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Article . 2017 . Peer-reviewed
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MODEL PREDIKSI PENYAKIT GINJAL KRONIK MENGGUNAKAN RADIAL BASIS FUNCTION

Authors: Stefanus Santosa; Agus Widjanarko; Catur Supriyanto Supriyanto;

MODEL PREDIKSI PENYAKIT GINJAL KRONIK MENGGUNAKAN RADIAL BASIS FUNCTION

Abstract

Penyakit ginjal kronik adalah suatu sindrom klinis. Penyakit ini disebabkan oleh penurunan fungsi ginjal yang bersifat menahun, progresif, bersifat persisten, dan irreversibel. Diagnosa dini diperlukan agar penderitanya tidak mengalami infark ginjal atau kematian mendadak. Pencegahan dapat dilakukan melalui prediksi yang tepat. Penelitian Prediksi Penyakit Ginjal Kronik pada saat ini telah dilakukan oleh beberapa peneliti. Namun peningkatan akurasi diperlukan untuk menunjang tugas dan fungsi tenaga medis dalam menegakkan diagnosa. Saat ini tingkat akurasi model penelitian sebelumnya baru mencapai 91.71 %. Guna meningkatkan akurasi tersebut penelitian ini menggunakan pendekatan Radial Basis Function. Eksperimen dilakukan dengan parameter uji iterasi 500 - 10000 dan konstanta pembelajaran antara 0.15- 0.3. Dari uji coba tersebut didapatkan hasil yang lebih baik daripada penelitian sebelumnya, yakni sebesar 93.75% pada konstanta pembelajaran 0.2 dan iterasi 2000

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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