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This paper examines the implementation of translanguaging pedagogies within digital learning environments and their effectiveness in developing multilingual competence among Generation Z learners. Through a mixed-methods study involving 186 students and 14 educators across six higher education institutions, this research investigates how strategic integration of translanguaging practices in digital spaces supports linguistic flexibility, metalinguistic awareness, and cross-cultural competence. Findings reveal that digitally-mediated translanguaging approaches resulted in significant improvements in learners' willingness to communicate across languages (p<.01), metalinguistic awareness (p<.001), and cross-cultural communication efficacy (p<.01) compared to monolingual instructional approaches. The research further identifies five key digital translanguaging strategies that effectively leverage Generation Z's technological aptitude and multimodal literacy. This study contributes to the growing field of multilingual digital pedagogy by demonstrating how translanguaging can be systematically integrated into digital learning environments to foster linguistic repertoire expansion that aligns with the communicative needs of increasingly globalized contexts. The pedagogical framework presented offers practical guidance for educators seeking to implement translanguaging approaches in various digital learning modalities while accommodating Generation Z's learning preferences and multilingual development.

This paper examines the implementation of translanguaging pedagogies within digital learning environments and their effectiveness in developing multilingual competence among Generation Z learners. Through a mixed-methods study involving 186 students and 14 educators across six higher education institutions, this research investigates how strategic integration of translanguaging practices in digital spaces supports linguistic flexibility, metalinguistic awareness, and cross-cultural competence. Findings reveal that digitally-mediated translanguaging approaches resulted in significant improvements in learners' willingness to communicate across languages (p<.01), metalinguistic awareness (p<.001), and cross-cultural communication efficacy (p<.01) compared to monolingual instructional approaches. The research further identifies five key digital translanguaging strategies that effectively leverage Generation Z's technological aptitude and multimodal literacy. This study contributes to the growing field of multilingual digital pedagogy by demonstrating how translanguaging can be systematically integrated into digital learning environments to foster linguistic repertoire expansion that aligns with the communicative needs of increasingly globalized contexts. The pedagogical framework presented offers practical guidance for educators seeking to implement translanguaging approaches in various digital learning modalities while accommodating Generation Z's learning preferences and multilingual development.

Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

The accuracy of language in news texts is critical because appropriate language makes it easier for readers to understand. The quality of correct and appropriate language is essential in conveying information that is clear, accurate, and easy for readers to understand. Language errors in news texts can interfere with understanding and affect readers' minds. Therefore, correcting language errors in news texts, especially for junior high school students, is essential as part of the learning process. This research aims to provide a deeper understanding of language errors in the news texts studied, using data collection methods, listening and note-taking techniques, and analysis using the agih method. The research used a qualitative descriptive design approach to analyze errors in language use in news texts in the April 2023 Edition of Derap Guru Magazine, which included errors in conjunctions, punctuation, spelling, standard words, capital letters, abbreviated words, and ineffective sentences. Students can improve their language skills by analyzing language usage errors in news texts as teaching materials while deepening their understanding of news texts and effective language use.

The accuracy of language in news texts is critical because appropriate language makes it easier for readers to understand. The quality of correct and appropriate language is essential in conveying information that is clear, accurate, and easy for readers to understand. Language errors in news texts can interfere with understanding and affect readers' minds. Therefore, correcting language errors in news texts, especially for junior high school students, is essential as part of the learning process. This research aims to provide a deeper understanding of language errors in the news texts studied, using data collection methods, listening and note-taking techniques, and analysis using the agih method. The research used a qualitative descriptive design approach to analyze errors in language use in news texts in the April 2023 Edition of Derap Guru Magazine, which included errors in conjunctions, punctuation, spelling, standard words, capital letters, abbreviated words, and ineffective sentences. Students can improve their language skills by analyzing language usage errors in news texts as teaching materials while deepening their understanding of news texts and effective language use.

This research is a needs assessment evaluation which aims to determine the effectiveness of the information technology-based learning program, namely online or online learning to emphasize the difference between the desired or should be or expected conditions (what is) or real / real conditions. in the Covid-19 era with truth and validity data, facts, or information. The research was conducted using mixed methods research or a combination of qualitative and quantitative research in one study with evaluation of "needs assessment", data analysis with descriptive statistics. Collecting data using observation instruments, documentation and questionnaires, distributing questionnaires by means of random or random techniques, data processing refers to the Likert scale with the SPSS program computer The research results from the data on the achievement of class based learning process performance and information technology in 2020 15.78%, while from the research results; the highest score was 88, the lowest score was 50, the mean 66.47, the standard deviation was 11,780, the score scale ranges from 50 to 88, meaning that The effectiveness of online informatics technology-based learning methods in the Covid-19 era can be categorized as unsuccessful according to predetermined learning outcomes    

This research is a needs assessment evaluation which aims to determine the effectiveness of the information technology-based learning program, namely online or online learning to emphasize the difference between the desired or should be or expected conditions (what is) or real / real conditions. in the Covid-19 era with truth and validity data, facts, or information. The research was conducted using mixed methods research or a combination of qualitative and quantitative research in one study with evaluation of "needs assessment", data analysis with descriptive statistics. Collecting data using observation instruments, documentation and questionnaires, distributing questionnaires by means of random or random techniques, data processing refers to the Likert scale with the SPSS program computer The research results from the data on the achievement of class based learning process performance and information technology in 2020 15.78%, while from the research results; the highest score was 88, the lowest score was 50, the mean 66.47, the standard deviation was 11,780, the score scale ranges from 50 to 88, meaning that The effectiveness of online informatics technology-based learning methods in the Covid-19 era can be categorized as unsuccessful according to predetermined learning outcomes    

Parental self-efficacy is an important predictor that influences the positive behavior of parents in parenting. This study aims to determine the effect of smart parenting training on increasing parental self-efficacy of working mothers with toddlers. This study used a quasi-experimental design with the untreated control group design with dependent pretest and posttest samples. A total of 14 participants were divided into two groups, namely seven participants in the experimental group and seven participants in the control group. Smart parenting training uses experiential learning models and e-learning video-based methods. Measurements in this study used a short version of the Self-efficacy for Parenting Tasks Index-Toddler Scale (SEPTI-TS). The results of data analysis using the Mann-Whitney U show that there is a significant difference in parental self-efficacy (ρ=0.002) in the experimental group and the control group, and based on the Wilcoxon sign rank test shows that there is an increase in parental self-efficacy in the experimental group (ρ=0.018) after receiving smart parenting training, whereas in the control group participants (ρ=0.680) there was no increase in parental self-efficacy. The results showed that smart parenting training affected increasing parental self-efficacy for working mothers with toddlers.    

Parental self-efficacy is an important predictor that influences the positive behavior of parents in parenting. This study aims to determine the effect of smart parenting training on increasing parental self-efficacy of working mothers with toddlers. This study used a quasi-experimental design with the untreated control group design with dependent pretest and posttest samples. A total of 14 participants were divided into two groups, namely seven participants in the experimental group and seven participants in the control group. Smart parenting training uses experiential learning models and e-learning video-based methods. Measurements in this study used a short version of the Self-efficacy for Parenting Tasks Index-Toddler Scale (SEPTI-TS). The results of data analysis using the Mann-Whitney U show that there is a significant difference in parental self-efficacy (ρ=0.002) in the experimental group and the control group, and based on the Wilcoxon sign rank test shows that there is an increase in parental self-efficacy in the experimental group (ρ=0.018) after receiving smart parenting training, whereas in the control group participants (ρ=0.680) there was no increase in parental self-efficacy. The results showed that smart parenting training affected increasing parental self-efficacy for working mothers with toddlers.    

The learning system in the majority of Polytechnics uses Blended Learning systems including face to face, practice / workshop and online with learning composition; 40% theory and 60% practice with industry link and match mechanisms. For industry link and match, a comprehensive policy between ministries is needed to determine the functional position of the Learning Technology Developer (PTP) as an integrated manager of the learning program in tertiary institutions especially the Polytechnic both various learning resources, methods, teaching materials, media and learning environments so that learning outcomes can increase the production of goods and services quickly, effectively and efficiently through meaningful, enjoyable learning. The method used in this research is "descriptive quantitative" because it describes, describes, and interprets the conditions, events, processes that are happening in the context of the problem. This research is intended to explore and clarify a phenomenon or social reality clearly. Online and conventional system learning methods or blended learning enable HR outcomes that are able to overcome technological disruption, on the other hand the hopes of the President and Menristekdikti that the ability to deal with the industrial revolution 4.0 in the era of technological disruption and globalization competition is not only through special abilities obtained because of completing master's education, master's degree in tertiary education which is said to produce responsive ability of industry 4.0 involvement but through improvement of learning culture. Indicator 0.033% of HR career as Developers of Learning Technology in tertiary institutions shows low regard for tertiary institutions in developing learning programs in the development of learning programs both the management of various learning resources, methods, media, teaching materials and learning environments according to the need for meaningful and enjoyable learning, this is caused by professional ego, sectoral ego.    

The learning system in the majority of Polytechnics uses Blended Learning systems including face to face, practice / workshop and online with learning composition; 40% theory and 60% practice with industry link and match mechanisms. For industry link and match, a comprehensive policy between ministries is needed to determine the functional position of the Learning Technology Developer (PTP) as an integrated manager of the learning program in tertiary institutions especially the Polytechnic both various learning resources, methods, teaching materials, media and learning environments so that learning outcomes can increase the production of goods and services quickly, effectively and efficiently through meaningful, enjoyable learning. The method used in this research is "descriptive quantitative" because it describes, describes, and interprets the conditions, events, processes that are happening in the context of the problem. This research is intended to explore and clarify a phenomenon or social reality clearly. Online and conventional system learning methods or blended learning enable HR outcomes that are able to overcome technological disruption, on the other hand the hopes of the President and Menristekdikti that the ability to deal with the industrial revolution 4.0 in the era of technological disruption and globalization competition is not only through special abilities obtained because of completing master's education, master's degree in tertiary education which is said to produce responsive ability of industry 4.0 involvement but through improvement of learning culture. Indicator 0.033% of HR career as Developers of Learning Technology in tertiary institutions shows low regard for tertiary institutions in developing learning programs in the development of learning programs both the management of various learning resources, methods, media, teaching materials and learning environments according to the need for meaningful and enjoyable learning, this is caused by professional ego, sectoral ego.