MODELING AND FORECASTING ANTE-NATAL CARE ATTENDANCE USING BOX AND JENKINS METHOD

AJIBODE, I. A and Sikiru, O. A. (2021) MODELING AND FORECASTING ANTE-NATAL CARE ATTENDANCE USING BOX AND JENKINS METHOD. In: Presented at the 5th National Conference of the School of Pure & Applied Sciences Federal Polytechnic Ilaro held between 29 and 30th September, 2021. Theme: Food Security and Safety: A Foothold for Development of Sustainable Economy in Nigeria, 29th – 30th September, 2021, The Federal Polytechnic, Ilaro.

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Abstract

Ante-natal care is a type of preventative health care in which expectant mothers are taught healthy practices during pregnancy by health professionals in order to have a solid understanding of probable indications during pregnancy and childbirth. The availability of high-quality antenatal care and its coverage, particularly in developing nations, is excellent. Furthermore, quality services, particularly in Nigeria, are a consequence of the quantity of women who require such services vs the amount of professionals available. As a result, the goal of this study was to look at the rate of ante-natal care attendance at Federal Medical Centre in Abeokuta, Ogun State, between 2010 and 2019. The data used were all secondary data, and the analysis was done using the Box-Jenkin method. The data was differencing to make it steady and then utilized for parameter estimation. The Akaike Information Criterion (AIC) was used to determine the optimal model for the series. The ARIMA (3, 1, 3) model was judged to be the best model for capturing the data at the conclusion of the investigation. As a result, the study recommends that policymakers make efforts to expand the number of staff and timely service delivery for ante-natal attendance among women in Nigeria, as the projection value shows a constant growth in the rate of attendance up to 2022.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User: Mr. Bolanle Yisau I.
Date Deposited: 02 Mar 2022 11:08
Last Modified: 02 Mar 2022 11:17
URI: http://eprints.federalpolyilaro.edu.ng/id/eprint/1971

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