<![CDATA[Forest fire detection system is one of important tools in preventing and mitigating forest and land fires. In Indonesia, the detection of forest and land fires relies on hotspot information captured from satellites. However, the location obtained by the satellite has a horizontal error of 2 km from the ground check data. Therefore, these information are less relevant to the actual location. In this research, an android app is proposed to extract Exchangeable Image Format (EXIF) photo metadata. The metadata has image information such as latitude and longitude, to obtain the location of forest fires reported by the application user. In addition, this research implemented one of the image processing methods to classify fire and smoke in images of fires. Color filtering method is used based on the color space of Red Green Blue (RGB), Hue Saturation Value (HSV) and YCbCr. This classification process aims to ease the burden on the admin in confirming user reports. The results of the fire and smoke classification process are described using a confusion matrix. This matrix produces an accuracy rate of 75%, a precision of 80% and a recall of 80% for a fire classification and an accuracy of 70%, a precision of 92% and a recall of 87% for smoke classification. There are 25% and 30% of misclassified data of fire and smoke. This is because the color filtering method classifies each color pixel from the image, therefore many pixels that are not classified as fire or smoke images are classified because there are other objects that have a range of colors to classify fire and smoke]]>
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