Data Science Insights
Vol. 3 No. 2 (2025): Journal of Data Science Insights

Digital Data Collection among Low ICT-Literate Rural Communities: A Case Study using Google Forms via Smartphones

Wan Ishak, Wan Hussain (Unknown)
Yamin, Fadhilah (Unknown)
Ismail, Risyawati Mohamed (Unknown)
Mustafar, Mastora (Unknown)
Abu Bakar, Siti Zakiah (Unknown)



Article Info

Publish Date
01 Aug 2025

Abstract

This study investigates the use of Google Forms as a digital tool for daily livestock monitoring among rural, low ICT-literate chicken farmers in Malaysia. A total of 198 responses were collected via smartphones through WhatsApp-distributed forms, allowing participants to self-report poultry conditions while reducing the need for frequent site visits. While the approach proved accessible and cost-effective, analysis revealed significant data quality issues, including inconsistent data entry (e.g., mixed numeric and textual values), unstructured categorical responses, duplicate submissions, ambiguous placeholder values, and the absence of unique identifiers. These challenges limited the reliability and usability of the dataset for meaningful analysis. To address these issues, the study recommends implementing structured input fields, validation rules, unique respondent IDs, and user training materials tailored to low digital literacy. This paper highlights both the potential and pitfalls of digital self-reporting tools in underserved rural contexts and provides practical recommendations for improving data quality in similar monitoring efforts. The findings offer valuable guidance for researchers and practitioners designing data collection systems in constrained environments.

Copyrights © 2025






Journal Info

Abbrev

jdsi

Publisher

Subject

Computer Science & IT Engineering

Description

Data Science Insights, with ISSN 3031-1268 (Online) published by PT Visi Media Network is a journal that publishes Focus & Scope research articles, which include Data Science and Machine Learning; Data Science and AI; Blockchain and Advance Data Science; Cloud computing and Big Data; Business ...