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<![CDATA[PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA ]]>
<![CDATA[Hidayah, Annisa Yuniar]]>;
<![CDATA[Riski, Abduh]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 18 No 2 (2018): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v18i2.17249
<![CDATA[Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from infrared cameras, therefore this study uses infrared imagery as an image to be corrected. The method that will be used to improve the image, namely Cellular Automata method. The edge detection using the Prewitt operator will be used as the initial state of Cellular Automata cells. The results obtained from this research is Cellular Automata method can improve the quality of infrared image well. Visually, the Cellular Automata method successfully improves image contrast and retains the infrared image detail so as not to reduce the value of information from the image. Calculated using the Linear Index of Fuzziness, the results of the Cellular Automata method are better only on some imagery only when compared to the Histogram Equalization mode. Keywords: Infrared Image, Image Enhancement, Cellular Automata]]>
<![CDATA[PENGAMANAN CITRA GRAYSCALE MENGGUNAKAN ALGORITMA AES 128 DENGAN KUNCI CITRA GRAYSCALE ]]>
<![CDATA[Umam, Ahmad Khoirul]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>;
<![CDATA[Riski, Abduh]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v18i1.17243
<![CDATA[Cryptography is the science of maintaining or securing an information by scrambling or hiding information so that it is difficult to analyze. The algorithm used in this study is the AES 128 algorithm that has been changed using the grayscale image. The AES algorithm is a modern algorithm that replaces the DES algorithm, and is an algorithm that is chosen to secure a data / message because it is efficient and has strong security. In the process, the grayscale image key is divided into 16 blocks of pixels, pixels are operated on each block with XOR operations so that one character will be obtained for each block. From the XOR process of pixels in 16 blocks, 16 characters or 128 bits long will be obtained. The data used in this study are plain images in the form of grayscale images and keys in the form of grayscale images as well. Grayscale (plain image) images will be encrypted with an image key that is also a grayscale image. Initially, the key will be taken from a grayscale image by dividing 16 blocks to get a 128-bit long key, then generating the key with the key generator in the AES algorithm so that it will get 10 sub-keys. Then encryption is done with 10 subkeys that were obtained using the AES algorithm. The results of the encryption process will produce an encoded image or cipher image that does not contain information from the plain image. The results of this algorithm are fairly safe against attacks because they have varied and sensitive keys. Keywords: Cryptography, AES, Rijndael Algorithm, Grayscale]]>
<![CDATA[IMPLEMENTASI ALGORITMA GREY WOLF OPTIMIZER (GWO) DI TOKO CITRA TANI JEMBER ]]>
<![CDATA[Lestari, Vidiyanti]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>;
<![CDATA[Santoso, Kiswara Agung]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 19 No 2 (2019): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v19i2.17269
<![CDATA[Generally, optimization is defined as the process of determining the minimum or maximum value that depends on the function of the goal, even now there are many problems regarding optimization. One of them is the problem regarding the selection of goods to be included in a limited storage medium called Knapsack problem. Knapsack problems have different types and variations. This study will solve the problem of bounded knapsack multiple constraints by implementing the Grey Wolf Optimizer (GWO) algorithm. The problem of bounded knapsack multiple constraints has more than one subject with the items that are inserted into the dimension storage media can be partially or completely inserted, but the number of objects is limited. The aim of this study is to determine the results of using the Grey Wolf Optimizer (GWO) algorithm for solving the problem of multiple constraints bounded knapsack and compare the optimal solutions obtained by the simplex method using the Solver Add-In in Microsoft Excel. The data used in this study is primary data. There are two parameters to be tested, namely population parameters and maximum iteration. The test results of the two parameters show that the population parameters and maximum iterations have the same effect, where the greater the value of the population parameters and the maximum iteration, the results obtained are also getting closer to the optimal value. In addition, based on the results of the final experiment it is known that the comparison of the results of the GWO algorithm and the simplex method has a fairly small percentage deviation which indicates that the GWO algorithm produces results that are close to the optimal value. Keywords: GWO algorithm, Knapsack, Multiple Constraints Bounded Knapsack.]]>
<![CDATA[PENERAPAN ARTIFICIAL FISH SWARM ALGORITHM (AFSA) PADA MULTIPLE TRAVELLING SALESMAN PROBLEMS (m-TSP) ]]>
<![CDATA[Fismaya, Florencia Wahyu Ganda]]>;
<![CDATA[Riski, Abduh]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 20 No 1 (2020): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v20i1.17220
<![CDATA[Selling or trading in the industrial 4.0 era as it can now be done by opening a shop online. Therefore, shopping at this time can also be done online also, so that the online shop owners require orders that do not allow for Cash On Delivery (COD) transactions using package delivery services. This research discusses about finding a solution for good shipping with a minimum total mileage of several couriers at PT. Titipan Kilat District Banyuwangi uses AFSA as a settlement algorithm. The experimental process is carried out by using several parameter values to determine the parameters that affect the final solution. Each parameter will be tested with a maximum of 1000 iterations, then the best results will be tested again with a maximum iteration of 2000, and 5000 and will be compared with the original distance traveled by the couriers. The final solution offered in the form of a delivery route by three couriers with the total distance (Z) of the third courier is 87.28 Km with the smallest iteration value reaching the local minimum in iteration 1169. Keywords: artificial fish swarm algorithm (afsa), multiple travelling salesman problem (m-tsp), route, total mileage.]]>
<![CDATA[PENERAPAN ALGORITMA PENGUINS SEARCH OPTIMIZATION (PeSOA) DAN ALGORITMA MIGRATING BIRDS OPTIMIZATION (MBO) PADA PERMASALAHAN KNAPSACK 0-1 ]]>
<![CDATA[Abdullah, Rinaldy Ahmad]]>;
<![CDATA[Riski, Abduh]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 19 No 2 (2019): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v19i2.17270
<![CDATA[Every person would want maximum profit with as little as possible resources or capital. One example in everyday life is the problem of limited storage media but is required to get the maximum benefit. From this problem comes the term known as the knapsack problem. One of the problems with Knapsack is knapsack 0- 1, where knapsack 0-1 is a problem of storing goods where the item will be completely inserted or not at all. Completion of knapsack 0-1 problems can be helped using a metaheuristic algorithm. Metaheuristic algorithms include the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm. This study aims to determine the resolution of knapsack 0-1 problems using the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm and compare the optimal solutions obtained. This research method is divided into three main parts. First take data that includes the name of the item, the purchase price, the selling price and the weight of each item. The second is applying the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization algorithm (MBO) on 0-1 knapsack problems. The third program is made to facilitate the calculation of data with the help of Matlab R2015b software. The results of this study found that both algorithms both reached the optimal solution, but the convergence and running time obtained were different. The Migrating Birds Optimization (MBO) algorithm is faster converging than the Penguins Search Optimization (PeSOA) algorithm to get the optimal solution. And also the Migrating Birds Optimization (MBO) algorithm has better running time than the Penguins Search Optimization (PeSOA) algorithm to achieve maximum iteration. Keywords: Whale optimization algorithm, multi knapsack 0-1 problem with multiple constraints.]]>
<![CDATA[Algoritma Elephant Herding Optimization: Permasalahan Multiple Constraints Knapsack 0-1 ]]>
<![CDATA[Regita, Yulia Dewi]]>;
<![CDATA[Santoso, Kiswara Agung]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v18i1.17241
<![CDATA[Optimization problems are often found in everyday life, such as when determining goods to be a limited storage media. This causes the need for the selection of goods in order to obtain profits with the requirements met. This problem in mathematics is usually called a knapsack. Knapsack problem itself has several variations, in this study knapsack type used is multiple constraints knapsack 0-1 which is solved using the Elephant Herding Optimization (EHO) algorithm. The aim of this study is to obtain an optimal solution and study the effectiveness of the algorithm comparing it to the Simplex method in Microsoft Excel. This study uses two data, consisting of primary and secondary data. Based on the results of parameter testing, the proven parameters are nClan, nCi,α,β and MaxGen have a significant effect. The final simulation results have also shown a comparison of the EHO algorithm with the Simplex method having a very small percentage deviation. This shows that the EHO algorithm is effective for completing optimization multiple constraints knapsack 0-1. Keywords: EHO Algorithm, Multiple Constraints Knapsack 0-1 Problem.]]>
<![CDATA[PENGAMANAN POLYALPHABETIC DENGAN AFFINE CIPHER BERDASARKAN BARISAN FIBONACCI ]]>
<![CDATA[Astuti, Lestari Fidi]]>;
<![CDATA[Santoso, Kiswara Agung]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 19 No 2 (2019): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v19i2.17274
<![CDATA[Affine cipher is a classic cryptographic algorithm substitution technique. Substitution technique is the encryption process for every character in the plaintext will be subtituted by another character. Affine cipher uses two types of keys. Each character of plaintext to be encrypted substituted by the same key. This research discusses about modify one of the key affine cipher, to produce a different key that will be substituted with each plaintext character. Key modifications are made by the Fibonacci sequence rules. This study also compares affine cipher and key modification affine cipher by finding corelation coeffiecient values. The results obtained from the comparison of the two algorithms, encryption that uses affine cipher key modification is better than affine cipher. Keywords: Cryptography, Affine Cipher, Fibonacci, Correlation Value]]>
<![CDATA[PENGAMANAN IMAGE DENGAN MODIFIKASI ALGORITMA ELECTRONIC CODE BOOK (ECB) ]]>
<![CDATA[Asti, Melinda]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>;
<![CDATA[Santoso, Kiswara Agung]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 18 No 2 (2018): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v18i2.17252
<![CDATA[Cryptography is knowledge of encoding data to ensure the confidentiality, security, validity and integrity of data. Cryptography is divided into two namely classical cryptography and modern cryptography. One example of modern cryptography is the Electronic Code Book (ECB). Electronic Code Book (ECB) is a modern cryptographic method used to encrypt and decrypt text, images and more. The image is formed from several pixels which consist of several bits in a pixel. Bits are divided into two namely Least Significant Bit (LSB) and Most Significant Bit (MSB).LSB is the four rightmost bits while MSB is the leftmost four bits of a pixel. The purpose of this study is to compare the level of security of Electronic Code Book (ECB) image security results with the results of securing an Electronic Code Book (ECB) modified image. The data used in this study are 8 RGB and Greyscale images also a key in the form of one ASCII character. The results obtained show that securing images with modified Electronic Code Book (ECB) is safer than securing images with Electronic Code Book (ECB) based on histogram analysis, differential analysis and correlation coefficients. Keywords: ASCII, Electronic Code Book (ECB), Most Significant Bit (MSB)]]>
<![CDATA[Determination of All Minimum Spanning Tree on Weighted Connected Graph ]]>
<![CDATA[Hartati, Tri]]>;
<![CDATA[Ubaidillah, Firdaus]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 15 No 2 (2015): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v15i2.23722
<![CDATA[Minimum Spanning Tree is spanning tree with minimum weigth. There are algorithms was used to get MST, include Kruskal’s Algorithm and Prim’s Algorithm. But all of that just give one solution, although MST problems have many solution. The ways to get all of MST from a simple weighted connected graph G can do by: the first, decide reference MST, is one of MST from G. Then choose all edges of graph G which use in MST. Futhermore decide equivalen class from every edges in graph G is not contained in reference MST with less weight or equal maximum weight in reference MST and decide choosen subset. Combinating choosen subset so getting all of MST from random simple weighted connected graph. There are two special criteria in decision all MST of simple weighted connected graph, are decision all MST with combine choosen edge is not make cycle and decision all MST with combine choosen edge make cycle. The purposes are counting and getting all MST which formed by a random simple weighted connected graph.]]>
<![CDATA[PERBANDINGAN PLAYFAIR CIPHER DENGAN 3D PLAYFAIR CIPHER PADA PENGAMANAN CITRA ]]>
<![CDATA[Sukmawati, Rika Ayu]]>;
<![CDATA[Riski, Abduh]]>;
<![CDATA[Kamsyakawuni, Ahmad]]>
<![CDATA[ Majalah Ilmiah Matematika dan Statistika Vol 21 No 1 (2021): Majalah Ilmiah Matematika dan Statistika ]]>
Publisher : <![CDATA[Jurusan Matematika FMIPA Universitas Jember ]]>
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DOI: 10.19184/mims.v21i1.23116
<![CDATA[The development of sending messages that are increasingly easy and sophisticated makes it easier for third parties to access or sabotage the contents of the message, so we need a science called cryptography to secure the message. This research is to secure the message on image encoding using Playfair Cipher and 3D Playfair Cipher. The process of encryption and decryption on Playfair Cipher uses two-letter pairs (bigram), while in 3D Playfair Cipher uses three-letter pairs (trigrams). The encryption process uses Playfair Cipher and 3D Playfair Cipher to produce a different image cipher with plain image visually. In the decryption process, the cipher image returns into the plain image using Playfair Cipher and 3D Playfair Cipher. Histogram analysis, NPCR, and UACI are used to see the difference between ordinary images and password images using Playfair Cipher and 3D Playfair Cipher. The average results of histogram analysis that shows safe based on research data are 14061,483 using 3D Playfair Cipher, the average NPCR results that show safe based on research data are 99.2% using Playfair Cipher, and the average UACI results showing safe based on research data is 29.1% using 3D Playfair Cipher. The results of the study indicate that the proposed method can be used to secure the message.]]>
