Abstract.A file security is one method to protect data confidentiality, integrity and information security. Cryptography is one of techniques used to secure and guarantee data confidentiality by doing conversion to the plaintext (original message) to cipher text (hidden message) with two important processes, they are encrypt and decrypt. Some researchers proposed a hybrid method to improve data security. In this research we proposed hybrid method of AES-blowfish (BF) to secure the patient's medical report data into the form PDF file that sources from database. Generation method of private and public key uses two ways of approach, those are RSA method f RSA and ECC. We will analyze impact of these two ways of approach for hybrid method at AES-blowfish based on time and Throughput. Based on testing results, BF method is faster than AES and AES -BF hybrid, however AES-BF hybrid is better for throughput compared with AES and BF is higher.

Ekosistem mangrove telah ada dikenal lama memiliki banyak fungsi dan merupakan penghubung penting dalam menjaga keseimbangan biologis di ekosistem pesisir. Ekosistem hutan bakau merupakan habitat penting bagi organisme laut. Hutan mangrove sebagai salah satu ekosistem wilayah pesisir dan lauatan sangat potensial bagi kesejahteraan masyarakat baik dari segi ekonomi, sosial, dan lingkungan hidup. Ekosistem mangrove di kelurahan Nelayan Indah sekarang ini dalam keadaan kritis ketersediaannya. Hal ini disebabkan adanya degradasi hutan mangrove akibat penebangan yang melampaui batas kemampuan kelestariannya. Kegiatan penanaman mangrove di kelurahan Nelayan Indah Kota Medan, sebagai upaya untuk rehabilitasi kawasan setelah banjir rob, tergolong berhasil. Keberhasilan kegiatan penanaman mangrove, tidak hanya tergantung pada pemilihan jenis mangrove yang akan ditanam tetapi juga pemilihan lokasi penanaman harus sesuai bagi pertumbuhan mangrove.

Abstract. ASCII characters have a different code representation where each character has a different numeric value between the characters to each other. The characters is usually used as a text message communication has the representation of a numeric code to each other or have a small d ifference. The value o f the difference can be used as a substitution of the characters so it will generate a new message with a size that is a little mo re. This paper discusses the utilization value of the difference of characters ASCII in a message to a much simpler substitution by using a dynamic-sized window in order to obtain the difference fro m ASCII value contained on the window as the basis in determin ing the bit substitution on the file co mpression results.

Currently, Indonesia is still under the influence of the COVID-19 virus. Indonesian people buy necessities of life on the online market. Clothing is a daily necessity that people often buy online. This has an impact on increasing online clothing sales, but not all clothes are according to the tastes of buyers. Therefore we need an application that is used to speed up changing the color of clothes according to the needs of buyers. The chroma key application that is used to change the color of the clothing image uses the HSV and morphology classification methods. Edge detection and median filters are used to improve the quality of color shift results with HSV. This application is built using MatLab 2015a programming. The test results show that the HSV classification method is better at changing the color of the clothing image than the morphological method. The HSV classification method was successful in changing the color of clothes well with a 100% success rate. While the morphological method succeeded in changing the color of the clothes with a success rate of 60%.

<p class="Abstrak">Kompresi citra dapat dilakukan dengan menggunakan <em>color quantization</em> di mana dengan mengurangi jumlah warna yang terdapat pada citra maka akan dapat mengurangi jumlah bit yang digunakan untuk merepresentasikan warna – warna tersebut. Semakin rendah jumlah warna yang dikurangi dalam rangka mencapai rasio kompresi yang optimal berdampak pada terdegradasinya kualitas dari citra. Secara umum <em>color quantization</em> menggunakan model <em>clustering </em>dalam proses pembentukan <em>color palette</em> yang akan digunakan sebagai referensi pada saat kuantisasi. Penelitian ini menggunakan model <em>clustering</em> berdasarkan nilai <em>max variance</em> pada <em>channel</em> RGB secara terpisah. Proses <em>clustering</em> dilakukan dengan membelah populasi <em>cluster </em>sebelumnya menggunakan nilai <em>mean</em> dari <em>channel </em>RGB yang memiliki nilai <em>variance </em>tertinggi. <em>Color palette</em> kemudian dibentuk menggunakan <em>centroid</em> hasil dari proses <em>clustering</em>. Percobaan pada beberapa citra uji dengan format 32bpp yang kemudian dikompresi menggunakan kuantisasi warna pada format 8bpp dan 4bpp memberikan kualitas dan rasio kompresi yang cukup baik yang diukur menggunakan ukuran MSE, PSNR dan CR di mana nilai MSE yang diperoleh berkisar 3.87 sampai 6.3 pada kuantisasi 8bpp dan 13.39 sampai 19.62 pada kuantisasi 4bpp. Sedangkan rasio kompresi yang diperoleh adalah sebesar 1.44 sampai 2.09 pada kuantisasi 8bpp dan 2.87 sampai 4.23 pada kuantisasi 4bpp.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstract</strong></em></p><p class="Judul2"><em>Image compression can be done by using color quantization where by reducing the number of colors contained in the image it can reduce the number of bits used to represent the colors. The lower the number of colors reduced in order to achieve the optimal compression ratio has an impact on the quality of the image. In general, color quantization uses clustering models in the process of constructing color palette that will be used as a reference during quantization. This study uses a clustering model based on the max variance value on the RGB channel separately. The clustering process is done by dividing the previous cluster population using the mean value of the RGB channel which has the highest variance value. The color palette is then formed using centroids resulting from the clustering process. Experiments on some test images in 32bpp format which are then compressed using color quantization in 8bpp and 4bpp formats provide a fairly good quality and compression ratio </em><em>with</em><em> MSE, PSNR and CR</em><em> assessment where the MSE values obtained ranged from 3.87 to 6.3 at 8bpp quantization and 13.39 to 19.62 at 4bpp quantization. While the compression ratio obtained is 1.44 to 2.09 at 8bpp quantization and 2.87 to 4.23 at 4bpp quantization </em></p><p class="Abstrak"><em><strong><br /></strong></em></p>