Smooth Support Vector Machine (SSVM) for classification of Human Development Index

Human Development Index (HDI) is measuring achievements of human development based on basic components of quality of life. Human development index is low score if HDI is less than 60, moderate HDI between 60 to less than 70, high HDI between 70 to less than 80, and equal to 80 and more than 80 belon...

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Bibliographic Details
Published in:Journal of physics. Conference series 2019-05, Vol.1217 (1), p.12114
Main Authors: Darsyah, M Y, Suprayitno, I J, Fuzi, F, Otok, Bambang W, Ulama, B S S
Format: Article
Language:English
Subjects:
Algorithms
Classification
Human Development Index
Kernel functions
Physics
Polynomials
Radial basis function
Support vector machines
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Summary:Human Development Index (HDI) is measuring achievements of human development based on basic components of quality of life. Human development index is low score if HDI is less than 60, moderate HDI between 60 to less than 70, high HDI between 70 to less than 80, and equal to 80 and more than 80 belong to high HDI. Smooth Support Vector Machine (SSVM) is a classification technique that is new. The algorithm used is Newton Armijo with linear kernel, polynomial kernel, and Radial Basis Function (RBF) kernel. The result of classification of human development index with SSVM method with linear kernel shows the prediction accuracy 84.77%, polynomial kernel 61.65%, and RBF kernel 100%. Radial Base Function Kernel (RBF) is the most accurate kernel in predicting human development index.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1217/1/012114