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This research is driven by the urgency of maintaining the quality of the Indonesian language in the realm of online journalism, particularly on major media platforms such as CNN Indonesia. Online media plays a central role as the primary source of information, but the speed of publication often encounters linguistic errors that have the potential to damage credibility and lead to misinterpretation among readers. The focus of the study on syntactic errors is crucial because errors in sentence structure, diction, and conjunctions directly affect the meaning and effectiveness of communication. This study aims to analyze and describe the forms of syntactic errors (including sentence pattern errors, non-standard diction, and conjunction redundancy) and offer recommendations for improvement based on standard Indonesian language rules. The method used is a qualitative descriptive approach with a syntactic approach. Data in the form of linguistic units at the phrase, clause, and sentence levels from all CNN Indonesia news texts for the period of August 2025, collected using the Listen and Note Technique. The findings are anticipated to show a dominance of sentence ineffectiveness, incorrect use of conjunctions, and temporally illogical diction errors. This research is expected to contribute as a practical guide for editors and news writers to improve the quality of editing, while also supporting literacy efforts and the use of good and correct Indonesian in the digital public space.

This study aims to compare the performance of Multiple Linear Regression (MLR) and Random Forest Regression (RFR) in predicting student performance based on academic scores. Student performance is defined as the average of math scores, Reading Scores, and writing scores. This study uses a quantitative approach with a comparative design based on predictive modeling. The data used is secondary data from the Student Prediction dataset obtained through the Kaggle platform, which was processed using the Python programming language through the Google Colab platform. The analysis stages included the formation of performance variables, the separation of training and test data with a ratio of 80:20, model training, and evaluation using the Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R²) metrics. The results show that the Multiple Linear Regression model produced an MSE value of 2.74 × 10⁻²⁸, an MAE of 1.51 × 10⁻¹⁴, and an R² of 1.000. Meanwhile, Random Forest Regression produced an MSE of 0.296, an MAE of 0.375, and an R² of 0.998. These findings indicate that both models have a very high level of accuracy, but Multiple Linear Regression provides the best performance. This is due to the strong linear relationship between the input variables and the target variables formed directly from the combination of academic values. Thus, the linear regression model is proven to be more suitable for use in data structures that have simple linear relationships compared to ensemble-based models.

English is an international language that plays an important role for students in the era of globalization; however, speaking anxiety or fear of speaking remains a major obstacle in academic practice within higher education institutions. This anxiety emerges as a complex psychological phenomenon involving cognitive, affective, and social aspects, rather than merely an issue of language proficiency. This study examines the problems faced by students, particularly those majoring in non English disciplines, in overcoming speaking anxiety in English academic settings. A descriptive qualitative approach was employed, with data collected through semi-structured interviews involving students of PASIM National University who exhibited varying levels of speaking anxiety. The data were analyzed using qualitative analysis techniques to identify emerging patterns and themes.The findings indicate that speaking anxiety is caused by fear of making pronunciation and grammatical errors, concern about receiving negative evaluations, limited vocabulary, and a lack of experience in communicating in English. These conditions are further exacerbated by limited opportunities for speaking practice, non-interactive learning methods, and insufficient support from teachers and peers. Students developed adaptive strategies such as relaxation techniques, thorough preparation, positive self-talk, and consistent language practice. To create a safe learning environment in which students can speak English effectively, this study proposes learning strategies that are more inclusive, supportive, and grounded in psychological principles.  

Fear of making mistakes is one of the psychological factors that may hinder students’ participation in English speaking activities. In vocational high school settings, speaking competence is particularly important because students are expected to communicate effectively in both academic and professional contexts. However, many learners remain reluctant to speak English due to concerns about making errors. Understanding this phenomenon is essential for supporting students’ oral language development. This study investigated students’ fear of making mistakes in English speaking performance at SMK PGRI Sumbermanjing, East Java, Indonesia. The study aimed to explore the factors contributing to students’ fear of making mistakes and examine how this fear affected their speaking performance in classroom activities. A qualitative case study design was employed. Twenty students were selected through purposive sampling. Data were collected through classroom observations, semi-structured interviews, and document analysis. The data were analyzed using thematic analysis to identify recurring patterns and themes. The findings revealed four major factors associated with students’ fear of making mistakes: fear of pronunciation errors, fear of negative evaluation from peers, limited vocabulary knowledge, and fear of teacher correction. These factors influenced students’ speaking performance by reducing confidence, increasing hesitation, limiting classroom participation, and encouraging avoidance of speaking opportunities. Fear of negative evaluation and pronunciation-related concerns were reported most frequently among participants. In conclusion, fear of making mistakes remains an important challenge affecting students’ English speaking performance. Creating supportive classroom environments and providing meaningful speaking opportunities may help students participate more confidently in English communication activities.

Manual management of sports field bookings is still widely practiced and often leads to scheduling conflicts, data recording errors, and low service efficiency. This study aimed to design and develop a desktop-based sports field booking application that automates the booking process and manages schedules in a structured manner. The research employed a system design and development method using an object-oriented programming (OOP) approach. Data were collected through direct observation of the booking process, interviews with field managers, and documentation of system requirements. The application was developed using the Python programming language with the PyQt5 framework for the graphical user interface and MySQL as the database management system. The results showed that the developed application is capable of managing field data, schedules, bookings, and user information in an integrated manner while reducing recording errors and minimizing scheduling conflicts. The application of OOP resulted in a modular, well-organized, and maintainable system structure. This application is expected to improve the efficiency and accuracy of sports field booking management and provide a practical solution for implementing a computerized booking system.

Students of vocational high schools are required to write an internship report as a form of accountability for completing their industrial training. However, various language errors are still found in students’ PKL reports. This study aims to describe and analyze morphological errors in the PKL reports of vocational high school students majoring in Electronics Engineering. The study employed a descriptive qualitative approach using document analysis. A total of 223 PKL reports were written by all students of SMK Negeri 3 Yogyakarta in 2025. The research data consisted of 25 PKL reports from students of the Electronics Engineering major selected through purposive sampling. Data analysis was carried out through the stages of identification, classification, description, quantification, and interpretation of morphological errors, with data validity ensured through theoretical triangulation. The results show that 286 morphological errors were identified, consisting of prefix errors (96), suffix errors (52), confix errors (41), reduplication errors (28), compound word errors (34), and base-form errors (35). Prefix errors were the most dominant type, accounting for 33.6% of all errors. These findings indicate that students still experience difficulties in applying affixation rules and forming standard words in formal written language. Such errors are influenced by interference from spoken language and the technical language used in the workplace. This study highlights the importance of structured and contextual morphology instruction to improve the quality of vocational students’ PKL report writing.

Administration is an activity that must be managed effectively to support public service quality, and one of the main keys to achieving a good administrative system is the utilization of information technology, which is currently developing rapidly. Administrative activities at the Wendewa Barat village hall are still carried out using conventional and ineffective methods, particularly in population data recording, which relies on manual bookkeeping. This approach is time-consuming, labor-intensive, prone to errors, and incurs higher operational costs. Therefore, an integrated system is needed to manage administrative activities more efficiently, accurately, and systematically. This research aims to develop a web-based population administration system to improve administrative performance at the Wendewa Barat village office. The system development employs the waterfall method, which consists of several stages, including requirements analysis, system design, implementation, system testing, and maintenance. The system is built using the PHP programming language with the CodeIgniter framework and utilizes a MySQL database for data management. Additionally, jQuery is applied in several system functions to enhance system interactivity, effectiveness, and user interface attractiveness.

This study analyzes efforts to develop and foster the Indonesian language through the use of standard and nonstandard words at MTS Bahlul Ulum. The increasing use of nonstandard words among students, influenced by social media and cross-regional interactions, has led to a decline in the awareness of using standard language in academic contexts. A descriptive qualitative approach was used with teachers and students of Class VII H at MTS Bahlul Ulum during the first semester of the 2025/2026 academic year. Data were collected through observation, interviews, and documentation of Student Worksheet (LKPD) results containing 50 questions on standard and nonstandard words. The findings showed that before the language development program, students had an average score of 62.4 in understanding standard and nonstandard words, with errors in commonly used informal words like vidio (standard: video) and antri (standard: antre). After the program, which included class discussions, conversation simulations, and interactive worksheets, the average score increased to 78.6, with 82% of students scoring above 78. The error rate decreased from 45% to 18%, indicating that interactive and contextual language development is effective. Continuous training and curriculum integration are essential to strengthening the use of standard language in the digital era.

This study aims to develop a Student Progress Assessment Information System for PAUD Laskar Pelangi as a solution to various problems that arise in the academic data management process, which was previously carried out manually. The management of student grades, student data, class data, and subject data often encountered obstacles such as delays, recording errors, difficulty in searching for data, and inaccuracies in report preparation. To overcome these issues, a web-based information system was developed to manage all data in an integrated and more efficient manner. The system development method used the Website Development Life Cycle approach, and the application was implemented using the PHP programming language. The system is designed to enable the admin to manage student data, class data, subject data, grades, and automatically generate student grade reports. Database implementation was carried out to ensure that data is stored properly and can be accessed easily. Functional testing was conducted to ensure that all features operate according to user needs. The results of the study show that the developed information system is capable of improving administrative efficiency, accelerating the grade processing workflow, minimizing recording errors, and generating student grade reports quickly and accurately. Therefore, this system provides significant benefits for PAUD Laskar Pelangi in improving the effectiveness of academic administrative management and can be further developed according to the school's needs.

This study aims to design a web-based information system for vehicle management and monitoring at Bengkel Merdeka Motor, which previously relied on manual recording processes. Manual data management caused several problems, including data loss, inaccurate records, difficulties in monitoring service progress, and delays in report generation. This research applies the Object-Oriented Analysis and Design (OOAD) method supported by Unified Modeling Language (UML) to analyze system requirements and design the proposed system. The research methodology includes requirements analysis, analysis of existing and proposed systems, system design, and user interface design. The proposed system integrates vehicle data management, service offers, work orders (SPK), service progress monitoring, invoice generation, and automatic monthly reporting into a single web-based platform. The results show that the designed system improves data accuracy, operational efficiency, and transparency of service information. In addition, real-time monitoring features support better coordination between administrators and mechanics. The implementation of this system is expected to enhance service quality, reduce administrative errors, and support managerial decision-making at Bengkel Merdeka Motor.

Currently, the skills needed to advance a tourist area are influenced by the availability of human resources who can speak English and understand local culture well. Unfortunately, improving English proficiency remains a challenge. Additionally, another issue appears as the Alpha generation is exposed to a great deal of English-language social media content; however, this does not appear to be directly correlated with an improvement in their English proficiency. It appears that the English Club instructors at SMA Fons Vitae 1 Jakarta were also aware of these two problems. Therefore, on September 11, 2025, an ABDIMAS activity entitled "Giving and Asking for Direction" training was held with the production of a short film. This activity was attended by 15 participants, 10 boys and 5 girls, a combination of students from grades 10 and 11. The results of the training showed that the pre-production process of making a short film provided a space for participants to recognize and explore Indonesian cultural heritage. Furthermore, the production process of making a short film made participants not afraid of speaking English. In the post-production process, participants can also edit parts of the video that are less than satisfactory because they can re-record if there are errors in pronunciation and grammar.

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.

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.

The use of protective equipment in the form of helmets is an important aspect of ensuring motorcycle rider safety. However, violations of helmet usage still frequently occur and are difficult to monitor continuously. This study proposes a real-time helmet detection system using the YOLOv8 object detection method. The YOLOv8n model was trained using a helmet and no-helmet image dataset that underwent data augmentation to improve the model’s robustness against variations in environmental conditions. The system was implemented using the Python programming language with the support of the Ultralytics and OpenCV libraries. The system input was obtained from a webcam with a resolution of 640×640 pixels, where each video frame was processed in real time to detect the Helmet and No Helmet classes. The system displays bounding boxes and class labels in real time and is equipped with a violation duration calculation mechanism. When a no-helmet condition is detected continuously, the system generates pop-up alerts and automatic notifications via the Telegram application. The experimental results show that the system is capable of detecting helmet usage and no-helmet violations in real time with stable performance. The integration of violation duration calculation helps reduce momentary detection errors and improves the reliability of identifying valid violations

The development of social media platforms like TikTok has created new spaces for digital economic activities, including the practive of thrifting, which has now become a trend among the public. However, government policies that block these activities have sparked various public reactions. This study aims to analyze public sentiment regarding the issue of thrifting bans on the TikTok platform using the Bidirectional Long Short-Term Memory (Bi-LSTM) method. This method was chosen because it can understand text context from both directions, allowing it to capture deeper semantic meaning. The dataset consist of 4,000 TikTok user comments collected through a crawling process. The research stages include data preprocessing, sentiment labeling, splitting training and test data, training the Bi-LSTM model, and evaluating performance using accuracy, precision, recall, and F1-score metrics. The research results show that the Bi-LSTM model achieved an accuracy of 86.15%, with stable classification performance and minimal error rate. These findings indicate that Bi-LSTM is effective for sentiment analysis of public opinions on Indonesian language social media, particularly on context specific policy issues. Further development can be carried out by adding pre-trained embeddings or attention mechanisms to improve the model’s performance.

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.  

This study aims to optimize Indonesian language development, especially in correcting language errors in seventh-grade students through French fries as an interactive learning tool. This classroom action research was conducted in one cycle on 30 students of grade VII-E of SMP Negeri 12 Tasikmalaya in the 2025/2026 academic year. A qualitative approach with data collection techniques in the form of observation, sentence correction tests, interviews, and documentation was used in this study. The results showed that the use of French fries media with incorrect sentences in it can improve students' ability to identify and correct errors in spelling, grammar, and word choice. The percentage of completeness of sentence correction skills increased from 33.33% (pre-action) to 86.67% after the implementation of the action. This media can also increase student motivation and involvement in learning. It can be concluded that this French fries media is effective to be used as an aid in Indonesian language development that is fun and highly contextual.  

This research aims to explain the symptoms of language errors, especially ambiguity at the semantic level in packaged advertising products. Ambiguity is a form of duplicity that can confuse listeners, making the message conveyed by the speaker difficult to understand. Advertising, as a communication and information medium, uses spoken and written language to convey messages or opinions. The advertisements analyzed in this research include advertisements for medicines, drinks and food. This research uses a descriptive qualitative method, by producing descriptive data in the form of written words on packaging advertisements. The research subjects were packaged advertising products which were analyzed using data collection techniques in the form of reading and taking notes on the advertisements obtained. It is hoped that the results of this research will provide an overview of the potential for language errors in packaging advertising which can cause ambiguity or confusion for consumers. This research also aims to analyze how ambiguity in advertising language can influence consumer perceptions and explain the implications of these language errors on the effectiveness of advertising in attracting attention and influencing consumer purchasing decisions.

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

Financial administration plays a crucial role in village-level governance, requiring transparency, accountability, and efficiency in the use of public funds. Currently, the Hameli Ate Village Office still relies on manual methods to manage its financial administration, including recording cash receipts and expenditures using notebooks and simple spreadsheets. This approach presents various issues, such as the risk of data loss, calculation errors, delays in report preparation, and difficulties in tracking and collecting financial transaction data. This study aims to develop a web-based financial administration information system to assist village officials in managing financial data more effectively, efficiently, and in an integrated manner. The methods applied include observation, interviews, and document collection to understand system requirements, while the system development process is implemented using the Waterfall model, which consists of the stages of analysis, design, implementation, testing, and maintenance. The system was built using the PHP programming language and a MySQL database and is designed to generate financial reports automatically and in real time. The testing results show that the system can handle income and expenditure data more quickly, accurately, and in a user-friendly manner. With the implementation of this information system, the financial administration process at the Hameli Ate Village Office becomes more transparent, accountable, and facilitates data-driven decision-making.