ANALISIS KEAMANAN DATA DENGAN TEKNIK STEGANOGRAFI PADA CITRA DIGITAL MENGGUNAKAN METODE LEAST SIGNIFICANT BIT (LSB)

Knowledge of data security at this point is very important. This is because there is an internet network that makes it easy to exchange data so that many people use it. However, not everyone can use the internet wisely as a means of exchanging data. Things like this can actually trigger crimes such as data theft. Therefore it is necessary to have a handling of data security to ensure that confidential messages or information are protected from irresponsible parties. One way to secure data is to hide it using steganography techniques. Steganography techniques require media to be a container for messages to be hidden. The method used is Least Significant Bit. The pre-processing stage was carried out using Jupyter Notebook software and a steganography program that was run on Visual Studio Code software using the Python programming language. The purpose of this study is to determine the performance of the Least Significant Bit method on RGB, Grayscale, and HSV images. The tests carried out include looking at the comparison of the resulting image quality (fidelity) and the return of the contents of the image message (recovery). Security check testing is done by looking at the histogram results. Then testing the comparison of image similarity is done by knowing the MSE and PSNR values. The results of this study indicate that grayscale images have a higher degree of similarity between cover images and stego images than RGB and HSV with an average MSE value = 0.000702 and PSNR = 80.33818794. Next, the insertion capacity test is carried out by comparing the size of the image based on the number of characters used