Prediction of The Number of Pulmonary Tuberculosis Disease Using The Moving Average Forecasting Method And Time Series Decomposition

  • Dicky Novanda Universitas Merdeka Malang
  • Rahmatina Hidayati Universitas Merdeka Malang
Abstract views: 139 , PDF downloads: 105
Keywords: Tuberculosis, Forecasting, Moving Average, Multiplicative Decomposition, Additive Decomposition

Abstract

Abstract: Indonesia is the third country with the largest number of deaths due to pulmonary tuberculosis infection. In order to suppress the spread of tuberculosis in Indonesia, in 2021 the government launched a tuberculosis control program which aims to prevent and reduce the spread. One effort to assess whether the program that has been implemented is operating well or not is to forecast the incidence of pulmonary tuberculosis. This research aims to predict the incidence of pulmonary tuberculosis to provide useful information for health workers and related parties in efforts to prevent and control pulmonary tuberculosis at Hospital X, Malang City in 2024. The method that will be used to predict the number of tuberculosis sufferers is a moving average. and time series decomposition. The multipicative decomposition method produces the smallest MAPE, namely 15.37%, which is in the good category compared to additive and moving average decomposition. In 2022 and 2023 there will be a significant spike in pulmonary tuberculosis cases at Hospital X Malang City and men have a higher risk factor than women. Most cases of pulmonary tuberculosis infection occur in the elderly (46-65 years) and adults (26-45 years) age groups.

Downloads

Download data is not yet available.

References

[1] N. Husna Muchtar, D. Herman and Yulistini, (2018), "Gambaran Faktor Risiko Timbulnya Tuberkulosis Paru pada Pasien yang Berkunjung ke Unit DOTS RSUP Dr. M. Djamil Padang Tahun 2015," Jurnal Kesehatan Andalas, vol. 7, no. 1, pp. 80-86.
[2] S. Andayani, (2020), "Rediksi Kejadian Penyakit Tuberkulosis Paru Berdasarkan Jenis Kelamin," Jurnal Keperawatan Muhammadiyah Bengkulu, vol. 8, no. 2, pp. 135-140.
[3] T. Maretanata Pujianti, D. Damayant and F. Erawantini, (2014), "Perencanaan Kebutuhan Tempat Tidur Di Rumah Sakit Paru Jember Tahun 2013-2015," Jurnal Manajemen Informasi Kesehatan Indonesia, vol. 2, no. 1, pp. 61-67.
[4] H. A. Susanto, A. Sakka and L. Tina, (2016), "Prediksi Kejadian Penyakit Tb Paru Bta Positif Di Kota Kendari Tahun 2016-2020," JIM Kesmas: Jurnal Ilmiah Mahasiswa Kesehatan Masyarakat, vol. 1, no. 2, pp. 1-13.
[5] R. Rachman, (2018), "Penerapan Metode Smoothing pada Peramalan Produksi Industri Garment," Jurnal Informatika, vol. 5, no. 1, pp. 211-220.
[6] S. Yuni, M. W. Talakua and Y. A. Lesnussa, (2015), "Peramalan Jumlah Pengunjung Perpustakaan Universitas Pattimura Ambon Menggunakan Metode Dekomposisi," Barekeng: Jurnal Ilmu Matematika dan Terapan, vol. 9, no. 1, pp. 41 - 50.
[7] M. Agustina Making, Y. Kristiani Banhae, M. Yoani Vivi Bita Aty, Y. Mau, P. Selasa and Israfil, (2023), "Analisa Faktor Pengetahuan Dan Sikap Dengan Perilaku Pencegahan TB Paru Pada Kontak Serumah Selama Era New Normal Covid 19," Jurnal Penelitian Perawat Profesional, vol. 5, no. 1, pp. 43-50.
[8] Kementerian, "Peraturan Menteri Kesehatan Republik Indonesia Nomor 67," Kementerian, Jakarta, 2016.
[9] G. Ardesfira, H. Fitriah Zedha, . I. Fazana, J. Rahmadhiyanti, S. Rahima and S. Anwar, (2022), "Peramalan Nilai Tukar Rupiah Terhadap Dollar Amerika Dengan Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA)," JAMBURA JOURNAL OF PROBABILITY AND STATISTICS, vol. 3, no. 2, pp. 71-84.
[10] E. S. Bilaffayza, Wahyudin and D. Herwanto, (2023), "Peramalan Permintaan Metode Moving Average dan Linier Regression dalam Memprediksi Produksi Produk Disc Brake K93 (Studi Kasus PT United Steel Center Indonesia)," JRSI: Jurnal Rekayasa Sistem dan Industri, vol. 10, no. 1, pp. 32-38.
[11] D. Anisya Ramdani and F. Nurul Azizah, (2019), "Analisis Perbandingan Peramalan Permintaan Pelumas Pt Xyz Dengan Metode Moving Average, Exponential Smoothing Dan Naive Method," in Seminar Nasional Official Statistics.
[12] M. A. Maricar, (2019), "Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing untuk Sistem Peramalan Pendapatan pada Perusahaan XYZ," Jurnal Sistem Dan Informatika (JSI), vol. 13, no. 2, pp. 36-45.
[13] Makkulau, R. Raya and S. Marlinda, (2017), "Aplikasi Metode Dekomposisi Pada Peramalan Jumlah Kelahiran," in Seminar Nasional Teknologi Terapan Berbasis Kearifan Lokal (SNT2BKL).
[14] S. Andayani, (2020), "Prediksi Kejadian Penyakit Tuberkulosis Paru Berdasarkan Jenis Kelamin," Jurnal Keperawatan Muhammadiyah Bengkulu, vol. 8, no. 2, pp. 135-140.

PlumX Metrics

Published
2024-05-10
How to Cite
[1]
D. Novanda and R. Hidayati, “Prediction of The Number of Pulmonary Tuberculosis Disease Using The Moving Average Forecasting Method And Time Series Decomposition”, antivirus, vol. 18, no. 1, pp. 37-45, May 2024.
Section
Articles