ANALISIS DATA MINING CUACA MENGGUNAKAN ATURAN ASOSIASI DAN REGRESI LOGISTIK KERNEL
Knowledge about patterns and relationships plays an important role in agriculture policy making. The level of rainfall is one of the factors affect the productivity of plants for food commodities. Association rules and kernel logistic regression (KLR) are data mining techniques to assist in making a...
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| Main Authors: | , |
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| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2013
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/126700/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=66929 |
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| Institution: | Universitas Gadjah Mada |
| Summary: | Knowledge about patterns and relationships plays an important role in agriculture
policy making. The level of rainfall is one of the factors affect the productivity of
plants for food commodities. Association rules and kernel logistic regression (KLR)
are data mining techniques to assist in making a decision. Model utilization depicts a
probability and finds the rules occur in large amounts of the data. The author conduct
a study of the data obtained from the Indonesian Meteorological, Climatological and
Geophysical - Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) and
Statistics Indonesia - Badan Pusat Statistik (BPS). This final project aims to give
conclusion that the kernel logistic regression |
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