Abstract
Rabies is a zoonotic disease that is usually transmitted to humans through animal bites. It can cause severe damage to the central nervous system and is generally fatal. Dog bite cases are considered the leading cause of rabies transmission in Bali. The government's preventive action is expected to reduce the problem of increasing the number of dog bite cases so that it does not spread quickly and cause casualties. Data mining is an attempt to extract knowledge from a set of data. The use of data mining in this study is to forecast the number of dog bite cases in Bali. Forecasting predicts what will happen in the future based on relevant data in the past and placing it in a mathematical model. Data mining methods used in forecasting dog bite cases are backpropagation, holt-winters, polynomial regression methods. This forecasting aims to help the government predict dog bite cases in the coming period to prepare appropriate countermeasures. Forecasting is done using data on bite cases every month in Bali province for five years, from 2015 to 2019. Dog bite case data is divided into four datasets for each attribute, namely data on the number of dog bite cases, the number of vaccinations, the number of male deaths, the number of female deaths. The four datasets are divided into training data and testing data to share 80% training data and 20% testing data. The results obtained are that the backpropagation method is better at predicting dog bite case data with an average MAPE error rate of 11.59%, while the holt-winters method has an average MAPE error rate of 16.05%, and the polynomial regression method has an average MAPE error rate of 19.91%
 Keywords : Dog Bites, Rabies, Forecasting, Backpropagation, Holt-Winter, Polynomial Regression
Highlights
Rabies is a disease that can cause severe damage to the central nervous system and is generally fatal
Backpropagation, holt-winter, and polynomial regression methods are often used in forecasting data in the form of time series
The Polynomial Regression method is the value of the dependent variable in rising or falling linearly or occurring parabolically if the data is made in a scatter plot and is a nonlinear regression method [7]
Summary
Rabies is a disease that can cause severe damage to the central nervous system and is generally fatal. A Comparison Between Backpropagation, Holt-Winter, and Polynomial Regression Methods 251 in Forecasting Dog Bites Cases in Bali (Gede Eridya Bayu Seyoga) p-ISSN: 2252-3006 e-ISSN: 2685-2411 among the main factors transmitting rabies to humans [1]. Forecasting data on dog bite cases uses data in the form of time series. Backpropagation, holt-winter, and polynomial regression methods are often used in forecasting data in the form of time series. The holt-winters method is one of the exponential smoothing methods, namely triple exponential smoothing, which combines simple smoothing series, trend effects, and seasonal effects. This method is used to overcome forecasting in times series data that has trend and seasonal indicators. The Polynomial Regression method is the value of the dependent variable in rising or falling linearly or occurring parabolically if the data is made in a scatter plot (the relationship between the dependent and independent variables is quadratic) and is a nonlinear regression method [7]
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