Skripsi

KOMBINASI METODE CASE BASED REASONING (CBR) DAN PARTICLE SWARM OPTIMIZATION (PSO) UNTUK KLASIFIKASI PENYAKIT HEPATOCELLULAR CARSINOMA BERDASARKAN FAKTOR RISIKO

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Penilaian

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This research was developed to produce software to detect Hepatocellular Carcinoma disease using Case-Based Reasoning (CBR) and Particle Swarm Optimization (PSO). First, Case-Based Reasoning is applied to preprocess the data set, so that the weight vector for each attribute will be used in Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) is used for decision-making based on selected features and recognized diseases. This test is done by looking at iterations and particles. Based on the test, the highest accuracy is 76.96% using 100 iterations and 20 particles. It can be concluded from these results that the calculation of case-based reasoning and particle swarm optimization is said to be quite accurate in the early detection of disease.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002719	T51255	T512552021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T512552021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xvi, 104 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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