Automating Cloud-Based Device Log Processing Using Google Apps Script - Muhammad Hasbi Asshidiqi; Muhammad Hilman Naufal; Muhamad Fikri; Oky Tria Saputra (Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID), 2026)
Device log management is often a challenge for system administrators due to large data volumes and unstructured formats. Manual processing is time-consuming and prone to human error. This research aims to implement an automated device log processing system utilizing Google Apps Script (GAS) as a cloud-based processing engine. The research method used is Research and Development (R&D), consisting of log data collection, automation script design, integration with Google Sheets as a database, and functional testing. The results show that the developed system is capable of parsing log data in real-time, categorizing log types based on urgency levels, and presenting them in structured reports. Efficiency testing demonstrates a reduction in data processing time by [X]% compared to conventional methods. The conclusion of this study is that Google Apps Script provides a cost-effective and efficient solution for managing device logs for medium-scale institutions.