Aiti: Jurnal Teknologi Informasi
Vol 23 No 2 (2026)

Analisis penerapan pembelajaran TPACK menggunakan metode Random Forest pada SMK Negeri 5 Sarmi di Bonggo

Aprilia Aprilia (Universitas Kristen Satya Wacana)
Suprihadi Suprihadi (Universitas Kristen Satya Wacana)



Article Info

Publish Date
12 Jun 2026

Abstract

Modern education emphasizes the integration of knowledge, skills, attitudes, and mastery of Information and Communication Technology (ICT). One popular technology-based learning model is Technological Pedagogical Content Knowledge (TPACK), which synergizes technological, pedagogical, and content knowledge. This study analyzes TPACK implementation at SMK Negeri 5 Agribusiness and Agrotechnology Sarmi using random forest classification. Data collection involved questionnaires distributed to students and teachers, with responses categorized into five comprehension levels: “Very Good”, “Good”, “Fair”, “Poor”, and “Very Poor”. The dataset was split into 80:20 training-test ratios. After training the random forest model, performance was evaluated using standard metrics and a confusion matrix. Additionally, a feature importance analysis was conducted to identify the most influential components in the model. Results showed 96% classification accuracy, with Technological Content Knowledge (TCK) emerging as the most significant factor. Pedagogical Content Knowledge (PCK), Content Knowledge (CK), and Technological Pedagogical Content Knowledge (TPACK) themselves had the lowest importance scores, indicating that these components require prioritization for optimal technology-enhanced learning development at SMK Negeri 5 Agribusiness and Agrotechnology Sarmi.

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Journal Info

Abbrev

aiti

Publisher

Subject

Computer Science & IT

Description

AITI: Jurnal Teknologi Informasi is a peer-review journal focusing on information system and technology issues. AITI invites academics and researchers who do original research in information system and technology, including but not limited to: Cryptography Networking Internet of Things Big Data Data ...