Codeless Data Science with KNIME: Data Analysis and Optimization Without Coding - Ahmad Faiz Dermawan; Muhammad Ajar Danu Wiratama; Maulana Faiz; Khoirudin Sidik; Azril Ferdiansyah Romadoni; Mirza Sutrisno; Yana Adharani; Rully Mujiastuti; Nurvelly Rosanti (Society : Jurnal Pengabdian Masyarakat, 2026)
In the era of digital transformation, data analysis skills have becomeessential competencies for students and the general public. However,data science learning is often perceived as complex due to its relianceon programming skills. To address this issue, a communityengagement program in the form of a webinar and workshop entitled“Codeless Data Science Using KNIME: Data Analysis andOptimization without Coding” was conducted. This program aimedto enhance participants’ literacy and understanding of fundamentaldata science concepts through a codeless approach using the KNIMEAnalytics Platform. The activity was implemented in two main stages:a webinar session focusing on conceptual explanations and the datascience workflow, followed by a hands-on workshop session involvingpractical data analysis and predictive modeling through visualworkflows without coding. Program evaluation was conducted usinga post-activity feedback questionnaire. The results indicated that69.4% of participants were very satisfied, 22.2% were satisfied, 5.6%felt neutral, and 2.8% were dissatisfied with the overallimplementation. These findings demonstrate that the majority ofparticipants responded positively to the materials, delivery methods,and overall organization of the activity. Therefore, this communityengagement program can be considered effective in promotinginclusive and accessible data science learning through a codelessapproach.