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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Buana Informatika Atrium : Jurnal Arsitektur Technologia: Jurnal Ilmiah Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) IJITEE (International Journal of Information Technology and Electrical Engineering) BALANGA: Jurnal Pendidikan Teknologi dan Kejuruan Belom Bahadat : Jurnal Hukum Agama Hindu Indonesian Community Journal Jurnal Atma Inovasia JOINTECOMS (Journal of Information Technology and Computer Science) Journal of Artificial Intelligence in Architecture Scientica: Jurnal Ilmiah Sains dan Teknologi Diteksi : Jurnal Pengabdian Kepada Masyarakat Satya Dharma: Jurnal Ilmu Hukum
Kristianti, Novera
Universitas Palangka Raya
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Journal : Jurnal Buana Informatika

 1 
Analisis Pengaruh Citra Gelap, Normal, Terang Terhadap Wavelet Orthogonal Kristianti, Novera; Purnawati, Niwayan; Rolando, Bryand
Jurnal Buana Informatika Vol 9, No 2 (2018): Jurnal Buana Informatika Volume 9 Nomor 2 Oktober 2018
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.769 KB) | DOI: 10.24002/jbi.v9i2.1698

Abstract

Abstract. An image is classified into dark, normal, and bright image. The images are grouped in the dark images according to the histogram and the mu value. An image consists of information and redundancies. The use of wavelet is considered effective in image compression and it does not only cut down the memory usage but also it makes devices work faster. In this study, an analysis in conducted on the influence of dark, normal, and bright images on the orthogonal wavelet. Peak Signal to Noise Ratio (PSNR) is used to compare 17 functions of wavelet orthogonal in the image compression of dark, normal, and bright images. PSNR is a measurement parameter commonly used for measuring the quality of image reconstruction which is then compared with the original image. Compression ratio is used to measure the reduction of the data size after the compression process. Based on the research on the dark, normal, and bright image, the findings reveal that bright image has got the lowest PNSR value at all image testing while the normal image has the highest PSNR value at the wavelet orthogonal application. Keywords : Image compression, Orthogonal wavelet, PSNR, compression ratio.Abstrak. Suatu citra dikelompokkan menjadi citra gelap, citra normal, dan citra terang. Pengelompokan citra menjadi warna gelap terlihat dari histogram dan nilai rerata intensitas (mu). Citra terdiri atas informasi dan redudansi. Penggunaan wavelet dinilai efektif dalam kompresi citra dan menurunkan penggunaan memori serta membuat perangkat menjadi lebih cepat. Pada penelitian ini, dilakukan analisis pengaruh citra gelap, citra normal, dan citra terang terhadap wavelet orthogonal. Peak Signal to Noise Ratio (PSNR) digunakan untuk membandingkan 17 fungsi wavelet orthogonal dalam kompresi citra gelap, citra normal, dan citra terang. PSNR adalah parameter ukur yang sering digunakan untuk pengukuran kualitas gambar rekonstruksi, yang lalu dibandingkan dengan gambar asli. Rasio kompresi digunakan untuk mengukur pengurangan ukuran data setelah proses kompresi. Berdasarkan penelitian pada citra gelap, citra normal, dan citra terang diperoleh bahwa citra terang menghasilkan nilai PSNR paling kecil untuk seluruh citra uji dan citra normal menghasilkan nilai PSNR paling besar dalam penerapan wavelet orthogonal. Kata kunci : Kompresi citra, Wavelet orthogonal, PSNR, rasio kompresi.
Analisis Pengaruh Citra Gelap, Normal, Terang Terhadap Wavelet Orthogonal Novera Kristianti; Niwayan Purnawati; Bryand Rolando
Jurnal Buana Informatika Vol. 9 No. 2 (2018): Jurnal Buana Informatika Volume 9 Nomor 2 Oktober 2018
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v9i2.1698

Abstract

Abstract. An image is classified into dark, normal, and bright image. The images are grouped in the dark images according to the histogram and the mu value. An image consists of information and redundancies. The use of wavelet is considered effective in image compression and it does not only cut down the memory usage but also it makes devices work faster. In this study, an analysis in conducted on the influence of dark, normal, and bright images on the orthogonal wavelet. Peak Signal to Noise Ratio (PSNR) is used to compare 17 functions of wavelet orthogonal in the image compression of dark, normal, and bright images. PSNR is a measurement parameter commonly used for measuring the quality of image reconstruction which is then compared with the original image. Compression ratio is used to measure the reduction of the data size after the compression process. Based on the research on the dark, normal, and bright image, the findings reveal that bright image has got the lowest PNSR value at all image testing while the normal image has the highest PSNR value at the wavelet orthogonal application. Keywords : Image compression, Orthogonal wavelet, PSNR, compression ratio.Abstrak. Suatu citra dikelompokkan menjadi citra gelap, citra normal, dan citra terang. Pengelompokan citra menjadi warna gelap terlihat dari histogram dan nilai rerata intensitas (mu). Citra terdiri atas informasi dan redudansi. Penggunaan wavelet dinilai efektif dalam kompresi citra dan menurunkan penggunaan memori serta membuat perangkat menjadi lebih cepat. Pada penelitian ini, dilakukan analisis pengaruh citra gelap, citra normal, dan citra terang terhadap wavelet orthogonal. Peak Signal to Noise Ratio (PSNR) digunakan untuk membandingkan 17 fungsi wavelet orthogonal dalam kompresi citra gelap, citra normal, dan citra terang. PSNR adalah parameter ukur yang sering digunakan untuk pengukuran kualitas gambar rekonstruksi, yang lalu dibandingkan dengan gambar asli. Rasio kompresi digunakan untuk mengukur pengurangan ukuran data setelah proses kompresi. Berdasarkan penelitian pada citra gelap, citra normal, dan citra terang diperoleh bahwa citra terang menghasilkan nilai PSNR paling kecil untuk seluruh citra uji dan citra normal menghasilkan nilai PSNR paling besar dalam penerapan wavelet orthogonal. Kata kunci : Kompresi citra, Wavelet orthogonal, PSNR, rasio kompresi.
Co-Authors Ahmad Abdul Hadi Albertus Joko Santoso Alif Tuharea, Mohammad Andhika Maharani, Anastasya Andrea Micelle, Fito Anugrahnu, Dian Putra Aprilita Aprilita Ariesta Lestari Asri Fridtriyanda Audy Mirelia W.S Aviedo Murel, Muhammad Bobby Frana, Muhammad Breby Franksoa Tarigan, Fajar Bryand Rolando Deo Eka Putra, Rholand Deria Girace Gebrila, Desi Efrans Christian Febri Yoga Saputra, Mochammad Felicia Sylviana Fernando, Samuel Fransisco, Theo Gedeon Grivaldi, Antonio Delano Hartono, Timothy Priambodo Jadiaman Parhusip, Jadiaman Kristian, Erick Kristiani, Margareta Kudadiri, Angelina Kurniasi, Ririn Leonardo, Tomas Lusia Kiareni, Cindi Mahatmanti , Anin Dita Maria, Firda Kristeni Nabila Edison, Wafiq Nahumi Nugrahaningsih Natasya, Apriliani Niwayan Purnawati Nova Noor Kamala Sari Nurika Nurlia Eka Damayanti Okta Onie D. Sanitha Onie D. Sanitha Onie Dian Sanitha Onie Dian Sanitha Pebrian Siregar, Efrandi Pranowo Pranowo Priskila, Ressa Purnawati, Niwayan Putra, Putu Bagus Adidyana Anugrah Putri, Jesica Paskaria Putri, Oktaviani Enjela Rahman Maulana, Aulia Rahman, Resha Ananda Raka Yustianto, Samuel Ressa Priskila Rinsaghi, Yudha Rolando, Bryand Sanjayanto Nugroho Saputri, Belia Septa Natalina, Melinda Septian Geges Septian Geges Silvia, Putri Sorisa, Cinda Taufiqurahman Theo Fransisco Theo Fransisco Theo Fransisco Valerius Wilson, Yonas Viktor Handrianus Pranatawijaya Watie W.N, Rusma Widiatry Widiatry, Widiatry Wirayuda, Akbar Yunida Iashania Yusuf Aditya Sihombing Zulfina, Safira