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All Journal Square : Journal of Mathematics and Mathematics Education Sigma&Mu: Journal of Mathematics, Statistics and Data Science
Madaki, Umar Yusuf
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Education Mathematics

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Time Series Analysis for The Treatment of Typhoid (Enteric) Fever in Maiduguri: Using Arima Model Kaigama, Aishatu; Madaki, Umar Yusuf
Square : Journal of Mathematics and Mathematics Education Vol 5, No 1 (2023)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2023.5.1.18282

Abstract

This research employs the ARIMA model to conduct a thorough time series analysis on the treatment of typhoid (enteric) fever in Maiduguri. The study reveals the presence of both trend and seasonality in the data, with the trend indicating a recent reduction in the recorded data. Using autocorrelation and partial autocorrelation function (ACF and PACF), the data can also be utilized to determine the model's order. The model obtained is subjected to model diagnostics to determine its efficiency and the model is used to forecast the typhoid fever. From the forecast graph shows that there may be a decrease in future years due to the pattern of the series the impression, we obtain from the graph is that predicted series seems to be trend upward and then downward. ARIMA (1,0,0) has the minimum value of AIC therefore it found to be best model. Hence, the model to fit the typhoid fever based on diplomatic test, which is LJung Box test from the family of Box Janks procedure, then our P-value is less than 0.05 level of significant, we reject the null hypothesis and conclude that the typhoid fever is statistically significant at 5% level of significant. Forecast of typhoid fever from February to December 2025 we also conclude that the typhoid fever is stable. Improve Sanitation and Hygiene: Implement measures to improve sanitation and hygiene practices, especially in areas with high disease prevalence. This may include promoting access to clean water, proper waste management, and hygiene education campaigns.Keyword: ARIMA Model, Typhoid fever, Box janks, WHO, Model diagnostic.
Cured Fraction Models on Survival Data and Covariates with a Bayesian Parametric Estimation Methods Madaki, Umar Yusuf; Babura, Babangida Ibrahim; Sani, Muhammad; Abdullahi, Ibrahim
Sigma&Mu: Journal of Mathematics, Statistics and Data Science Vol. 1 No. 1 (2023): March
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/sigmamu.v1i1.45

Abstract

A cure fraction models are usually meant for survival data that contains a proportion of non subject individuals for the event under study. In order to estimate the cure fraction, two models namely mixture model and non-mixture model were commonly deployed. In this work, mixture and non-mixture cure fraction models were presented with survival data structure based on the beta-Weibull distribution. The beta-Weibull distribution is a four parameter distribution developed in this work as an alternative extension to the Weibull distribution in the analysis of lifetime data. The proposed extension allows the inclusion of covariates analysis in the model, in which the estimation of parameters were done under Bayesian approach using Gibbs sampling methods
Time Series Analysis for The Treatment of Typhoid (Enteric) Fever in Maiduguri: Using Arima Model Kaigama, Aishatu; Madaki, Umar Yusuf
Square : Journal of Mathematics and Mathematics Education Vol. 5 No. 1 (2023)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2023.5.1.18282

Abstract

This research employs the ARIMA model to conduct a thorough time series analysis on the treatment of typhoid (enteric) fever in Maiduguri. The study reveals the presence of both trend and seasonality in the data, with the trend indicating a recent reduction in the recorded data. Using autocorrelation and partial autocorrelation function (ACF and PACF), the data can also be utilized to determine the model's order. The model obtained is subjected to model diagnostics to determine its efficiency and the model is used to forecast the typhoid fever. From the forecast graph shows that there may be a decrease in future years due to the pattern of the series the impression, we obtain from the graph is that predicted series seems to be trend upward and then downward. ARIMA (1,0,0) has the minimum value of AIC therefore it found to be best model. Hence, the model to fit the typhoid fever based on diplomatic test, which is LJung Box test from the family of Box Janks procedure, then our P-value is less than 0.05 level of significant, we reject the null hypothesis and conclude that the typhoid fever is statistically significant at 5% level of significant. Forecast of typhoid fever from February to December 2025 we also conclude that the typhoid fever is stable. Improve Sanitation and Hygiene: Implement measures to improve sanitation and hygiene practices, especially in areas with high disease prevalence. This may include promoting access to clean water, proper waste management, and hygiene education campaigns.Keyword: ARIMA Model, Typhoid fever, Box janks, WHO, Model diagnostic.
Co-Authors Abdullahi, Ibrahim Babura, Babangida Ibrahim Kaigama, Aishatu Sani, Muhammad