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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Alfi, Ahmad Haikal
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Decision Sciences, Operations Research & Management

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THYROID DISEASE CLASSIFICATION ANALYSIS USING XGBOOST MULTICLASS panjaitan, haris samuel pranada; Gulo, Agustinus; Alfi, Ahmad Haikal; Harmaja, Okta Jaya; Indra, Evta
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 6 No. 1 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2831

Abstract

ABSTRAK- Sickness is an unusual condition of the body or mind that causes discomfort, malfunction, or suffering to the sick person. One disorder that occurs due to a lack of health concerns is thyroid disease. The thyroid is a butterfly-shaped endocrine gland near the neck's bottom. The diagnosis of thyroid disease is complicated because the symptoms of thyroid disease can fluctuate based on the rise and fall of thyroid hormones, which increase the utilization of oxygen by the body's cells. In this case, a thyroid examination by a doctor and proper interpretation of clinical data is required to identify thyroid disease. However, the limitations of a doctor due to age and time constraints lead to a lack of interpretation of patient clinical data. Therefore, a study was conducted on the analysis of thyroid disease classification to simplify and speed up the process of diagnosing thyroid disease using the Xgboost Multiclass method, which is expected to get an accuracy value above 90%. Keywords: Classification, Thyroid, Xgboost Multiclass, Machine Learning
Co-Authors Gulo, Agustinus Indra, Evta Okta Jaya Harmaja panjaitan, haris samuel pranada