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Application of Fuzzy TOPSIS Method as a Decision Support System for Achievement Student Selection Anggoro, Vani Krismo; Riski, Abduh; Kamsyakawuni, Ahmad
Jurnal ILMU DASAR Vol 24 No 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v24i1.16792

Abstract

Achievement student selection aims to appreciate students who have achieved an achievement, both in the academic and non-academic fields. This activity is carried out in stages, starting from departments, faculties, and universities, to the national level. In the selection process, several criteria were used: GPA, scientific work, presentation, English, and achievements were featured and involved several juries to avoid subjectivity in the assessment. This study aims to get the best results from the decision support system in Achievement student election in the Mathematics Department of Jember University. Therefore, we need the fuzzy TOPSIS method to avoid and minimize problems and to make multi-criteria decision-making easier. This study's ranking results were obtained from the fuzzy TOPSIS method and standardized assessment method (based on higher education guidelines). From the four candidates who participated in this selection, the two methods give different results in the last two ranks. The fuzzy TOPSIS method ranking shows the results sequentially for candidates B, C, A, and D. In contrast, and the standardized assessment method ranking shows the results sequentially for candidates B, C, D, and A. This difference is caused by the value of the criteria factor and the weight of the candidate criteria, but the fuzzy TOPSIS method is simpler than the standardized assessment method. So that it can be recommended for the next period achievement student election at the department, faculty, or university level.
Development Design Labako Batik with Combine Fractal Geometry Dragon Curve and Tobacco Leaf Motif Wulandari, Eka Yuni; Purnomo, Kosala Dwidja; Kamsyakawuni, Ahmad
Jurnal ILMU DASAR Vol 18 No 2 (2017)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1410.076 KB) | DOI: 10.19184/jid.v18i2.5650

Abstract

Labako Batik is a typical batik Jember, derived from the term "La Bako" is the language of Madura that describes the activities of farmers to plant and process the leaves of tobacco. The resulting motives are inspired by the potential of natural resources in Jember such as tobacco, cocoa, dragon fruit, coffee, bamboo, birds and butterflies. The selection of tobacco leaf pattern because Jember Regency as one of the best tobacco producing cities in Indonesia, so that the form of tobacco leaf becomes the most dominant characteristic in making Batako Labako. In recent years the application of fractal forms in batik began to be popularly known as fractal batik. Fractal batik is batik whose design is made with mathematical formulas done with computer technology. Development of Labako batik motif by generating the pattern of tobacco leaves using L-System and then combining with the fractal geometry of dragon curve that has been modeled, using techniques of geometry transformation in Matlab software. Keywords: labako batik, tobacco leaf, fractal, dragon curve, l-system
Implementasi Algoritma Reversed Vigenere Encryption pada Pengamanan Citra Santoso, Ahmad Rico; Riski, Abduh; Kamsyakawuni, Ahmad
BERKALA SAINSTEK Vol 6 No 2 (2018)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v6i2.9224

Abstract

Pengamanan data atau informasi penting dilakukan untuk mencegah bocornya suatu pesan atau informasi kepada orang yang tidak berhak menerima. Pengamanan suatu data dapat dilakukan dengan menggunakan suatu teknik penyandian yang dinamakan dengan kriptografi. Pada penelitian ini, data yang digunakan adalah pesan/informasi berupa citra RGB sebanyak 10 buah citra. Pesan atau informasi pada penelitian disandikan menggunakan algoritma Reversed Vigenere Encryption. Tujuan dari penyandian citra RGB ini adalah untuk mengetahui bagaimana langkah-langkah enkripsi dan dekripsi serta hasil keamanan dari penyandian citra terhadap serangan-serangan kriptoanalisis. Adapun metode yang digunakan untuk menganalisis hasil enkripsi adalah anilisis histogram dan analisis diferensial. Hasil dari proses enkripsi dan dekripsi citra dapat dilakukan dengan baik namun masih menghasilkan cipherimage yang membentuk sebagian pola dari citra asli sehingga mudah ditebak oleh seseorang. Pada analisis histogram nilai-nilai pixels dari cipherimage belum menyebar secara merata sehingga hasil dari enkripsi citra masih memiliki ketahanan yang lemah terhadap serangan-serangan kriptoanalisis tipe statistik. Pada analisis diferensial, nilai NPCR menghasilkan nilai 100% yang berarti setiap pixels pada citra asli berubah bentuk secara total. Kata Kunci: Kriptografi, Citra RGB, Reversed Vigenere Encryption.
Perbaikan Citra Inframerah dengan Metode Divide-Conquer dan Metode Histogram Equalization Kaesardi, Dinda Septika; Riski, Abduh; Kamsyakawuni, Ahmad
BERKALA SAINSTEK Vol 6 No 2 (2018)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v6i2.9226

Abstract

CCTV (Closed Circuit Television) atau kamera pengawas yang berbasis inframerah banyak dijumpai di tempat-tempat umum seperti persimpangan jalan, perkantoran, pertokoan, dll. Inframerah merupakan suatu radiasi elektromagnetik yang di dalam kamera CCTV berfungsi untuk mengadaptasi gambar dalam keadaan kurang cahaya menjadi terlihat oleh mata dalam mode grayscale. Namun, citra inframerah ini mengalami sedikit derau (noise), kurang tajam, kabur, dsb. Sehingga diperlukan suatu proses perbaikan citra. Penelitian ini akan membahas perbandingan metode Histogram Equalization dan Divide-Conquer, kemudian kedua citra hasil dibandingkan berdasarkan visual dan Liniear Index of Fuzziness. Berdasarkan hasil penelitian, metode Divide-Conquer menghasilkan kualitas citra yang lebih baik secara visual ataupun dengan Linear Index of Fuzziness dibanding dengan Histogram Equalization. Jika dengan dibandingkan dengan citra asli, kedua metode menghasilkan citra yang lebih baik. Namun, hasil citra Histogram Equalization lebih terang sehingga ada beberapa detail citra yang hilang. Kata Kunci: Perbaikan citra, citra inframerah, Histogram Equalization, Divide-Conquer, Linear Index of Fuzziness.
Text Insertion and Encryption Using The Bit-Swapping Method in Digital Images Santoso, Kiswara Agung; Fakih, Muhammad Fahmil; Kamsyakawuni, Ahmad
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.7395

Abstract

Communication is an essential aspect of everyday life, involving the transmission of information through various media. Technological advances have made communication easier but have also increased privacy and data security risks. Several efforts are made to maintain the security of digital information, including coding information (cryptography) and hiding information (steganography). In this article, the author secures information through a combination of cryptography and steganography. To secure text data, we encrypt by exchanging bits between adjacent characters. Subsequently, the encrypted text is hidden within an image. The security analysis results show the successful reconstruction of the message from the stego image and the successful restoration of the message to its original form. The use of the bit swapping method in the text message encryption process has been proven to enhance the security level of the ciphertext, as indicated by the lower TPK calculation value of 0.33 compared to the TPK value in previous studies. Additionally, embedding the ciphertext into digital images has been demonstrated to further increase the security level of the message, evidenced by the NPCR calculation value of 0.0000109% and the UACI calculation value of 0.000000555%. These very small values indicate no significant changes.
Comparison Classification Of Tomatoes Ripeness Based On RGB, HSV And CMYK Colors Based On Correlation Coefficient Kiswara Agung Santoso; Kamsyakawuni, Ahmad; Siti Virna Rohmatul Izza
Journal of Computers and Digital Business Vol. 3 No. 3 (2024)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v3i3.410

Abstract

This article discusses the classification of tomato fruit maturity based on color space. Several studies have been conducted to measure maturity levels using RGB and HSV color spaces. In this article, researchers classify the ripeness of tomatoes using the CMYK color space, which researchers have never done before. Next, the classification results of the CMYK color space are compared with the RGB and HSV color spaces. The CMYK color space is a secondary color commonly seen by the human eye. CMYK colors are colors produced from a combination of RGB colors. Comparison of classification results based on CMYK, RGB, and HSV color spaces was carried out using the correlation coefficient and mean square error (MSE). The correlation coefficient is a method that is often used to measure the similarity between 2 images, where the closer to 0 the correlation value, the better
Determining The Ripeness Level Of Crystal Guava Fruit Using Backpropagation Neural Network Shofia Nabila Azzahra; Ahmad Kamsyakawuni; Abduh Riski
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 15 No 03 (2024): Vol.15, No. 3 December 2024
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2024.v15.i03.p04

Abstract

The ripeness of crystal guava fruit is currently sorted conventionally by analyzing the colour of the rind visually with the human eye. However, this method has several weaknesses that result in low accuracy and inconsistency. Therefore, automatic determination of ripeness level is necessary to increase accuracy and obtain precise information. This research uses the HSI colour space as an interpretation of fruit image characteristics and uses the Backpropagation algorithm to perform classification. This study utilizes image data of crystal guava fruit, categorizing them into four stages of ripeness: unripe, half-ripe, ripe, and very ripe. There are 140 fruit image data with 35 data for each ripeness category. Each image will be processed with median filter, cropping and segmentation. The HSI value will be taken from the image and processed at the classification stage using the Backpropagation algorithm. In classification using Backpropagation Neural Network, the best network model in this study was achieved in the 3 10 4 network architecture with a binary sigmoid activation function, learning rate = 0.3, and batch size = 64. This model produces a loss value of 0.5364 with an accuracy of 0.9 in testing process.
Sistem Biometrik Pengenalan Wajah dengan Metode Grey Level Co-Occurrence Matrix dan Support Vector Machine Adhitiyah Redaya Kusuma Bhakti; Abduh Riski; Ahmad Kamsyakawuni
IJAI (Indonesian Journal of Applied Informatics) Vol 7, No 2 (2023)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v7i2.69069

Abstract

Abstrak Teknologi biometrik wajah dikembangkan untuk mengenali seseorang secara unik. Pada penelitian ini biometrik diaplikasikan pada aplikasi pengenalan wajah dengan citra wajah manusia sebagai objeknya menggunakan metode Grey Level Co-Occurrence Matrix dan Support Vector Machine. Metode GLCM merupakan metode yang digunakan untuk proses ekstraksi fitur citra. Sedangkan SVM digunakan untuk proses pengenalan/identifikasi. Tujuan dari penelitian ini adalah mendapat hasil akurasi yang baik untuk pengenalan wajah melalui kedua metode yang digunakan. Hasil yang diperoleh dari penelitian ini adalah akurasi pada data pelatihan sebesar 93% dengan total 200 citra wajah. Sedangkan pada data pengujian diperoleh akurasi sebesar 90% untuk 50 citra wajah.===================================================AbstractFacial biometric technology was developed to uniquely recognize a person. In this research, biometrics was applied to face recognition applications with human face images as objects using the Gray Level Co-Occurrence Matrix and Support Vector Machine methods. The GLCM is a method used for the image feature extraction process. While SVM is used for the identification process. The purpose of this research is to get good accuracy results for face recognition through the two methods used. The results obtained from this research are the accuracy of the training data by 93% with a total of 200 face images. While the test data obtained an accuracy of 90% for 50 face images.
MEDICAL IMAGE ENCRYPTION USING DNA ENCODING AND MODIFIED CIRCULAR SHIFT Santoso, Kiswara Agung; Kamsyakawuni, Ahmad; Seggaf, Muhammad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1010.265 KB) | DOI: 10.30598/barekengvol16iss1pp233-240

Abstract

This paper proposes a new encryption method for the encryption of medical images. The method is used to divide the image into several blocks and then scramble the image blocks using DNA chains and then shift the pixels in a circle with certain rules. To provide a more secure result, the input key contains a DNA chain and is equipped with complementary rules, and is converted into a hexadecimal number using a DNA coding table. Experimental results and values of NPCR and UACI show that the scheme achieves good encryption and decryption results.
APPLICATION FUZZY MAMDANI TO DETERMINE THE RIPENESS LEVEL OF CRYSTAL GUAVA FRUIT Kamsyakawuni, Ahmad; Riski, Abduh; Khumairoh, Anisa Binti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.239 KB) | DOI: 10.30598/barekengvol16iss3pp1087-1096

Abstract

Crystal guava is one of Indonesia's flora diversity. The rind of the unripe crystal guava fruit is green, and the rind of the ripe crystal guava fruit is yellowish green. However, it is difficult to determine the ripeness of crystal guava due to the similar color of the fruit skin. Determining fruit ripeness is uncertain and therefore requires a way to deal with this uncertainty. One of the methods you can use is fuzzy Mamdani. In this study, the ripeness level of crystal guava is determined using fuzzy Mamdani. Crystal guava fruits fall into four ripeness categories: raw, half ripe, ripe, and very ripe. The data used is in the form of an RGB image separated from the background so that only crystal guava fruit objects are captured. The image of the fruit object was then extracted by looking for the median red, green, and blue at each pixel of the image. This value is used as input for the fuzzy Mamdani process. The fuzzy set and fuzzy rules that have been formed can be applied to determine the maturity level of crystal guava fruit by validating the results of 140 image data with an accuracy of 83,5%.