## 5 Result  
### Classification of Landsat Images  
The pyroclastic dimension area was analyzed using supervised classification using the artificial neural network approach in the ENVI program. We used the gap-filled Landsat data to delineate the pyroclastic deposit surrounding areas through supervised classification. We established four classes for Mount Sinabung and Mount Merapi. The focus of this study is the pyroclastic deposits, which are marked as red. The classes used on Mt. Sinabung are forest (green), farmland (yellow), water and shadow (blue) and pyroclastic deposit (red). Mt. Merapi is divided into forest (green), farmland (yellow), cloud (blue) and pyroclastic deposit (red).  
Land classification on Mount Sinabung using the artificial neural network approach is shown in Figure 5. The land classification is divided into four classes based on its color: green as forest,  
Figure 4: Artificial neural network model used for data analysis. Input layer data Regions 1–4, which are select in ENVI. The output layer is the classification map.  
yellow as farmland, blue as water and shadow and red as pyroclastic precipitate. We selected Landsat image data in this study taken on 7 February 2007 as data before eruption, 17 November 2011 as data after the first eruption, 1 July 2016 as data after the second eruption and 28 July 2017 as current pyroclastic deposit data. Based on the supervised classification maps of Mt. Sinabung (Figure 5), the pyroclastic flow depositional area was primarily in the southern region of Mt. Sinabung before the first eruption in 2010. However, the pyroclastic flow deposit migrated to the eastern part of the volcano after the 2010 eruption (Figure 5a,b). The next eruption was in 2013-2017 (Figure 5b,c), and from the land classification data, it can be seen that after the second eruption on 1 July 2016, there was a very big change in the pyroclastic deposits of Mount Sinabung. The pyroclastic precipitate flows to the southeast and extends downward with a shape resembling a landslide. On 28 July 2017, it was seen that pyroclastic deposits did not change too much from the previous year.  
Figure 5: Supervised classification maps from ANN processing in the ENVI program of the Mount Sinabung Landsat Imagery taken on: (**a**) 7 February 2007; (**b**) 17 November 2011; (**c**) 1 July 2016; and (**d**) 28 July 2017.  
Land classification on Mount Merapi using the artificial neural network approach is shown in Figure 6. The land classification is divided into four classes based on its color: green as forest, yellow as farmland, blue as cloud and red as pyroclastic precipitate. We selected Landsat image data in this study taken on 16 June Landsat 2007 as data before eruption, 10 May 2011 and 2 November 2014 as data after the big eruption in 2010 and 23 May 2017 as current pyroclastic deposits. Based on the supervised classification maps of Mount Merapi (Figure 6), the pyroclastic flow depositional area primarily existed in the southwestern region before the eruption in 2010. However, the pyroclastic flow deposit migrated to the southern part of the volcano after the 2010 eruption.  
Figure 6: Supervised classification maps using ANN processing in the ENVI program of Mount Merapi Landsat imagery data taken on: (**a**) 16 June 2007; (**b**) 10 May 2011; (**c**) 2 November 2014; and (**d**) 23 May 2017.