No abstract

The security aspect is very important in data transmission. One

Information security is very important and has been widely implemented. Cryptography and steganography are two common methods that can be implemented to secure and conceal the information. In this research, the proposed AES algorithm for cryptography and DWT for steganography. However, in case of implementing DWT as steganography, there is a weakness which is a lower capacity. Based on DWT's problem, proposed Huffman Coding to reduce the total of the message's bit and increase the capacity. In the implementation, a message will be processed by using AES and compressed by using Huffman Coding then conceal in a cover using DWT. After doing several experiments using a 128x128 pixel message image and a 512x512 pixel of the cover image, achieved the average of MSE is 1.5676 and the average of PSNR result is above 40 db which is 46.1878.

Rapid development of Internet makes transactions message even easier and faster. The main problem in the transactions message is security, especially if the message is private and secret. To secure these messages is usually done with steganography or cryptography. Steganography is a way to hide messages into other digital content such as images, video or audio so it does not seem nondescript from the outside. While cryptography is a technique to encrypt messages so that messages can not be read directly. In this paper have proposed combination of steganography using discrete cosine transform (DCT) and cryptography using the one-time pad or vernam cipher implemented on a digital image. The measurement method used to determine the quality of stego image is the peak signal to noise ratio (PSNR) and ormalize cross Correlation (NCC) to measure the quality of the extraction of the decrypted message. Of steganography and encryption methods proposed obtained satisfactory results with PSNR and NCC high and resistant to JPEG compression and median filter. Keywords—Image Steganography, Discrete Cosine Transform (DCT), One Time Pad, Vernam, Chiper, Image Cryptography

ABSTRAKMeningkatnya kebutuhan daging sapi, berdampak pada harga daging sapi. Harga daging sapi yang terus menerus mengalami kenaikan, tentunya menyebabkan penurunan penjualan daging sapi. Untuk mengantisipasi hal tersebut, maka beberapa pedagang mencampurkan daging sapi dengan daging babi. Dipilihnya daging babi, karena harga daging babi lebih murah dan warna serta tekstur daging babi yang mirip dengan daging sapi. Secara kasat mata daging sapi dan daging babi sulit untuk dibedakan bagi orang awam. Oleh karena itu, perlu adanya sistem yang dapat membedakan kedua daging. Penelitian ini menggunakan metode klasifikasi untuk membedakan kedua daging. Metode klasifikasi menggunakan algoritma Learning Vector Quantization. Dan penelitian ini memiliki tiga tahapan utama seperti preprocessing, segmentasi warna, ekstraksi fitur, dan klasifikasi. Preprocessing digunakan untuk mendapatkan Region of Interest (ROI) dengan memotong citra dan mengubah ukuran citra. Segmentasi warna menggunakan metode HSV untuk mendapatkan kedalaman warna citra dan ekstraksi fitur mengguakan Gray Level Co-occurrence Matrix (GLCM) untuk mendapatkan fitur dari kontras, korelasi, energi, dan homogenitas. Hasil klasifikasi dengan algoritma LVQ mendapatkan akurasi tertinggi 76,25%. Algoritma telah diuji dengan MSE untuk mengetahui minimum error dan PSNR digunakan sebagai pengukuran kualitas citra pengolahan. Kata kunci: klasifikasi daging, LVQ, HVS, GLCM, MSE, PSNR. ABSTRACT The increasing need of beef, has an impact on the price of beef. The price of beef that continues to