S Prawira, Nanda
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Peningkatan Kemampuan Mahasiswa ITPA dalam Analisis Data Pertanian melalui Pelatihan Data Mining dengan Google Colab Febriansyah; Muntari, Siti; S Prawira, Nanda
Jurnal Pengabdian Magister Pendidikan IPA Vol 8 No 2 (2025): April-Juni 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v8i2.11745

Abstract

In the era of precision agriculture and information digitalization, the ability to manage and analyze large-scale data (big data) has become a strategic competency, especially in addressing the challenges of modern agriculture. One of the main issues faced by vegetable farmers in the partner community area is the difficulty in accurately predicting harvest yields due to the lack of data-driven analysis based on historical records. In fact, substantial data on production, climate, and market prices are available but have not been optimally utilized, either by farmers or by agricultural students as future professionals in the field. Initial observations indicate that students of the Institut Teknologi Pagar Alam (ITPA) lack sufficient understanding and skills in applying data mining methods to extract meaningful information from agricultural data. This community service activity was designed to improve data literacy and technical skills among ITPA students through training on data mining techniques using Google Colab. Google Colab was chosen as it supports Python programming execution in a cloud computing environment without the need for local software installation, and it enables collaboration and efficiency in processing large datasets. The training involved 10 students, divided into two sessions covering an introduction to data mining concepts, agricultural dataset processing, and the implementation of classification and clustering algorithms. Post-training evaluation showed a significant improvement in both conceptual understanding and practical abilities among participants. This training is expected to enable students to become drivers of digital transformation in the agricultural sector through more strategic use of data.