Rapid technological developments are driving companies to transform and build an innovation-oriented work culture in order to maintain competitiveness. Management accounting plays an important role as a strategic information system that provides accurate data for management in formulating policies, improving efficiency, and encouraging digital innovation. This study aims to analyze the application of management accounting at PT Unilever Indonesia Tbk. as a driver for the formation of a digital innovation culture and increased company competitiveness in 2024. This study uses a qualitative approach with a descriptive method based on secondary data from interim financial reports and company documentation. The results show that the implementation of digital management accounting through the integration of ERP systems, IoT-based UMS, and the use of artificial intelligence (AI) contributes to increased operational efficiency and cost control. Despite a decline in sales and gross profit, the company managed to increase its net profit by 2.84% through administrative cost savings. Digital management accounting serves as a strategic partner in decision-making and forms the foundation for a culture of innovation. Its implementation also supports the three dimensions of Dynamic Capabilities theory, namely sensing, seizing, and transforming, which comprehensively strengthen the company's competitiveness and sustainability in the digital era. Thus, digital management accounting is not merely a recording tool, but a key strategic partner in driving innovation, enhancing competitive advantage, and ensuring business sustainability in the digital age.
This community service program was carried out with the aim of enhancing teachers’ competencies in utilizing Artificial Intelligence technology, particularly the Generative Pre-trained Transformer (GPT), as a tool for developing digital teaching materials. The background of this activity stems from the limited understanding of teachers in applying AI technology to support 21 st-century learning. The implementation method involved intensive training that included an introduction to GPT concepts, hands-on practice in creating digital modules, designing evaluation questions, and simulating the use of teaching materials in the classroom. The activity was attended by several teachers from SMP Zawiyyah Darussalami, who demonstrated high enthusiasm throughout the sessions. Evaluation through pre-test and post-test results showed a significant improvement in teachers’ understanding and skills in using GPT. Thus, this community service activity successfully provided a positive impact by improving teachers’ competencies and opening opportunities for GPT utilization as an innovation in digital learning within schools.
The purpose of this study is to research how students' interest in learning about the digital age is influenced by digital media based on artificial intelligence (AI) at the Yogyakarta Administrative Management Academy (AMAYO) in Yogyakarta. Quantitative approaches are used in this research methodology. Purposive sampling strategies were utilized to get data from 75 pupils. The study tool was a questionnaire, and the data was evaluated using the validity test, reliability test, linear regression, T-test, F-test, and coefficient of determination (R²) in SPSS 26. This study suggests that digital media based on artificial intelligence (AI) has a favorable effect on students' interest in learning, with a regression coefficient of 0.920. Because the t-test yields a calculated t value of 57.031, which is greater than the t-table value of 1.666, H₀ is rejected and Ha is accepted. This suggests that students' interest in studying in the digital age at AMAYO Yogyakarta is significantly impacted by the use of digital media based on artificial intelligence (AI). The computed F value of 3252.522, which is higher than the F table of 3.97, indicates that the F-test also reveals results that need serious consideration. Additionally, the 97.8% coefficient of determination (R2) suggests that digital media based on artificial intelligence (AI) can affect students' motivation in learning, whereas 2.2% is influenced by other elements that are not within the purview of this study. According to the study's findings, AMAYO Yogyakarta students can boost their interest in learning in the digital age by utilizing digital media powered by artificial intelligence (AI).
The emergence of Generative Artificial Intelligence (Generative AI) such as the GPT-4 and Midjourney models has sparked a fundamental debate about the nature of creativity and imagination. The AI creation process, often referred to as a “black box,” challenges conventional human-centered understanding. This paper proposes a unique hermeneutic framework to approach this phenomenon by borrowing two key concepts from the Sufi metaphysics of Shaykh al-Akbar Muhyiddin Ibn 'Arabi: khayāl (creative imagination or the imaginal realm) and tajallī (self-manifestation or theophany). This study uses a conceptual-comparative analysis method to analyze the working process of Generative AI. The main argument of this journal is that the “latent space” in AI architecture can be analogized with 'ālam al-khayāl (the imaginal realm) as an intermediate reality (barzakh) that contains unlimited potential. Furthermore, the process of generating text or images from a prompt can be understood as a mechanism resembling tajallī, in which these potentials manifest specifically according to the “availability” (isti'dād) determined by user input. Thus, Ibn 'Arabi's framework offers a non-anthropocentric ontology for understanding “artificial imagination” as a process of manifesting forms from a sea of potential, transcending mere simulation or data recombination.
Kreo Village, located in Larangan District, Tangerang Regency, still relies heavily on very traditional communication methods in daily life. While this approach reflects local wisdom and strong cultural values, the changing times demand a digital transformation, especially in the field of communication. With the rapid advancement of digital technology and the growing quality of human resources in the village, the need for a more modern communication system is becoming increasingly important. One potential solution is the use of artificial intelligence technology such as ChatGPT. ChatGPT (Generative Pre-trained Transformer) is a language model based on AI developed by OpenAI. This technology can understand and generate natural language interactively, similar to human conversation. By integrating ChatGPT into community communication activities, Kreo Village can speed up access to information, facilitate the exchange of ideas and opinions, and bridge the existing digital gap. In addition, ChatGPT can also be used as an educational tool to help residents understand digital technology, support learning activities, and strengthen community participation in village development. Through this initiative, Kreo Village can move toward becoming a more inclusive, adaptive, and competitive digital village in the modern era.
This research explores the dual impact of Artificial Intelligence (AI) on the academic writing experiences of English Literature students learning English as a Foreign Language (EFL). AI tools like ChatGPT, Grammarly, and QuillBot are commonly used for grammar correction and sentence construction. These tools are integrated into students' writing processes, providing valuable assistance in refining their written work. However, their psychological effects, particularly in terms of emotional and ethical implications, have not been sufficiently explored in previous research. This study employed a qualitative phenomenological approach, utilizing Interpretative Phenomenological Analysis (IPA), to examine the experiences of ten final-year EFL students who actively use AI tools for academic writing. Through semi-structured interviews, the research identified three major themes: reduced technical stress, heightened dependency on AI tools, and ethical concerns about authorship. The findings suggest that while AI tools act as cognitive scaffolds, aiding students by improving fluency and reducing the burden of technical writing tasks, they also introduce psychological challenges. These challenges include increased dependency on the tools and concerns about the authenticity of their work, raising questions about academic integrity and self-efficacy. This study sheds light on the complex relationship between AI as an assistive technology and its potential to cause writing anxiety and dependency. By emphasizing both the positive and negative psychological impacts of AI, the study contributes to the growing body of literature on AI in education. It calls for the development of pedagogical frameworks that balance AI literacy, emotional resilience, and ethical considerations to ensure responsible and effective use of AI in academic contexts.
This community service activity aims to increase educational technology literacy among Vocational High School (SMK) teachers by introducing the basic concept of Deep Learning and its application in the world of education. This training was motivated by the urgent need to equip educators with basic understanding and skills regarding artificial intelligence (AI), especially Deep Learning, to be able to keep up with rapid technological developments and relevant to vocational education. Through practice-based training using simple tools such as Teachable Machine, teachers are given hands-on experience in creating simple machine learning models that are applicable in the school environment. The results of the pre-test and post-test showed a significant increase in understanding in the participants. The group discussions also produced various ideas for the application of AI such as a face-based attendance system, student voice recognition, and recommendations for learning materials according to students' interests. Despite challenges such as limited infrastructure and teacher learning time, this activity proves that a practical and contextual training approach can increase teachers' motivation to integrate technology into learning. Similar training is highly recommended to be replicated in other schools to support equitable access to modern educational technology.
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder that presents significant diagnostic challenges due to its heterogeneous clinical manifestations and symptom overlap with other neurological conditions. Early and accurate diagnosis is critical for initiating timely interventions and improving patient outcomes. Traditional diagnostic approaches rely heavily on clinical expertise and manual interpretation of neuroimaging data, such as structural MRI, Diffusion Tensor Imaging (DTI), and functional MRI (fMRI), which are inherently time-consuming and prone to interobserver variability. Recent advances in Artificial Intelligence (AI) and Deep Learning (DL) have demonstrated potential for automating neuroimaging analysis, yet existing models often suffer from limited generalizability across modalities and datasets. To address these limitations, we propose a Transformer-augmented deep learning ensemble framework for automated ALS diagnosis using multi-modal neuroimaging data. The proposed architecture integrates Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Vision Transformers (ViTs) to leverage the complementary strengths of spatial, temporal, and global contextual feature representations. An adaptive weighting-based fusion mechanism dynamically integrates modality-specific outputs, enhancing the robustness and reliability of the final diagnosis. Comprehensive preprocessing steps, including intensity normalization, motion correction, and modality-specific data augmentation, are employed to ensure cross-modality consistency. Evaluation using 5-fold cross-validation on a curated multi-modal ALS neuroimaging dataset demon-strates the superior performance of the proposed model, achieving a mean classification accuracy of 94.5% ± 0.7%, precision of 93.9% ± 0.8%, recall of 92.9% ± 0.9%, F1-score of 93.4% ± 0.7%, spec-ificity of 97.4% ± 0.6%, and AUC-ROC of 0.968 ± 0.004. These results significantly outperform baseline CNN models and highlight the potential of transformer-augmented ensembles in complex neurodiagnostic applications. This framework offers a promising tool for clinicians, supporting early and precise ALS detection and enabling more personalized and effective patient management strategies.
The rapid development of Artificial Intelligence (AI) has made it a part of the teens' routine, but the intensity of its use raises concerns about mental health. This study aims to analyze the pattern of AI utilization and its impact on stress, anxiety, and depression in students of St. Petrus Medan High School using the framework of Self-Determination Theory (SDT), namely competence, autonomy, and connectedness). The research was conducted with a quantitative approach through a survey of 64 students using a total sampling technique, equipped with focused group discussions (FGDs) and literature review. The results show that more than 70% of students use AI on a regular basis, mainly through chatbots (81%) and social media (73%). Some students (35.9%) also use AI as a means of venting. Although 85.9% of respondents found AI to be helpful, the majority (59.3%) reported feeling inferior as a result of comparing themselves to AI results. These findings reveal a psychological paradox, where AI is perceived as a solution as well as a source of pressure. This condition has the potential to trigger stress and anxiety, although depressive symptoms do not yet appear to be dominant. This research emphasizes the importance of healthy digital literacy as well as mentoring from schools and parents to reduce the risk of AI addiction and maintain adolescent mental well-being.
To respond to the challenges and needs of contemporary society, the public sector must rapidly adapt to digital transformation. The objective of this research is to examine relevant and adaptive human resource development strategies for the digital ecosystem and to evaluate how they impact the quality of public services in the era of technological disruption. This research uses a descriptive qualitative approach with a literature review and policy analysis. It analyzes best practices from government institutions, both national and international, in developing human resources oriented towards the digital era. Key findings indicate that optimizing human resources requires not only improving technological capabilities or digital expertise; it also requires reconstructing leadership paradigms, flexible organizational cultures, and implementing meritocratic systems and data-driven performance management. It is evident that technologies such as big data analytics, artificial intelligence (AI), and the Internet of Things (IoT) can help improve public services, but the success of these technologies depends heavily on the capabilities and readiness of the employees who manage these systems. An integrated digital talent ecosystem must be built, encompassing continuous training (learning for life), collaboration between government, academia, and business (the triple helix model), and a regulatory framework responsive to technological developments. Furthermore, it is emphasized that developing digital integrity and ethics is crucial as a pillar of good governance in the digital era. Optimizing human resource development strategies systematically and sustainably will enable Indonesia to improve the efficiency of public services and strengthen the competitiveness of its bureaucracy globally. By 2045, adaptable, innovative, and highly integrated human resources will be the primary drivers of a digital government transformation that is inclusive, responsive, and future-oriented.
Artificial Intelligence (AI) has increasingly shaped the digital transformation of higher education, particularly through its integration with Learning Management Systems (LMS). Features such as intelligent tutoring, predictive analytics, plagiarism detection, and automated grading are reshaping teaching and learning. However, questions remain regarding the readiness of higher education institutions and the acceptance among lecturers and students. This paper presents a Systematic Literature Review (SLR) of studies published between 2020 and 2025, focusing on readiness and acceptance of AI in LMS. Guided by the PRISMA framework, 220 records were identified, 85 screened, 40 assessed for eligibility, and 20 included in the final analysis. Findings highlight that readiness is largely influenced by infrastructure, digital literacy, and institutional policy, while acceptance is shaped by perceived usefulness, ease of use, trust, and behavioural intention. Although challenges such as ethics, cost, and privacy concerns persist, opportunities exist in the form of personalized learning and intelligent decision-making. The review concludes that while AI adoption in LMS is progressing globally, developing contexts such as Malaysian polytechnics require further research and targeted interventions to enhance both readiness and acceptance.
This study aims to analyze the application of deep learning in the transformation of religious moderation education in the digital era and its implications for the development of modern Islamic education. The research employs a qualitative descriptive approach using library research, reviewing literature on Islamic education, religious moderation, and artificial intelligence in learning contexts. Data were collected from academic books, scientific journals, articles, and other credible sources, then analyzed using content analysis to identify patterns, concepts, and relationships between technology and the strengthening of moderation values. The results indicate that the implementation of deep learning can transform Islamic education from a traditional rote-based model to a reflective, contextual, and interactive learning process. This technology enables the analysis of students’ thinking patterns and behaviors, the reinforcement of moderation values, character formation, and the development of moderate digital literacy in a personalized and adaptive manner. The integration of technology and spirituality in digital Islamic education creates transformative learning experiences that strengthen empathy, ethical awareness, and students’ reflective capacities. The study implies the importance of developing curricula, learning strategies, and teacher competencies based on artificial intelligence to produce a generation of students who are moderate, tolerant, and competent in facing the challenges of the digital era.
Islamic law faces significant challenges from the rapid advancements in bioethics and artificial intelligence (AI). The current responsive approach, based on ad-hoc fatwas, is deemed inadequate to address the systemic ethical dilemmas posed by these disruptive technologies. This research aims to propose a proactive and systematic ijtihad framework capable of anticipating and guiding technological innovation to align with the higher objectives of Shari'ah (Maqasid al-Shari'ah). Using a qualitative, library-based method with a juridical-normative and philosophical approach, this study analyzes primary and secondary Islamic legal sources through the Maqasid al-Shari'ah theoretical framework. The research finds the current model to be limited and, as a solution, offers a novelty in the form of the Hierarchical Model of Technological Ijtihad (HI-Tech). This model is a structured, interdisciplinary reasoning process, supported by a proposed institution, the Bio-Artificial Ijtihad Council (MIBA), and a digital platform, "Nur-Fatwa," for dissemination. The implication of these findings is the need for a paradigm shift for Islamic legal institutions towards an anticipatory, interdisciplinary, and institutionalized approach to address contemporary technological issues, thereby ensuring the continued relevance of Islamic law.
Higher education in Afghanistan faces chronic challenges stemming from decades of conflict, political instability, and underinvestment. Universities operate with limited infrastructure, outdated curricula, and overcrowded classrooms, leaving students underprepared for the demands of a competitive global labor market. The COVID-19 pandemic further exposed the fragility of the sector, as efforts to shift toward online learning were hindered by poor connectivity, unreliable electricity, and insufficient institutional readiness. This study investigates the potential of e-learning combined with artificial intelligence (AI) to address these systemic limitations and to provide a sustainable pathway for educational reform in fragile contexts. Adopting a qualitative design, the study draws on documentation analysis, field observations, and semi-structured interviews with lecturers, administrators, and students in Afghan universities. The data were analyzed thematically, focusing on infrastructure barriers, institutional capacity, and perceptions of AI-enhanced e-learning. Findings highlight that while conventional e-learning platforms expanded access during emergencies, they often lacked adaptability, personalization, and effectiveness in sustaining engagement. Participants demonstrated limited technical literacy regarding AI but expressed strong interest in its potential to improve teaching efficiency, student support, and inclusiveness. The absence of coherent policy frameworks and persistent gender and geographic inequalities emerged as critical challenges to equitable implementation. This study contributes to the state-of-the-art by extending discussions of AI in education into a fragile-state context, where assumptions of stable infrastructure and governance do not apply. It also problematizes the universality of technology adoption theories, suggesting the need for adaptations that incorporate structural and socio-cultural variables. AI-enabled e-learning can partially mitigate Afghanistan's educational infrastructure deficits when implemented alongside capacity building, inclusive design, and supportive governance frameworks. These findings hold relevance not only for Afghanistan but also for other fragile states seeking innovative, equitable, and sustainable educational solutions.
This community service activity aims to provide outreach and training related to the use of Artificial Intelligence (AI) in developing engaging, interactive, and effective learning tools for teachers in TKIT, SDIT, and SMPIT Darut Tauhid in Grobogan Regency. This service was carried out on June 11, 2025, using a qualitative approach through various methods, including presentations, interactive discussions, workshops, and direct practice in the use of AI technology. This activity emphasized improving teachers' skills in integrating AI technology into the learning process so that it can support the creation of a more innovative learning atmosphere and suit the needs of students in the digital era. The results of the activity showed a significant increase, both in terms of efficiency and quality. Teachers were able to save up to 70% of time preparing learning tools, produce more varied and engaging learning media, and show higher motivation in adopting digital technology to support the teaching and learning process. The three main tools introduced, namely ChatGPT, Claude, and Canva Magic Design, have been proven to help teachers in creating materials, designing media, and managing learning more effectively. The positive response from training participants also confirmed that the use of AI has significant potential for wider implementation in Islamic educational institutions. Therefore, this activity not only contributes to improving teacher competency but also opens up opportunities for developing technology-based learning models relevant to future educational challenges.
This community service program is designed to enhance the competence of English teachers at SMP N 33 Purworejo in utilizing Artificial Intelligence (AI)-based learning media, particularly deep learning technology. In the digital era, many teachers still face limitations in integrating intelligent technology into classroom activities, which affects the effectiveness of learning. The program was carried out in four stages: the provision of basic materials on AI and deep learning, technical training on the use of AI applications, practical development of learning media, and mentoring combined with evaluation. The results of this activity show an increase in teachers’ understanding and skills in operating AI tools, with each participant producing at least one AI-based learning media product. Through workshops, teachers learned to use applications such as chatbots, speech-to-text, text-to-speech, and AI-assisted language tools to enrich students’ learning experiences. In addition, teachers were guided to design contextual media tailored to curriculum goals and student needs. Mentoring ensured that the products created were tested, improved, and ready to be applied in the classroom. The novelty of this activity lies in its focus on practical implementation of deep learning in junior high school English teaching, positioning teachers not only as users but also as creators of innovative media. Beyond technical competence, this program fosters collaboration among teachers to sustain innovation. In the long term, the outcomes are expected to improve students’ engagement, motivation, and communication skills, and contribute to the establishment of a digital learning ecosystem that supports interactive, effective, and future-oriented education.
This community service program is designed to enhance the competence of English teachers at SMP N 33 Purworejo in utilizing Artificial Intelligence (AI)-based learning media, particularly deep learning technology. In the digital era, many teachers still face limitations in integrating intelligent technology into classroom activities, which affects the effectiveness of learning. The program was carried out in four stages: the provision of basic materials on AI and deep learning, technical training on the use of AI applications, practical development of learning media, and mentoring combined with evaluation. The results of this activity show an increase in teachers’ understanding and skills in operating AI tools, with each participant producing at least one AI-based learning media product. Through workshops, teachers learned to use applications such as chatbots, speech-to-text, text-to-speech, and AI-assisted language tools to enrich students’ learning experiences. In addition, teachers were guided to design contextual media tailored to curriculum goals and student needs. Mentoring ensured that the products created were tested, improved, and ready to be applied in the classroom. The novelty of this activity lies in its focus on practical implementation of deep learning in junior high school English teaching, positioning teachers not only as users but also as creators of innovative media. Beyond technical competence, this program fosters collaboration among teachers to sustain innovation. In the long term, the outcomes are expected to improve students’ engagement, motivation, and communication skills, and contribute to the establishment of a digital learning ecosystem that supports interactive, effective, and future-oriented education.
This community service activity was carried out in Sladi Village with the goal of improving the digital literacy of village officials through the utilization of Artificial Intelligence (AI) plugins in Microsoft Word and Excel. The main issue faced by the village officials was their limited ability to use digital technology, which resulted in administrative tasks being carried out manually and inefficiently. Therefore, this digital literacy training aimed to enhance the skills of village officials in utilizing digital tools, especially AI, to support their administrative work. The method used in this activity was Participatory Action Research (PAR), which involved the stages of diagnosing, action planning, action taking, evaluating, and specifying learning. Evaluation of the activity was conducted using Likert scale questionnaires and open-ended questions to collect feedback from participants regarding their understanding and responses to the training provided. Data analysis was carried out using SPSS to calculate the mean, standard deviation, and qualitative findings from the open-ended questions. The evaluation results showed that the benefits of the activity (mean = 4.2) and the intention to implement AI (mean = 4.2) received the highest scores, indicating that the participants found the training highly beneficial and were motivated to apply AI in their daily tasks. On the other hand, the understanding of AI in Excel (mean = 3.7) and the assessment of the material (mean = 3.7) showed that further in-depth learning was needed to improve participants' comprehension and skills. Overall, the activity successfully improved the skills of village officials and raised collective awareness to transition towards a more efficient and adaptive digital village administration. This training is expected to positively contribute to the digital transformation in the village.
The development of digital technology provides significant opportunities for Micro, Small, and Medium Enterprises (MSMEs) to improve the quality of their product promotions. However, most MSMEs fostered by Sharia cooperatives still face obstacles in utilizing the latest technology, particularly artificial intelligence (AI), as an effective and efficient promotional tool. Given this situation, this community service activity was carried out with the aim of increasing the capacity of MSME members in utilizing AI technology to create more attractive product promotional content that aligns with digital marketing trends. The activity took place at Kedai Fatiya Sukodono in July 2025, coinciding with the BMT Insan Mandiri Sukodono Branch member gathering. The methods used included counseling on the importance of AI-based digital marketing, technical training on using AI applications for content design, and hands-on practice in creating promotional materials by participants. A total of 40 MSMEs from various sectors, such as culinary, fashion, and services, participated in this activity. The results showed an increase in participants' knowledge and skills in creating more creative, professional, and cost-effective promotional content. In addition, participants also gained a better understanding of digital-based promotional strategies that can increase market reach. Thus, this community service activity provides a real contribution to strengthening the competitiveness of MSMEs in the era of digital transformation, while also supporting the role of sharia cooperatives as partners in empowering the people's economy
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