approach in infrastructure planning and offer practical implications for logistics companies to optimize resources, minimize investment costs, and improve operational efficiency.

In today’s fast-evolving technological landscape, this study examines the profound integration of Artificial Intelligence (AI) into accounting and its far-reaching effects on the future of Nigeria financial markets. The incorporation of AI represents a fundamental shift in accounting, moving beyond conventional practices and ushering in unprecedented efficiency and advanced analytical capabilities. This transformation is instrumental in redefining accounting standards and influencing the broader economic dynamics of the financial sector. This paper aims to analyze the complex role of AI in accounting, evaluating its benefits, obstacles, and long-term potential. By connecting technological advancements with real-world accounting applications, the study provides an in-depth exploration of how AI is revolutionizing financial processes, its economic impact on Nigeria markets, and the balance between its advantages and inherent challenges. Additionally, the research proposes actionable strategies for optimizing AI adoption in accounting. The findings highlight that AI integration marks a critical advancement in accounting, improving precision, productivity, and strategic decision-making. Nevertheless, it also introduces hurdles such as workforce reskilling and ethical dilemmas. To address these challenges, the study recommends educational enhancements, policy adjustments, and cross-disciplinary cooperation to maximize AI’s potential in accounting. As a foundational contribution, this paper presents a compelling discussion on AI’s transformative role in accounting and its wider economic consequences, paving the way for future research and practical applications.

The purpose of this study was to determine the determinants of company value. The progress of globalization in the business world is currently growing rapidly. This can be seen from the rapid increase in data and innovation that encourages businesses to continue to grow. The company continues to strive to develop in accordance with the times that increase company value. The method used in this research is Systematic literature review (SLR). SLR is a research method to collect and evaluate research results related to topics that will become research topics. The data collection techniques used in this research are observation and literature research methods. The theory is obtained through Google scholar, dimensions, sinta kemendikbud, articles, journals, the data used in this study were collected by means of indirect data collection techniques and sourced from intermediary media the research data collection period is articles from 2023 to 2025. Factors that affect firm value, namely Intelectual Capital Disclosure (ICD), financial performance, and Good Corporate Governance (GCG). Overall, to achieve maximum firm value, business organizations should not only focus on the collection of intellectual capital, but also on openness in its disclosure as well as the implementation of strong GCG practices.

A single paragraph, maximum 250 words. Abstract content must contain (1) an overview of the object This study aims to identify and analyze various behavioral finance factors that influence investment decisions, especially among the younger generation and individuals who invest. The method used is the Systematic Literature Review (SLR) with data sources from Google Scholar in the period 2020 to 2024. The focus of this study is on factors such as regret aversion, mental accounting, illusion of control, and overconfidence. The results of research from various journals show that these psychological factors have a significant, although varying, influence on investment decisions. Some studies confirm the strong influence of these factors, while others provide different results. Therefore, it is very important for investors and policy makers to understand these dynamics in order to improve the quality of investment decision making.

Infused water is a functional beverage made by soaking slices of fruits, vegetables, and herbs in mineral water to produce a natural flavor and enhance nutritional content. In recent years, infused water has become part of a healthy lifestyle trend due to its claimed benefits, including detoxification, improved hydration, and immune system enhancement. This article aims to review the latest scientific literature on the potential benefits of infused water on immune function, particularly in the context of regular consumption of natural ingredients such as lemon, ginger, strawberries, and herbs that are rich in vitamin C, antioxidants, and flavonoids. The review was conducted by searching scientific databases such as PubMed, Google Scholar, and ScienceDirect, using inclusion criteria that covered publications from 2020 to 2024. The findings indicate that infused water containing vitamin C, gingerol, and polyphenolic compounds can help improve immune function by reducing oxidative stress, suppressing inflammatory responses, and stimulating immune cell activity such as lymphocytes and macrophages. Furthermore, optimal hydration from infused water supports various physiological processes of the immune system. In conclusion, infused water holds potential as a simple, natural, and cost-effective strategy to support immune health. However, further research is needed to evaluate its efficacy, optimal formulations, and dosage for maximum benefit.

The Kampunge Arek Suroboyo Gender- and Child-Friendly (KAS-RPA) Program is an initiative launched by the Surabaya City Government to establish a child-friendly city through women's empowerment and child protection. This program focuses on various key indicators, including education, health, caregiving, safety, and creativity. This community service activity aims to provide assistance in the development of the KAS-RPA portfolio in RW 04, Gundih Sub-District, Bubutan District, Surabaya City, which serves as the designated community service site. The method employed in this community service program includes socialization of the KAS-RPA program to local cadres, followed by intensive consultations and discussions. The assistance process encompasses the identification of village potentials, collection of relevant documentation, and portfolio development in accordance with established guidelines. The outcome of this community service demonstrates the successful implementation of all KAS-RPA program indicators in RW 04, supported by the residents' favorable socio-economic awareness and educational background. This has resulted in a safe and comfortable living environment, with minimal occurrences of violations against children's rights or violence against women.In conclusion, the collaboration between facilitators and local cadres has proven effective in exploring and implementing the program's indicators. It is recommended that the program's coverage area be expanded and that similar activities be continuously conducted to maximize the program's positive impact throughout the city.

Firm value is the investors’ perception of a company's success in maximizing shareholder wealth, which is reflected through its stock price. The purpose of this study is to examine the effect of corporate social responsibility (CSR), investment decisions, and profitability on firm value in the consumer non-cyclicals sector listed on the Indonesia Stock Exchange (IDX) during the 2021–2023 period, with leverage as a control variable. This study employs a quantitative approach with an associative research design. The sample consists of 20 companies selected using purposive sampling, resulting in a total of 60 observations over three years. The analysis technique used is multiple linear regression with the assistance of SPSS software. The results show that CSR and profitability have a positive affect on firm value, while investment decisions do not have an affect. This study implies that companies need to enhance CSR practices and profitability to improve their firm value in the eyes of investors. Additionally, this study contributes theoretically to the development of literature on the factors influencing firm value and can serve as a reference for future research.

This study aims to analyze the performance and conduct reverse engineering of the Francis Turbine runner at the Tanggari 1 Hydroelectric Power Plant (PLTA Tanggari 1) through 3D scanning and Computational Fluid Dynamics (CFD) simulation. The main objective is to evaluate the turbine's efficiency and identify areas for improvement in the runner geometry. Data from the 3D scan are used to reconstruct a CAD model, which is then numerically tested to predict hydraulic performance. CFD simulations are carried out under various guide vane openings and head variations. The simulation results show a maximum efficiency of 93% at a head of 122.4 meters with a guide vane opening angle of 26° and a flow rate of 8.5 m³/s. The resulting performance curve and hill chart indicate the optimal operating point or Best Efficiency Point (BEP), which serves as a critical reference for turbine operation settings. Flow phenomena such as separation and vortex formation were detected under off-BEP operating conditions, potentially causing pressure fluctuations and vibrations. As a technical recommendation, it is advised to operate the turbine close to the BEP to minimize vibrations and energy losses. Furthermore, the runner geometry obtained from reverse engineering can serve as a basis for component refabrication and the development of new runner designs that are more adaptive to varying load conditions.

The development of construction materials is currently very rapid, including in the manufacture of fishing boats that still use wood. As an alternative, High Density Polyethylene (HDPE) plastic can replace wood because of its various advantages. The process of making fishing boats uses the plastic welding method, where the material is heated close to the melting temperature with a welding gun. The welding rod melts due to heat and is pressed continuously while the welding gun moves backward. This study aims to determine the effect of variations in the hot gas welding process on mechanical tests, especially bending tests on plastic welding joints. The two independent variables used are the hot gun temperature (250°C, 300°C, and 350°C) and the V bevel angle (60°, 75°, and 90°). The five controlled variables include the anvil temperature of 150°C, 3,2 mm thick HDPE plastic sheet, hot gas speed welding method, 5 mm diameter HDPE plastic additives, 7 liters/minute air flow rate, 1.2 mm/s welding speed, and 2 mm root gap. The research results are expected to obtain the maximum value of the bending test strength from the interaction of hot gun temperature variations and V-beam angles, as well as being a reference in making fishing boat bodies from HDPE using the hot gas welding method.

Engine overheating is a critical condition that can cause damage to internal components, reduce operational efficiency, and lead to overall system failure. The absence of an automatic protection system is one of the primary factors contributing to damage. This study aims to design and test a temperature sensor-based safety device that can automatically cut off the engine's working system when the temperature exceeds the safe limit. The method used is descriptive statistical analysis to evaluate the effect of independent variables (operational time duration and workload) on the dependent variable (coolant temperature). The system was tested through water heating simulation using an electric heater and controlled by an Arduino Nano microcontroller, a MAX6675 temperature sensor. Testing was carried out with variations in power load (150, 300, 450, 600, and 750 Watts) and operational duration (20, 40, and 60 minutes). Temperature data were collected and analyzed using ANOVA to determine the effect of load and time on temperature increase. The results showed that the temperature increased significantly with increasing power load, with temperatures approaching 100°C at loads ≥450 Watts in less than 20 minutes. The load variable shows a significant effect on temperature (p < 0.05), while the duration of time shows a nonlinear but not statistically significant upward trend. The safety device is proven to be able to automatically disconnect the system when the temperature reaches the specified maximum limit, thus effectively preventing engine damage due to overheating.

Motorcycles are two-wheeled vehicles that have a fairly high economic value compared to other vehicles in the general public. Motorcycles are formed from several constituent components such as the vehicle frame, engine, transmission, final gear, and wheels. One of them that will be discussed is the use of final gear. The purpose of this study is to determine the amount of torque produced from 3 variations of final gear 13Tx49T, 14Tx48T, 15Tx50T on the 2017 r15v3 motorcycle. From the data obtained, the maximum torque size at the final gear use size 13Tx49T = .... Nm at a speed of 8000 rpm. 14Tx48T = .... Nm at a speed of 8000 rpm. 15Tx50T = .... Nm at a speed of 8000 rpm. Meanwhile, the difference in torque ratio produced by the final gear (standard) size 14Tx48T with the size 15Tx50T the difference in value = ... Nm. final gear size 15Tx50T more (big/small), Large difference in torque ratio size 13Tx49T with size 14Tx48T value difference = ... Nm over (large/small) 14Tx48T, Large difference in torque ratio of size 15Tx50T with size 13Tx49T is value difference = .... Nm larger/smaller 13Tx49T/15Tx50T than 13Tx49T/15Tx50T size.

SPP Bandung plays a role in managing the distribution of shipments effectively and efficiently. SPP Bandung handles two types of distribution, namely primary distribution outside the Bandung area and secondary distribution to 12 distribution centers within the Bandung area. Currently, SPP operates six fleets to serve both types of distribution. However, the current distribution system has not optimized the fleet capacity, resulting in a waste of time and resources. This study uses a quantitative approach to analyze and develop an optimal distribution route strategy. By applying the saving matrix, nearest insertion, and nearest neighbor methods, the analysis results showed a decrease in total mileage from 261.8 km to 249.6 km and fuel cost efficiency from Rp210,377.33 to Rp198,539.33. The aving matrix method proved to be effective in route optimization, but other methods can also be considered for maximum improvement.