Prediksi Indeks Inovasi Global Indonesia Menggunakan Hybrid  Machine Learning

Patah Herwanto; Fathurrahman Pratama Putra; Rani Apriliani Aditya; Harmansyah Nasution

doi:10.37151/jsma.v17i2.268

Patah Herwanto Universitas Ekuitas Indonesia
Fathurrahman Pratama Putra ITENAS Bandung
Rani Apriliani Aditya
Harmansyah Nasution

DOI: https://doi.org/10.37151/jsma.v17i2.268

Keywords: Indeks Inovasi Global, machine learning, deret waktu, pengambilan keputusan, inovasi nasional

Abstract

Indeks Inovasi Global (Global Innovation Index / GII) merupakan indikator strategis yang digunakan untuk menilai daya saing dan kapasitas inovasi suatu negara. Bagi Indonesia, dinamika nilai GII mencerminkan akumulasi kebijakan, investasi, serta kesiapan sistem inovasi nasional yang berkembang secara bertahap dan bersifat temporal. Oleh karena itu, diperlukan pendekatan analitis yang adaptif untuk memprediksi perubahan GII guna mendukung perencanaan dan pengambilan keputusan strategis berbasis data. Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi model prediksi Indeks Inovasi Global Indonesia menggunakan pendekatan hybrid machine learning berbasis data deret waktu. Metode penelitian dilakukan melalui analisis komparatif beberapa model pembelajaran mesin, yaitu Random Forest, XGBoost, dan Long Short-Term Memory (LSTM), dengan menerapkan validasi temporal untuk mengidentifikasi pola hubungan antarperiode serta menilai kinerja prediktif model. Hasil penelitian menunjukkan bahwa model berbasis machine learning mampu menghasilkan prediksi yang stabil dan konsisten, dengan kinerja GII tahun sebelumnya (lag₁) berperan dominan dalam membentuk nilai GII pada periode berjalan. Temuan ini mengindikasikan bahwa kinerja inovasi nasional lebih dipengaruhi oleh kesinambungan kebijakan dan akumulasi kapasitas jangka menengah dibandingkan intervensi jangka pendek. Implikasi penelitian ini memberikan kontribusi praktis bagi perumus kebijakan dan pengelola sistem inovasi dalam merancang strategi inovasi berkelanjutan yang berorientasi pada penguatan daya saing nasional berbasis analitik prediktif.

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