Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding

Anandita, Ida Bagus Gede; Gunadi, I Gede Aris; Indrawan, Gede

doi:10.31598/sintechjournal.v1i1.179

Cited by 4 publications

(5 citation statements)

References 1 publication

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“…Pada penelitian sebelumnya [20] berhasil memanipulasi gambar yaitu pada gambar medis sinar-x dengan mengecilkan ukuran penyimpanan gambar, namun gambar yang dihasilkan tetap terlihat dengan jelas melalui perbandingan algoritma Run Length Encoding, Huffman, dan Lempel Ziv Welch. Pada saat memanipulasi gambar tidak hanya dengan mengecilkan ukuran gambar contohnya dengan meningkatkan kontras pada gambar atau mengubah dan menambahkan objek pada gambar [21] [22].…”

Section: Pendahuluanunclassified

Implementasi Steganografi Gambar Menggunakan Algoritma Generative Adversarial Network

Khairunnisak,

Fahmi,

Suhartono

2023

SINTECH Journal

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Abstract In the era of information technology, it is very important to protect data and information so that irresponsible parties do not misuse it. One technique for securing data is steganography. Steganography is a technique of hiding messages in a medium. One of the media for hiding messages is pictures. However, steganography techniques can still be detected by steganalysis techniques. Steganalysis is a technique for analyzing hidden messages in steganography. Therefore this study applies image processing techniques with the Generative Adversarial Network algorithm model, which aims to manipulate images so that steganalysis techniques cannot detect hidden messages. Proof of the results of applying the Generative Adversarial Network algorithm using a web-based application containing message hiding and extraction functions. The results obtained are that the Generative Adversarial Network algorithm can be applied to create mock objects, and images can revive based on training data which is a model for how the algorithm works. In addition, the results of testing the Generative Adversarial Network algorithm were successfully applied to image steganography which functions to prevent steganalysis techniques from trying to detect messages in images. Future research is expected to be able to select steganographic images other than the results from the training data model according to the original size chosen randomly according to the selection of the user.

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Section: Pendahuluanunclassified

Implementasi Steganografi Gambar Menggunakan Algoritma Generative Adversarial Network

Khairunnisak,

Fahmi,

Suhartono

2023

SINTECH Journal

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“…Uji akurasi dilakukan untuk mengetahui tingkat akurasi dengan mencari nilai kesalahan dan korelasi terhadap suatu metode dalam penyelesaian masalah [9] [10]. Uji akurasi bisa juga dilakukan dengan melakukan uji kinerja metode untuk menganalisa dan melakukan perbandingan hasil [11]. Selanjutnya hasil peramalan dianalis kemudian dikaji dengan kombinasi metode yang berbeda untuk meningkatkan akurasi hasil.…”

Section: Pendahuluanunclassified

Pendekatan Z-Score Dan Fuzzy Dalam Pengujian Akurasi Peramalan Curah Hujan

Radhitya¹,

Sudipa²

2020

SINTECH Journal

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Determination of rainfall is important to determine the intensity of rain that occurs in an area. Rain intensity that is too high will certainly have a bad impact. Forecasting or prediction techniques are used to determine the likelihood of intensity occurring in the following year. However, rainfall data are continuous numerical data. Measurement of accuracy becomes more difficult if the data type is like that. So, this study tests the accuracy of rainfall forecasting in the city of Denpasar from a different perspective. This test combines the Z-score method and the Fuzzy set theory to normalize and classify rainfall data. This combination determines the degree of rainfall membership divided into Upper, Middle, and Lower levels. Based on the results of rainfall accuracy testing starting in 2012-2016 obtained an average value of accuracy of 85% with training data that is data in 2007-2015. The normalization process greatly affects the value of the training data.

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“…KB ini selanjutnya akan digunakan sebagai dasar dari Machine Learning System sebagai pengetahuan awalnya. Terdapat beberapa contoh algortima diantaranya Run Length Encoding, Huffman, dan Lempel Ziv Welch [17]. Namun pada penelitian ini menggunakan algoritma Radial Basis Function Network (RBFN).…”

Section: Metodeunclassified

Perancangan Pengujian Preference Test, Uji Hedonik Dan Mutu Hedonik Menggunakan Algoritma Radial Basis Function Network

2019

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Wheat Bread producers are required to produce quality products and are liked by consumers. Increasing the quality of bread will certainly have an impact on sales to be generated. One of the efforts in improving the quality is by doing Hedonic test and Hedonic Quality test. This study aims to develop a system capable of providing an assessment of new products to be released on the market. Hedonic quality is used as a variable for assessing bread products with 4 variables, which include flavor, taste, appearance, and texture. While the hedonic test using six classes is very very like, very like, like, rather like, and do not like, then this result will be used as a class of Knowledge Based (KB). This research uses Radial Basis Function Network (RBFN) algorithm, yielding 98,8% accuracy with 10 fold testing technique. The final goal of the development of this system will create a system capable of providing an assessment of a wheat bread product.

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Analisis Kinerja Dan Kualitas Hasil Kompresi Pada Citra Medis Sinar-X Menggunakan Algoritma Huffman, Lempel Ziv Welch Dan Run Length Encoding

Cited by 4 publications

References 1 publication

Implementasi Steganografi Gambar Menggunakan Algoritma Generative Adversarial Network

Implementasi Steganografi Gambar Menggunakan Algoritma Generative Adversarial Network

Pendekatan Z-Score Dan Fuzzy Dalam Pengujian Akurasi Peramalan Curah Hujan

Perancangan Pengujian Preference Test, Uji Hedonik Dan Mutu Hedonik Menggunakan Algoritma Radial Basis Function Network

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