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All Journal Instructional Development Journal Journal of Information Systems and Informatics
Widowati
Diponegoro University
Computer Science & IT Education Social Sciences Other

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Mathematical Communication Process Profile of Prospective Mathematics Teachers Based on Self-Confidence Darto; Kartono; Widowati; Mulyono
Instructional Development Journal Vol. 9 No. 1 (2026): IDJ
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

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Abstract

Self-confidence is one of the affective aspects that can support mathematical communication skills. The research focuses on explaining students' mathematical communication processes in solving problems regarding self-confidence. The approach used is qualitative. The research instrument consists of questionnaires, tests, and interviews. The results of the self-confidence questionnaire were categorized into high, medium, and low. Each category took one person as a respondent. Data analysis uses the reduction stage, displaying results and conclusions. The research results are a mathematical communication process based on self-confidence, including identification, representation, algorithms, and evaluation. Students in the high and medium self-confidence categories show characteristics of good communication processes, namely identification, representation, algorithms, and evaluation. Students use symbols appropriately to explain known information and problems and write detailed answers. Students in the low self-confidence category need help translating mathematical information and symbols. This results in the algorithm stage needing to get the right results. This condition shows that the identification and representation stages are critical initial processes in mathematical communication
Toward AI-Based Child Emotion Early Warning Systems in Child-Oriented Digital Environments: A Socio-Technical Systematic Review Ratih Titi Komala Sari; Widowati; Adi Wibowo
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1811

Abstract

AI-based emotion recognition is gaining increasing attention in child-oriented digital environments, including digital play, AI toys, online learning, therapeutic platforms, and interactive child-computer systems. However, the translation of recognized emotions into responsible caregiver-facing early warnings remains insufficiently explored. This systematic literature review synthesizes technical and socio-technical perspectives on child emotion recognition, focusing on sensing modalities, AI approaches, datasets, alert interpretation, trust, privacy, ethics, governance, and caregiver acceptance. Following PRISMA 2020 guidelines, 400 records from Scopus and IEEE Xplore were screened, resulting in 32 studies included in the core synthesis. The findings reveal that facial-expression analysis and convolutional neural networks dominate current research, while child-specific datasets, multimodal learning, real-world validation, uncertainty communication, privacy-by-design, and caregiver-centered evaluation remain limited. This review proposes a socio-technical framework linking AI emotion inference with explainable alert translation, privacy-aware governance, and caregiver decision support. The proposed emotion-to-alert mechanism remains conceptual and requires empirical validation before practical deployment.
Co-Authors Adi Wibowo Darto Kartono Mulyono Ratih Titi Komala Sari