Analysis of reading ambassadors and literacy mother programs in Indonesia using unsupervised machine learning: A trigram analysis and topic modeling approach

Abstract

Background

Reading Ambassadors and Literacy Mothers play a strategic role in enhancing the literacy culture within Indonesian society.

Purpose

This study aims to analyze discourse and public perception regarding the roles of Reading Ambassadors and Literacy Mothers using an unsupervised machine learning approach.

Research Design

A qualitative research design was applied, utilizing open-ended survey questions to gather public opinion.

Study Sample

Data were collected from 1,041 respondents across Indonesia.

Data Collection and/or Analysis

The data were gathered through open-ended questions between mid-September and mid-October 2024 as part of a program effectiveness evaluation. Trigram analysis and topic modeling were used to analyze the responses.

Results

Findings revealed recurring phrases reflecting public perceptions and expectations of the Reading Ambassador and Regional Literacy Mother programs. Key themes included their impact on literacy improvement and public aspirations for their continued role in promoting literacy.

Conclusions

The study provides in-depth insights into public sentiment about these programs, offering data-driven recommendations to strengthen national literacy policies.