Kohesi: Jurnal Sains dan Teknologi

Articles

Vol. 10 No. 8 (2026): Kohesi: Jurnal Sains dan Teknologi, ISSN 3025-1311

DATA CRAWLING TECHNIQUES IN SOCIAL MEDIA AS AN INITIAL STAGE IN UNDERSTANDING BASIC MACHINE LEARNING TECHNIQUES (CASE STUDY: RAM PRICE INCREASE 2025)

Submitted
January 7, 2026
Published
2026-01-07

Abstract

Social media is an important data source for understanding public responses to technological issues. This study aims to apply data crawling techniques as an initial stage of basic machine learning with a case study of the increase in Random Access Memory (RAM) prices in 2025. Data was collected from the Twitter (X) platform using the Twitter API, then went through pre-processing, tokenization, and token frequency analysis stages. The results of the study show that pre-processing effectively improves the quality of text data, while token frequency analysis is able to identify dominant words that represent the focus of public discussion. This study confirms that data crawling and token frequency analysis are important foundations in the initial pipeline of text-based machine learning.

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