Autoregressive Integration Moving Average (ARIMA) Model for Prices of Selected Grains in the South West Nigeria

Dauda, T. O.; Tiamiyu-Ibrahim, S.

doi:10.18805/ag.d-239

Cited by 4 publications

(2 citation statements)

References 4 publications

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“…Consequently, the poor or limited access to technological resources makes it difficult to use demonstrations to teach Accounting concepts. This resonates with Dauda and Olawale's (2020) research study that indicated that students in Nigeria have limited access to educational technologies, because their schools are not equipped with these. The findings showed that Grade 10 Accounting teachers resort to using their laptops when teaching Accounting concepts.…”

Section: Discussionmentioning

confidence: 63%

Collaborative teaching strategies used to enhance learning of accounting concepts

Ndovela,

Hlongwane,

Ngwenya

2023

IJRBS

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Collaborative teaching strategies that teachers use to enhance learning of accounting concepts were explored in schools located in the Pinetown education district in South Africa. The study employed a qualitative case study within the interpretivist paradigm. A purposive sample of five Grade 10 Accounting teachers from five secondary schools was selected to participate in the study. Individual semi-structured interviews and focus group interviews were used to generate data that was analyzed through thematic analysis. The study found that accounting teachers emphasize the necessity of using diverse collaborative strategies to teach accounting concepts. A questioning approach to the teaching of accounting was used to ascertain learners’ experiences and prior knowledge. Infusing technology and group discussions were utilized to encourage learner involvement and participation in the teaching of accounting concepts. The study emphasizes the need for accounting teachers to strengthen learners’ understanding of concepts in Grade 10 by actively engaging them during the process of teaching and learning.

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Section: Discussionmentioning

confidence: 63%

Collaborative teaching strategies used to enhance learning of accounting concepts

Ndovela,

Hlongwane,

Ngwenya

2023

IJRBS

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“…The authors applied the ARIMA techniques to forecast the prices of rice (Adam, 2022;Fernando et al, 2021) and sugar (Şahinli, 2021). The researchers used this technique for forecasting chili (Septiani & Setyowati, 2021), palm oil (Yee & Humaida, 2021), and numerous other items (Zhou, 2021;Astiningrum et al, 2021;Taofik & Tiamiyu-Ibrahim, 2021) prices.…”

Section: Food Price Forecasting Using Several Approachesmentioning

confidence: 99%

An Extreme Learning Machine Approach for Forecasting the Wholesale Price Index of Food Products in India

Das,

Chakrabarti

2023

JST

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Precise food price forecasting is crucial for any country, and searching for appropriate approach(s) from an assortment of available strategies toward this objective is an open problem. The current Indian Wholesale Price Index (WPI) series contains sixty individual food items in the 'manufacture of food product' category. This work considered the monthly data from April 2011 to June 2022, i.e., one hundred thirty-five months' data of these sixty WPIs. The researchers extracted the linearity, curvature, and autocorrelation features for each WPI. The curvature and linearity-based grouping of these WPIs revealed that the WPIs are heterogeneous. This work proposed an extreme learning machine (ELM) approach for forecasting these WPIs. The present work employed the following twenty-two time-series forecasting techniques: six standard methods (Auto ARIMA, TSLM, SES, DES, TES, and Auto ETS), five neural networks (Auto FFNN, Auto GRNN, Auto MLP, Auto ELM, and proposed ELM), and eleven state-of-art techniques (two ARIMA-ETS based ensembles, an ARIMA-THETAF-TBATS based ensemble, one MLP, and seven LSTM-based models) to identify the best forecasting approach for these WPIs. For the majority of WPIs, the offered ELM attained suitable performance in the case of fifteen months of out-of-sample forecasting. Nearly eighty-seven percent of cases achieved high accuracy (MAPE ≤ ten) and outshined others. Upon accuracy comparison, both forecast-MAPE and forecast-RMSE, between the proposed ELM and others, this paper observed that the proposed ELM's performance is more favorable. This paper's findings imply that the proposed ELM is a promising prospect to offer accurate forecasts of these sixty WPIs.

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Time Series: Predicting Nigerian Food Prices using ARIMA Model and R-Programming

Ndunagu

Aderemi

Jimoh

et al. 2022

2022 5th Information Technology for Education and Development (ITED)

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Autoregressive Integration Moving Average (ARIMA) Model for Prices of Selected Grains in the South West Nigeria

Cited by 4 publications

References 4 publications

Collaborative teaching strategies used to enhance learning of accounting concepts

Collaborative teaching strategies used to enhance learning of accounting concepts

An Extreme Learning Machine Approach for Forecasting the Wholesale Price Index of Food Products in India

Time Series: Predicting Nigerian Food Prices using ARIMA Model and R-Programming

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