KOREKSI BIAS STATISTICAL DOWNSCALING DENGAN PENDEKATAN REGRESI NON PARAMETRIK DERET FOURIER (Studi Kasus: Proyeksi Tingkat Kenyamanan Indonesia di bawah Skenario Perubahan Iklim)

ASRORI, GUFRON HAMDANI (2023) KOREKSI BIAS STATISTICAL DOWNSCALING DENGAN PENDEKATAN REGRESI NON PARAMETRIK DERET FOURIER (Studi Kasus: Proyeksi Tingkat Kenyamanan Indonesia di bawah Skenario Perubahan Iklim). Sarjana / Sarjana Terapan (S1/D4) thesis, Universitas Muhammadiyah Semarang.

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Abstract

ABSTRAK Hamdani, Asrori Gufron. 2022.Koreksi Bias Statistical Downscaling dengan Pendekatan Regresi Non Parametrik Deret Fourier. Skripsi, Program Studi Statistika. Universitas Muhammadiyah Semarang. Pembimbing: I. Tiani Wahyu Utami, S.Si.,M.Si.,II. Fatkhurokhman Fauzi,S.Si.,M.Stat. Kata Kunci : Deret Fourier, Earth System Models (ESMs), Regresi Nonparametrik, Statistical Downscaling, Temperature Hummadity Index (THI) Earth System Models (ESM) adalah model yang dapat mensimulasikan, memprediksi perubahan iklim yang terjadi di masa lalu, sekarang, dan membuat skenario perubahan iklim di masa depan. Luaran ESM belum mampu mewakili iklim skala lokal..Salah satu upaya untuk mengatasi masalah tersebut adalah Teknik Statistical Downscaling (SD). Berbagai teknik Statistical Downscaling (SD) telah digunakan dalam kajian iklim di negara-negara lintang tinggi, sedangkan di wilayah lintang rendah (Tropik, seperti Indonesia) masih sangat terbatas. Hasil SD masih memiliki bias yang cukup besar, dibutuhkan suatu metode yang berfungsi untuk mengurangi bias. Metode koreksi bias yang digunakan dalam penelitian ini adalah Regresi Nonparametrik Deret Fourier. Penelitian ini menurunkan skala (downscale) dan koreksi bias pada data Relative Hummadity dan Temperature luaran ESM skenario RCP 4.5. Hasil analisis yang bisa dijelaskan oleh SD adalah data dependen Merra-2 (lokal) mempengaruhi proses penurunan skala downscaling terhadap RCP 4.5 dengan grafik yang bergerak mendekati data Merra-2. Hasil dari koreksi bias menggunakan metode Regresi Nonparametrik Deret Fourier pada penelitian ini untuk Relative Hummadity menghasilkan sebesar 97% dengan MSE 0,3223 dan pada Temperature menghasilkan 98% dan MSE 0,0290 sehingga model yang didapatkan sederhana. Untuk Temperature Hummadity Index (THI) di Indonesia dalam kategori comfortable (nyaman) terjadi pada tahun 2006-2057.   ABSTRACT Hamdani, Asrori Gufron. 2022. Downscaling Statistical Bias Correction with Fourier Series Non-Parametric Regression Approach. Thesis . Statistics Study Program. Muhammadiyah University of Semarang . Supervisor: 1.Tiani Wahyu Utami, S.Si, II. Fatkhurokhman Fauzi,S.Si.,M.Stat. Earth System Models (ESM) are models that can simulate, predict climate changes that have occurred in the past, present, and create future climate change scenarios. The output of ESM has not been able to represent the local scale climate. One of the efforts to overcome this problem is the Statistical Downscaling Technique (SD). Various Statistical Downscaling (SD) techniques have been used in climate studies in high-latitude countries, while those in low-latitude regions (the Tropics, such as Indonesia) are still very limited. SD results still have a large enough bias, we need a method that functions to reduce bias. The bias correction method used in this study is Fourier Series Nonparametric Regression. This study downscales and corrects the bias of the Relative Hummadity and Temperature data for the ESM RCP 4.5 scenario. The results of the analysis that can be explained by SD are Merra-2 (local) dependent data influencing the downscaling process of RCP 4.5 with a graph that moves closer to Merra-2 data. The results of the bias correction using the Fourier Series Nonparametric Regression method in this study for Relative Hummadity yielded 97% with MSE 0.3223 and for Temperature yielded 98% and MSE 0.0290 so that the model obtained was simple. For the Temperature Hummadity Index (THI) in Indonesia in the comfortable category, it occurred in 2006-2057. Keywords: Earth System Models (ESMs), Fourier Series, Nonparametric Regression, Statistical Downscaling, Temperature Hummadity Index (THI)

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