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Comparison of Machine Learning Land Use-Land Cover Supervised Classifiers Performance on Satellite Imagery Sentinel 2 using Lazy Predict Library Muhamad Iqbal Januadi Putra; Vincent Alexander
Indonesian Journal of Data and Science Vol. 4 No. 3 (2023): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v4i3.102

Abstract

The utilisation of various supervised classifier algorithms in classifying land use and land cover (LULC) from satellite imagery has been widely used worldwide, yet the implementation using lazy predict library remained unexplored. This study aims to create the LULC supervised classifier model for Sentinel 2 satellite images using lazy predict library and assess its capability for creating multiple machine learning models. The result of this study shows that lazy predict library can generate 26 machine learning models in efficient few lines of code and less time-consuming. Most LULC models generated by lazy predicts has performance metrics above 90% with time computation between 0 and 1 seconds. While lazy predict library has benefits to generate various machine learning models at once, it has drawbacks in terms of its feasibility for the machine learning production, its obstacle running in local environment, and its requirements for the RAM computation.
MAPPING APATITE-ILMENITE RARE EARTH ELEMENT MINERALIZED ZONE USING FUZZY LOGIC METHOD IN SIJUK DISTRICT, BELITUNG Muhamad Iqbal Januadi Putra; Sobirin
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 1 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a2828

Abstract

District of Sijuk located in Belitung Island is rich with non-lead mineral content. As the part of Southeast Asia’s Lead Belt, the presence of Apatite-Ilmenite Rare Earth Element formed by the region’s geological condition is very likely. However, there has not been any activity to map and identify the apatite-ilmenite distribution in this region. Therefore, the objective of this study was to map the mineralized apatite-ilmenite in Sijuk District. Using remote sensing technology, Landsat 8 OLI were utilized to map the distribution of mineralized apatite-ilmenite rare earth element. Alteration mineral carrier, geological structure, and lithology data were all used as variables. Landsat-8 was pre-processed using band ratio and Directed Principal Component Analysis (DPCA) method for gaining alteration variable. The fuzzy logic method was then deployed for integrating all data. The result of this research showed the potential distribution of mineralized apatite-ilmenite with a total area of 1,617 ha. The most prioritized areas for apatite-ilmenite mineral exploitation are located in Air Seruk Village’s IUP (Izin Usaha Pertambangan/Mining Business License), Sijuk Village’s IUP, and Batu Itam Village’s IUP. This study also illustrates the orientation of the metal utilization of apatite-ilmenite in district Sijuk.