Claim Missing Document
Check
Articles

Found 2 Documents
Search

PEMODELAN STATISTICAL DOWNSCALING REGRESI KUANTIL LASSO DAN ANALISIS KOMPONEN UTAMA UNTUK PENDUGAAN CURAH HUJAN EKSTRIM Santri, Dewi; Hanike, Yusrianti
MAp (Mathematics and Applications) Journal Vol 2, No 1 (2020)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1152.01 KB) | DOI: 10.15548/map.v2i1.1639

Abstract

Curah hujan ekstrim yang sering terjadi di Indonesia menimbulkan berbagai dampak negatif bagi masyarakat. Terdapat banyak pemodelan curah hujan yang telah dilakukan untuk meminimumkan dampak yang terjadi. Global circulation model (GCM) diyakini menjadi metode terbaik untuk meramalkan data curah hujan ekstrim. Kelemahan dari data GCM adalah masih bersifat global sehingga akan sulit untuk menjelaskan keragaman dalam skala lokal yang lebih rinci. Statistical Downscaling (SD) hadir untuk menangani permasalahan tersebut. SD menghubungkan antara data luaran GCM dan curah hujan untuk menduga perubahan pada skala lokal dengan menggunakan metode regresi. Untuk mengakap nilai ekstrim dari curah hujan maka digunakan metode regresi kuantil. Data luaran GCM yang memiliki multikolinearitas tidak dapat langsung diterapkan dalam model SD. Metode-metode yang dapat digunakan untuk mengatasi masalah multikolinearitas dalam SD antara lain metode analisis komponen utama (AKU) dan metode shrinkage seperti Least Absolute Shrinkage and Selection Operator (LASSO). Metode AKU paling sering digunakan dalam mereduksi dimensi data luaran GCM dan menangani masalah multikolinearitas. Metode shringkage selain dapat menghilangkan multikolinearitas juga dapat meminimumkan ragam penduga parameter dari model regresi. Tujuan penelitian ini adalah  menentukan model curah hujan ekstrim di Kabupaten Indramayu dengan pendekatan SD menggunakan metode regresi kuantil dengan LASSO dan AKU serta memilih model SD terbaik dari kedua metode yang digunakan tersebut. Hasil penelitian menunjukkan bahwa dugaan curah hujan ekstrim di kabupaten Indramayu dengan model SD menggunakan regresi kuantil dengan LASSO menghasilkan prediksi yang lebih konsisten terhadap berbagai selang waktu dugaan dibandingkan model yang menggunakan metode AKU.AbstractExtreme rainfall that frequently occurs in Indonesia has negative impact to society. there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. GCM data has global scale and unable to provide reliable information at local scale. Statistical Downscaling (SD) has been developed in an attempt to bridge this scale gap. SD uses regression models to represent the link between GCM data and local rainfall. Quantile regression is used to catch the extreme rainfall.  GCM data which has multicolinearity can not be directly applied in SD model. The methods that can be used to overcome multicollinearity are principal component analysis (PCA) and shrinkage methods such as Least Absolute Shrinkage and Selection Operator (LASSO) and ridge. PCA is the most commonly used in SD modeling. PCA can reduce the dimension of GCM data and multicollinearity. Shringkage method can eliminate multicolinearity and minimize variance. The objectives of this study are modeling SD using quantile regression with LASSO and PCA to predict extreme rainfall in Indramayu and to choose the best SD model of  both methods. The result shows that the prediction of extreme rainfall in Indramayu with SD models using quantile regression with LASSO is more consistent at any time prediction compared to models using PCA.
Teachers’ Perception and Practices of Intercultural Communicative Competence Integration in EFL Classroom: A Systematic Literature Review Nafisah, Shofia; Oktarina, Ika; Santri, Dewi; Suwartono, Tono
Educalitra: English Education, Linguistics, and Literature Journal Vol. 3 No. 1 (2024)
Publisher : English Language Education Study Program, Faculty of Social, Economics, and Humanities, University of Nahdlatul Ulama Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10596576

Abstract

Intercultural communicative competence stands as a cornerstone in modern English as a Foreign Language education, playing a pivotal role in nurturing learners' abilities to navigate diverse cultural landscapes. This systematic review meticulously examines the perspectives and practices of EFL educators in integrating intercultural communicative competence into language teaching, drawing insights from a comprehensive analysis of diverse studies across global contexts, the systematic review methodology of Gough and Newman’s way employed. The findings underscore a discrepancy between teachers' positive perceptions and practices in integrating intercultural communicative competence into the EFL classroom. Besides, the researchers highlight the responsibility of educators in fostering inclusive learning environments that empower learners with the indispensable skills for successful cross-cultural communication in an interconnected world.