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The integration of Information and Communication Technology (ICT) and tools like Canva has revolutionized English Language Teaching (ELT) in Indonesia, shifting from traditional methods to interactive, student-centered approaches. This study aims to explore the benefits and challenges of incorporating these technologies into ELT practices. Employing a qualitative literature review methodology, the research analyzed over 20 empirical studies from 2020 to 2023 on Canva and ICT in Indonesian ELT, supplemented by global Computer-Assisted Language Learning (CALL) frameworks. Key findings reveal that ICT and Canva enhance student motivation, creativity, and communicative skills through multimodal and constructivist learning, while fostering authentic language exposure and collaboration. However, challenges include inadequate infrastructure, limited teacher training, digital inequities between urban and rural areas, ethical issues such as copyright infringement, and increased teacher workload. The implications underscore the need for systematic professional development, institutional support, curriculum alignment, and policies promoting equitable access to ensure transformative and sustainable technology integration in Indonesian ELT.  

The objective of this study is to investigate several facets of the role that educators play in the verbal abuse and bullying prevention of students at SMP Negeri 1 Tanjung Raja in Tanjung Raja District, Ogan Ilir Regency. The qualitative descriptive method is being used in this study. The researchers conduct observations and interviews as part of their data collection methods. There were seven informants in total for this investigation. This study is being conducted at Tanjung Raja sub-district, Jalan Sultan Mahmud Badaruddin II, in the Ogan Ilir Regency. The study's findings indicate that educators have a positive impact in educating students about bullying and how to protect themselves from various risks. In addition to this, the role of the teacher and the curriculum in the school is crucial in providing a safe and nurturing environment for the development of the students. It is anticipated that the research findings will be able to make a contribution to more effective education reform in SMP Negeri 1 Tanjung Raja and other schools.  

The animated film KPop Demon Hunters quickly became a worldwide hit, reaching the top of Netflix's global charts with over 33 million views in just two weeks. The highly acclaimed film KPop Demon Hunters has been the subject of some research due to its notable accomplishment. Yet, none of the research above discusses the symbolism that is richly put in the movie. Thus, the research attempts to elaborate on the representation of symbolism in order to provide an alternative viewpoint of the Kpop Demon Hunters, particularly the well-known villain, the Saja Boys. In order to study the underlying meaning of the Saja Boys, the author employs the qualitative method and applies Vrabel's study of deadly sin in relation to the religious symbol. This study concludes that the members of the Saja Boys represent symbolism of the deadly sins, which are anger, envy, greed, lust, pride, gluttony, and sloth. These vices are shown from the behavior of the Saja Boys, such as barking towards fans aggressively, being envious of one’s freedom and happiness, stocking food as much as possible, giving sexual gratification through physical appearance, and being overly proud of it. Not only that, the members of Saja Boys also portrayed the action of overconsumption and laziness.

This study examines students’ perceptions of the use of online platforms for English listening practice. The research employs a mixed-methods approach involving 150 undergraduate students through questionnaires and semi-structured interviews. The findings indicate that the majority of students hold positive attitudes toward the use of online platforms, primarily due to time flexibility, diverse content, and the ability to learn independently. Nevertheless, several challenges were identified, including internet connectivity issues that disrupt the learning experience, a lack of personalized feedback, and difficulties in maintaining learning motivation. Features such as adjustable playback speed, the availability of transcripts, and interactive exercises received high levels of satisfaction. Overall, the study concludes that although online platforms have great potential to enhance English listening skills, their effectiveness largely depends on proper implementation, adequate technical infrastructure, and active support from educators. Therefore, this study recommends improvements in technical aspects and the development of more effective learning methods to achieve more optimal outcomes.

This study aims to comprehensively describe the psychological dynamics of Natta's character in the novel Rumah Tanpa Cahaya through the framework of Sigmund Freud's psychoanalytic theory. The main focus of the study is to analyze the structural interactions of personality including the Id, Ego, and Superego, and to identify various self defense mechanisms activated by the character due to the internal conflict he experiences. The method used is descriptive qualitative with a literary psychology approach as the main analytical basis for dissecting the hidden inner character. The results of the study indicate that Natta's character's behavior is a form of integrative struggle that demands immediate gratification (Id), rational consideration of painful reality (Ego), and strong moral pressure from the internalization of social norms (Superego). Natta's Id demands the fulfillment of basic needs for security and affection. Meanwhile, the Superego provides moral pressure that triggers disproportionate anxiety. Natta's Ego operates as a mediator that works hard to balance the drives of the Id and the demands of the Superego, which forces the Ego to activate self-defense mechanisms such as repression, rationalization, and especially sublimation. This mechanism serves as a psychic barrier to maintain her mental stability and prevent her from experiencing total collapse due to the accumulation of past trauma. Overall, this novel depicts the complexity of the human psyche in the face of existential crises and unresolved past wounds.

This study analyzes the sociolinguistic phenomena of code-switching and code-mixing in the academic context of students in Pekalongan, Central Java. As a region with diverse backgrounds dominated by the Pekalongan dialect (Ngapak Javanese), interactions between students create space for complex language dynamics. This study aims to identify variations, roles, and factors that cause code-switching and code-mixing in student interactions. The method applied is descriptive qualitative with data collection through inactive participant observation, recording, and in-depth interviews at various universities in Pekalongan. Data analysis is carried out through the steps of data reduction, data presentation, and verification using triangulation techniques. The results show that the application of language codes is divided into two categories: an internal category that includes Indonesian and regional languages (Javanese), and an external category that includes foreign languages (English or Arabic). Code-mixing can be found at the word, phrase, and clause levels. The main factors that drive this phenomenon include participants, conversation themes, situational circumstances, and the purpose of communication in building solidarity among group members (ingroup).  The Pekalongan dialect plays a crucial role as a means of communication to build closeness and demonstrate local identity, amidst the need to use formal language on campus. This research concludes that code-switching and code-mixing are not merely linguistic phenomena, but also ways in which students adapt socially to balance their cultural identity with academic demands.  

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

. Film as a mass communication medium not only functions as entertainment, but also as a means of representing power relations in society. Miracle in Cell No. 7 works by Hanung Bramantyo show various forms of official domination and legal inequality which are relevant to be studied through a hegemony perspective. This research aims to describe the forms of hegemony that appear in the film and interpret the social criticism conveyed through the narrative and visualization. The research uses qualitative methods with listening and note-taking techniques, then the data is analyzed through reduction, presentation and drawing conclusions based on Antonio Gramsci's theory of hegemony. The research results show that this film contains four forms of hegemony: ideological hegemony through the instillation of disciplinary values; hegemony of power through apparatus domination and abuse of authority; cultural hegemony through the imposition of a single standard of behavior; and moral hegemony through the formation of ethical judgments that benefit those in power. These findings indicate that films not only present emotional stories, but also present criticism of legal injustice and structural domination. This research confirms that visual media plays an important role in forming public awareness regarding the practice of power in social life.

This study aims to comprehensively describe the psychological dynamics of Natta's character in the novel Rumah Tanpa Cahaya through the framework of Sigmund Freud's psychoanalytic theory. The main focus of the study is to analyze the structural interactions of personality including the Id, Ego, and Superego, and to identify various self defense mechanisms activated by the character due to the internal conflict he experiences. The method used is descriptive qualitative with a literary psychology approach as the main analytical basis for dissecting the hidden inner character. The results of the study indicate that Natta's character's behavior is a form of integrative struggle that demands immediate gratification (Id), rational consideration of painful reality (Ego), and strong moral pressure from the internalization of social norms (Superego). Natta's Id demands the fulfillment of basic needs for security and affection. Meanwhile, the Superego provides moral pressure that triggers disproportionate anxiety. Natta's Ego operates as a mediator that works hard to balance the drives of the Id and the demands of the Superego, which forces the Ego to activate self-defense mechanisms such as repression, rationalization, and especially sublimation. This mechanism serves as a psychic barrier to maintain her mental stability and prevent her from experiencing total collapse due to the accumulation of past trauma. Overall, this novel depicts the complexity of the human psyche in the face of existential crises and unresolved past wounds.

This study analyzes the sociolinguistic phenomena of code-switching and code-mixing in the academic context of students in Pekalongan, Central Java. As a region with diverse backgrounds dominated by the Pekalongan dialect (Ngapak Javanese), interactions between students create space for complex language dynamics. This study aims to identify variations, roles, and factors that cause code-switching and code-mixing in student interactions. The method applied is descriptive qualitative with data collection through inactive participant observation, recording, and in-depth interviews at various universities in Pekalongan. Data analysis is carried out through the steps of data reduction, data presentation, and verification using triangulation techniques. The results show that the application of language codes is divided into two categories: an internal category that includes Indonesian and regional languages (Javanese), and an external category that includes foreign languages (English or Arabic). Code-mixing can be found at the word, phrase, and clause levels. The main factors that drive this phenomenon include participants, conversation themes, situational circumstances, and the purpose of communication in building solidarity among group members (ingroup).  The Pekalongan dialect plays a crucial role as a means of communication to build closeness and demonstrate local identity, amidst the need to use formal language on campus. This research concludes that code-switching and code-mixing are not merely linguistic phenomena, but also ways in which students adapt socially to balance their cultural identity with academic demands.  

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

. Film as a mass communication medium not only functions as entertainment, but also as a means of representing power relations in society. Miracle in Cell No. 7 works by Hanung Bramantyo show various forms of official domination and legal inequality which are relevant to be studied through a hegemony perspective. This research aims to describe the forms of hegemony that appear in the film and interpret the social criticism conveyed through the narrative and visualization. The research uses qualitative methods with listening and note-taking techniques, then the data is analyzed through reduction, presentation and drawing conclusions based on Antonio Gramsci's theory of hegemony. The research results show that this film contains four forms of hegemony: ideological hegemony through the instillation of disciplinary values; hegemony of power through apparatus domination and abuse of authority; cultural hegemony through the imposition of a single standard of behavior; and moral hegemony through the formation of ethical judgments that benefit those in power. These findings indicate that films not only present emotional stories, but also present criticism of legal injustice and structural domination. This research confirms that visual media plays an important role in forming public awareness regarding the practice of power in social life.

Private vehicles are a frequently used mode of transportation because they are considered more practical. However, using private vehicles carries several risks, such as traffic accidents due to drivers losing focus on the road due to other activities, such as making calls on smartphones, drinking, or operating the radio. Approximately 90% of accidents are caused by human error. Convolutional Neural Network (CNN) is a type of neural network commonly used on image data. CNN is often used for image classification due to its high performance and accuracy. Therefore, this study aims to analyze the performance of CNN for the classification of distracted driving activities. The results show that the CNN model is able to effectively classify images of distracted driving activities, with an accuracy of approximately 99% across all datasets and across all input image size variations. Furthermore, the results of this study also show that differences in right-hand and left-hand drive datasets do not significantly affect model accuracy. Variations in input image size also do not significantly affect model accuracy, but do affect the training duration.

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

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

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

The rapid development of modern manufacturing technology has driven the emergence of human-robot collaboration (HRC) as part of the transformation toward a human-centric intelligent production system. In collaborative work environments, robots are not only required to work efficiently but also to interact safely and responsively with operators. However, most conventional industrial robot systems still use rigid motion controls and are unable to dynamically adapt to human activity around them.This research aims to develop a human-robot collaboration system by integrating computer vision technology to detect operator movement and applying adaptive control algorithms to the robot manipulator. The research methodology includes designing a collaborative workstation, implementing a computer vision-based motion detection system, developing an adaptive control algorithm, and evaluating system performance through various experimental scenarios. Evaluation parameters include task completion time, safe distance, and system response time.The results show that the developed system significantly improves the efficiency and safety of human-robot interaction compared to conventional systems, with shorter task times, optimal safe distances, and faster system response to operator movements.

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

The integration of Artificial Intelligence (AI) into educational settings, particularly in formative assessments, offers significant benefits in terms of personalized learning, real time feedback, and increased efficiency. However, the successful implementation of AI driven formative assessments depends not only on technological capabilities but also on socio cultural and organizational factors that shape its adoption. This study explores the socio technical factors influencing the use of AI in formative assessments, emphasizing the importance of considering cultural diversity, institutional culture, and educators' beliefs. AI technologies, while powerful in automating grading and providing personalized assessments, often face limitations in addressing complex student responses that require human judgment. Furthermore, cultural factors, such as students' prior exposure to technology and different cultural attitudes towards AI, play a critical role in the acceptance and effectiveness of these tools. Organizational factors, including leadership support, digital literacy, and the readiness of institutions to adopt AI, are also key determinants in the successful implementation of AI systems in education. Teachers’ beliefs about assessment influence their acceptance and use of AI tools, highlighting the need for professional development and training to ensure that AI enhances pedagogical goals rather than replacing human expertise. The study concludes that the alignment of technology, culture, and assessment beliefs is essential for the effective use of AI driven formative assessments in educational settings. Recommendations for educational institutions include adopting a socio technical approach to AI integration, with a focus on providing resources, training, and fostering a culture of innovation. Future research directions should focus on expanding studies to diverse educational contexts, conducting longitudinal research on AI’s impact on learning outcomes, and exploring additional socio technical frameworks to guide AI adoption in education.

This study explores the integration of critical pedagogy with digital literacy, aiming to reconceptualize digital literacy beyond its traditional focus on technical proficiency and operational skills. Traditional digital literacy models emphasize the ability to navigate and use technology, primarily focusing on operational tasks such as managing digital devices, utilizing software, and performing specific functions. However, these models often overlook the broader implications of technology on society, including its role in shaping power dynamics and perpetuating social inequalities. By integrating critical pedagogy, this study argues that digital literacy should not only encompass technical skills but also encourage learners to critically assess the social, political, and cultural implications of digital tools. The critical digital literacy approach promotes social justice, equity, and empowerment by encouraging learners to question, reflect on, and challenge the ways in which technology influences their lives and society at large. Through critical engagement with digital tools, learners are empowered to challenge existing power structures, fostering social transformation. The study discusses how educators can integrate critical digital literacy into teaching practices, moving beyond traditional skill based models by encouraging critical thinking, ethical use of technology, and a deeper understanding of the role digital technologies play in shaping societal structures. Moreover, the study highlights the transformative potential of critical digital pedagogy, proposing it as a tool for educational equity and social change. By reconceptualizing digital literacy through a critical pedagogical lens, this study offers a framework that empowers students to become not just proficient digital users but active participants in societal transformation, contributing to a more inclusive and just digital future. The study also suggests areas for future research, including empirical investigations on the practical implementation of critical digital literacy frameworks across various educational settings and contexts.