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Daengku: Journal of Humanities and Social Sciences Innovation
Published by PT. Mattawang Mediatama Solution
ISSN : -     EISSN : 27756165     DOI : https://doi.org/10.35877/454RI.daengkuv1i1
Core Subject : Humanities, Education, Social,
Humanities Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Other
The Daengku seeks to publish high-quality research papers, review articles, and book reviews that make a contribution to knowledge through the application and development of theories, new data exploration, and/or scientific analysis of salient policy issues. The Scope of the Daengku includes the following areas: Social Sciences: Anthropology, Asian Studies, Communication, Demography, Development, Gender Studies, Government & Public Policy, Human Ecology, International Relations, Media Studies, Peace and Conflict, Political Science, Science, Technology & Society, Sociology. Humanities: Cultural Studies, Education, History, Human Geography, Linguistics, Philosophy, Religion.
Arjuna Subject : Umum - Umum
Articles 485 Documents
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Designing an Intelligent Decision Support System for Evaluating Teaching Effectiveness in Technology-Enhanced Classrooms Ramadiani Ramadiani; Azainil Azainil; Kenya Permata Kusumadewi; Guellica Agnesia Claudia Thanos; Toong Hai Sam
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4848

Abstract

The rapid digital transformation of education has significantly increased the adoption of technology-enhanced classrooms, generating substantial educational data that can support intelligent instructional evaluation. However, conventional teacher assessment systems remain limited by subjectivity, inconsistent evaluation standards, and the inability to analyze multidimensional learning analytics data effectively. This study aims to design an Intelligent Decision Support System (IDSS) for evaluating teaching effectiveness in smart classroom environments using the ELECTRE (Elimination and Choice Translating Reality) method integrated with Artificial Intelligence (AI)-based educational analytics. The proposed framework combines learning analytics indicators, machine learning models, and outranking-based multi-criteria decision-making to support transparent and data-driven educational governance. The evaluation criteria include student engagement, attendance rate, assignment completion, student satisfaction, learning outcomes, classroom interaction, technology integration, and instructor responsiveness. The computational process involved decision matrix construction, normalization, weighted normalization, concordance-discordance analysis, and aggregate dominance evaluation. The results demonstrated that the ELECTRE method effectively identified dominant teaching alternatives and handled conflicting instructional criteria systematically. Teacher 3 achieved the highest performance ranking due to superior instructional performance across all evaluation indicators. Additionally, AI-based predictive analysis improved evaluation accuracy and instructional pattern identification within technology-enhanced classrooms. The study contributes theoretically by extending the application of ELECTRE within intelligent educational DSS frameworks and practically by providing educational institutions with a scalable and transparent mechanism for evaluating teaching effectiveness. The proposed system supports smart educational governance, data-driven decision-making, and sustainable classroom quality assurance in digital learning ecosystems.
Trust-Mediated AI Continuance Intention among Pre-Service Teachers: Integrating UTAUT and the Extended S-O-R-S Framework with AI Brain-Rot Exposure M. Miftach Fakhri; Andika Isma; Sahabuddin Sahabuddin; Pramudya Asoka Syukur; Rosidah Rosidah
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4849

Abstract

The rapid use of artificial intelligence (AI) in teacher education raises important concerns about whether pre-service teachers will continue using AI despite emerging risks such as perceived AI brain-rot exposure. Therefore, this study examines how UTAUT-related stimuli, institutional support, and perceived AI brain-rot exposure influence the intention to continue using AI through trust in AI. This study employed a quantitative cross-sectional survey design involving 247 pre-service teachers enrolled in teacher education programmes in Indonesia, all of whom had prior experience using AI for academic or teaching-related purposes. Data were analyzed using Partial Least Squares Structural Equation Modeling. The results showed that performance expectancy and social influence significantly increased trust in AI, whereas effort expectancy and institutional support did not significantly influence trust. Perceived AI brain-rot exposure also significantly influenced trust in AI, but the relationship was positive, suggesting that awareness of AI-related cognitive risks may coexist with selective or calibrated trust. Trust in AI strongly influenced continuance intention and mediated the effects of performance expectancy, social influence, and perceived AI brain-rot exposure on the continuance intention. The model explained 72.1% of the variance in trust in AI, and 62.6% of the variance in continuance intention. This study contributes to the literature by extending the UTAUT and S–O–R with a stressor perspective and by introducing perceived AI brain-rot exposure as an emerging construct in AI-in-education adoption research. These findings suggest that teacher education programmes should prioritize demonstrating AI's concrete pedagogical benefits and fostering reflective AI literacy to build trust, rather than relying solely on institutional policy or ease-of-use considerations.
From Growth Mindset and Social Media Influence to Learning Outcomes: A PLS-SEM Study in Indonesian Higher Education Andika Isma; Andi Naila Quin Azsisah Alisyahbana; Sahabuddin Sahabuddin; Akhmad Khairul Shiddiq; Della Fadhilatunisa
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4850

Abstract

This study examines how growth mindsets and social media influence shape learning outcomes through student engagement and digital literacy in digitally mediated higher education. Survey data were collected from 478 undergraduate students enrolled at higher education institutions in Indonesia and analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. The measurement model demonstrated satisfactory reliability, convergent validity, and discriminant validity. The structural model explained 67.3% of the variance in learning outcomes, 60.5% in student engagement, and 40.7% in digital literacy, indicating a substantial explanatory power. Growth mindset positively predicted learning outcomes, student engagement, and digital literacy, with the strongest substantive effect observed on student engagement. Social media influence positively predicted student engagement and digital literacy but did not have a significant direct effect on the learning outcomes. Student engagement and digital literacy both positively predicted learning outcomes, and indirect-effect analysis confirmed several mediating pathways linking growth mindset and social media influence to learning outcomes. These findings indicate that the academic benefits of digital higher education are not produced by mindset or social media exposure alone. Learning outcomes improve when psychological dispositions and social-digital interactions are translated into active engagement and effective digital literacy.
The Mediating Role of Social-Emotional Learning in the Relationship Between Emotional Intelligence and Students' Self-Confidence in Islamic Education Muh Syahrul Sarea; Muh Bachtiar Aziz; Sulaeman; Faisal
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4853

Abstract

The dominance of cognitive-oriented and dogmatic instruction in Islamic Religious Education (PAI) frequently provokes academic anxiety, causing students to remain passive despite possessing adequate emotional regulation. This study aims to investigate the mediating role of Social-Emotional Learning (SEL) in the relationship between Emotional Intelligence (EI) and students' self-confidence in religious classrooms. Employing an explanatory cross-sectional survey design, data was collected from 78 high school students selected through purposive sampling. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with a 5,000-subsample bootstrapping procedure. The results indicate that EI has a significant direct effect on both SEL and self-confidence. However, the key finding confirms that SEL acts as the most dominant predictor and serves as a complementary partial mediator in the relationship between EI and self-confidence. This study concludes that internal emotional regulation (EI) is a necessary but insufficient condition to generate self-confidence without a psychologically safe classroom ecosystem. Practically, the integration of SEL deconstructs the religious classroom from a mere space for theological dogma transfer into an inclusive dialogic space that aligns with the core values of tazkiyatun nafs (purification of the soul).
The Strategic Role and Implementation of the Sustainable Development Goals through Public Libraries: A Multi-Case Study in Seven Provinces with the Highest Regional Competiveness Index (RCI/IDSD) Scores in Indonesia Anita Tri Widiyawati; Kanyarat Kwiecien; Lan Thi Nguyen
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4861

Abstract

Public libraries have become important organizations in fostering and stimulating inclusive and sustainable development in contemporary knowledge societies. This research adopted an integrated mixed-methods approach by examining the role of public libraries in Indonesia in supporting the implementation of the Sustainable Development Goals (SDGs). The qualitative research showed that libraries were inclusive knowledge organizations that connect the global development and the local community through policy alignment, digital transformation, and multistakeholder cooperation. Libraries fostered development of literacies and encourage social inclusion, ensure cultural preservation and boost community empowerment, although some issues remain, like inadequate resources, technological inequality and uneven institutional capacity. The measurement model yielded strong and valid constructs for the key dimensions of the initiative, namely administration, staff, training, resources, infrastructure, partnerships, and SDG outcomes (People, Planet, Prosperity and Peace), shown by standardized estimates which were all significant. The findings established that successful implementation of SDGs by libraries hinges upon the quality of governance, collaborative networks, and adaptive delivery of services. The research revealed that public libraries become strategic actors in the field of inclusive and sustainable development, especially at the local level. Stronger institutional and digital capacities, along with better-integrated planning, are needed to optimize the contribution of libraries to the SDG, it was pointed out.
Predicting Student Academic Success Using Machine Learning Models: A Learning Analytics Approach in Higher Education Arief Hidayat; Swasti Maharani; Dendi Pratama; Ramadiani Ramadiani; S Sujito; Addy Septyawan; Dian Wardiana Sjuchro
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4881

Abstract

Rapid deployment of digital learning technologies in the higher education sector has created immense amounts of educational data that could be leveraged to enhance student success and institutional effectiveness. Nevertheless, student dropout, poor academic performance, and lack of retention continue to plague universities across the world. In most cases, identification of academically struggling students is often late since existing models are largely reactive. Therefore, there is need for development of advanced learning analytics models that are able to forecast student performance in higher education institutions. The current study seeks to create an artificial neural network (ANN)-based learning analytics framework to predict student success in higher education institutions. A predictive analytical approach based on quantitatively evaluating a sample of 1,000 undergraduate students was used in the current study. Various attributes used to evaluate the students included demographic information, academic performance, LMS activity, and learning behaviors. Learning analytics indicators used in the model included previous GPA, attendance rate, assignment completion rate, quiz scores, logins per week, learning hours per week, discussion engagement, engagement index, interaction scores, and learning consistency. In the analysis, the model was validated and tested against accuracy, precision, recall, F1-score, ROC-AUC, confusion matrix, and cross validation tests. Results showed that accuracy, precision, recall, F1-Score, and ROC-AUC of the ANN model were 92.8%, 91.4%, 93.7%, 92.5%, and 0.96, respectively. Based on these outcomes, previous GPA, attendance rate, assignment completion rate, and various engagement indicators were found to be the strongest predictors of student success in college. On the theoretical front, contributions of this study include AI-assisted student performance and behavior prediction. Practically, a sophisticated warning system was developed in this study to assist in effective academic advisement and planning for student retention and academic improvement strategies.
Two Decades in Five Years: Mapping Digital HR, Workflow Automation, and Innovation Ecosystem Research (2020–2025) Arciana Damayanti; Asep Miftahuddin; Rofi Rofaida; Yoga Perdana; Rizqiana Arifatul Husna; Juliana Juliana
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4894

Abstract

Digital transformation has reshaped human resource management (HRM), giving rise to digital HR practices, workflow automation and innovation-ecosystem approaches. However, the literature on Digital HRM, electronic HRM (e-HRM), and innovation ecosystems remains scattered across disciplines and themes, leaving the field's intellectual structure, thematic evolution, and future directions only partially understood. This study reviews and maps research on digital human resource management, workflow automation, and innovation ecosystems published between 2020 and 2025 using a systematic literature review (SLR) combined with bibliometric analysis and following the PRISMA 2020 framework for a transparent and reproducible selection process. An initial search of the Scopus database returned 2,163 documents for review. After applying predefined inclusion and exclusion criteria, 244 journal articles were retained and analysed in Bibliometrix and Biblioshiny to examine publication trends, influential authors, journals, countries, and institutions, along with keyword co-occurrence and thematic structures. Research activity rose sharply over the period, at an annual growth rate of 23.84%, with the conceptual core of the field centring on e-HRM, digital HRM, digital transformation, workflow automation and innovation ecosystems. The thematic map identified technology, Industry 4.0, Society 5.0, and helix-based innovation models as the dominant driving themes. The Triple Helix and Quintuple Helix frameworks are well established, whereas Pentahelix-related work remains underexplored and is still emerging. This study offers a comprehensive picture of the intellectual landscape of digital HR transformation and innovation-ecosystem research and points to a clear opportunity for future work: bringing together workflow automation, digital HR practices, and Pentahelix-based collaboration to support sustainable workforce transformation and organizational innovation.
Mapping the Digital Ecosystem of Muslim-Friendly Tourism: Stakeholder Networks, Sentiment, and Themes on X Asep Miftahuddin; Juliana Juliana; Lazuardi Imani Hakam; Rizqiana Arifatul Husna; Muhammad Apriandito Arya Saputra; Budhi Pamungkas Gautama
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4895

Abstract

The rise of digital communication has reshaped the way tourism stakeholders interact, share information, and influence destination development. Muslim-Friendly Tourism has become one of the fastest-growing segments of the global industry; however, it has rarely been studied through a digital ecosystem lens. This study examines the halal tourism ecosystem by analyzing halal tourism conversations on X (formerly Twitter), mapping stakeholder interaction patterns, public sentiment, emotional responses, and dominant discussion themes. A dataset of 2,000 posts was collected via the SocialX platform between January 30, 2025, and March 30, 2026, and analyzed through an integrated framework combining Social Network Analysis, trend analysis, sentiment and emotion analysis, text clustering, topic modeling, and text network analysis. The network proved highly fragmented with 1,725 nodes, 1,417 directed edges, and 725 communities, reflecting the wide range of stakeholders involved; however, a few influential actors emerged as information brokers linking otherwise separate communities. Sentiment was predominantly neutral (46.75%), with positive sentiment (35.70%) clearly outweighing negative sentiment (17.55%), while happiness dominated the emotional landscape at 88.45%. The thematic analyses returned 14 discussion clusters and 117 topics, and the semantic network revealed three interconnected domains underpinning the ecosystem: the Destination and Policy Ecosystem, the Muslim Traveler Experience Ecosystem, and the Global Halal Travel Ecosystem. These findings extend Digital Ecosystem Theory to Muslim-Friendly Tourism and underscore the role of digital platforms in enabling stakeholder interaction, knowledge exchange, and value co-creation, offering practical guidance for policymakers, destination management organizations, and tourism businesses seeking to strengthen digital engagement and competitiveness
Instagram Marketing for Brand Awareness in Certification and Training MSMEs: Insights from Social Media Analytics Dian Addinna; Gilang Garnadi Suryadi; Yosep Hernawan; Edi Suryadi; Asep Miftahuddin; Rizqiana Arifatul Husna
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 2 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4896

Abstract

Early-stage micro, small, and medium enterprises (MSMEs) in the certification and training sector often struggle to build brand awareness on Instagram, where success depends heavily on trust, competence, and credibility. Most prior research has measured the effect of social media marketing through surveys rather than producing a directly applicable, data-driven model, and the certification services sector remains underexplored. This study addresses that gap by analysing Instagram discourse on professional certification and formulating an evidence-based Instagram marketing model. Using a social media analytics approach, 2,000 posts were collected through the SocialX application with the hashtag #sertifikasiprofesi and examined through five procedures: word cloud analysis, text network analysis, emotion analysis using an Indonesian RoBERTa model, sentiment network analysis, and BERTopic modelling. The findings show that the discourse is anchored in competency- and institution-oriented language (notably recognised schemes such as BNSP and LSP), framed around tangible career benefits, expressed through predominantly neutral-to-positive sentiment, and circulated within a sparse, broadcast-oriented network (288 nodes, 240 edges, density 0.6%) dominated by a few central institutional accounts. Based on these findings, this study proposes a marketing model that emphasises recognised credentials, concrete career outcomes, distinctive storytelling, cross-platform integration, and collaboration with influential accounts. The model is analytically derived; its implementation and evaluation are recommended for future research.
Development and Validation of Digital Readiness Assessment Instrument for Rural Enterprises: Evidence from BUMDES in Indonesia Abdurokhim Abdurokhim; Dendi Pratama; S. Sulastri; Whan Augustin Ainul Amri; Askarno Askarno
Daengku: Journal of Humanities and Social Sciences Innovation Vol. 6 No. 1 (2026)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.daengku4898

Abstract

Digital transformation remains a critical challenge for rural enterprises in developing economies, yet validated instruments to assess digital readiness in this context are scarce. This study develops and validates a comprehensive Digital Readiness Assessment (DRA) instrument specifically tailored for Badan Usaha Milik Desa (BUMDES) – Indonesia's village-owned enterprises. Through mixed-method research involving literature review, expert consultation, and empirical testing with 100 BUMDES in Cirebon Regency, we developed a 60-item instrument measuring five dimensions: awareness, management support, infrastructure, skills, and budget allocation. The instrument demonstrated excellent reliability (Cronbach's ? = 0.924) and strong construct validity through confirmatory factor analysis. Results reveal a significant paradox: while 67.4% of BUMDES show high awareness of digital importance, only 34.2% possess adequate digital skills and 31.8% allocate sufficient budget. ANOVA analysis (F=84.73, p<0.001) confirms significant differences across readiness dimensions, with awareness-capability gap identified as the primary barrier. Cluster analysis identifies three distinct readiness profiles: 'High Awareness-Low Capability' (43%), 'Moderate Readiness' (49%), and 'Digital Ready' (8%). The validated DRA instrument provides researchers and practitioners with a robust tool for assessing and benchmarking digital readiness in rural enterprise contexts, while findings inform targeted intervention strategies for digital transformation support.

Page 48 of 49 | Total Record : 485

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