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ANALISIS PENGELOMPOKAN DATA PERILAKU CYCLIC VOLTAMMETRY PADA SUPERKAPASITOR BERBASIS GRAPHENE OKSIDA MENGGUNAKAN ALGORITMA K-MEANS

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Penilaian

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The need for renewable energy is a pressure to develop further developments in overcoming the problem of depleting fossil fuel energy. There are an pressure to do some research on renewable energy or energy storage technologies. This research proposes a computational approach with unsupervised learning method in investigating cyclic voltammetry behavior using K-Means Clustering algorithm. This study applies the elbow method, silhouette coefficient, and Davies Bouldin Index in determining the optimal number of clusters in the data. As a result, the silhouette coefficient shows a better performance than the elbow method in determining the optimal cluster in the data and the application of the optimal cluster on the data is able to show the visualization of cyclic voltammetry behavior through descriptive analysis.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207003564	T78350	T783502022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T783502022

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

vi, 72 hlm.: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Pengolahan Data
Jurusan Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

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