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All Journal Jurnal Studi Inovasi Journal Emerging Technologies in Education
Jastacia, Bella
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Potensi Penggunaan Kecerdasan Buatan untuk Video Promosi Digital: Pendekatan Neuromarketing: POTENSI PENGGUNAAN KECERDASAN BUATAN UNTUK VIDEO PROMOSI DIGITAL: PENDEKATAN NEUROMMARKETING Jastacia, Bella; Adha Akbar, Deni
Jurnal Studi Inovasi Vol. 3 No. 4 (2023): Jurnal Studi Inovasi
Publisher : Inovbook

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52000/jsi.v3i4.140

Abstract

Pemilihan media produksi iklan dan pemasaran produk mengalami perubahan akibat revolusi industri 4.0. Ponsel pintar, komputer, dan gadget telah menggeser pencarian informasi produk konsumen dari media cetak ke digital. Video promosi digital (DPV) memberikan informasi terbaik tentang produk. Pemasar dapat menggunakan pendengaran dan penglihatan untuk mengkomunikasikan detail produk. Namun, produksi DPV mahal dan memakan waktu, mulai dari pembuatan film, pengeditan, rendering, dan penyiaran. AI dapat memangkas biaya produksi DPV dan mempercepat proses kreatif. Perangkat lunak AI memproses skrip ke dalam komputer untuk menghasilkan DPV. DPV akan mensurvei, mewawancarai, dan memfokuskan kelompok beberapa responden sebelum mempublikasikannya. Disamping itu, neuromarketing dapat mengakses pikiran dan emosi bawah sadar konsumen. Tinjauan penelitian ini menyelidiki AI berbasis neuromarketing untuk DPV.
Personalizing Learning Paths: A Study of Adaptive Learning Algorithms and Their Effects on Student Outcomes Hakim, Nur; Jastacia, Bella; Mansoori, Ahmed Al-
Journal Emerging Technologies in Education Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jete.v2i4.1365

Abstract

Background. In recent years, the demand for personalized learning experiences has increased, particularly in the context of adaptive learning algorithms that cater to individual student needs. However, there is still a lack of comprehensive studies that evaluate the effectiveness of these algorithms on student outcomes. This study seeks to address this gap by examining how adaptive learning algorithms can personalize learning paths and improve academic performance. Purpose. The research aims to explore the correlation between the implementation of these algorithms and student engagement, retention, and success rates. Method. To achieve this, a quantitative research method was employed, involving the collection of data from 200 students in an online learning environment. The students were divided into two groups: one using a traditional learning model and the other exposed to adaptive learning algorithms. Student outcomes, including engagement metrics, test scores, and retention rates, were tracked over a semester. Results. The results revealed a significant improvement in student engagement and academic performance in the group that utilized adaptive learning algorithms compared to the traditional learning group. Moreover, students in the adaptive learning group demonstrated higher retention rates and greater satisfaction with their learning experiences. Conclusion. In conclusion, the study suggests that adaptive learning algorithms play a crucial role in enhancing personalized learning paths, ultimately leading to improved student outcomes. These findings highlight the importance of integrating adaptive technologies in modern educational systems to foster more effective learning environments.
Co-Authors Adha Akbar, Deni Hakim, Nur Mansoori, Ahmed Al-