DATA MINNING UNTUK ANALISA TINGKAT KESEMBUHAN PASIEN TUBERKULOSIS (TB)

Podo Wiseso1 Muhammad Reza Redo2*
(1) Fakultas Teknologi dan Bisnis, Universitas Dharma Wacana
(2) Politeknik Negeri Lampung
(*) Corresponding Author

Abstract

Penelitian ini memanfaatkan teknik data mining untuk menganalisis tingkat kesembuhan pasien tuberkulosis (TB) di Provinsi Lampung, Indonesia, dengan menggunakan data dari Sistem Informasi Tuberkulosis Komunitas (SITK) dan Row Data Individu (RDI). Tujuan utama adalah mengidentifikasi faktor risiko yang mempengaruhi penularan TB, termasuk karakteristik individu dan faktor lingkungan. Metode K-means clustering digunakan untuk mengelompokkan data berdasarkan gejala dan durasi pengobatan, menghasilkan 19 klaster dengan pola spesifik. Gejala seperti demam meriang, sesak napas, dan batuk ditemukan penting dalam menentukan tingkat kesembuhan pasien. Analisis menunjukkan variasi signifikan dalam distribusi gejala di antara klaster, dengan beberapa klaster menunjukkan respons pengobatan yang lebih baik. Penelitian ini diharapkan dapat berkontribusi dalam upaya pengendalian TB dan mencapai Tujuan Pembangunan Berkelanjutan (SDGs) terkait kesehatan

Keywords

Analisis Data; Clustering; K-means; RDI

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References

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DOI: https://doi.org/10.53514/ir.v8i2.590

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