@thesis{thesis,
		author={Haidar  Fadhila Fiqa},
		title ={PERBANDINGAN METODE ARIMA DAN PROPHET DALAM PREDIKSI HARGA CABAI RAWIT DI PROVINSI JAWA TIMUR},
		year={2024},
		url={https://repository.ittelkom-pwt.ac.id/11397/},
		abstract={The price of cayenne pepper is a seasonal horticultural commodity, so its availability is not
consistent throughout the year, causing its price to fluctuate. Fluctuations, instability, and
uncertainty in the price of cayenne pepper in the future cause losses for society, especially people
who are classified as poor. Therefore, it is necessary to carry out predictive modeling using
appropriate methods based on past data. Autoregressive Integrated Moving Average (ARIMA) and
Prophet are time series-based prediction methods. The purpose of this study is to compare ARIMA
and Prophet to get the optimal model in predicting the price of cayenne pepper in East Java Province
for the next three months. ARIMA is effective in modeling trends and seasonal patterns in stable
historical data and is good at short-term prediction. Meanwhile, Prophet can predict well for data
with or without seasonal effects and is resistant to outliers, missing values, and is good at dealing
with trend changes automatically. The results show that ARIMA (7, 1, 7) is better than Prophet with
an RMSE value of 18723.92 and MAPE of 19.48%. The prediction results show a periodic decrease
in the price of cayenne pepper from May to July 2024. ARIMA results that are better than Prophet
can be caused by the data not having outlier values, so the advantages of Prophet in handling outlier
data are not relevant. In addition, ARIMA allows for more specific model customization through the
selection of parameters (p, d, q) that are optimal for the observed data.
Keywords: cayenne pepper, East Java, prediction, ARIMA, Prophet}
		}