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OPTIMASI BOBOT ATRIBUT PADA ALGORITMA C4.5 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION UNTUK PREDIKSI GULA DARAH

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Penilaian

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Drastic increase of blood sugar level after consuming the certain food because food consumed contain an uncontrolled blood sugar tendence. Many hospital health institution, public health center and clinic which handle the DM patient, from those institution still not provide the data quickly and accurately. The effectively is needed in managing the information with data mining, from large data will generate a new data and provide the information quickly and accurately. In predicting the disease, a lot of the research has been done, the computer science field particularly, with data mining technique to predict the disease using various algorithm such a C45 algorithm. From the research which has been done using C45 algorithm and algorithm C45 with Particle Swarm Optimization (PSO) on set data the effect of physical activity to blood sugar levels in the RSUD H. Abdul Manan Simatupang Kisaran generated the different accuracy. The accuracy value on the tests performed with the C4.5 algorithm is 86%, whereas the accuracy value on the C4.5 algorithm with PSO 95%, so the value difference on its accuracy is 9%. Whereas the evaluation on the ROC curve shows the difference of 0.033.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2007000028	T38451	T384512020	Central Library (REFERENSI)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T384512020

Publisher

Inderalaya : Prodi Magister Ilmu Komputer, Universitas Sriwijaya., 2020

Collation

vii, 40 hlm.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Sistem Informasi Manajemen
Magister Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

NO

Other version/related

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