APLIKASI METODE ARIMA BOX-JENKINS UNTUK MERAMALKAN KASUS DBD DI PROVINSI JAWA TIMUR

Muhammad Bintang Pamungkas, Arief Wibowo

= http://dx.doi.org/10.20473/ijph.v13i2.2018.183-196
Abstract views = 534 times | views = 586 times

Abstract


The Box-Jenkins forecasting method is one of the time series forecasting methods. This method uses past values as dependent variables and independent variables are ignored. Box-Jenkins (ARIMA) method has advantages that can be used on non-stationary data, can be used on all data patterns including seasonal data patterns so this method can be used to predict cases of DHF in East Java Province. This research was conducted to determine the best model with seasonal ARIMA forecasting model and also to analyze the result of DHF case forecasting in East Java Province. The analysis result shows that the best model for DHF case in East Java Province is ARIMA (1,1,2)(2,1,1)12. The best model has fulfilled the test requirement that is parameter significance test and diagnostics check. Forecasting results show the number of DHF cases in 2017-2018 will experience an upward trend. The total number of DHF cases in 2017 was 14,277 cases and increased to 22,284.54 DHF cases in 2018. The forecasting results showed that the highest peak of DHF cases occurred in January 2017 with 1,914.22 cases and then decrease in the next month until the lowest case occurred in October with 768.46. The forecast for 2018 also shows that the highest DHF cases occurred in January with 3455.55 and declined to the lowest in October with 1126.49 cases. MAPE value in the forecast is 43.51%. The MAPE value indicates that the forecasting is good enough, adequate and feasible to use.

Keywords


ARIMA, time series, seasonal, DHF case

Full Text:

PDF

References


Aritonang, L. 2009. Peramalan Bisnis. Jakarta : Ghalia Indonesia.

Ardini, S.R., Nita, A., Fedri, R. 2015. Dampak Perubahan Iklim Terhadap Kejadian Demam Berdarah Di Jawa Barat. Jurnal Ilmu Kesehatan Masyarakat. Jawa Barat: Universitas Padjajaran. Vol 1: 43-47.

Baroroh, N. 2013. Analisis Pengaruh Modal Intelektual terhadap Kinerja keuangan Perusahaan Manufaktur di Indonesia. Jurnal Dinamika Akutansi. Vol 5(2): 173-182.

Fathi, Keman, S., Wahyuni, C.U. 2005. Peran Faktor Lingkungan dan Perilaku terhadap Penularan Demam Berdarah Dengue di Mataram. Jurnal Kesehatan Lingkungan. Vol 2(1): 1-10.

Halide, Halmar, Rais dan P. Ridd. 2011. Early Warning System for Dengue Hemorrhagic Fever (DHF) Epidemics in Makassar. Jurnal Matematika Dan Sains. Juli 2011.Vol 16 No 2.

Iriani, Y. 2012. Hubungan antara Curah Hujan dan Peningkatan Kasus Demam Berdarah Dengue Anak di Kota Palembang. Jurnal Sari Pediatri. Vol 13(6): 378-383.

Kemenkes RI. 2010. Buletin Jendela Epidemiologi. Pusat Data dan Surveilans Epidemiologi Kementerian Kesehatan RI

Kemenkes RI. 2015. Pedoman Pengendalian Deman Berdarah Dengue Di Indonesia. Jakarta :Kementerian Kesehatan RI.

Luluk N.K. 2016. Aplikasi ARIMA Untuk Meramalkan Jumlah DBD Di Pusksmas Mulyorejo. Jurnal Biometrika dan Kependudukan. Surabaya: Universitas Airlangga. Vol 5(2): 177-186.

Makridakis, S., Wheelwright, S.C., Victor, E.M. 1999. Metode dan Aplikasi Peramalan, second edition. Erlangga: Jakarta.

Margaretha, M.S. 2007. Pengaruh Iklim Terhadap Kasus Demam Berdarah Dengue. Jurnal Kesehatan Masyarakat. Jakarta: Universitas Trisaksi. Vol 2(1): 11-18.

Mustazahid, A.W. 2013. Hubungan Kejadian Deman Berdarah Dengan Iklim di Kota Semarang Tahun 2006-2011. Unnes Journal of Public Health. ISNN 2252-6528.

Perwitasari, D., Yusniar, A. 2015. Model Prediksi Demam Berdarah Dengue dengan Kondisi Iklim di Kota Yogyakarta. Jakarta: Pusat Teknologi Intervensi Kesehatan Masyarakat.

Dinkes Provinsi Jawa Timur. 2016. Profil Kesehatan Jawa Timur. Surabaya. 2015

Rais. 2009. Pemodelan Data Time Series dengan Metode Box-Jenkins. JIMT. Jurnal Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam. Tadulako: Universitas Tadulako. Vol. 6 (1), pp. 1-10.

Sitorus, J. 2003. Hubungan Iklim dengan Kasus Penyakit Demam Berdarah Dengue di Kotamadya Jakarta Timur Tahun 1998-2002. Tesis. Universitas Indonesia.

Srikiatkhachorn A. 2010. Dengue Hemorrhagic Fever: The Sensitivity and Sensitivity of the WHO Definition for Identification of Severe Cases of Dengue in Thailand, 1994-2005. Clinical Infectious Diseases. 50:1135-1143.

Sulasmi, S. 2013. Kejadian Deman Berdarah Dengue Kabupaten Banjar Berdasarkan Data Curah Hujan Normal Bulanan. Jurnal Epidemiologi dan Penyakit Bersumber Binatang. Vol 4 (4): 171-174.

Sukowati S., Achmadi U.F., dan Sudjana P. 2010. Demam Berdarah Dengue. Buletin Jendela Epidemiologi. Vol 2(1): 20−26.

Tantawichien, T. 2012. Dengue Fever and Dengue Haemorrhagic Fever in adolescents and adults. Paediatrics and International Child Health .Vol 32 :22-27.

Wahyono T., Haryanto., Budi., Mulyono., Sigit., Adiwibowo.,Andrio. 2010. Faktor-faktor Yang Berhubungan Dengan Kejadian Demam Berdarah dan Penanggulanganya di Kecamatan Cimanggis, Depok, Jawa Barat. Buletin Jendela Epidemiologi. Vol 2.

Wei, W.S. 1994. Time Series Analysis: Univariate and Multivariate Method. Addison Wesley Publishing Company. New York.

Yulianti, F. 2012. Modelling dan Forecasting Tingkat Produksi Gas di Indonesia Menggunakan Metode ARIMA. Skripsi. Depok: Fakultas Teknik Program Sarjana Teknik Industri Universitas Indonesia.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2018 The Indonesian Journal of Public Health

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

INDEXING BY:

   

View My Stats