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All Journal JURNAL TEKNOLOGI INFORMASI Jurnal Indonesia Sosial Teknologi Eduvest - Journal of Universal Studies Jurnal Pengabdian Teknologi, Ekonomi dan Humaniora Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Journal Technology Information and Data Analytic
Bagus Tri Mahardika
Universitas Darma Persada
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Neuroscience Social Sciences Other

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Perbandingan Algoritma Decision Tree dan K-Means Clustering Untuk Menentukan Penghargaan Terhadap Loyaltas Customer Mahardika, Bagus Tri; Prastowo, Donnie Varyasetya
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.82

Abstract

PT Tangguh Buana Roda Indonesia has difficulty in retaining loyal customers due to less than optimal customer management. This research proposes the use of a data mining-based system to categorize loyal customers using the K-Means and Decision Tree methods. The evaluation shows that the combination of K-Means and Decision Tree algorithms provides a higher average accuracy of 93.7175%. Compared to using Decision Tree alone which reached 92.8525% and K-Means which was only 91.667%. With the combination of these two algorithms, it is expected to support the awarding of loyal customers and strengthen the relationship between customers and companies. The system that has been created is web-based which will facilitate strategic planning to increase customer loyalty.
The Use of AI Tools in Supporting Academic Activities for High School/Vocational School Teachers in Bekasi S.Pd., MT, Herianto; Mahardika, Bagus Tri; Syofian, Suzuki; Saputra, Yan Sofyan Andhana; Darsono
JEPTIRA Vol 3 No 2 (2025)
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/jeptira.v3i1.97

Abstract

The goal of this community service project was to improve lecturers' and teachers' abilities to use cutting-edge prompting strategies based on artificial intelligence (AI) as a breakthrough in teaching. Chain of Thought (CoT) and Role Prompting, two crucial prompting techniques that have been demonstrated to greatly enhance human-AI interaction in educational settings, were the main topics of the course. Twenty-five participants from different educational institutions participated in a series of workshops, practical exercises, and case-based discussions. The findings showed that participants' capacity to create efficient and contextually relevant prompts had significantly improved. Additionally, the training helped teachers become more technologically literate and acted as a link to assist the continuous digital transformation of education. The initiative highlights the importance of equipping educators with AI-related skills that are both practical and pedagogically meaningful, especially as generative technologies become increasingly embedded in learning environments.
Co-Authors Afri Yudha Aji Setiawan Aji Setiawan Andi Susilo andi susilo Aqil Fathoni, Muhammad Faiz Atik Kurnianto Budiarjo, Wisnu DARSONO Dwiky Muhammad Reza Eva Novianti Hasan, Albantani Meiditya Herianto Mochammad Fiqri Ash'ari Muhammad Reza, Dwiky Prastowo, Donnie Varyasetya S.Pd., MT, Herianto Siregar, Rolan Sofyan, Yan Suzuki Syofian Trisna Ardi Wiradinata Yahya Yan Sofyan Andhana Saputra Yendi Esye