Implementing Fuzzy C-Means Clustering with Java and Oracle

Name: Implementing Fuzzy C-Means Clustering with Java and Oracle
Brand: Independently Published
SKU: 9798258700131
Price: 2266.0 INR
Availability: InStock

by Eko Heryanto

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ISBN13: 9798258700131
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: April 24, 2026
Pages: 234
Original Price: GBP 20.05
Language: English
Edition: N/A
Item Weight: 318 grams
BISAC Subject(s): Software Development & Engineering / Quality Assurance & Testing

About The Book

Benchmarking, the process of establishing clear boundaries between points on the Jakarta Stock Exchange Composite Stock Price Index (JCI BEJ), is crucial for determining and identifying which index points fall into the high, low, or average groups. This is necessary as a standard for determining which index points fall into which group. Without benchmarking, problems arise due to varying human perceptions, which naturally differ in assessing index points (based on individual estimates), whether a particular index point falls into the high, low, or average category. There are no clear boundaries between index points.
Fuzzy C-Means, a method for clustering a data set into several groups by dividing the data evenly, is one method for benchmarking the JCI BEJ.
Fuzzy C-Means, which is based on fuzzy logic, groups data based on the distance between the centroid and the data. Each data point has a degree of membership within each cluster. The data with the highest degree of membership will become a member of the cluster for which that degree of membership is targeted.
This book implements Fuzzy C-Means Clustering, which benchmarks the 2005 Jakarta Composite Index (JCI), making it easier for users to perform historical technical data analysis.
From the results of trials on several types of Jakarta Composite Index (JCI), it was concluded that benchmarking can be performed on various types of Jakarta Composite Index (JCI), and that useful information can be obtained if the JCI pattern is analyzed more deeply and linked to time variables.We will use java and oracle to design this program.

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