Pencitraan Banjir Rob Zona Medan Utara Menggunakan Regresi Logistik dan Artificial Neural Network Serta Global Information System - Pyanto, Farino (Lembaga Penelitian dan Pengabdian kepada Masyarakat, 2023)
Perlunya memetakan zona terancam banjir rob berdasarkan faktor-faktor penyebab banjir rob di wilayah Medan Utara sebagai dasar bagi stakeholder dalam rangka penanganan banjir rob. Indikator kerawanan terhadap banjir rob mencakup curah hujan, drainage density, land use, jarak ke sungai, jenis tanah, elevasi, kemiringan, aspek, jarak ke muara. Analisis data menggunakan GIS dan regresi logistik serta ANN. Lokasi penelitian adalah kecamatan Belawan, Marelan dan Labuhan. Hasil analisis yang didapat, yaitu faktor curah hujan, drainage density, elevasi, jarak ke muara, aspek berpengaruh terhadap kerawanan banjir rob. Sedangkan indikator land use, jenis tanah, jarak ke sungai, kemiringan tidak berpengaruh terhadap kerawanan banjir rob. Hasil analisis menunjukkan peringkat indikator yang mempengaruhi terhadap kerawanan banjir rob dari pertama sampai sembilan adalah jarak ke muara, elevasi, aspek, jarak ke sungai, jenis tanah, land use, kemiringan, curah hujan dan drainage density. Sampel 209 dengan 9 dan 7 faktor didapat ketepatan model penelitian sebesar 86,1%. Hasil penelitian dengan rumus MAPE menunjukkan akurasi data train percobaan 1 sebesar 64,5662% dan data tes percobaan 1 sebesar 75,7515%. Sementara data train percobaan 2 sebesar 70,5429% dan data tes percobaan 2 sebesar 78,5544%. The need to map tidal flood threat zones based on the factors that cause tidal floods in the North Medan area as a basis for stakeholders in the context of tidal flood management. Indicators of vulnerability to tidal flooding include rainfall, drainage density, land use, distance to the river, soil type, elevation, slope, aspect, distance to the estuary. The purpose of this study was to map the level of vulnerability to tidal floods in the northern coastal area of Medan and identify the factors that influence tidal flooding. Data analysis using GIS and logistic regression and ANN. The research locations are Belawan, Marelan and Labuhan districts. The results of the analysis obtained, namely the factors of rainfall, drainage density, elevation, distance to the estuary, aspects that influence tidal flood vulnerability. While the indicators of land use, soil type, distance to the river, slope have no effect on tidal flood hazard. The results of the analysis show that the ranking of indicators that affect the tidal flood vulnerability from first to nine is distance to the estuary, elevation, aspect, distance to the river, soil type, land use, slope, rainfall and drainage density. Sample 209 with 9 and 7 factors obtained the accuracy of the research model of 86.1%. The results of the study using the MAPE formula showed that the accuracy of the first trial train data was 64.5662% and the first experimental test data was 75.7515%. While the data for trial 2 was 70.5429% and the data for trial 2 was 78.5544%.