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The integration of artificial intelligence chatbots as virtual teaching assistants (VTAs) represents a transformative shift in student support services within higher education. This study investigates the implementation, effectiveness, and impact of AI-powered chatbots in providing academic support, administrative assistance, and personalized guidance to university students. Employing a longitudinal mixed-methods approach over 18 months, this research analyzed data from 2,347 students across 15 universities that deployed VTA systems, examining interaction patterns, student satisfaction, learning outcomes, and cost-effectiveness. Quantitative analysis of 487,392 chatbot interactions revealed that VTAs successfully handled 78.4% of student queries without human intervention, with response times averaging 3.2 seconds compared to 4.7 hours for traditional support channels. Qualitative findings from focus groups and interviews highlighted students' appreciation for 24/7 availability, immediate responses, and non-judgmental interactions, while also revealing concerns about empathy limitations, complex query handling, and the desire for human connection in critical situations. The study demonstrates that VTAs significantly improve support service accessibility and efficiency while reducing operational costs by an average of 43%. However, optimal implementation requires careful integration with human support staff, continuous training of AI systems, and attention to equity issues in digital access. This research contributes to understanding how AI can augment rather than replace human educators, offering evidence-based recommendations for implementing VTA systems that enhance student success while maintaining the human elements essential to quality education.

Halal tourism has continued to grow as a highly attractive segment for Muslim travelers, particularly in the provision of Sharia-compliant accommodation such as Islamic hotels. This study aims to examine consumer perceptions of halal food-and-beverage facilities and Sharia-based operational standards in Islamic hotels across the Greater Jakarta area (Jabodetabek). A descriptive quantitative approach was employed, involving 150 respondents who had stayed in Sharia hotels. Data were collected through closed-ended Likert-scale questionnaires and analyzed using the Weighted Mean Score (WMS) technique to evaluate respondents’ assessments of each indicator. The results indicate that consumer perception of halal food-and-beverage facilities falls into the very high category, with average scores exceeding 4.838. Consumers acknowledged that Sharia hotels maintain halal assurance, hygiene, and food safety through proper processing and the availability of halal certification. Regarding operational aspects, consumer perception is also classified as very good, with an average score of 4.606, particularly for policies prohibiting unmarried couples from sharing a room and banning entertainment deemed inappropriate or immoral. However, the use of Sharia-compliant financial institutions still requires improvement. Overall, the findings affirm that Sharia hotels in Jabodetabek have successfully implemented most Sharia principles, although further enhancement of internal operational practices is needed to achieve more comprehensive Sharia compliance.

The attendance recording system at PLN ULP Tanjungbalai still relies on manual, paper-based methods, resulting in delays in data recap, reduced efficiency, and a high potential for recording errors. This condition affects the accuracy of employee attendance information, which is essential for administrative activities and managerial decision-making. Based on these issues, this practical work aims to design and develop a web-based e-attendance application as a solution to enhance efficiency, processing speed, and the accuracy of attendance recapitulation. The system was developed using PHP as the programming language and MySQL as the database management system, following several stages including requirement analysis, system design using UML, and implementation of a web-based user interface. The application provides essential features such as user login, daily attendance recording, employee data management, attendance notes (permission, sickness, etc.), and automatic attendance report generation. The system is designed for two types of users—Admin and Employees—each with specific access rights. The implementation results indicate that the e-attendance application significantly improves the efficiency of attendance administration at PLN ULP Tanjungbalai. Data collection and recapitulation become faster, more structured, and less prone to errors, while also enabling administrators to monitor employee attendance in real time. Therefore, this web-based e-attendance application serves as an effective solution to support operational activities and enhance the quality of employee attendance management.

Background: The development of industrial technology in the Industry 4.0 era has encouraged the implementation of intelligent monitoring systems to improve machine reliability and operational efficiency. However, machine fault diagnosis systems based on artificial intelligence often face limitations in terms of interpretability because the models used are complex and difficult to explain. Objective: This study aims to develop a deep learning-based industrial machine fault diagnosis system integrated with an Explainable Artificial Intelligence (XAI) approach to improve diagnostic accuracy while providing interpretable insights for users. Method: The research method involves collecting data from industrial machine sensors consisting of vibration signals, temperature measurements, and acoustic signals, followed by data preprocessing and feature extraction processes. The processed data are then used to train a deep learning-based diagnostic model, after which explainability methods such as SHAP or LIME are applied to analyze the contribution of each feature to the model’s prediction results. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results: The results indicate that the proposed deep learning model achieves better performance compared to conventional machine learning methods such as Support Vector Machine and Random Forest. Furthermore, the explainability analysis reveals that vibration amplitude, increases in machine component temperature, and anomalies in acoustic signals are the main factors influencing machine fault detection. Therefore, the proposed system not only improves the accuracy of machine fault diagnosis but also provides transparency in the decision-making process, thereby supporting the implementation of predictive maintenance in smart manufacturing environments.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

Background: The development of modern manufacturing systems requires production scheduling strategies that not only improve productivity but also optimize energy utilization. Multi-machine production systems with job-shop configurations exhibit high complexity due to dynamic interactions between machines, job queues, and varying processing times, making conventional scheduling methods less effective in handling changing operational conditions. Objective: This study aims to develop and evaluate a reinforcement learning based production scheduling approach to improve production efficiency while reducing energy consumption in multi-machine manufacturing systems. Methods: This research employs a job-shop based multi-machine production simulation model as the experimental environment. The scheduling problem is formulated as a Markov Decision Process, enabling the implementation of reinforcement learning algorithms, namely Q-learning and Deep Q-Network, to learn optimal scheduling policies through interaction with the simulation environment. Energy consumption parameters are incorporated into the reward function so that the learning agent can consider energy efficiency in the scheduling decision-making process. System performance is evaluated using three main metrics, namely energy consumption, throughput, and makespan. Results: The experimental results show that the reinforcement learning based scheduling approach achieves better performance compared to conventional scheduling methods, resulting in lower energy consumption, higher job completion rates, and shorter production completion times within the multi-machine manufacturing system.

The UNAMA Library employs information systems to enhance its academic services. Nevertheless, its administrative framework continues to encounter obstacles, such as inadequate service system support for users, constrained resources allocated for the management and upkeep of the system, an absence of standardized protocols for addressing technical challenges, and insufficient assessment system efficacy. If these issues remain unaddressed, the operational effectiveness of the library information system will be compromised, thereby thwarting the objective of delivering dependable information services. This investigation seeks to illuminate the maturity level of information system governance as delineated by COBIT 2019 within the Decision Support Systems (DSS) domain, specifically focusing on the DSS01 (Manage Operations) and DSS02 (Manage Service Requests and Incidents) processes. The findings suggest that the degree of information system governance capability the UNAMA Library is situated at the Established Process level (level 3), signifying that the process has undergone implementation; however, it has yet to be comprehensively documented and consistently evaluated. Moreover, a disparity persists between the existing state and the anticipated capability level of the organization, particularly concerning IT operations management, the standardization incident handling, and the documentation of operational procedures. An elucidation of the expected level is articulated, especially in terms of operational standards, incident documentation, and IT infrastructure oversight. Recommendations encompass the formulation of standard operating procedures (SOPs), the enhancement of documentation practices, and periodic assessments grounded in COBIT 2019. These findings are anticipated to assist libraries in augmenting the efficacy of information systems governance and the quality of IT services.

This study aims to analyze the impact of business combinations through acquisition on the financial performance of PT Sarana Menara Nusantara Tbk. The research employs a descriptive quantitative approach, focusing on the acquiring firm in the Indonesian telecommunications infrastructure sector. The data used are secondary data obtained from the company’s annual financial statements for the period 2019–2023, sourced from the Indonesia Stock Exchange and the company’s official website. Financial performance is analyzed using Return on Assets (ROA), Return on Equity (ROE), Net Profit Margin (NPM), and Debt to Equity Ratio (DER) by comparing the periods before, during, and after the acquisition conducted in 2021. The results indicate that the acquisition exerted short-term pressure on asset efficiency and profitability, as reflected by the decline in ROA and NPM in the year of acquisition. However, in the post-acquisition period, the company demonstrated an improvement in operational performance, particularly in Net Profit Margin, suggesting that the economic benefits of the business combination gradually materialized. Meanwhile, fluctuations in ROE and DER reflect adjustments in the capital structure following the acquisition. These findings suggest that the success of an acquisition cannot be evaluated solely based on short-term financial performance but requires continuous assessment to capture its medium- and long-term effects. This study provides practical implications for management in formulating post-acquisition integration strategies and contributes empirically to the accounting and finance literature on business combinations in Indonesia.

As a maritime nation with vast sea territories, Indonesia faces significant challenges in safeguarding its waters, particularly in strategic regions such as the Natuna Sea. This area is vulnerable to various threats, including territorial violations, marine resource theft, and illegal underwater activities. This study aims to formulate a concept for the utilization of Autonomous Underwater Vehicles (AUVs) as an alternative solution to enhance underwater security systems in the region. The method employed is Research and Development (R&D), adopting model development steps and complemented by a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis to assess the feasibility and effectiveness of AUVs in the context of Indonesian maritime defense. The research findings indicate that the main strength of AUVs lies in their technological capability to effectively detect underwater threats. Although they have weaknesses, such as high operational costs, dependency on imported components, and limitations in battery endurance and sonar capabilities, these factors do not significantly hinder AUV effectiveness. Major opportunities arise from global technological advancements, yet challenges remain due to insufficient government policy support. The threats faced include the risk of sabotage and extreme weather conditions. Therefore, the recommended strategies are to maximize the use of technology, strengthen supporting regulations, and address logistical and financial barriers to realize effective and sustainable AUV operations in the Natuna Sea.

The growing demand for transparency, accountability, and measurable performance has transformed higher education institutions into complex public organizations required to deliver reliable and stakeholder-oriented services. Within this governance-driven environment, institutional governance plays a fundamental role in shaping service excellence and institutional legitimacy. Drawing on a public administration perspective, this study examines how governance dimensions influence academic service performance in higher education. This research employs a qualitative descriptive-analytical design. Data were collected through in-depth interviews, document analysis, and institutional observations involving university leaders, academic administrators, faculty members, and students. The analysis focuses on governance dimensions—transparency, accountability, participation, effectiveness, and responsibility—and their integration into institutional systems such as performance management, quality assurance, and digital infrastructure. The findings reveal that governance frameworks are formally established through regulations and digital systems; however, their operational integration remains uneven. Transparency improves service reliability when supported by consistent information management, while accountability mechanisms tend to emphasize procedural compliance rather than performance-based evaluation. Stakeholder participation is institutionalized but largely consultative. The study concludes that service excellence in higher education is a governance-driven outcome that requires systemic alignment between governance principles, institutional capacity, and performance management processes. Strengthened governance integration enhances service reliability and institutional legitimacy.

Advances in information technology increasingly require communities to adapt to digital communication tools, particularly email, which functions as a key digital identity for account registration, information exchange, and online transactions. Despite its importance, digital literacy remains limited among the general public, especially rural housewives, many of whom lack awareness of the need for email accounts, have limited operational skills, and are vulnerable to cyber risks such as phishing and data theft. To address this issue, a workshop entitled “Fundamentals of Using Gmail and Account Security” was conducted for the PKK women’s group in Jompo Kulon Village to improve basic digital skills and promote safe online practices. The program aimed to introduce the functions and benefits of email, assist participants in independently creating Gmail accounts, provide knowledge on securing accounts through two-factor authentication, and train participants to send and receive emails. The workshop was delivered through an interactive face-to-face approach combining short presentations and hands-on practice using participants’ mobile devices. Initial sessions explained email as a digital identity, followed by guided account creation and security setup. The final session focused on practicing email communication to reinforce understanding. The results showed high participant engagement, with most participants successfully creating Gmail accounts, understanding essential digital security concepts, and demonstrating basic email usage skills. Overall, the activity increased awareness of personal data protection and is expected to serve as an initial step in strengthening digital literacy among women, enabling them to better adapt to ongoing technological developments.

This study explores the roles of innovation and perseverance as critical success factors for young entrepreneurs in the fried chicken business through an in-depth case study of Fried Chicken Smile, located in Medan Tembung Subdistrict. The research focuses on how young entrepreneurs are able to survive and grow in a highly competitive culinary market dominated by global brands such as KFC. Using a qualitative research approach, data were collected through in-depth interviews with business owners and employees, direct field observations, and documentation analysis. The study is supported by several theoretical perspectives, including Grit Theory, which emphasizes perseverance and passion for long-term goals; Entrepreneurial Behavior Theory, which explains proactive and adaptive business behavior; and Schumpeter’s Innovation Theory, which highlights innovation as a driver of competitive advantage. The findings indicate that business success is influenced by continuous product innovation, particularly through adapting menu flavors to local tastes, maintaining consistent operational quality, and implementing effective digital marketing strategies via social media platforms. In addition, strong social support from family, peers, and local communities plays a significant role in sustaining entrepreneurial motivation. Overall, the study demonstrates that the combination of innovation, persistence, and social capital enhances competitiveness and supports the growth of micro, small, and medium enterprises (MSMEs). These findings provide valuable insights for the development of young entrepreneurship in Indonesia’s dynamic culinary sector.

This research was conducted at PT PLN Nusantara Power UP Paiton, one of the largest coal-fired power plants (PLTU) in Indonesia, which focuses on reducing the generation of hazardous and toxic oil waste through the implementation of an oil purification system. The use of large amounts of lubricating oil in the Electro-Hydraulic System (EHS) has the potential to produce high amounts of used oil waste. To address this, the company implemented two main technologies, namely Water Content and Varnish Removal, which function to reduce water content and varnish layers so that the oil can be reused without reducing engine performance. This research used a quantitative descriptive method with data collection techniques through field observations, interviews, and operational documentation from 2021 to 2024. The results showed that the oil purification system was able to reduce hazardous and toxic waste generation by 11.46 tons over four years. In addition to providing environmental benefits, the implementation of this system also resulted in savings in oil waste costs of approximately Rp6,200,560,000. Technically, purification maintains engine performance by reducing water and varnish content, while from an environmental perspective, this activity supports the principle of reduce in hazardous and toxic waste management. Overall, the oil purification system has proven effective in improving operational efficiency, extending oil life, and supporting sustainable waste management for industrial operations.

Interoperability has become a critical enabler of integrated service delivery in contemporary digital government. However, despite significant technological investments, many governments continue to experience fragmented service systems and limited public value outcomes. This study examines how institutional design shapes interoperability capacity and how interoperability contributes to public value creation within digital government frameworks. Employing a qualitative explanatory case study approach, data were collected through semi-structured interviews, document analysis, and institutional observations. The findings reveal that interoperability is not solely a technical function but an institutional capability embedded in governance structures, regulatory frameworks, data standards, and coordination mechanisms. While technical data exchange mechanisms exist, institutional fragmentation, regulatory ambiguity, and limited cross-agency collaboration constrain seamless integration. The study demonstrates that institutional design mediates the relationship between interoperability and public value creation by influencing the effectiveness of integrated service delivery. Public value gains are evident in operational efficiency and accessibility; however, improvements in legitimacy, trust, and service coherence remain incremental where institutional alignment is weak. The research contributes to digital governance literature by conceptualizing interoperability as an institutional construct and highlighting the necessity of governance reform for sustainable public value generation. The findings suggest that governments must prioritize institutional coherence, standardized data governance, and collaborative coordination frameworks to fully realize the transformative potential of digital government.

This study aims to evaluate the public transportation service policy of Trans Jatim Bus Corridor 2, operating on the Mojokerto–Surabaya route, using the six evaluation indicators proposed by William N. Dunn: effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness. Employing a qualitative descriptive approach, data were collected through interviews, direct observations, and secondary data analysis. The findings reveal that the Trans Jatim Corridor 2 service has significantly contributed to improving accessibility and mobility for the people of East Java. In terms of effectiveness, the service meets transportation policy objectives by offering strategic routes, consistent schedules, and accessible bus stops. Efficiency is demonstrated through optimal utilization of limited fleets and operational costs, while still meeting high passenger demand. Regarding adequacy, the service is generally sufficient; however, overcrowding during peak hours indicates the need for capacity improvements. Equity is reflected in the widespread distribution of bus stops, although disparities remain in the availability of facilities and route information across several stops. The service shows high responsiveness through quick handling of passenger complaints via applications and social media. Additionally, service appropriateness is evident in its punctual operations supported by GPS-based monitoring and real-time information through the TRANSJATIM-AJAIB application. Overall, the evaluation shows that Trans Jatim Corridor 2 provides effective, efficient, and responsive public transport services, yet requires improvements in capacity and equitable distribution of facilities to achieve optimal service quality.

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

This study aims to examine the effect of green innovation on company value, with financial performance as a mediating variable, in the mining industry. This study uses a systematic literature review approach by examining various relevant previous studies. The results of the study indicate that green innovation plays a significant role in improving environmental performance and operational efficiency of companies, which in turn positively impacts financial performance. Good financial performance is a key factor in strengthening company value and stakeholder trust. These findings confirm that the implementation of green innovation not only supports environmental sustainability but also provides long-term economic benefits for mining companies. This study also found that companies that successfully implement green innovation tend to have a better image in the eyes of investors and the public, which contributes to increasing the company's market value. These findings confirm that the implementation of green innovation not only supports environmental sustainability but also provides long-term economic benefits for mining companies, strengthening their position in an industry that increasingly prioritizes sustainability and social responsibility.

This community service activity was conducted at Grind Now Coffee Bar, an MSME in Batam City’s food and beverage sector, to address challenges in managing raw material inventory, which often led to inaccurate stock records, shortages, and overstocking, affecting daily operations and efficiency. The program aimed to improve inventory management by applying the Economic Order Quantity (EOQ) and Reorder Point (ROP) models, providing a systematic and measurable approach to procurement. Activities included detailed observation of operational practices, interviews with staff to understand current challenges, collection of data on raw material usage and purchasing patterns, and the implementation of a website-based inventory control system to streamline record-keeping and monitoring. The results showed that EOQ and ROP models helped determine optimal order quantities and appropriate reorder timing, while the inventory system improved organization, reduced errors, and enabled real-time stock monitoring. Overall, this intervention enhanced decision-making, promoted operational efficiency, and supported the sustainability and competitiveness of Grind Now Coffee Bar.

The interval between 2018 and 2025 represents a defining epoch in financial assurance, characterized by a systemic collision between traditional audit methodologies and the exponential sophistication of fraudulent actors. This research employs a comprehensive library research methodology, utilizing Systematic Literature Review (SLR) to evaluate the evolving landscape of audit and fraud. The study traces the theoretical migration from Cressey’s Fraud Triangle to multidimensional frameworks like the Fraud Pentagon, which emphasizes the roles of arrogance and competence. Through a forensic examination of catastrophic audit failures including Wirecard, FTX, and the emerging risks of crypto-assets, the research identifies recurring patterns of auditor failure in assessing operational risks and internal controls. Furthermore, the report analyzes the dual-edged impact of Artificial Intelligence (AI); while machine learning algorithms offer enhanced detection capabilities, the rise of Generative AI (GenAI) and deepfake technology has empowered perpetrators to execute sophisticated "synthetic reality" frauds. The study critically evaluates regulatory responses, particularly the revision of International Standard on Auditing (ISA) 240, which mandates a more proactive "fraud lens." The findings suggest that the auditing profession faces an existential crisis of relevance, necessitating a fundamental shift toward a forensic mindset supported by advanced technological integration.

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.