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This study aims to evaluate the effectiveness of various doses of 6.25% Poly Aluminium Chloride (PAC) and 0.1% polymer flocculant in reducing Total Suspended Solids (TSS) and assessing pH changes in coal stockpile wastewater at PT PLN Nusantara Power UP Paiton Unit 9. Stockpile wastewater typically contains high levels of suspended solids originating from water spray activities that carry fine coal particles. The coagulation–flocculation process was performed using the jar test method with PAC dosages of 35 ppm, 50 ppm, and 65 ppm, along with flocculant dosages of 6 ppm and 7 ppm. pH and TSS were analyzed before and after treatment to assess process effectiveness. The results indicate that a PAC dosage of 35 ppm combined with a 6 ppm flocculant achieved the highest TSS removal efficiency of 98.15%. Increasing PAC dosage resulted in reduced performance due to overdosing effects, leading to charge destabilization and impaired floc formation. These findings highlight the importance of optimizing coagulant dosage to improve stockpile wastewater quality for safe reuse in operational activities.

The rapid development of information technology encourages companies to optimize administrative sistems, including employee payroll processes, to ensure greater operational effectiveness and data accuracy. PT Infokom Internusa still utilizes manual and semi-computerized methods in payroll management, which may lead to calculation errors, data duplication, data inconsistency, and delays in report generation. These issues can affect overall organizational performance and decision-making efficiency. This study aims to design and develop a Java-based Employee Payroll Information Sistem to improve efficiency, accuracy, transparency, and security in payroll processing. The research employs the Waterfall software development model, which consists of requirement analysis, sistem design using Unified Modeling Language (UML), implementation using the Java programming language and MySQL database, and comprehensive sistem testing. The results indicate that the developed sistem is capable of automating salary calculations, allowances, deductions, tax computations, and report generation in an integrated and structured manner. The sistem also reduces manual errors, minimizes redundancy, and accelerates payroll administration processes. Therefore, the proposed information sistem can significantly enhance the performance, productivity, and service quality of the HR and finance departments at PT Infokom Internusa.

This study aims to analyze the strengthening of higher education governance in realizing transparent and accountable academic services. In the context of the globalization of higher education and increasing public accountability demands, universities are required not only to excel academically but also to provide services that are open, responsive, and accountable. This research employs a qualitative approach with a descriptive-analytical design. Data were collected through in-depth interviews, observations, and documentation studies involving university leaders, academic administrators, lecturers, and students. Data analysis was conducted interactively through data reduction, data display, and conclusion drawing. The results indicate that the principle of transparency has been implemented through digital-based academic information systems; however, consistency in updating information still needs improvement. Accountability has been supported by standard operating procedures and service evaluations, although performance measurement based on indicators has not been fully integrated. Stakeholder participation has been facilitated through evaluation forums, but involvement in strategic decision-making remains limited. Overall, the dimensions of transparency, accountability, participation, effectiveness, and responsibility are interrelated in shaping the quality of academic services. This study emphasizes that strengthening governance must be systemically internalized within organizational culture and institutional operational systems to enhance trust and stakeholder satisfaction.

This study aims to analyze the organizational structure, main tasks and functions, and challenges faced by the Legal Section in carrying out its role as a center for local government legal services. The research method used a qualitative approach through interviews with the Head of the Legal Section, direct observation in the work environment, and literature studies of various related documents and regulations. The results of the study indicate that the organizational structure of the Legal Section consists of functional positions, implementing officers, and temporary employees, each of which has a crucial role in supporting the legal product drafting process. However, the effectiveness of organizational performance still faces obstacles, particularly related to employee discipline, work ethic, and efforts to build a culture of bureaucratic integrity. The Head of the Legal Section emphasized that the quality of human resources is a key factor in determining the success of the process of harmonization of regulations and legal services. Thus, a sustainable apparatus development strategy and strengthening of the work system are needed so that the Legal Section can carry out its functions optimally in supporting the implementation of the Palangka Raya City government.

The plastic recycling industry generates wastewater that poses a potential threat to aquatic environments if not managed optimally. Performance evaluation of Wastewater Treatment Plants (WWTP) is typically conducted partially by comparing outlet parameters against effluent standards, often failing to depict water quality conditions holistically. Therefore, this study employs the Water Quality Index (WQI) approach using the Canadian Council of Ministers of the Environment (CCME) method to evaluate the performance of PT X's WWTP in East Java. This research utilized secondary data from inlet and outlet wastewater quality tests over 23 months (January 2024–November 2025), covering 10 parameters. Analysis was conducted by calculating removal efficiency and determining factors F1 (scope), F2 (frequency), and F3 (amplitude) as the basis for the WQI-CCME calculation. The results indicate that the WWTP achieved high efficiency (>80%) in reducing dominant parameters such as TSS, TDS, BOD, and COD. However, violations of effluent standards were still observed in certain parameters. The obtained WQI-CCME value was 69,30, categorized as "Fair" with a moderate level of violation. These findings demonstrate that although the WWTP meets regulatory standards, the WQI-CCME approach provides a more comprehensive assessment of performance. Optimization of advanced treatment units is recommended to improve effluent quality and sustainable WWTP performance.                                                                   

In this paper, we study the use of linear programming for the performance enhancement of fortified queues systems in which resources are unreliable in terms of variation and a case study on Marjan Hospital is considered. The quality management maturity level in the hospital was measured by an integrated inspection tool; senior management was found to be concerned for quality of service improvement and implementation of modern technology systems. Strengths and weaknesses in that activity are shown, and it is evidenced the need of boosting the quality of service activities and promoting the coordination between the different areas. From the findings, the study recommends the use of linear programming technique,Orgers should as well enhance proper training and development and Acquisition of modern day technology for effective performance improvement and quality of service. The study demonstrates that the adoption of linear programming techniques could be a viable solution to optimize resource allocation and enhance performance in the hospital's queue systems. Additionally, the research underscores the importance of investing in staff training and development programs, as well as the acquisition of state-of-the-art technology, to further improve service delivery and ensure sustainable quality improvement in the long term.

The implementation of e-government is one of the local government's strategies in improving the quality of public services and realizing Good Governance. This study aims to analyze the implementation of e-government through the Tangerang LIVE Application as an effort to improve Good Governance in the Tangerang City Government. The research method used is a qualitative literature study approach through the search and analysis of various literature sources in the form of books, scientific journals, and official government documents related to e-government, the Tangerang LIVE Application, and the principles of Good Governance. This research analysis uses the Good Governance principles framework according to the United Nations Development Programme (UNDP), which includes transparency, participation, responsiveness, effectiveness and efficiency, and accountability. The results of the study indicate that the implementation of the Tangerang LIVE Application contributes positively to increasing public information disclosure, expanding public participation, accelerating government responses to public complaints, increasing the effectiveness and efficiency of public services, and strengthening the accountability of local government performance. However, there are several obstacles to achieving Good Governance through the Tangerang Live application and these obstacles become an evaluation of the Tangerang City government to innovate through e-government that supports the improvement of Good Governance in the Tangerang City Government. This study recommends strengthening digital literacy, improving institutional coordination, and sustainable system development to ensure optimal and inclusive e-government implementation.

Traditional arts in Indonesia face a growing threat not from physical displacement, but from algorithmic distortion. This study examines how social media algorithms shape and distort public perception of Indonesian traditional arts — specifically jaranan and barongan — through the lens of Van Dijck's (2013) popularity principle: the principle that content distribution is determined by interaction volume rather than cultural value. Employing qualitative thematic content analysis, this study analyzes comments on five viral social media videos sourced from YouTube and TikTok, each depicting riots or tension at traditional art performances. Findings demonstrate that the popularity principle operates consistently and cumulatively across all five samples: algorithmically provocative titles, emotional polarization in comment sections, and micro-behavioral signals such as watch duration and replay collectively function as interaction signals that drive the platform to distribute riot content far more widely than culturally substantive footage. The consequences extend beyond perception: event organizers suffer long-term reputational and economic damage, while collective stereotypes — associating jaranan with violence and disorder — become sufficiently entrenched to surface spontaneously in unrelated contexts. A comparative analysis of a Kangen Band concert video reveals that these stereotypes have already achieved the status of cultural reference points. This study argues that strategic resistance is possible: the same algorithmic logic that amplifies negative content can be deployed to circulate culturally rich content, provided that artists, communities, and government commit to producing content designed to generate high-quality interaction. The challenge is to transform social media from a distorting mirror into an instrument of cultural preservation.

The objective is to analyze the competitiveness of modern retail through the integration of SWOT analysis as a basis for formulating more targeted strategies using qualitative descriptive methods. This paper identifies the strengths, weaknesses, opportunities, and threats that drive the performance of modern retail based on literature and empirical findings from various previous studies. The results of the analysis show that the main strengths of modern retail lie in product completeness, competitive prices, strategic locations, and operational efficiency. Meanwhile, weaknesses arise from suboptimal digitization, minimal online promotion, limited service innovation, and outdated inventory management. Meanwhile, opportunities arise from changes in digital-based shopping behavior, while threats emerge from the dominance of large retailers, e-commerce competition, and economic fluctuations. Based on the SWOT integration, a strategy is formulated that includes strengthening digitalization, optimizing online marketing, improving service quality, and modernizing operational systems to support long-term competitiveness.

Queueing systems play an important role in evaluating service performance, especially in small-scale businesses such as barbershops, where fluctuating customer arrival patterns and limited service capacity often lead to long waiting times. This study aims to analyze the performance of barbershop services using the M/M/1 queueing model and an analytical approach based on experimentally tested arrival (λ) and service (μ) rates. The model was selected because it represents a single-server system with Poisson arrivals and exponentially distributed service times, closely matching real barbershop operational characteristics. Using assumed realistic parameters, the analysis shows that when λ = 12 customers per hour and μ = 6 customers per hour, the system becomes unstable with a utilization rate (ρ) exceeding 1, indicating continuous queue growth. Further simulations with increased service rates demonstrate significant improvements: at μ = 15, the system achieves ρ = 0.8 with an average waiting time of 16 minutes, while at μ = 13, the system remains stable but experiences a long waiting time of approximately 55 minutes. These findings emphasize that barbershop performance is highly sensitive to service speed and that even small increases in μ can produce substantial improvements in queue stability and customer waiting times. The study concludes that barbershops must ensure adequate service capacity—either through optimizing service duration, improving worker efficiency, or adding servers—to maintain service quality and enhance customer satisfaction.

This study aims to systematically analyze the influence of Work Family Conflict (WFC) and Work Life Balance (WLB) on employee performance through a Systematic Literature Review (SLR) approach. The increasing demands of work and family roles in modern organizational settings make these variables highly relevant in organizational behavior research. The SLR procedure was conducted based on guidelines by Kitchenham and Wahono, consisting of planning, conducting, and reporting stages. Literature searches were performed across several academic databases, including Google Scholar, Garuda Ristek, ResearchGate, and university journal portals, covering publications from 2020 to 2025. From a total of 5,992 identified articles, 28 studies met all inclusion and quality criteria and were reviewed in depth. The findings indicate that Work Family Conflict consistently exerts a negative effect on employee performance by increasing stress, reducing concentration, and impairing psychological well-being. Conversely, Work Life Balance demonstrates a significant positive influence on performance, as employees who successfully balance their professional and personal responsibilities tend to exhibit higher productivity, job satisfaction, and engagement. Furthermore, factors such as organizational support, flexible working arrangements, and job satisfaction are shown to mediate or moderate the relationship between WFC, WLB, and employee performance. This study contributes by mapping the latest empirical patterns and providing recommendations for organizations to develop supportive work policies that enhance employee well-being and sustainable performance.

Student dropout remains a significant challenge for higher education institutions as it impacts academic quality, educational management efficiency, and students' success in completing their studies. Therefore, an approach that can identify students at risk of dropping out is necessary so that timely academic interventions can be made. This study aims to develop a dropout detection model using an Artificial Neural Network (ANN). The data used come from a publicly available higher education dataset, ensuring research reproducibility. Data preprocessing steps were carried out to improve data quality before modeling, and the Synthetic Minority Over-Sampling Technique combined with Edited Nearest Neighbors (SMOTE-ENN) was applied to address class imbalance issues. The ANN model's performance was evaluated using accuracy, precision, recall, F1-score, and area under the ROC curve (ROC-AUC). The test results show that the ANN model can provide excellent predictive performance in detecting at-risk students. The application of SMOTE-ENN also proved to enhance the model’s sensitivity toward the minority class, as indicated by improvements in recall and F1-score. These findings indicate that the developed ANN model has the potential to be used as a student dropout detection system to support data-driven decision-making and strategy development within higher education institutions.

The National Student Arts Festival and Competition (FLS3N) is an event aimed at developing students’ talents and achievements in the arts, including solo vocal competitions. The assessment process in this category involves multiple criteria, which may lead to subjectivity in decision-making. This study aims to design and develop a web-based Decision Support System (DSS) for selecting non-academic students in the FLS3N solo vocal category using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The assessment criteria are based on the 2025 FLS3N Technical Guidelines, consisting of voice quality, vocal technique, expression, and performance. The TOPSIS method is applied to generate alternative rankings based on the highest preference value. The system is developed using a web-based software development approach and tested using participant data from both male and female categories. The results indicate that the system can provide objective and consistent ranking recommendations, thereby assisting schools in selecting the best students to represent them in the FLS3N competition.

The growth of e-commerce in Indonesia has led to an increase in product reviews, including for beauty products on Tokopedia and Shopee. These reviews serve as important sources of information to assess consumer satisfaction; however, manually analyzing thousands of reviews daily is impractical. This study applies Natural Language Processing (NLP) with Naive Bayes, C4.5, XGBoost algorithms to classify sentiment in Indonesian-language reviews. The dataset used consists of 76,256 reviews labeled as positive, negative, and neutral. The research stages include text preprocessing, feature representation using BoW and TF-IDF, data balancing through SMOTE, and model performance evaluation based on accuracy, precision, and recall. Differences in results among the algorithms were analyzed using ANOVA. The results show that Naive Bayes achieved the highest accuracy at 67.71%, followed by XGBoost at 65.91%, and C4.5 at 58.39%, with Naive Bayes performing best in identifying positive and negative sentiments, while XGBoost and C4.5 handled more complex data patterns effectively. These findings provide guidance for sentiment analysis in Indonesian and support businesses in obtaining automated insights from customer reviews to improve product quality and services.

This study examines the influence of work discipline, training, and motivation on employee performance at PDAM Tirta Ayu, Tegal Regency. In a public service organization such as PDAM, employee performance is crucial to ensure customer satisfaction and strengthen institutional competitiveness. A quantitative survey method was used with questionnaires distributed to all 115 employees using a saturated sampling technique, as the entire population was included. The independent variables analyzed were work discipline (attitude, compliance with rules, responsibility), training (materials, methods, instructor competence, duration, facilities), and motivation (intrinsic and extrinsic). Employee performance, as the dependent variable, was measured using indicators of work quality, work quantity, teamwork, and problem-solving ability. The data were processed through multiple linear regression to assess simultaneous and partial effects. The research findings revealed that work discipline, training, and motivation each have a positive and significant impact on employee performance, but for training has a positive and insignificant effect, this is shown by the significant results of each significant level for work discipline sig value = 0.000 (<0.05), training sig value = 0.632 (>0.05) and motivation with sig value = 0.000 (<0.05). These results highlight the importance of strengthening employee discipline, implementing well-structured and sustainable training programs, and fostering sustainable motivation strategies. This research provides practical implications for PDAM Tirta Ayu management in designing policies to improve overall employee performance, thereby improving service quality and organizational competitiveness.  

Traffic congestion is a persistent challenge in urban areas in Indonesia, where increasing vehicle density creates the need for intelligent traffic monitoring systems. This study aims to develop a real-time vehicle parking system using the YOLOv8 object detection model to provide efficient traffic analysis from live CCTV broadcasts and recorded videos. This study uses a quantitative experimental approach with the implementation of the YOLOv8m model using the Ultralytics library in Python, tested on data collected from CCTV cameras A TCS Dishub Medan and additional footage from mobile devices. Vehicles are detected and counted in two directions up (Up) and down (Down) using virtual detection lines on the video frame. The system performance is evaluated by automatic detection counting with manually recorded ground truth data. The results show that on live CCTV broadcasts, the YOLOv8m model achieves an average precision of 98.96%, a recall of 96.59%, and an F1 score of 97.74% for upstream traffic, while for downstream traffic it achieves 100% precision, 95.64% recall, and an F1 score of 97.730/0. On the other hand, on high-quality recorded videos, all performance metrics achieve 100%, indicating perfect detection accuracy. These findings confirm the effectiveness of YOLOv8 in real-time traffic monitoring, but also indicate that video quality and stream stability affect detection performance. In conclusion, the developed system shows strong potential to support smart city traffic management solutions. Future research should focus on performance optimization under low-resolution live streaming conditions to improve accuracy in practical applications.  

This study aims to examine and analyze the effects of product quality and distribution channel on repurchase intention, with customer satisfaction and customer trust serving as mediating variables. The research employed a quantitative method with a causal-explanatory approach. The study population consisted of customers at the Weber building materials manufacturing company in East Java, with a sample of 275 respondents selected using purposive sampling. Data were collected via questionnaires and assessed using a Likert scale. The data analysis was conducted using the Structural Equation Modeling (SEM) technique with Partial Least Squares (PLS) software. The findings of the study reveal the following: 1) Product quality has a significant positive effect on customer satisfaction; 2) Product quality has a significant positive effect on customer trust; 3) Product quality has a significant positive effect on repurchase intention; 4) Distribution channel has a significant positive effect on customer satisfaction; 5) Distribution channel has a significant positive effect on customer trust; 6) Distribution channel has a significant positive effect on repurchase intention; 7) Customer satisfaction has a significant positive effect on customer trust; 8) Customer satisfaction has a significant positive effect on repurchase intention; 9) Customer trust has a significant positive effect on repurchase intention.

This study aims to analyze the influence of behavioral values and personality on the performance motivation of Gojek partner drivers in Medan City. The growth of application-based transportation services requires driver performance that is shaped not only by external organizational factors but also by internal characteristics inherent to each individual. Using a descriptive qualitative approach through a literature-based review, this study examines how behavioral values such as honesty, discipline, responsibility, and work ethics strengthen drivers’ commitment and consistency in delivering services. Furthermore, personality traits including emotional stability, perseverance, friendliness, and adaptability are found to significantly contribute to drivers’ ability to manage work pressure and maintain high-quality interactions with customers. The analysis reveals that strong behavioral values foster intrinsic motivation that enhances job performance, while positive work behavior and stable personality traits reinforce extrinsic motivation through customer satisfaction and improved ratings. Overall, behavioral values, work behavior, and personality are interrelated and collectively shape the performance motivation of partner drivers. These findings highlight the importance of character development, behavioral training, and personal competency enhancement to sustainably improve the quality of application-based transportation services.

This study presents a meta-analysis of open-access accounting information systems (AIS) literature in Indonesia during the digital transition period of 2015-2025. The primary objective is to identify and map the taxonomy of Independent Variables (X) and Dependent Variables (Y) predominantly used in academic and practical research. Through a systematic review of 15 key accredited articles with Digital Object Identifiers (DOI), this research finds that AIS success determinants (Variable X) have evolved from purely technical factors to integrative clusters encompassing Human Capital (competence, training), Organizational (culture, management commitment), and Technological (infrastructure, internal control) aspects. Meanwhile, Dependent Variables (Y) have shifted from mere technical user satisfaction to strategic impacts such as financial report quality, operational efficiency, and MSME business performance. These findings indicate that AIS research in Indonesia is heavily influenced by public sector regulatory contexts and cloud technology adoption in the MSME sector. This report serves as a reference framework for future researchers to explore emerging variables such as artificial intelligence and cybersecurity behavior within the accounting ecosystem.

The development of digital technology has led to an increase in the use of short video-based entertainment applications, including the Melolo application. However, the free version still has various complaints, such as inconsistent subtitles, unintuitive navigation, force close glitches, and unstable advertisements, so user satisfaction analysis is needed. This study aims to measure the level of satisfaction of users of the free version of the Melolo application using the End User Computing Satisfaction (EUCS) method, which covers five variables, namely content, accuracy, format, ease of use, and timeliness. Data was collected through an online questionnaire of 385 Melolo app users in Jambi City and analyzed using Structural Equation Modeling (SEM) with the help of SmartPLS 4. The results showed an R-Square value of 0.546, indicating that the model was able to explain 54.6% of the changes in user satisfaction levels. The variables of content and timeliness were found to have a significant effect on user satisfaction, while accuracy, format, and ease of use had no significant effect. These results indicate that content quality and system timeliness are the main factors in increasing user satisfaction. Therefore, Melolo app developers are advised to maintain content quality and improve system performance and stability to optimize the user experience.