Forecasting Humidity in Sragen Using Semiparametrik Regression Based on Penalized Fourier Series Estimator

DOI

10.2991/978-2-38476-428-0_3How to use a DOI?

Keywords

Semiparametric; Fourier Series Estimator; Relative Humidity; Penalized Least Square

Abstract

This study examines the use of a semiparametric regression model with a Penalized Least Squares (PLS)-based Fourier Series estimator to analyze the relationship between relative humidity and surface temperature in Sragen Regency. Combining parametric and nonparametric components, the model effectively addresses complex climate data patterns. A dataset of 100 observations was analyzed under three training data scenarios N = 70, N = 80, and N = 90, yielding optimal Fourier coefficients of 6, 1, and 1. The resulting Mean Absolute Percentage Error (MAPE) values were 1.496268, 1.58244, and 1.627225, with corresponding minimum Generalized Cross Validation (GCV) values of 0.3462398, 0.3863733, and 0.3866026. The model demonstrated its forecasting capability for the next 10 periods using test data sizes of N = 30, N = 20, and N = 10, achieving MAPE values of 1.526222, 1.354613, and 1.055469. These results underscore the model’s ability to capture the inverse relationship between humidity and temperature. The study highlights the Fourier-based semiparametric approach’s effectiveness in dynamic scenarios and recommends applying it to other climate variables or regions to further evaluate its adaptability and robustness.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ihsan Fathoni Amri
AU  - Ariska Fitriyana Ningrum
AU  - Alwan Fadlurohman
AU  - Saeful Amri
AU  - Dannu Purwanto
AU  - Yusrin Yusrin
PY  - 2025
DA  - 2025/05/31
TI  - Forecasting Humidity in Sragen Using Semiparametrik Regression Based on Penalized Fourier Series Estimator
BT  - Proceedings of the 3th Lawang Sewu International Symposium on Humanities and Social Sciences 2024 (LEWIS HUSO 2024)
PB  - Atlantis Press
SP  - 24
EP  - 38
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-428-0_3
DO  - 10.2991/978-2-38476-428-0_3
ID  - Amri2025
ER  -