CD Skripsi

Penerapan Fuzzy K-Nearest Neighbor Untuk Klasifikasi Pengangguran Terhadap Penduduk Kota Batam

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ABSTRACT
The increasing population of Indonesia may cause unemployment problems.
Unemployment may occur due to an imbalance in the number of workers with the
number of jobs. Based on data from Statistics Agency, one of the cities facing the
problem of unemployment in Indonesia is Batam, which is located in the Riau
Islands Province. Batam has the highest unemployment rate in the Riau Islands,
which is 11,79%. This study aims to classify unemployment of Batam residents
using the Fuzzy K-Nearest Neighbor (Fuzzy K-NN) method. This method is data
mining analysis that determine class label based on the class that has maximum
membership value. The data used is the result of the Batam labor force survey
(Sakernas) in August 2020. From the total data of Sakernas, composition of
training data and test data is 70% and 30%. Based on the results of the Fuzzy KNN
classification, obtained the highest accuracy by 82.93% on the test of K, that
is when K = 500, with sensitivity by 11,11% and specificity by 92,23% and m
used is 2.
Keywords: Classification, data mining, fuzzy k-nearest neighbor, sakernas,
unemployment.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1803113091

Penerbit

Pekanbaru : Universitas Riau – FMIPA – STATISTIKA Universitas Riau – FMIPA – STATISTIKA., 2022

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1803113091

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Deti

Versi lain/terkait

Lampiran Berkas

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