Analisis Prediktif Tren Pendidikan di Indonesia Menggunakan KNN Studi Kasus Data Pendidikan 2021-2023

Penulis

  • Mukhtada Billah Nasution Universitas Jambi
  • Akhiyar Waladi
  • Ulfa Khaira
  • Pradita Eko Prasetyo Utomo

Kata Kunci:

Indonesian Education, Education Trends, K-Nearest Neighbor Algorithm, Education Digitalization, Education Data Analysis

Abstrak

This research focuses on the importance of education in improving the competitiveness of the younger generation in Indonesia, especially in facing the challenges of globalization and the digital revolution. Education trends in Indonesia during the 2021-2023 period have been dominated by two main factors, namely digitalization and equal access to education. A data-driven approach is used to predict education trends in 2024, using the K-Nearest Neighbor (KNN) algorithm to analyze data from the Central Statistics Agency (BPS) regarding the percentage of the population aged 25 years and over who have at least a high school education, categorized by gender. The result of this research will predict the trend of education in each region in 2024 whether it is decreasing, stable, or increasing. Through data collection and literature study, this research identifies relevant patterns and presents statistically-based predictions that can serve as a reference for stakeholders in the development of education in Indonesia. The results of this study are also expected to provide insights for policymakers in formulating effective strategies to address the education gap and promote inclusive digitalization..

Unduhan

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Diterbitkan

2025-01-20