The Implementation of Least Square Method on the Palm Shells Sales Forecasting Application

Fahirah,; Wulandari, Lily

doi:10.5815/ijieeb.2020.05.01

Cited by 2 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the Least Square Method has been applied to forecast the sale of palm shells, enabling companies to set more accurate sales targets and estimate sales for the forthcoming month over a year, starting from one month after the actual sales period. The data tested using the Mean Absolute Percentage Error (MAPE) revealed an error rate of 5.935% [25].…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Analysis of the Ornamental Angelfish Export Market Demand: An Application of the Least Square Method

Kasmi¹,

Aman²,

Asriany³

et al. 2023

ISI

View full text Add to dashboard Cite

Fluctuations in the stock levels of the ornamental angelfish export market have highlighted the necessity for an effective demand prediction system. In response to this need, the present study undertakes the development of a demand prediction model, employing the Least Square Method, for the ornamental angelfish market. The model is evaluated using a dataset comprising 4166 individual records across three ornamental angelfish samples from the year 2021. The model's predictive accuracy is quantitatively assessed through the Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) compared to actual data. The results indicate a high level of accuracy, with an average MSE value of 39, an average MAD value of 5, and an average MAPE value of 5%. This study's findings contribute valuable insights to the ornamental angelfish export industry, demonstrating the efficacy of the Least Square Method in forecasting demand, and propose potential trajectories for further research.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Predictive Analysis of the Ornamental Angelfish Export Market Demand: An Application of the Least Square Method

Kasmi¹,

Aman²,

Asriany³

et al. 2023

ISI

View full text Add to dashboard Cite

show abstract

“…predicted and observed values divided by the observed data (actual data), then displayed using percentages. The MAPE formula is seen in equation [30,31,32].…”

Section: Forecastingmentioning

confidence: 99%

Point Based Forecasting Model of Vehicle Queue with Extreme Learning Machine Method and Correlation Analysis

Kasliono¹,

Suprapto²,

Makhrus³

2021

IJISA

View full text Add to dashboard Cite

Traffic is a medium to move from one point to another. Therefore, the role of traffic is very important to support vehicle mobility. If congestion occurs, mobility will be hampered so that it gives influence to other sectors such as financial, air pollution and traffic violations. This study aims to create a model to predict vehicle queue at the traffic lights when its status is red. The prediction is conducted by using Neural Network with Extreme Learning Machine method to predict the length of the vehicle queue, and Correlation Analysis was used to measure the correlation between the connected roads. The conducted experiments use data of the length of the vehicle queue at the traffic lights which was obtained from DISHUB (Transportation Bureau) DI Yogyakarta. Several experiments were carried out to determine the optimum prediction model of vehicle queue length. The experiments found that the optimum model had an average MAPE value of 15.5882% and an average Running Time of 5.2226 seconds.

show abstract

The Implementation of Least Square Method on the Palm Shells Sales Forecasting Application

Cited by 2 publications

References 2 publications

Predictive Analysis of the Ornamental Angelfish Export Market Demand: An Application of the Least Square Method

Predictive Analysis of the Ornamental Angelfish Export Market Demand: An Application of the Least Square Method

Point Based Forecasting Model of Vehicle Queue with Extreme Learning Machine Method and Correlation Analysis

Contact Info

Product

Resources

About