(untitled) (Jurnal Ilmu dan Teknologi Kelautan Tropis, 2020)
Backscattering can describe sediments’ condition in the bottom waters, including the grain size of the bottom waters sediments. This study aims to detect, classify, and estimate the bottom watershed based on backscattering values using Angular Response Analysis (ARA) and Support Vector Machine (SVM) so that a spatial map of sediment distribution is obtained in Gulf of Palu. Bathymetry data and backscattering intensity were taken on 5-9 October 2018 using the multibeam echosounder Kongsberg EM 302 with a frequency of 30 kHz, and ten sediment samples in 2012 belong to PUSHIDROSAL. The sediment distribution from the Gulf of Palu with the ARA method is dominated by sand and silt. Simultaneously, the distribution of sediments using the SVM method is dominated by silty sand, silt, and sand. Accuracy test results for the ARA methods produce an overall accuracy with a value of 50%. In comparison, Accuracy test results for the SVM method produce an overall accuracy with a value of 60%. The prediction of the basic types of waters in Palu Bay that are most close to the actual state is the prediction results using the SVM method, namely silt, silt, and sand.