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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Pendidikan MIPA
Rosdiana, Tjaturningsih
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Computer Science & IT Education

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Developing Electronic Student Worksheets Based on Ethnoscience to Train Smart Risk-Taking Behaviour and Growth Mindset Viyanti, Viyanti; Sunyono, Sunyono; Rosdiana, Tjaturningsih; Anggreini, Anggreini; Jarwadi, Jarwadi; Priowicaksono, Noorman
Jurnal Pendidikan MIPA Vol 25, No 1 (2024): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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Abstract: This study aims to determine the practicality and effectiveness of electronic student worksheets based on ethnoscience in training smart risk-taking behavior and a growth mindset. The research employed a hybrid type III mixed-method with a sequential explanatory design, combining quantitative and qualitative approaches. The subjects of the study were junior high school students in Lampung Province, selected randomly. The worksheets were developed based on ethnoscience principles, integrating local culture, traditional knowledge, and scientific knowledge, with validity tested by experts. Quantitative data were collected through product validity tests and hypothesis testing, while qualitative data were gathered through interviews and observations. Quantitative analysis showed a validity score of 91.60% with very high criteria, and hypothesis testing indicated significant differences between the experimental and control classes in the ability to exhibit smart risk-taking behavior and a growth mindset. Based on these results, it is concluded that ethnoscience-based worksheets are effective in training smart risk-taking behavior and a growth mindset, emphasizing the importance of integrating local cultural context in educational tools to enhance learning outcomes and personal development. This approach helps bridge the gap between traditional knowledge and modern scientific understanding, creating a more holistic educational framework.         Keywords: electronic student worksheets, ethnoscience, growth mindset, smart risk-taking behavior.DOI: https://doi.org/10.23960/jpmipa/v25i1.pp127-141
WORD2VEC OPTIMALIZATION USING TRANSFER LEARNING IN INDONESIAN LANGUAGE FOR HIGHER EDUCATION Hadianti, Sri; Riana, Dwiza; Tohir, Herdian; Jarwadi, Jarwadi; Rosdiana, Tjaturningsih; Sopandi, Evi; Kristiyanti, Dinar Ajeng
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6051

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Natural language processing (NLP) in Indonesian faces challenges due to limited linguistic resources, particularly in developing optimal word embedding models. This study optimizes the Word2Vec model for Indonesian in higher education contexts by leveraging transfer learning and lexicon expansion. Using a dataset of 4,463 higher education related tweets consisting of positive and negative sentiment categories, the proposed NewWord2Vec model combined with a Support Vector Machine (SVM) classifier achieved a 4% improvement in word detection accuracy compared to the standard Word2Vec. This enhancement demonstrates better performance in capturing linguistic nuances and sentiment orientation in Indonesian text. However, the model’s applicability remains limited to higher education terminology, and potential biases from transfer learning must be addressed. Future research should expand the dataset to diverse domains and refine the transfer learning process to better capture contextual variations in Indonesian. These findings contribute to advancing NLP applications in Indonesian, particularly for automated assessment systems, recommendation tools, and academic decision-making processes
Co-Authors Anggreini, Anggreini Dinar Ajeng Kristiyanti, Dinar Ajeng Dwiza Riana Evi Sopandi, Evi JARWADI, JARWADI Priowicaksono, Noorman Sri Hadianti Sunyono - - Tohir, Herdian Viyanti Viyanti