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All Journal Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika
Pricilla Sisi Austin Soko
Universitas Negeri Surabaya
Education Mathematics

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Prediksi Tingkat Pengangguran Terbuka di Indonesia Menggunakan Metode Numerik Ekstrapolasi Berbasis Python Pricilla Sisi Austin Soko; Rudh Renata; Akhmad Ilhamzah; Rahmawati Erma Standsyah; Dian Savitri
Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika Vol 14 No 1 (2026)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/smj.v14i1.11547

Abstract

Abstract The Open Unemployment Rate (OUR) is a strategic indicator reflecting labor market conditions and the effectiveness of national economic development policies. The development of Indonesia’s OUR during the 2015-2023 period exhibits a fluctuating pattern, influenced by structural economic dynamics and external shocks, thereby necessitating a predictive approach to support medium-term policy planning. This study aims to analyze the trend of Indonesia’s OUR, project its development through 2029 using a numerical approach, and assess the role of numerical methods as policy-support tools aligned with national development directions. The method employed is numerical extrapolation Lagrange polynomials using time-series OUR data. The results indicate that utilizing the entire historical dataset produces unstable and unrealistic projections due to the emergence of the Runge phenomenon. In contrast, restricting the model to more recent data yields stable and economically plausible projections. The projected OUR for the 2025-2029 period lies within the range of approximately ±4.46% to ±4.81%, reflecting a post-pandemic downward trend and remaining consistent with recent data patterns. These findings demonstrate that numerical approaches can provide relevant quantitative insights into the future trajectory of unemployment and have the potential to function as supportive instruments in labor policy formulation, provided they are applied cautiously and not used as the sole basis for decision-making. Keywords: Unemployment Rate; Extrapolation; Prediction; Python; Analysis.
Co-Authors Akhmad Ilhamzah Dian Savitri Rahmawati Erma Standsyah Rudh Renata