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The rapid expansion of e-commerce in Indonesia has resulted in a significant rise in the number of customer reviews, which serve as a valuable source of insight for understanding consumer satisfaction. This study aims to classify or identify sentiments from product reviews on the Tokopedia platform into three categories, using the Support Vector Machine algorithm. The classification method data were ethically collected through web scraping and include review text, ratings, and the number of “likes.”  The preprocessing stage involved several NLP techniques such as pre-procesesing data representation was generated using the Term Frequency–Inverse Document Frequency method, while the issue of class imbalance was addressed using the Synthetic Minority Over-sampling Technique.  Based on the test results, the SVM model achieved an accuracy of 79.48% on the test data using a linear kernel, showing the best performance in classifying positive sentiments. However, the classification of neutral and negative sentiments still requires improvement. This study demonstrates that the combination of the TF-IDF method, additional numerical features, and data balancing techniques can produce an an efficient sentiment analysis model within the e-commerce domain.

The problems in rice fields are complex and varied, depending on geographic location, rice variety, and growing season. Pests often cause serious economic losses. The Solar Sonic Repeller is an innovative portable pest control device designed to address pest problems by utilizing renewable energy, specifically solar energy. This product aims to offer an environmentally friendly and efficient solution. It works by emitting ultrasonic sound waves with a frequency of 30,000–40,000 Hz. The device's advantages lie in its portability and energy independence, thanks to the use of a charging module powered by an integrated photovoltaic (PV) panel with automatic battery charging during the day. The first test measured the output frequency using an oscilloscope to verify that the oscillator circuit produced waves at the specified frequency. The second test measured the device's effectiveness by examining the pest response to the device at various distances. This test was effective within a maximum radius of approximately 14 m from the center point, covering a rice field area of ​​250 m2.

PAMTIRTA Tempino is an institution that provides clean water services in the Tempino area. The process of recording water use and monitoring water turbidity is still done manually, making it prone to recording errors and making it difficult to monitor the water quality distributed to the community. This study aims to design a website-based water turbidity recording and monitoring system by focusing on User Interface (UI) and User Experience (UX) aspects using the Design Thinking method. The research follows five stages of Design Thinking: empathize, define, ideate, prototype, and test. Data collection involves observation and in-depth interviews with PAMTIRTA officers. The results include a design with key features such as digital water meter recording, turbidity monitoring dashboards, and complaint services. The prototype was tested using Maze and the System Usability Scale (SUS), achieving a score of 80.1 and falling into the "Good" category (grade B). These results demonstrate that the UI/UX design effectively provides an easy-to-understand, operationally suitable, and efficient solution for PAMTIRTA Tempino's water recording and turbidity monitoring needs. This design offers a ready-to-implement solution to improve the efficiency, accuracy, and quality of clean water services in the Tempino area.  

This study examines the relationship between market efficiency and digital financial innovation in the context of global financial transformation over the past decade, when fintech, cryptocurrency, and Decentralized Finance (DeFi) have significantly altered price formation and information dissemination mechanisms. The main issue raised is whether the Efficient Market Hypothesis (EMH) theory remains relevant in the face of digital market dynamics characterized by high volatility, speculative behavior, and regulatory uncertainty. The objective of this study is to assess the impact of digital innovation on information efficiency, price transparency, and the stability of modern financial markets. The study used the Systematic Literature Review (SLR) method, examining 15 scientific articles published between 2015 and 2025 from various academic databases. The findings indicate that digital technology increases access and speed of information distribution, but does not always result in consistently efficient markets. Crypto and DeFi markets have been shown to exhibit fluctuating efficiency due to price anomalies, information asymmetry, and weak regulation. Overall, the literature synthesis confirms that market efficiency in the digital era is dynamic and influenced by the interaction between technology, investor behavior, and governance quality. This study concludes that the EMH remains relevant as a basic framework, but needs reinterpretation to suit the complex and rapidly changing characteristics of digital markets.

PT Mandiri Banana Indonesia still requires further development and arrangement of its layout and facilities to enhance the efficient and optimal use of land. This study aims to determine whether the existing layout at PT Mandiri Banana Indonesia is effective in supporting operational flow and the uninterrupted progression of the production process. The research adopts a quantitative descriptive approach, which is used to measure the correlation between activities through the Activity Relationship Chart (ARC) and Total Closeness Rating (TCR) methods. These methods enable the analysis to be presented in a measurable and objective manner as a basis for improving the facility layout. This study proposes a new layout design for the main production area and supporting facilities. The proposed layout is based on the results of ARC and TCR analyses, which indicate several critical spatial interrelationships among the facilities. Based on the findings and discussion regarding the application of the Activity Relationship Chart (ARC) and Total Closeness Rating (TCR) in designing the facility layout at PT Mandiri Banana Indonesia, it may be inferred that layout improvement exerts a significant impact on enhancing workflow efficiency and the overall work environment. The proposed alternative layout is expected to achieve a safer, more hygienic, and more productive spatial arrangement by establishing a clear separation between the production zone, administrative zone, and supporting areas.

This study aims to analyze multiple-choice questions related to phase e elements, namely the Principles and Basic Concepts of Accounting and Basic Banking, using the Anates program. The study involved 20 participants, consisting of college students and vocational high school students. The Anates application program serves as a tool to process academic evaluation data accurately and efficiently. The method used in this study is quantitative and is described descriptively, resulting in analytical findings including weighted data scores, test reliability, discriminative power, difficulty level, validity level, and distractor quality. The results from the Anates program make it easier for teachers to evaluate the quality of learning and develop more focused, innovative, and student-centered teaching plans. This research is expected to provide benefits in improving students' accounting knowledge, and teachers are expected to be able to adjust their teaching methods and strategies dynamically, thereby supporting the optimal improvement of students' learning outcomes in this digital era.

Zinc (Zn) is one of the most common heavy metal contaminants found in industrial wastewater and solid residues such as slag, electroplating waste, and metal ash. At excessive concentrations, Zn can cause environmental disturbances, including toxicity to aquatic organisms, disruption of microbial activity, and groundwater contamination. Long-term exposure may also lead to bioaccumulation and potential health risks to humans. This article presents a comprehensive literature review that discusses the chemical properties of Zn, its environmental behavior, and the development of recent treatment technologies within the last five years. Several techniques, including adsorption using modified or composite materials, biosorption utilizing microalgae and agricultural biomass, as well as solidification–stabilization with amendment agents such as biochar or iron-sulfide compounds, are evaluated and compared. The literature indicates that no single treatment method is universally effective for all waste types; therefore, hybrid or integrated treatment systems are considered more efficient and sustainable. Based on the reviewed evidence, this study proposes an engineering concept that emphasizes environmental safety, cost-effectiveness, and industrial applicability.

This study analyzes the gap in the implementation of Information Technology IT service management at an internet service provider in Purwokerto using the ITIL V4 Service Value System SVS framework. The company faces a number of major problems, such as delays in incident handling, data fragmentation between operational applications, low automation in network monitoring, and suboptimal coordination between the technical and customer service divisions. The purpose of this study is to evaluate the level of compliance of current service practices with ITIL V4 SVS best practices and to formulate recommendations for improvements that can increase operational efficiency and service reliability. The research uses a qualitative descriptive method with a case study approach, with data collected from interviews and observations in the technical and customer service divisions, then analyzed based on the five main components of ITIL V4 SVS. The results show that the company has implemented several ITIL principles, particularly in terms of customer value focus and process simplicity, but the implementation of iterative feedback, data integration, and automation is still at a low level of maturity. This study concludes that strengthening the real-time monitoring system, increasing cross-divisional visibility, and establishing a Continual Improvement Register are important steps towards realizing more efficient, responsive, and sustainable IT service management.

This community service activity aims to strengthen teachers' capacity to manage deep learning through the utilization of artificial intelligence (AI) in elementary school classrooms. The rapid development of AI technology provides opportunities for teachers to design more personalized learning, conduct assessments efficiently, and make data-driven learning decisions. The program is implemented in three stages: preparation, execution, and evaluation. The preparation stage includes the development of training modules and mapping relevant AI applications to support deep learning. The execution stage consists of workshops, hands-on practice using AI applications, and collaborative development of teaching materials by teachers. Evaluation is conducted through reflective assessments, task performance evaluations, and follow-up interviews. The results of the activity show significant improvements in teachers' understanding of AI-based deep learning management, including the ability to use AI for lesson planning, formative assessment, and analyzing students' learning progress. Teachers also reported increased confidence in integrating AI into teaching activities and recognized the benefits of AI in promoting students' higher-order thinking skills. This program demonstrates that strengthening teachers' competencies in utilizing AI can enhance the quality of deep learning management in elementary schools.

The study aims to improve the passion fruit syrup production system at Harisma Home Industry, which has been hindered by an inefficient facility layout and complicated raw material flow. These issues lead to longer processing time, higher operator workload, and reduced production capacity. To solve this, the research uses the Activity Relationship Chart (ARC) and Total Closeness Rating (TCR) to evaluate and redesign the layout. TCR results show that the Raw Material Warehouse has the highest priority with a score of 119, requiring an Absolutely Important (A) relationship with the Production Room. The Parking Area and Waiting Room also fall into the Absolutely Important category, as they support smooth movements of materials and visitors. Meanwhile, the Toilet has a Very Important (E) relationship with the Waiting Room due to comfort and accessibility needs. Based on these proximity requirements, a new layout was designed by placing the Raw Material Warehouse next to the Production Room to create a faster and more efficient material flow. Other facilities were rearranged to minimize unnecessary movement. This new layout is expected to streamline processes, reduce congestion, and enhance overall capacity and operational performance.

Innovation is the process of optimizing various resources to produce more efficient and sustainable solutions. This study aims to examine the relationship between resources and innovation strategies in supporting sustainable entrepreneurship through a Systematic Literature Review (SLR) approach. A total of 25 scientific articles were analyzed using PRISMA guidelines to examine the role of resources such as human, technological, information, financial, and physical resources in the context of product, process, and managerial innovation. The research findings indicate that the success of innovation is strongly influenced by the organization's ability to utilize and synergize its resources, especially in the development of internal capabilities such as tacit knowledge, research and development activities, and digital technology. Human resource creativity is the main driver of product innovation, while process innovation is strengthened by the application of technology and a learning culture. Managerial innovation is heavily influenced by entrepreneurial orientation and dynamic capabilities in responding to change. The implementation of sustainable innovation strategies such as green, digital, and social innovations also increases business competitiveness through cross-sector collaboration. This study emphasizes the importance of integrated resource management and innovative strategies to achieve sustainability, especially in the small and medium enterprise sector.

The Innovation Development Program conducted by Group 2 in Gunung Sari Ulu Village consisted of a structured series of mentoring activities designed to strengthen the financial literacy and marketing capabilities of local UMKM. The program focused on guiding participants in recording simple cash flow using the Monly AI application, which helped them understand how Artificial Intelligence can support more accurate and organized financial management. In addition, participants were taught how to properly separate incoming and outgoing transaction notes so that their business finances could be monitored more clearly and systematically. The program also introduced strategies for promoting products through digital marketing, enabling UMKM to expand their market reach by utilizing online platforms and creating more appealing promotional content. Overall, this activity aimed to broaden the participants’ knowledge of AI-based financial recording while also equipping them with practical marketing skills needed to increase visibility and attract consumer purchasing power. By integrating technology with improved marketing practices, the program sought to empower UMKM to operate more efficiently, enhance their competitiveness, and strengthen the sustainability of their business activities within the local community.

The increase in the population of Medan City has a direct impact on the increasing demand for housing and settlements, which is not always in line with environmental carrying capacity and the fulfillment of livable housing standards. Residential buildings contribute significantly to energy and water consumption, as well as environmental degradation, thus requiring a sustainable design approach. This study aims to formulate criteria and principles for the design of simple, livable houses by applying the concept of green buildings. The research method used is descriptive qualitative with a focus on the design of class 1a residential buildings. The study was conducted through a review of relevant regulations and standards, including the Ministry of Public Works and Public Housing's Green Building principles, the GREENSHIP Homes assessment system by the Green Building Council Indonesia, and livable housing indicators from the North Sumatra II Housing Provision Implementation Center. The results of the study show that the application of green building concepts in Small Houses can be realized through proper site management, optimization of natural lighting and ventilation, efficient use of energy and water, sustainable waste and wastewater management, and the selection of environmentally friendly building materials. The application of these principles can produce Small Houses that not only meet livable standards but also contribute to environmental sustainability.

This study aims to analyze the effectiveness of human resource (HR) governance in improving employee performance at the Serang City Cooperatives and SMEs Office in 2025. The research method used is a quantitative approach with a survey design, involving 100 employees as respondents. Data were collected through questionnaires and analyzed using multiple linear regression to test the effect of HR governance variables, which include planning, organizing, implementing, and supervising, on employee performance. The results of the study indicate that HR governance has a positive and significant influence on improving employee performance at the Serang City Cooperatives and SMEs Office. Specifically, clear HR planning, efficient organization, structured implementation, and effective supervision have been shown to increase employee productivity and work quality. The implication of this study is the importance of improving and strengthening HR governance as a strategy to improve employee performance, which ultimately can increase productivity, efficiency, and effectiveness in carrying out the duties and responsibilities of local government agencies.

Coffe is one of Indonesia’s leading commodities, known for its diverse flavors and aromas. Traditionally, coffee quality assessment is conducted manually through cupping tests performed by expert panelists. However, this method is subjective and requires considerable time and cost. This study aims to implement an Artificial Neural Network (ANN) using the backpropagation algorithm to classify coffee types based on sensory parameters such as flavor, aroma, acidity level, and body. Simulated data were generated from five common Indonesian coffee varieties: Arabica Gayo, Robusta Lampung, Arabica Toraja, Liberica Jambi, and Excelsa. The results show that the ANN-based classification system with a 4-8-1 architecture achieved an accuracy rate of 93% after 500 training epochs, with a final error value of 0.07. The implementation of this method provides an efficient and objective technological alternative to assist the coffee industry in maintaining product quality and automatically identifying coffee types.    

Information system security faces serious challenges due to increasingly complex cyber attacks. Intrusion Detection Systems (IDS) require efficient approaches to handle high-dimensional data such as the NSL-KDD dataset with 41 features. This study aims to implement the Genetic Algorithm (GA) for feature selection on the NSL-KDD dataset to improve the efficiency and accuracy of network attack detection. The method used is computational experimental research, involving data preprocessing, GA implementation for feature selection, building a classification model using Random Forest, and performance evaluation based on accuracy, precision, recall, F1-score, and computation time. The results show that GA successfully reduced features from 41 to 12 features (70.7% reduction), significantly improving computational efficiency. However, model accuracy slightly decreased from 0.4973 to 0.4951, indicating that while GA is effective for feature selection, the elimination of certain features may reduce classification capability. The implication of this study is that GA can be used as a tool to simplify intrusion detection models, but it should be combined with parameter optimization and data imbalance handling to achieve more optimal performance.  

Digital development has significantly influenced business practices, particularly for Micro, Small, and Medium Enterprises (MSMEs), which are required to adapt to technological changes in order to remain competitive. However, many MSMEs still rely on conventional marketing methods and have limited understanding of digital marketing and digital financial management. This community service program aims to strengthen MSMEs’ competitiveness through the implementation of digital marketing strategies that support market expansion and improve business sustainability. The program was conducted using a qualitative descriptive approach through a series of community service activities, including field observations, interviews, seminars, and mentoring sessions for MSME actors. The focus of the activities was to introduce and assist MSMEs in utilizing digital marketing platforms, particularly social media such as Instagram, TikTok, and Facebook, as well as online marketplaces, to promote products more effectively. In addition, MSME participants were introduced to basic digital financial applications to support more structured and transparent financial recording. The results of the community service activities indicate positive changes among MSME participants, including increased awareness of the importance of digital marketing, improved product branding, broader market reach beyond local areas, and better financial management practices compared to previous manual recording methods. The adoption of digital marketing strategies enabled MSMEs to communicate product information more efficiently and build consumer trust through online presence. This community service program demonstrates that digital marketing assistance combined with practical mentoring can enhance MSMEs’ competitiveness and contribute to improving community economic welfare. Continuous support and consistency from MSME actors are essential to ensure the sustainability of digital transformation initiatives.

Rapid advances in Information Technology (IT) in the 21st century have significantly transformed educational practices, particularly in vocational high schools (SMK) specializing in Software Engineering (RPL). Traditional learning media, such as textbooks, static slides, and lectures, often fail to provide an interactive learning experience, limiting students’ engagement and reducing the effectiveness of knowledge retention. To overcome this challenge, this study focuses on developing and validating an interactive quiz application called VOCANETIC, designed as an innovative learning aid for SMK RPL students. The research uses a Research and Development (R&D) approach, emphasizing the stages of product development, expert validation, and feasibility assessment. VOCANETIC is developed using VB.NET in the Microsoft Visual Studio environment, and MySQL is employed for efficient data management and storage. The application features interactive quizzes, real-time feedback, and user-friendly interfaces to enhance student engagement and motivation. Based on evaluation and analysis by expert validators, VOCANETIC meets the “Proper” feasibility criteria, demonstrating usability, interactivity, and educational effectiveness. The results indicate that VOCANETIC is capable of supporting active learning, improving students’ understanding of software engineering concepts, and providing an effective platform for self-assessment and practice. In conclusion, the VOCANETIC application is proven to be a valid, reliable, and practical tool that can be implemented as an interactive learning medium in SMK RPL, offering an innovative approach to facilitate student learning and engagement in the digital era.                                                              

The growth of artificial intelligence (AI) in healthcare is causing big shifts in management roles and how ready organizations are, especially in private hospitals. In Medan City, rising competition, a small healthcare workforce, and strict accreditation requirements all make it even more important to use digital technology to make operations more efficient. This study seeks to examine the impact of AI on organizational readiness, utilizing management performance as a mediating variable. Quantitative approaches were employed via a survey of managers and administrative personnel at private hospitals, and the data were analyzed using path analysis with SPSS. The findings indicate that AI exerts a favorable and considerable influence on management performance, which in turn directly enhances organizational readiness. Additionally, managerial performance has been demonstrated to mediate the relationship between AI and organizational readiness. These findings address a research gap concerning the mechanisms of AI's role in the managerial context of hospitals in developing countries and offer practical implications for fortifying digital strategies, cultivating human resource competencies, and augmenting organizational capabilities in response to technology-driven healthcare transformation.

Production quantity planning is a crucial component in the bottled water industry (AMDK) to ensure that consumer demand is met efficiently. Inaccuracies in determining the amount of production can lead to overproduction and supply shortages, which ultimately leads to increased operational costs and decreased customer satisfaction. This study applies the Sugeno fuzzy logic method to predict the amount of production based on two main variables, namely weekly demand and raw material stock. The analysis stages include the fuzzification process, the preparation of the rule base, inference using the zero-order Sugeno method, and defuzzification using the Weighted Average (WA) method. The data used is synthetic data that represents the operational conditions of the medium-scale bottled water industry. The results show that the Sugeno fuzzy system is able to produce production predictions that are adaptive and responsive to fluctuations in demand and stock availability. This model provides consistent and stable output, so it can help companies in determining the optimal production amount. These findings confirm that Sugino's fuzzy approach can be an effective decision support tool in bottled water production management, especially in the face of uncertainty and variability in market demand.