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All Journal Jurnal Tekno Insentif Asean Journal of Science and Engineering (AJSE) Brilliance: Research of Artificial Intelligence
Wahyudin, W.
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Engineering Materials Science & Nanotechnology Mathematics Other

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Chatbot Artificial Intelligence as Educational Tools in Science and Engineering Education: A Literature Review and Bibliometric Mapping Analysis with Its Advantages and Disadvantages Al Husaeni, Dwi Fitria; Haristiani, Nuria; Wahyudin, W.; Rasim, R.
ASEAN Journal of Science and Engineering Vol 4, No 1 (2024): AJSE: March 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ajse.v4i1.67429

Abstract

This research was conducted to analyze the application, utilization or use of AI chatbots in the education sector based on several previous studies. Bibliometric analysis is used to identify the current status of research and critical points in bibliometric data mapping can help predict future research trends. Data searches were carried out on the Scopus database with the keywords "Chatbot" AND "education" with a research year range of 2007-2024. There were 376 articles found. The research results show that research on chatbots, especially in the education sector, is increasingly in demand. In 2023 there will be a drastic increase in the number of studies regarding chatbots in the education sector compared to previous years. This is because chatbots are considered to be an interesting tool to use in education because they enable a more innovative teaching process in terms of improving learning processes and outcomes. There are 25 countries that have contributed to related research, with the United States, Australia, United Kingdom, China and Taiwan in the top five. This research also shows that there are 26 subject areas that have used chatbots in the education sector. The use of chatbots in the education sector has advantages and disadvantages. With the completion of this research, it is hoped that it can become material for consideration for related research.
How to Count Speed? Utilizing Android Applications to Support a Concept Attainment Model to Help Mathematical Thinking Skills Abidin, Zaenal; Herman, Tatang; Wahyudin, W.; Wiryanto, W.; Farokhah, Laely; Penehafo, Amadhila Elina
ASEAN Journal of Science and Engineering Vol 4, No 2 (2024): AJSE: September 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ajse.v4i2.72528

Abstract

Examining and explaining the mathematical thinking skills of primary school students who employed an Android app as a concept attainment technique was the aim of this study. The inquiry used a 3 x 2 factorial design and a quantitative methodology. The study included twenty-eight fifth-grade students from two different courses. The results showed that students' mathematical thinking skills differed between those taught using a conventional strategy and those taught using a concept attainment method using an Android app and digital comic. Different mathematical thinking abilities are shown by students with levels of self-efficacy, according to the other research. This is because, in comparison to students in other groups, students with high levels of self-efficacy have more prior knowledge. Ultimate result shows no relationship between developing mathematical thinking skills and self-efficacy. This study could help educate people about various educational programs and media that can be used to enhance their capacity for mathematical thinking.
Prediction of House Price using the Multivariate Adaptive Regression Spline Method ISKANDAR, AYSHA ALIA; Al Husaeni, Dwi Fitria; Sahidin, M. Zaenal Iskandar; Riza, Lala Septem; Wahyudin, W.
Jurnal Tekno Insentif Vol 19 No 1 (2025): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v19i1.1858

Abstract

Kekritisan lingkungan adalah kondisi suatu wilayah yang menunjukkan tingkat kerusakan atau kekritisan yang dapat memengaruhi kemampuan lingkungan dalam mendukung kehidupan manusia dan ekosistem. Faktor penyebabnya meliputi rendahnya vegetasi (NDVI), meningkatnya lahan terbangun (NDBI), suhu permukaan tinggi (LST), dan kepadatan penduduk. Tujuan penelitian ini menganalisis tingkat kekritisan lingkungan di Kota Bandar Lampung serta hubungan antara parameter tersebut terhadap kekritisan lingkungan. Metode yang digunakan adalah algoritma Environmental Critical Index (ECI) yaitu pendekatan integratif yang menggabungkan beberapa parameter lingkungan untuk menilai tingkat kekritisan wilayah secara spasial dan kuantitatif dengan data citra Landsat 8 (2014) dan Landsat 9 (2023). Hasil penelitian menunjukkan adanya peningkatan kekritisan cukup signifikasan sebesar 50% terjadi pada area sangat kritis seluas 1.447,74 ha. Sebaliknya terjadi penurunan pada area tidak kritis sebesar 35% atau seluas 1.029,16 ha dan pada area kritis sebesar 15% atau seluas 418,58 ha. Faktor yang paling berpengaruh terhadap kekritisan lingkungan adalah NDBI.
Machine Learning-Based Clustering for Program Learning Outcomes in Higher Education: A Systematic Review Wahyudin, W.; Riza, Lala Septem; Erlangga, E.; Al Husaeni, Dwi Novia
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5953

Abstract

This study aims to systematically review the application of machine learning-based clustering algorithms in the evaluation of Graduate Learning Outcomes (CPL) in higher education. The review was conducted using the PRISMA approach on articles published in the Scopus database during the period 2020–2025. A total of 52 articles were analyzed to identify trends in the algorithms used, implementation challenges, and their contributions to curriculum development. The findings show that algorithms such as K-Means, Hierarchical Clustering, and Fuzzy C-Means are frequently used in mapping student competencies. However, their implementation in practice remains limited due to insufficient model validation, lack of justification for algorithm selection, and a disconnect between analytical results and academic decision-making. This situation reflects a broader issue in the integration of machine learning into educational contexts, where the technical potential of algorithms has not yet been fully translated into meaningful pedagogical impact. As a conceptual contribution, this study develops a machine learning-based computational model that includes the stages of CPL data collection, preprocessing, cluster modeling, result evaluation, and integration into curriculum policy. The proposed model is designed to enhance transparency, adaptability, and evidence-based decision-making in curriculum management systems. This study also highlights the need for the development of soft clustering techniques, integration with digital learning systems, and attention to the ethics and transparency of algorithms in data-based evaluation. Thus, this study emphasizes the importance of bridging the gap between algorithmic analysis and applicable educational strategies within higher education institutions.
Co-Authors Al Husaeni, Dwi Fitria Al Husaeni, Dwi Novia Erlangga, E. Farokhah, Laely ISKANDAR, AYSHA ALIA Lala Septem Riza Nuria Haristiani Penehafo, Amadhila Elina Rasim, R. Sahidin, M. Zaenal Iskandar Tatang Herman, Tatang Wiryanto, W. Zaenal Abidin