PREDIKSI CURAH HUJAN SEBAGAI PENUNJANG KEGIATAN MICE MENGGUNAKAN MODEL BASED FORECASTING
DOI:
https://doi.org/10.51878/knowledge.v5i1.4961Keywords:
Prediksi Curah Hujan, ARIMA, SARIMA, MICE, SurabayaAbstract
Surabaya as a metropolitan city has a rapidly growing Meetings, Incentives, Conferences and Exhibitions (MICE) sector. However, the main challenge in organizing MICE is the weather, especially rainfall which can disrupt various activities. Therefore, this research aims to predict rainfall using the AutoRegressive Integrated Moving Average (ARIMA) and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models to support planning for MICE activities in the city of Surabaya. The data used is daily rainfall data for the last 10 years obtained from the Surabaya City Public Works (PU) Department. The research results show that the SARIMA model has better performance than ARIMA in predicting rainfall. The ARIMA model produces a Mean Absolute Error (MAE) of 0.328 and a Root Mean Square Error (RMSE) of 0.408, while the SARIMA model provides more accurate prediction results with an MAE of 0.180 and an RMSE of 0.238. Comparison of models at three observation stations (Wonokromo, Gubeng, and Tandes) also shows the consistent superiority of SARIMA in capturing seasonal patterns contained in rainfall data. The results of these predictions can be used as a basis for planning MICE activities, selecting event times and locations, as well as mitigating risks due to high rainfall. With more accurate prediction models, MICE organizers can minimize weather disruptions and increase event operational efficiency. It is hoped that this research can become a reference in making data-based decisions to deal with climate change and its impacts in the future.
ABSTRAK
Surabaya sebagai kota metropolitan memiliki sektor Meetings, Incentives, Conferences, and Exhibitions (MICE) yang berkembang pesat. Namun, tantangan utama dalam penyelenggaraan MICE adalah cuaca, khususnya curah hujan yang dapat mengganggu berbagai kegiatan. Oleh karena itu, penelitian ini bertujuan untuk memprediksi curah hujan menggunakan model AutoRegressive Integrated Moving Average (ARIMA) dan Seasonal AutoRegressive Integrated Moving Average (SARIMA) guna mendukung perencanaan kegiatan MICE di Kota Surabaya. Data yang digunakan merupakan data curah hujan harian selama 10 tahun terakhir yang diperoleh dari Dinas Pekerjaan Umum (PU) Kota Surabaya. Hasil penelitian menunjukkan bahwa model SARIMA memiliki performa yang lebih baik dibandingkan ARIMA dalam memprediksi curah hujan. Model ARIMA menghasilkan Mean Absolute Error (MAE) sebesar 0.328 dan Root Mean Square Error (RMSE) sebesar 0.408, sedangkan model SARIMA memberikan hasil prediksi yang lebih akurat dengan MAE sebesar 0.180 dan RMSE sebesar 0.238. Perbandingan model di tiga stasiun pengamatan (Wonokromo, Gubeng, dan Tandes) juga menunjukkan konsistensi keunggulan SARIMA dalam menangkap pola musiman yang terdapat dalam data curah hujan. Hasil prediksi ini dapat digunakan sebagai dasar dalam perencanaan kegiatan MICE, pemilihan waktu dan lokasi acara, serta mitigasi risiko akibat curah hujan tinggi. Dengan model prediksi yang lebih akurat, penyelenggara MICE dapat meminimalkan gangguan cuaca dan meningkatkan efisiensi operasional acara. Penelitian ini diharapkan dapat menjadi referensi dalam pengambilan keputusan berbasis data guna menghadapi perubahan iklim dan dampaknya di masa depan.
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