PENGARUH FAKTOR SOSIODEMOGRAFI, KARAKTERISTIK FISIK WILAYAH DAN UPAYA PELAYANAN KESEHATAN TERHADAP PENYAKIT MALARIA DI KABUPATEN PESAWARAN PROVINSI LAMPUNG

Firman, 1820011003 (2021) PENGARUH FAKTOR SOSIODEMOGRAFI, KARAKTERISTIK FISIK WILAYAH DAN UPAYA PELAYANAN KESEHATAN TERHADAP PENYAKIT MALARIA DI KABUPATEN PESAWARAN PROVINSI LAMPUNG. Other thesis, UNIVERITAS LAMPUNG.

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Abstrak (Berisi Bastraknya saja, Judul dan Nama Tidak Boleh di Masukan)

Malaria merupakan salah satu penyakit menular yang masih menjadi masalah kesehatan. Tahun 2020 dilaporkan bahwa kasus malaria di dunia sepanjang tahun 2019 sebanyak 229 juta kasus dengan kematian 409 ribu orang meninggal dunia karena malaria terutama anak Balita. Penyakit malaria tahun 2019 di Indonesia sebanyak 250.644 kasus, di Provinsi Lampung 1.521 kasus dan di Kabupaten Pesawaran 888 kasus dengan dengan beberapa kali terjadi kejadian luar biasa (KLB). Terjadinya kasus malaria dipengaruhi oleh banyak faktor diantaranya adalah sosiodemografi, karakteristik fisik wilayah dan upaya pelayanan kesehatan. Penelitian ini bertujuan untuk menentukan pengaruh sosiodemografi, karakteristik fisik wilayah dan upaya pelayanan kesehatan serta menyusun rekomendasi dalam upaya pengendalian malaria berbasis model prediksi di Kabupaten Pesawaran. Penelitian ini adalah penelitian observasional dengan desain penelitian potong lintang (cross sectional). Sampel sebanyak 436 orang dengan teknik pengumpulan data menggunakan data sekunder yang bersumber dari e-sismal dan register laboratorium Puskesmas sedangkan pengambilan data primer dengan panduan kuesioner untuk mengukur variabel penelitian termasuk koordinat tempat tinggal. Penelitian ini menggunakan pendekatan hubungan kausal antara variabel (Y) dan variabel (X). Model dipilih adalah regresi logistik dengan variabel respon menggunakan skala biner, yaitu malaria versus tidak malaria. Didapatkan model Ln (p[Malaria]=1]) (1−p[Malaria=1]) = 1.14306 – 0.0202340 [UMR] + 1.27568 [JKEL] – 0.527641 [D1_NLYN/PTMB] - 0.563427 [D1_PTNI/BRKBN] – 0.788517 [D1_PDGG/WRST] – 1.14061 [D1_TPAKP] + 0.627210 [D2_SMP] + 1.61759 [D2_SMA] + 2.46045 [D2_PT] + 4.25364 [KRMH] - 4.97580 [MOAN] + 0.0260722 [KTD] + 4.57420 [D3_JTV5] + 0.883319 [D3JTV10] + 2.11497 [D3_JTV20 + 2.87183 [D4_LGN] – 2.09404 [D4_RWA] + 0.154395 [D4_TMBT] – 1.114470 [D4_SBTR] + 3.06017 [D4_SLIG] – 1.28773 [D4_KLGL] - 1.83076 [D5_LVCD] - 2.12563 [D5_PLMT] – 2.70970 [D6_LLINs] - 2.67014 [D6_IRS] – 3.22031 [MBS] Kata kunci : malaria, sosiodemografi, karakteristik fisik wilayah, upaya pelayanan kesehatan. Malaria still remains as a public health concern in the world including in Indonesia. World Health Organization (WHO) estimated 229 million cases of malaria reported in 2019. Malaria is also known as one of infectious diseases with significant fatality. Malaria has caused 409,000 deaths occurred in 2019. Under-five children were identified as the most vulnerable groups in term of death’s occurrence. It was estimated that 67% of all malaria deaths alleged with children in the age group. In Indonesia, there were 250.664 malaria cases reported in 2019. Particularly in Lampung Province, the public health report showed that there were 1.521 cases of malaria. Pesawaran is one of endemic areas in Lampung Provinces with high occurrences of malaria. There were 888 cases reported and it was identified that malaria outbreaks occurred several times in Puskesmas ‘s Area. There are several factors related to malaria occurrences, including sociodemographic factors, physical area characteristic, and health service interventions. This study is aimed to identify the relationship of those factors to malaria occurrences especially in Pesawaran District. In addition, findings of the study will be able to contribute the development of malaria controls program based on prediction models in Pesawaran District. This is an observational study with cross-sectional study design. Primary and secondary data were collected throughout the study. Standard questionnaires were used to collect primary data in order to identify study variables including the domicile coordinate of the study population. Additionally, there were 436 samples collected from secondary data. The data were taken from e-sismal application and Puskesmas laboratory’s registers. The study applied variable (Y) and variable (X) causal model with logistic regression model using binary scales, malaria versus non-malaria. Get Ln (p[Malaria]=1]) (1−p[Malaria=1]) = 1.14306 – 0.0202340 [UMR] + 1.27568 [JKEL] – 0.527641 [D1_NLYN/PTMB] - 0.563427 [D1_PTNI/BRKBN] – 0.788517 [D1_PDGG/WRST] – 1.14061 [D1_TPAKP] + 0.627210 [D2_SMP] + 1.61759 [D2_SMA] + 2.46045 [D2_PT] + 4.25364 [KRMH] - 4.97580 [MOAN] + 0.0260722 [KTD] + 4.57420 [D3_JTV5] + 0.883319 [D3JTV10] + 2.11497 [D3_JTV20 + 2.87183 [D4_LGN] – 2.09404 [D4_RWA] + 0.154395 [D4_TMBT] – 1.114470 [D4_SBTR] + 3.06017 [D4_SLIG] – 1.28773 [D4_KLGL] - 1.83076 [D5_LVCD] - 2.12563 [D5_PLMT] – 2.70970 [D6_LLINs] - 2.67014 [D6_IRS] – 3.22031 [MBS] Keyword: malaria, sociodemographic, physical area characteristic, health service intervensions

Jenis Karya Akhir: Tesis (Other)
Subyek: 600 Teknologi (ilmu terapan) > 630 Pertanian dan teknologi yang berkaitan
Program Studi: Fakultas Pertanian dan Pascasarjana > Prodi Magister Ilmu Lingkungan
Pengguna Deposit: UPT . Meda Sulistiana
Date Deposited: 31 May 2022 02:19
Terakhir diubah: 31 May 2022 02:19
URI: http://digilib.unila.ac.id/id/eprint/62206

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