Implementasi Ekstraksi Ciri Histogram dan K-Nearest Neighbor untuk Klasifikasi Jenis Tanah di Kota Banjar, Jawa Barat

Land plays an essential role in the availability of nutrients and water to support our life on earth. Soil quality can be observed based on its color and texture characteristics. By knowing the quality of the soil, the most suitable plants for planting can be determined. This study is conducted to examine the soil quality in Langensari. The most regions in Langensari are in the altitude of fewer than 25 meters above sea level that they are very potential for agriculture and plantation. The proposed system used in this research is a cross-sectional image of the ground as input. The image is then extracted using histogram feature extraction to obtain the intensity, standard deviation, skewness, energy, entropy and smoothness values. K-Nearest Neighbor is then used to classify the results. The proposed system was tested using 20 test images. Based on the experiment result, the system can classify soil types appropriately with accuracy reaching 60% when value of K = 1and K=3.

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