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All Journal Journal of Multidisciplinary Science: MIKAILALSYS Asian Journal of Science, Technology, Engineering, and Art ALSYSTECH Journal of Education Technology International Journal of Education, Culture, and Society Mikailalsys Journal of Mathematics and Statistics International Journal of Humanities, Education, and Social Sciences
Stephen, Mathew
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Journal : Asian Journal of Science, Technology, Engineering, and Art

 1 
Comparative Study on Forecast Performance from Decomposition, Winter’s and Sarima Models Stephen, Mathew; Ogunmola, Adeniyi; Akobi, Clement Ogbeche; Michael, Ibrahim
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 6 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i6.4040

Abstract

This study investigates the forecasting accuracy of three univariate time series models—Decomposition, Winter’s method, and Seasonal Autoregressive Integrated Moving Average (SARIMA) to predict the Agricultural GDP of Nigeria. Quarterly data on Nigeria's Agricultural GDP from 2010 to the first quarter of 2023, obtained from the National Bureau of Statistics, were analyzed. The study applied Box-Jenkins SARIMA modeling, time series decomposition, and Winter’s method to compare their forecasting accuracy using Root Mean Square Error (RMSE) as the selection criterion. The results revealed that the SARIMA (0, 0, 2)(2, 1, 0) model outperformed the other methods, with the lowest RMSE, indicating its superior accuracy in forecasting Agricultural GDP. Winter’s method and the Decomposition method. The forecast from the SARIMA model indicated a positive trend in Nigeria’s Agricultural GDP over the study period, reinforcing the sector’s critical role in economic growth.
A Statistical Evaluation of the Occurence of Meningitis in Takum, Taraba State, Nigeria Idi, Danjuma; Akobi, Clement; Stephen, Mathew; Bamigbala, Olateju Alao
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 6 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i6.4112

Abstract

Meningitis remains a critical public health issue in Nigeria, particularly within the dry season when environmental factors such as low humidity and dust elevate transmission risks. Using historical incidence data from 2012 to 2021, this study utilizes the Autoregressive Integrated Moving Average (ARIMA) model estimate and predict the occurrence of meningitis occurrences. Findings frm the study revealed that the ARIMA(1,1,0) model emerged as the optimal fit, capturing the seasonal patterns and temporal trends in meningitis cases. This study recommends the integration of ARIMA-based forecasting into Nigeria’s public health strategies to strengthen early warning systems, optimize resource deployment, and enable more proactive responses during high-risk periods.
Regression Analysis on the Impact of Agriculture, Industry and Service Sector on Economic Growth in Nigeria Michael, Ibrahim; Akobi, Clement; Stephen, Mathew
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 5 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i5.3772

Abstract

This study investigates the impact of agriculture, industry, and the service sector on Nigeria's economic growth from 1990 to 2022, using data obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin. Employing an Ordinary Least Squares (OLS) regression model, the research explores the contributions of these key sectors to Nigeria's Gross Domestic Product (GDP). The findings reveal that the industrial sector has a significant positive effect on GDP, emphasizing its crucial role in driving economic growth. The agricultural sector also contributes positively, though its impact is relatively modest, highlighting the need for modernization and investment to enhance productivity. Surprisingly, the service sector shows a statistically significant negative impact on GDP, contrary to its traditionally recognized role in economic expansion. This anomaly suggests underlying structural issues within the sector that require further investigation. The study's model explains approximately 59.65% of the variation in GDP, with no significant evidence of autocorrelation, heteroskedasticity, or multicollinearity affecting the results. Based on these findings, the study recommends targeted policy interventions to improve agricultural productivity, strengthen industrialization efforts, and reform the service sector to foster balanced and sustainable economic growth in Nigeria.
Co-Authors Adiele, Sunday Akobi, Clement Akobi, Clement Ogbeche BAMIGBALA, Olateju Alao Fadahunsi, John A. Idi, Danjuma Michael, Ibrahim Michael, Oshimagye Ibagye Ogunmola, Adeniyi Orume, A. K Reuben, Laraba Love Yusuf, Shadrach