Abstract
The region of Indonesia is very sparse and it has a variation condition in social, economic and culture, so the problem in education quality at many locations is an interesting topic to be studied. Database used in this research is Base Survey of National Education 2003, while a spatial data is presented by district coordinate as a least analysis unit. The aim of this research is to study and to applyspatial data mining to predict education quality at elementary and junior high schools using SARK riging method which combines an expansion SAR and Kriging method. Spatial data mining process has three stages. preprocessing, process of data mining, and post processing. For processing data and checking model, we built software application of Spatial Data Mining using SAR-Kriging method. An application is used to predict education quality at unsample locations at some cities at DIY Province. The result shows that SAR-Kriging method for some cities at DIY for elementary school has an average percentage error 6.43%. We can conclude that for elementary school, SAR-Kriging method can be used as a fitted model.
Keywords: Expansion SAR, SAR-Kriging, quality education
Pendahuluan
Pasial data mining merupakan penambangan pengetahuan dari data spasial dalam jumlah besar, merupakan bidang yang menarik untuk diteliti. Pengetahuan yang ditemukan dalam data spasial mempunyai berbagai bentuk, dapat didasarkan pada aturan pengelompokan atau diskriminan, ekstraksi dan deskripsi dari struktur cluster, asosiasi spasial, dan lain-lain. Metode spasial data mining dapat diterapkan dalam pemetaan mutu pendidikan, mengingat Indonesia memiliki sebaran lokasi yang luas, terdiri dari: provinsi, kabupaten /kota, kecamatan, dan desa.
Peneliti: A. Setiawan Abdullah dan R. Rosadi
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