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

Br. TARIGAN, DWI MEYLITASARI and Rini, Dian Palupi and Samsuryadi, Samsuryadi (2020) OPTIMASI BOBOT ATRIBUT PADA ALGORITMA C4.5 MENGGUNAKAN PARTICLE SWARM OPTIMIZATION UNTUK PREDIKSI GULA DARAH. Master thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Master)
Uncontrolled Keywords:	Data Mining, Mechine Learning
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Users 9209 not found.
Date Deposited:	08 Dec 2020 07:35
Last Modified:	08 Dec 2020 07:35
URI:	http://repository.unsri.ac.id/id/eprint/38451

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