Zakky, Mokhammad (2017) Pemodelan Kualitas Tim Nasional Sepakbola Negara Anggota Asian Football Confederation (AFC) dengan Pendekatan Geographically Weighted Regression (GWR). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indonesia merupakan negara dengan jumlah penduduk terbesar keempat yang memiliki potensi di banyak bidang, termasuk sepakbola. Namun faktanya prestasi timnas Indonesia masih minim, meski ekspektasi masyarakat tinggi. Berdasarkan publikasi ranking FIFA bulan Mei 2017, Indonesia berada di peringkat 177 dari 206 negara. Dibanding negara anggota Asian Football Confederation (AFC), prestasi Indonesia tertinggal jauh. Penelitian ini dilakukan untuk mengetahui hubungan poin ranking FIFA dengan enam variabel prediktor. Metode yang digunakan adalah Geographically Weighted Regression (GWR) karena adanya faktor spasial yang mempengaruhi. Hasil analisis didapat bahwa negara dengan rata-rata poin FIFA tinggi berada di Asia Barat dan Timur, sedangkan yang terendah di Asia Selatan dan Tenggara. Pemodelan GWR menghasilkan estimasi parameter berbeda dimana terdapat enam kelompok dengan variabel signifikan yang berbeda. Dengan menggunakan kriteria AIC, didapat hasil model GWR lebih baik dibanding regresi linier.
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Indonesia is the fourth largest country based on total population. Indonesia have great potential in many fields, including football. But in fact, the achievement of Indonesian football national team is still minimal despite the high expectation. Based on latest publication of FIFA rankings, Indonesia is ranked 177th out of 206 countries. Compared to other national football team in Asian Football Confederation (AFC), Indonesia still far behind. This study was conducted to determine the relation of FIFA ranking points with six predictor variables. The method that used is Geographically Weighted Regression (GWR) because influence of spatial factors. Based on analysis, the result obtained that countries with high average FIFA ranking points come from West Asia and East Asia, while the lowest come from South Asia and Southeast Asia. Modeling of GWR gives different parametes estimates where there are six groups with different significant variables. By using AIC criteria, can be concluded that GWR model is better than the linear regression model.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.536 Zak p |
| Uncontrolled Keywords: | Asian Football Confederation, Geographically Weighted Regression, Ranking FIFA, Sepakbola. |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Mokhammad Zakky |
| Date Deposited: | 23 Oct 2017 07:39 |
| Last Modified: | 05 Mar 2019 08:29 |
| URI: | http://repository.its.ac.id/id/eprint/47898 |
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