CD Skripsi

Analisis Penyakit Gangguan Kejiwaan Menggunakan Algoritma K-Means Clustering Pra Dan Pasca Pandemi Covid-19

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ABSTRACT
Psychiatric disorders are psychological diseases that occur in the human brain that
are not normal with various causes but are predominantly caused by great stress.
Turning to the global crisis caused by a virus (Covid-19), this virus has triggered
an increase in psychiatric disorders. Many studies have described that the Covid-
19 pandemic has affected the nervous system and psychiatric disorders, so mental
health is included in planning for dealing with a pandemic. Based on data from the
WHO survey results, it was found that the data pattern changed drastically. This
study aims to determine changes in data patterns of patients with psychiatric
disorders before and after the Covid-19 pandemic who were handled from January
2019 to February 2021 at Engku Haji Daud Hospital, Riau Islands Province, and
measure the accuracy of the method used. This study uses the K-Means Clustering
algorithm method to cluster data and uses the Silhoutte Coefficient to see how well
the quality of a cluster is produced. The stages in this research are data collection,
data pre-processing, clustering process, Silhoutte Coefficient Process, and result
Analisis. Based on this research, the graph of the experimental results of all prepandemic
Covid-19 data obtained the highest value at k5 with a Silhoutte
Coefficient value of 0.547. Meanwhile, in the post-pandemic Covid-19 data, the
highest value is k2 with a Silhoutte Coefficient value of 0.385. Based on the prepandemic
covid-19 clustering structure criteria, each experiment differs from one
another, while the post-pandemic conditions of the covid-19 structure criteria are
the same.
Keywords: Mental Disorders, Pre and Post Covid-19 Pandemic, K-Means
Clustering, Silhoutte Coefficient

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1703113910

Penerbit

Pekanbaru : Universitas Riau - FMIPA -SISTEM INFORMASI., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1703113910

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

tethi

Versi lain/terkait

Lampiran Berkas

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