Erni Romansyah
Universitas Muhammadiyah Mataram, Mataram, Indonesia

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Pendampingan Analisis Korelasi dan Regresi Linier Berganda Menggunakan JASP serta Interpretasi Berbasis DeepSeek dan ChatGPT Syaharuddin Syaharuddin; Earlyna Sinthia Dewi; Erni Romansyah; Novi Yanti Sandra Dewi; Zaenafi Ariani; Ahmad Hulaimi; M. Anugrah Arifin
Jurnal Pengabdian Kepada Masyarakat Vol 7 No 02 (2026): Jurnal Pengabdian Kepada Masyarakat (JPKM) Langit Biru
Publisher : Politeknik Penerbangan Indonesia Curug

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Abstract

Correlation and multiple linear regression analyses require an understanding of statistical concepts and the ability to accurately interpret the resulting output. The use of JASP, ChatGPT, and DeepSeek offers a supportive alternative to help academics understand statistical results and develop them into scholarly narratives. This activity aims to enhance the ability of lecturers to conduct correlation and multiple linear regression analyses using JASP and to interpret the output with the assistance of ChatGPT and DeepSeek. The participants comprised 23 lecturers from various faculties at Universitas Muhammadiyah Mataram, holding academic ranks ranging from junior lecturer and expert assistant to lecturer. The activity methodology included presentations on hypothesis testing concepts, prerequisite tests, and classical assumption tests; hands-on analysis using JASP; and exercises in describing and interpreting output via ChatGPT and DeepSeek. Evaluation was conducted using a seven-indicator Likert scale questionnaire, with responses converted to a 100-point scale. The evaluation results showed participant response rates ranging from 82.35% to 89.41%, indicating a positive reception regarding the use of JASP and AI to support statistical interpretation.