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Gesture  recognition  technology  is  used  to  detect  movements  through  image processing,   enabling  computers  or digital devices to understand and interpret human  body  movements  as  input  or  commands.   This  technology  has  great potential  to bridge communication between the deaf community and individuals without   hearing   impairments,    enhancing  interaction  and  enriching  mutual understanding between the two.  However,  the accuracy ofgesture recognition is often  affected  by variations in the distance between hand landmarks.  Based on this problem,  this research proposes a methodfor stabilizing the measurement of distances between landmark points  in gesture recognition through a polynomial regression  approach.   Specifically,   the  distance  between  hand  landmarks  is calculated and stabilized using polynomial  regression to improve the accuracy of gesture recognition.  This method is implemented using the MediaPipeframework to detect and track hands in real-time,  and the OpenCV library to manage video. The  research  results  show  that  this  approach  can  significantly  improve  the stability  and accuracy  of gesture detection.   The developed system successfully detects gestures for  letters A  through F with a high accuracy  rate,  averaging above 98,3%.  The use ofpolynomial regression helps enhance detection accuracy by reducing noise in the landmark data.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

The development of the digital economy has driven increased customer interaction through online chat services, making customer satisfaction a key factor in business success. Response speed and chat service quality are two important aspects in shaping the customer experience, but previous research has tended to examine them separately. This study aims to analyze the influence of online chat services and response speed on customer satisfaction partially and simultaneously. The method used is a qualitative approach with a literature review of 12 scientific articles from 2020–2025 obtained from academic databases such as Google Scholar and SINTA. The analysis technique used is descriptive-critical through the identification, comparison, and synthesis of previous research findings. The results show that online chat services have a positive effect on customer satisfaction, primarily through interaction quality such as information accuracy, ease of use, and problem-solving ability. Response speed has also proven to be an important determinant, where a fast response significantly increases customer satisfaction. However, speed without quality has the potential to decrease satisfaction. The discussion shows that the two variables have a complementary and inseparable relationship. Online chat services function as a medium for interaction, while response speed is a quality attribute that determines the effectiveness of the service. Therefore, the integration of both in one model is the main contribution of this research in filling the literature gap, especially in the context of e-commerce in Indonesia.

This study used a quantitative approach with a survey method, distributing questionnaires to salon businesses in West Semarang. The number of respondents in this study was 100–150 businesses selected using a purposive sampling technique. The independent variables in this study were digital accounting literacy and digital payments, while the dependent variable was financial performance. The results showed that digital accounting literacy had a positive and significant effect on salon financial performance, as a good understanding of digital financial recording and reporting can improve the accuracy and transparency of financial information. Furthermore, the use of digital payments has also been shown to have a positive impact on financial performance, as it can speed up transactions, increase customer convenience, and facilitate automated recording. Simultaneously, these two variables contribute significantly to improving the financial performance of salon businesses.

Background: Digital transformation in arts education has introduced new paradigms in pedagogical tools, yet the specific role of artificial intelligence in fostering creativity within dance education remains under-explored. Objective: This study aims to analyze the contribution of AI Motion technology to enhancing the creative thinking skills of junior high school students in dance learning. Method: A systematic literature review was conducted following the PRISMA 2020 guidelines. A total of 30 peer-reviewed articles published between 2023 and 2025 were selected from databases including Scopus, ScienceDirect, ERIC, Google Scholar, and Garuda. Data were analyzed using the qualitative descriptive framework of Miles and Huberman. Results: The findings demonstrate that AI Motion technology significantly improves movement accuracy by up to 41% and fosters four key dimensions of creativity: fluency, flexibility, originality, and elaboration. The technology provides real-time feedback and visualization, enabling students to transition from passive imitation to autonomous movement exploration. Conclusion: The integration of AI Motion is strategically aligned with the Indonesian Merdeka Curriculum, which emphasizes differentiated learning and 21st-century skills. However, successful implementation is contingent upon overcoming challenges related to teacher digital competency and infrastructure accessibility. This study provides a conceptual framework for modernizing arts pedagogy through AI-assisted creative exploration.

The ability to describe graphs accurately in English is an essential academic skill for EFL learners, particularly in higher education contexts where students are required to interpret and communicate visual data. However, many learners still experience difficulties in producing grammatically accurate graph descriptions. This study aims to investigate the level of grammatical accuracy demonstrated by EFL learners in graph description tasks and identify the grammatical aspects that require further improvement. Employing a descriptive qualitative approach, the research analyzed 30 samples of students’ written graph descriptions produced by undergraduate learners. The analysis focused on several grammatical aspects, including subject–verb agreement, tense consistency, article usage, sentence structure, prepositions, and punctuation. The findings reveal that students frequently struggle with subject–verb agreement and article usage, while punctuation errors occurred less frequently. The study highlights that grammatical accuracy remains an important challenge for EFL learners in academic writing tasks involving data interpretation. Therefore, it is recommended that grammar instruction be integrated more intensively into graph description activities in English classes. The findings are expected to contribute to the development of more effective teaching strategies in academic writing instruction for EFL learners.

This study aims to examine the role of information technology (IT) professional ethics as a preventive instrument in facing the escalation of cyber crime in Indonesia. Using the Systematic Literature Review (SLR) method with the PRISMA protocol, 17 selected scientific literature from the 2020-2026 period were analyzed comprehensively. The results of the study indicate that dominant operating modes such as ransomware on national infrastructure and mass data breaches in the banking and health sectors are rooted in the neglect of integrity and accountability principles. The discussion in this study confirms that the application of professional ethics based on the PAPA (Privacy, Accuracy, Property, Accessibility) framework is able to suppress the risk of internal threats and strengthen digital defense. The conclusion of the study shows that the synergy between the 2024 ITE Law regulations and the internalization of the professional code of ethics is the main key to data sovereignty in the digital era. The practical implications of this research recommend strengthening the ethics curriculum in IT higher education and ethical compliance audits in the public sector.

The increasing complexity of urban transportation systems demands intelligent and measurable navigation methods. Medan City, the capital of North Sumatra Province, has a dense road network with multiple route options that often confuse road users. Dijkstra's Algorithm, developed by Edsger Wybe Dijkstra in 1959, is a greedy-based computational approach proven effective for solving the shortest path problem on non-negative weighted graphs. This study applies Dijkstra's Algorithm to determine the shortest route from Medan Railway Station to Universitas Negeri Medan (UNIMED). The road network was modeled as an undirected weighted graph with 15 nodes and 16 edges, where edge weights represent actual road distances measured via Google Maps. The graph has a density of 0.152, confirming its sparse graph characteristic. Three alternative routes were identified and analyzed. The algorithm was implemented in Python 3 using the heapq module as a priority queue. Results show that the optimal route is A → B → C → E → F → M → N → O via Jl. M.T. Haryono, Jl. Aipda KS Tubun, Jl. Madong Lubis, and Jl. Prof. H.M. Yamin, with a total distance of 6.64 km. This achieves 99.1% accuracy compared to Google Maps, with a deviation of only 0.06 km. The optimal route is 6.25% more efficient than Alternative Route 1 (7.30 km) and 11.9% more efficient than Alternative Route 2 (7.54 km). The algorithm executes in under 1 millisecond with time complexity O((V+E) log V). These findings confirm Dijkstra's Algorithm as highly effective for medium-scale urban road network optimization.

This study aims to analyze the implementation of the Bravo PUPR Online attendance system in improving the work discipline of Civil Servants (ASN) at the National Road Implementation Center of East Nusa Tenggara. The research focuses on punctuality of attendance, consistency in fulfilling working hours, task completion, compliance with attendance procedures, alignment between recorded data and actual conditions, and acceptance of consequences for violations. The study employs a qualitative approach with data collection techniques including observation, documentation, and interviews with leaders, system operators, and ASN as direct users. The results indicate that the implementation of the Bravo PUPR Online attendance system has improved administrative order in attendance and increased ASN awareness of time discipline. However, work discipline has not been fully optimal, as several issues remain, such as inconsistent attendance, suboptimal fulfillment of working hours, and discrepancies between attendance data and actual field conditions. In addition, technical constraints such as internet connectivity and GPS accuracy, as well as behavioral factors like negligence and lack of supervision, also affect system effectiveness. In terms of compliance, the Bravo system integrated with e-HRM is considered effective in detecting violations and enforcing strict consequences, ranging from warnings to administrative sanctions. This demonstrates that the attendance system functions not only as a recording tool but also as an instrument for monitoring discipline.

This study aims to develop a sentiment classification method for YouTube user comments related to the game Love and Deepspace using the Naïve Bayes algorithm, focusing on improving the text data processing and understanding user perceptions. Comment data were collected through scraping from YouTube videos, followed by preprocessing including text cleaning, normalization, stopword removal, stemming, and translation into English. Initial labeling was conducted using TextBlob, then the data were randomly sampled for training the Naïve Bayes model. Evaluation involved comparing sentiment distributions and visualization using Word Cloud and bar charts. The Naïve Bayes model achieved an accuracy of 77.36% in sentiment classification. The sentiment distribution shows differences between TextBlob (positive: 1,011, neutral: 1,312, negative: 575) and Naïve Bayes (positive: 901, neutral: 1,627, negative: 370), with Naïve Bayes being more conservative. The Word Cloud visualization identifies dominant words such as "bang," "game," and "main," while the bar chart shows the largest proportion of neutral sentiment. Naïve Bayes is effective for sentiment classification on informal comment data, with significant differences from rule-based methods like TextBlob. This research contributes to the development of text data processing techniques and user perception analysis, as well as opening up optimization opportunities with other algorithms like SVM for better accuracy.

The selection process for accepting new employees is one of the important stages in a company to ensure that the candidates accepted have qualifications that suit the company's needs. At WINMART, the selection process is still carried out manually, so it is less efficient and prone to errors. Therefore, a system is needed that can assist in more objective and efficient decision making. This Decision Support System (DSS) is designed to assist the selection process for recruiting new employees using the Simple Additive Weighting (SAW) method, which can assess several relevant criteria, such as work experience, education, skills and competency tests. This system was built on a web basis, so it can be easily accessed by parties involved in the selection process, such as HRD and managers. The SAW method was chosen because of its ability to convert various subjective criteria into more objective numerical scores, so that selection results can be more transparent and accountable. By using this system, it is hoped that it can increase efficiency, accuracy and transparency in the new employee selection process at WINMART, as well as facilitate decision making in selecting candidates who best suit the desired criteria.

 The quality of digital system services in the ship clearance process is closely related to the work effectiveness of shipping agency companies. The advancement of port operational services is influenced by the system’s ability to provide convenience, speed, accuracy, and service integration for users. The system used in the ship clearance process must be able to meet user needs and support inter-agency coordination so that ship services can operate more effectively and efficiently. This study aims to analyze the performance level and the level of user importance regarding the implementation of the Single Submission Pengangkut System in the ship clearance process at PT Trans Cakrawala Perkasa. The research employed a descriptive quantitative approach with a sample of 30 respondents consisting of ship agents involved in the clearance process. Data were collected through questionnaires, observations, and literature studies. The data were analyzed using validity tests, reliability tests, conformity level analysis, and the Importance Performance Analysis (IPA) method. The results indicate that the SSM Pengangkut System has made a positive contribution to accelerating document processing, facilitating system usage, increasing work productivity, and supporting coordination among related agencies. Based on the IPA Cartesian diagram, one indicator was identified as a priority for improvement, while other indicators were categorized as maintain performance, low priority, and high performance with lower importance levels. Overall, the implementation of the Single Submission Pengangkut System has been running quite well; however, continuous evaluation and improvement are still needed to optimize the ship clearance process further.

The implementation of Electronic Medical Records (EMR) is a key component of healthcare digital transformation, as mandated by the Minister of Health Regulation Number 24 of 2022. EMR is expected to enhance efficiency, accuracy, and the quality of nursing services. However, its implementation at M Hospital continues to face challenges, particularly in terms of infrastructure readiness and the digital literacy of nursing staff. This study aims to analyze the effects of infrastructure readiness and digital literacy on the implementation of nursing EMR, with perceived usefulness as an intervening variable. A quantitative cross-sectional design was employed, involving all nurses at M Hospital, with a total sample of 100 respondents using total sampling. Data were collected through structured questionnaires and analyzed using SEM-PLS. The results indicate that infrastructure readiness and digital literacy have both direct and indirect effects on EMR implementation through perceived usefulness (p < 0.05). Among the independent variables, infrastructure readiness demonstrates the strongest influence. These findings support existing theories and prior research. From a managerial perspective, the results highlight the importance of improving infrastructure to optimize EMR implementation. In conclusion, infrastructure readiness and digital literacy significantly influence the successful implementation of nursing EMR, with perceived usefulness acting as a key mediating factor.

This research critically investigates the circulation of disinformation concerning the instability of fuel prices on the digital platform X and its subsequent implications for the polarization of modern society. In an era where unverified economic news frequently dictates public reaction, fake news often acts as a potent catalyst for mass anxiety. By implementing a quantitative framework driven by lexicon-based computational sentiment analysis, this study effectively processed a dataset of 500 public opinion samples extracted via Google Colab spanning from April 2024 to April 2026. To ensure computational accuracy and eliminate textual noise, the data underwent a rigorous preprocessing phase encompassing case folding, alongside the systematic removal of URLs, account mentions, numbers, hashtags, and punctuation marks. The statistical outcomes revealed a highly disproportionate emotional landscape, overwhelmingly dominated by 451 negative reviews. In stark contrast, neutral observations and positive affirmations were nearly absent, recording only 40 and 9 instances, respectively. The data compellingly illustrates that the relentless influx of pessimistic narratives regarding economic instability directly induces financial panic, undermines rational discourse, and severely fragments cyberspace into deeply polarized factions.

This study aims to understand the role of E-Commerce in building customer loyalty, explain the process of loyalty formation, and assess how customers perceive service quality in relation to loyalty, using the GoFood service in Jombang as a case study. The rapid growth of online food delivery services has intensified competition, making customer loyalty a critical factor for sustainability. Employing a qualitative case study approach, data were collected through in-depth interviews with 30 GoFood customers and several drivers in the Jombang area. The findings reveal that E-Commerce platforms significantly enhance loyalty through user-friendly application interfaces, supporting features (such as live tracking, history, and digital payments), and beneficial promotions. The loyalty formation process occurs gradually through consistent positive experiences, moving from customer satisfaction to trust, and ultimately to habitual use. Crucially, the quality of driver services—including politeness, effective communication, punctuality, and order accuracy—emerged as a key determinant of customer comfort and repeat orders. This study implies that for E-Commerce platforms to maintain a competitive edge, strategies must integrate digital convenience with consistently reliable human interactions. The research contributes empirical insights from a semi-urban Indonesian context, highlighting that customer loyalty is not merely transactional but is built on a combination of technological ease, economic value, and positive interpersonal service experiences.

Social media has evolved into a significant platform where consumers freely express their opinions, experiences, and levels of satisfaction regarding various products, including those offered by Micro, Small, and Medium Enterprises (MSMEs). The comments and reviews shared by customers on these platforms contain diverse sentiments that can serve as valuable indicators of how consumers perceive product quality. Understanding these sentiments is crucial for MSME owners, as it allows them to evaluate their products and adapt to market expectations more effectively. This study aims to analyze customer sentiment toward MSME products on social media by utilizing the Naïve Bayes algorithm, a widely used classification method in text mining. The data used in this research consist of customer comments collected from various social media platforms. The research process involves several stages, including data collection, manual labeling of sentiments, text preprocessing (such as tokenization, case folding, and stopword removal), and splitting the dataset into training and testing subsets. Subsequently, the classification process is carried out using the Naïve Bayes algorithm to categorize sentiments into positive, negative, and neutral classes. The results of this study demonstrate that the Naïve Bayes method is effective in classifying customer sentiments with a satisfactory level of accuracy. These findings provide a comprehensive overview of consumer perceptions regarding the quality of MSME products. Furthermore, this research is expected to assist MSME business owners in understanding customer feedback more systematically and using it as a basis for improving product quality and enhancing customer satisfaction in a competitive digital marketplace.

This study aims to analyze the level of student satisfaction in paying tuition fees (UKT) through the BRImo application at Universitas Negeri Gorontalo. The research applies the service quality (SERVQUAL) framework, which consists of five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. A qualitative descriptive approach was employed, with data collected through in-depth interviews, direct observations, and documentation. Participants included students who actively use the BRImo application for UKT payments as well as staff responsible for tuition management. Data analysis followed a systematic process involving data reduction, data display, and drawing conclusions to ensure accuracy and clarity of findings. The results indicate that using the BRImo application for tuition payment offers significant convenience and efficiency, allowing students to complete transactions without physically visiting the university payment office. Despite these benefits, several challenges were identified, including failed transactions, delays in payment confirmation, and suboptimal responses from customer service staff. Overall, the study concludes that student satisfaction with tuition payments via BRImo is considered fairly good. Nevertheless, improvements in reliability and responsiveness are recommended to further enhance the user experience and optimize the quality of service provided.  

This community service activity aimed to build a disaster preparedness culture through earthquake and tsunami simulation activities at Madrasah Aliyah Negeri 2 Suak Timah, West Aceh Regency. The activity was motivated by the high risk of earthquake and tsunami disasters in the coastal area of West Aceh and the limited understanding of students regarding disaster mitigation and evacuation procedures. This program was carried out through collaboration between the Regional Disaster Management Agency (BPBD) of West Aceh Regency, lecturers from the Civil Engineering Department of Teuku Umar University, the Samatiga Community Health Center, and the school. The methods used included education, socialization, demonstrations, and direct simulations regarding self-rescue actions during earthquakes and tsunamis. The simulation was conducted at Suak Timah Football Field as the evacuation gathering point. The results showed an increase in students’ and school members’ knowledge and preparedness in facing disasters. Participants were able to understand evacuation routes, perform self-protection actions, and follow evacuation procedures in an orderly and rapid manner. Evaluation results indicated that disaster mitigation understanding reached 85%, self-rescue ability 88%, accuracy in following evacuation routes 90%, discipline during simulation 92%, and participant involvement reached 95%. This activity also encouraged the formation of a disaster awareness culture and the emergence of active student roles as preparedness pioneers within the school environment. Therefore, disaster simulation proved to be an effective educational medium in improving the capacity and preparedness of school communities toward earthquake and tsunami risks.

The search and booking of boarding houses (kost) remain a significant challenge for newcomers in campus areas, particularly in Kelurahan Samata, home to UIN Alauddin Makassar, which admits approximately 15,000 new students annually. Many of these students come from outside the region and require temporary accommodation near the campus. This issue is primarily caused by limited access to information and the lack of an optimal system to support the search and booking process. Therefore, it is necessary to evaluate the level of user acceptance of the developed system. This study aims to analyze user acceptance of a boarding house search and booking information system in the case of Kelurahan Samata using the User Acceptance Testing (UAT) method. UAT is a testing approach used to determine whether a system meets user requirements, is accepted according to expected standards, and to identify the need for further improvements to ensure its feasibility for use. The UAT was conducted by end users, namely boarding house seekers and property owners/managers, by responding to 10 evaluation indicators: (1) ease of search, (2) time efficiency, (3) booking process, (4) geospatial search features, (5) completeness of information, (6) availability of suitable boarding houses, (7) accuracy of information, (8) ease of payment process, (9) check-in scheduling, and (10) navigation features for directions. The results of the User Acceptance Testing (UAT) indicate that the system achieved an average score of 87.77, suggesting that the system is highly acceptable and significantly facilitates users. These findings demonstrate that the system is well received by users, confirming that it functions effectively and is capable of accommodating all required functionalities.

The Village Fund Direct Cash Assistance Program (BLT-DD) is a social protection instrument designed to help low-income families meet their basic needs. However, its implementation often faces challenges such as targeting inaccuracies, limited data, and varying administrative capacity at the village level. This study aims to evaluate the implementation of BLT-DD using William N. Dunn’s six policy evaluation criteria through a Systematic Literature Review (SLR) approach, covering effectiveness, efficiency, equity, responsiveness, conceptual alignment, and implementation. The findings indicate that BLT-DD is fairly effective in helping households maintain consumption, yet its effectiveness and adequacy remain constrained by the amount of assistance and the quality of data collection. Program efficiency and responsiveness are relatively good in villages with sufficient governance capacity, while equity emerges as the weakest aspect due to inaccurate data verification. Conceptually, BLT-DD aligns with the needs of low-income communities, but implementation accuracy still requires reinforcement. Furthermore, the study highlights the need for more systematic monitoring mechanisms, cross-sectoral data integration, and administrative training for village officials to enhance service quality. Overall, BLT-DD provides valuable support but requires improvements in governance and data systems to optimize outcomes, including regular evaluation strategies and refinement of supporting regulations.