Penerapan Metode Regresi Logistik Ordinal pada Pemodelan Faktor Risiko yang Mempengaruhi Stadium Kanker Serviks di RS Onkologi Surabaya

Permata, Sheryn Dian (2020) Penerapan Metode Regresi Logistik Ordinal pada Pemodelan Faktor Risiko yang Mempengaruhi Stadium Kanker Serviks di RS Onkologi Surabaya. Other thesis, Institut Teknologi Sepuluh Nopember.

[thumbnail of 06211640000083-Undergraduate_Thesis.pdf]
Preview
Text
06211640000083-Undergraduate_Thesis.pdf

Download (1MB) | Preview

Abstract

Kanker serviks menduduki peringkat keempat di dunia sebagai jenis kanker yang paling sering menyerang wanita. Menurut Depkes RI, jumlah wanita penderita baru kanker serviks diperkirakan sekitar 90-100 kasus per-100.000 penduduk. Peningkatan upaya pencegahan dan deteksi dini sangat diperlukan oleh setiap pihak yang terlibat. Oleh sebab itu, penelitian yang menggunakan metode regresi logistik ordinal ini dilakukan untuk mengetahui faktor risiko yang mempengaruhi stadium kanker serviks, sehingga diharapkan mampu meningkatkan kesadaran tentang bahaya penyakit tersebut dan mendorong timbulnya tindakan preventif. Data yang digunakan adalah data sekunder yang diperoleh dari RS Onkologi Surabaya berupa data rekam medis yang tercatat mulai tanggal 1 Januari 2008 hingga 31 Januari 2016 dengan jumlah pasien sebanyak 140 orang. Hasil analisis menunjukkan bahwa Pasien kanker serviks yang melakukan pengobatan di RSOS terbanyak merupakan pasien yang didiagnosis stadium II yakni sebanyak 47 orang, pasien stadium III yaitu 45 orang, pasien stadium ≤ I sejumlah 30 orang, dan pasien stadium IV yakni sebanyak 18 orang. Lebih dari separuh pasien kanker serviks berusia antara 46-65 tahun. Mayoritas pasien memiliki status sudah menikah dengan persentase sebesar 97,1%. Pasien yang telah mengalami menopause (post-menopause) sebanyak 47,9%. Terdapat sebanyak 30% pasien pernah mengalami keguguran dan 19,3% memiliki riwayat kanker dalam keluarga. Rata-rata lama menderita pasien kanker serviks di RS Onkologi Surabaya adalah 5,26 bulan. Faktor risiko yang berpengaruh signifikan terhadap stadium kanker serviks adalah usia, status pernikahan, status menopause, dan lama menderita pasien.
====================================================================================================================
Cervical cancer is the fourth most frequent type of cancer in women. According to the Indonesian Ministry of Health, the number of women with new cases of cervical cancer is estimated at around 90-100 cases per 100,000 population. The increasing of efforts on prevention and early detection are important and needed to do by all people involved. Therefore, this research using ordinal logistic regression method was conducted to find out the risk factors that affect the stage of cervical cancer, and expected to be able to increase awareness about the dangers of this cancer as well as encourage the emergence of preventive steps. The data used were secondary data obtained from RS Onkologi Surabaya in the form of medical record that observed on 1 January 2008 up to 31 January 2016 containing 140 patients. The results of the analysis showed that most cervical cancer patients treated in RSOS were diagnosed with stage II there were 47 people, 45 patients with stage III, 30 patients with stage ≤ I, and 18 patients with stage IV . More than half of the patients were aged between 46-65 years old. The majority had married status with a percentage of 97.1%. About 47.9% patients went through menopause (post-menopause). There were 30% patients had experienced miscarriage and 19.3% had a family history of cancer. The average time of suffering from cervical cancer was 5.26 months. The risk factors that had a significant effect on cervical cancer stage were age, marital status, menopausal status, and duration of suffering from cervical cancer.

Item Type: Thesis (Other)
Uncontrolled Keywords: Faktor Risiko, Kanker Serviks, Regresi Logistik Ordinal, Stadium, Cervical Cancer, Ordinal Logistic Regression, Risk Factors, Stage
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HA Statistics > HA31.3 Regression. Correlation
Divisions: Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Sheryn Dian Permata
Date Deposited: 26 Aug 2020 02:55
Last Modified: 03 Jan 2024 08:02
URI: http://repository.its.ac.id/id/eprint/81274

Actions (login required)

View Item View Item