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All Journal ANDHARUPA Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Bohr: Jurnal Cendekia Kimia Journal of Computer Science and Technology Application
Septiani, Nanda
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Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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Journal : Journal of Computer Science and Technology Application

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Optimizing Student Engagement and Performance usingAI-Enabled Educational Tools Mirdad, Khaizure; Daeli, Ora Plane Maria; Septiani, Nanda; Ekawati, Anita; Rusilowati, Umi
CORISINTA Vol 1 No 1 (2024): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i1.22

Abstract

Education is the primary pillar in the progress of modern society. With the development of artificial intelligence (AI) technology, its potential to advance the learning process has become a major focus. This research focuses on the integration of AI-based educational tools to enhance student engagement and academic performance. Through experimental design with a control group, students were divided into two groups: one using AI tools while the other followed conventional methods. Students from various educational levels participated in this research. Data were collected through questionnaires and academic evaluations to compare the outcomes between the two groups. Data analysis was conducted using SmartPLS, enabling the evaluation of the impact of AI tools on student learning. The results indicate that AI integration enables a more personalized and responsive approach to the unique needs of students. It is expected that AI technology in education will bring significant changes in how students engage and achieve academic success. This research expands the understanding of the potential of AI in improving the education process. The integration of AI technology in learning is a progressive step toward a more adaptive and effective education system, preparing students for success in an increasingly connected and complex world
Optimizing Digital Marketing Strategies through Big Data and Machine Learning: Insights and Applications Andayani, Dwi; Madani, Muchlishina; Agustian, Harry; Septiani, Nanda; Wei Ming, LI
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.29

Abstract

In the dynamic realm of digital marketing, the convergence of Big Data and machine learning has ushered in transformative changes, reshaping strategies through advanced data analytics and predictive modeling. This paper examines the pivotal role of these technologies in enhancing marketing practices, focusing on their impact on consumer targeting, engagement, and overall campaign effectiveness. By harnessing vast datasets and applying sophisticated machine learning algorithms, marketers can now predict consumer behavior with unprecedented accuracy, personalize marketing messages, and optimize operational strategies to maximize engagement and return on investment. Despite the profound advantages, the integration of these technologies raises substantial challenges, including data privacy concerns and the need for specialized skills. Through a mixed-methods approach combining quantitative data analysis and qualitative interviews, this study not only demonstrates the improved predictive accuracy and segmentation capabilities afforded by these technologies but also discusses the barriers to their full potential realization. The findings highlight a clear trajectory towards more data-driven, responsive marketing paradigms, suggesting a future where digital marketing strategies are increasingly informed by insights derived from Big Data and machine learning. This paper aims to provide a comprehensive overview of the current landscape and future potential of these transformative technologies in digital marketing.
Co-Authors AA Sudharmawan, AA Agustian, Harry Daeli, Ora Plane Maria Dolan, Ellen Dwi Andayani, Dwi Ekawati, Anita Erwin Prasetya Toepak Immaniar, Dewi Madani, Muchlishina Marviola Hardini Mirdad, Khaizure Mochamad Heru Riza Chakim Mulyati Nasution, Erni Juliana Al Hasanah Ninda Lutfiani Nur Azizah Pérez, Carlos Qurotul Aini rusilowati, umi Singh Bist , Ankur Sriliasta Bangun, Cicilia Supriyanti, Dedeh Tatik Mariyanti, Tatik Untung Rahardja Victorianda Wahyu Nugroho Wei Ming, LI Yusrawati Yusrawati Zainum Ikhsan, Ramzi Zarasky, Dwiki Zulkarnain, Andy