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Pengukuran Perubahan Kualitas Warna Kain Tenun Malaka Berdasarkan Perbandingan Nilai RGB, MSE dan PSNR Bere, Maria Vianey Mega; Nani, Paskalis Adrianus; Mau, Sisilia Daeng Bakka; Siki, Yovinia Carmeneja Hoar; Jando, Emanuel; Bria, Yulianti Paula
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 4 No. 1 (2024): Juni 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v4i1.9215

Abstract

Kain tenun Malaka adalah kain tenun tradisional yang khas dari Kabupaten Malaka. Kain tenun Malaka memiliki makna, nilai, warna dan motif yang unik. Pewarnaan kain tenun dilakukan dengan pewarna alami dan buatan. Penggunaan detergen dan penjemuran kain tenun di bawah terik matahari akan menyebabkan hilangnya motif yang diinginkan, pudarnya warna kain, kualitas benang tidak tahan lama dan dapat mengurangi warna atau nilai estetika dari kain tenun. Pengetahuan ini kurang diketahui oleh masyarakat luas. Tujuan dari penelitian ini adalah untuk mengukur perubahan kualitas warna kain tenun Malaka apabila menggunakan detergen dan terpapar sinar matahari langsung. Kain tenun yang digunakan dalam penelitian ini terdiri dari tiga kain tenun dengan pewarna alami dan tiga kain tenun dengan pewarna buatan. Perbandingan nilai RGB, MSE dan PSNR digunakan untuk mengukur kualitas penurunan citra. Hasil pengujian menunjukkan adanya penurunan warna nilai RGB pada citra kain tenun, di mana adanya perubahan nilai Red, Green, dan Blue dari citra asli dengan citra sesudah dijemur. Nilai RGB kain tenun dengan pewarna alami 1 mengalami penurunan terbesar untuk warna red yang terjadi pada pukul 12.00-12.50 dengan persentase penurunan sebesar 31%. Persentase penurunan warna terbesar untuk green terjadi pada pukul 13.00-13.50 dengan persentase penurunan sebesar 39% dan persentase penurunan warna terbesar untuk blue terjadi pada pukul 11.00-11.50 dengan persentase penurunan sebesar 11%. Selain itu terdapat perubahan nilai MSE dan PSNR pada citra asli dan citra setelah dijemur yang menunjukkan adanya perubahan kualitas kain tenun. Hasil penelitian ini dapat mengedukasi masyarakat pengguna kain tenun Malaka agar dapat menjaga kualitas kain tenun dengan cara menghindari pencucian kain tenun menggunakan detergen dan penjemuran di bawah sinar matahari. Malaka woven fabric is a traditional woven fabric of Malaka District. Malaka woven fabric has unique meanings, values, colors, and motifs. Malaka woven fabric is colored with natural and artificial dyes. Using detergent and drying woven cloth in direct sunlight will cause the desired motif to disappear, the colors to fade, the thread to lose, the color to degrade and the aesthetic values of the woven fabric to be lost. This knowledge is less known by the society. This research aims to measure the decrease in the color quality of Malaka woven fabric when using detergent and exposed to direct sunlight. The woven fabrics used in this research consist of three woven fabrics with natural dyes and three woven fabrics with artificial dyes. Comparison of RGB, MSE and PSNR values ​​is used to measure the quality of image degradation. The test results show a decrease in the RGB color value in the woven fabric images, where there is a change in the Red, Green and Blue values ​​from the original images to the images after drying. The RGB value of woven fabric with natural dye 1 experienced the largest decrease for the red color which occurred at 12.00-12.50 with a decrease percentage of 31%. The largest percentage decrease in color for green occurred at 13.00-13.50 with a decrease percentage of 39% and the largest percentage decrease in color for blue occurred at 11.00-11.50 with a decrease percentage of 11%. Besides, there are changes in the MSE and PSNR values ​​in the original images and the images after drying, which indicates a change in the quality of the woven fabrics. The result of this research is essential to educate people who use Malaka woven fabrics to maintain the quality of woven fabrics by avoiding washing woven fabrics using detergent and drying in direct sunlight.
Perbandingan Metode Naïve Bayes dan K-Nearest Neighbor Terhadap Sentimen Analisis Pinjaman Online Yovinia Carmeneja Hoar Siki; Thomas Boris Asalodan Tokan; Donatus Joseph Manehat; Emerensiana Ngaga; Sisilia Daeng Bakka Mau
Jurnal Media Informatika Vol. 6 No. 3 (2025): Jurnal Media Informatika
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v6i3.5687

Abstract

This study aims to understand the public opinion in Indonesia regarding the existence of online loans. Online loans are a type of banking service through technology known as the Financial Technology (FinTech) Industry. According to a report by the Financial Services Authority, in August 2023, more than 13.37 million accounts were using this service. Online loan services are considered to provide convenience and comfort for consumers. However, many harmful cases have emerged, such as extremely high interest rates and aggressive debt collection practices that have caused public concern. Therefore, a sentiment analysis is conducted to understand public opinions, which can serve as a reference for online loan service providers and operators. By using 11,288 Indonesian-language tweets, the public opinion on online loans is analyzed. The study employs two sentiment analysis methods: Naïve Bayes and K-Nearest Neighbor. The results of the study show that the sentiment toward online loans is 62.29% negative, 33.19% neutral, and 5.52% positive. The results also indicate that the Naïve Bayes method has slightly higher accuracy (67%) compared to the K-Nearest Neighbor method (63%). It is hoped that this sentiment will have a positive impact on online loan service providers and operators.
Co-Authors Adri Gabriel Sooai Alfredo Abnit, Godefridus Alfry Aristo Jansen Sinlae Amfotis, David Andrianus Nani, Paskalis Angela Yunita Muti Anselmus Epi Jemagung Apelaby, Justinus Julio Krisna Azarya Bees Bala, Yustinus Jubiliano Ebang Bana, Mariana Sonya Anjela Sanam Bano, Maria Bano, Mariana Bei, Intan Sulistik Benyamin Lily, Budy Bere, Maria Vianey Mega Bria, Yunita Mildayani Putri Bruno C.N. Sutal, Anjelique Ceriana Kuanaben Clara, Emerensiana Aprilia Daeng Bakka Mau, Sisilia David Amfotis Donatus Joseph Manehat Donatus Joseph Manehat Emanuel Jando Emerensiana Ngaga Emerensiana Ngaga Emerensiana Ngaga Emerensiana Ngaga Emiliana Metan Meolbatak Eviana Nahak Ferdy Chanel D.rc Lay Frengky Tedy Frengky Tedy Gasperz, Elga Adeputra Hendrika Buik En Hokon, Sesilia Hingi Novita Sari Ignatius Pricher Agung Nirwanto Samane Imanuel Irvantus Nahak Joan Pierre Taolin Jose R . D. R X. Da Luz Joseph Manehat, Donatus Klotilda Olin Lalo, Aprilianus Kristianus Laurentino Da Costa Nunes Lediana Theresia Opat Maria Astiyani Nahak Maria J. Insantuan Maria Krisanti Ivoni Milo Maria Sinriana Maria Vianey Mega Bere Maximilianus Benge Meolbatak, Emiliana Metan Metkono, Beatrix Selia Mondolang, Alicia Herlin Naifio, Raynaldi Bouk Naikofi, Mauritius Ildo Rivendi Nani, Paskalis Adrianus Natalia Magdalena Rafu Mamulak Nikola Tolentini Nisa Aulia Pangu Loda, Januarya Paskalis Andrianus Nani Patrisius Batarius Pattiraja, Agustinus Harryanto Pattyraja, Agustinus Haryanto Paulina Aliandu Prasasto, Andrianus Robertus Dole Guntur Roselina Nanur Sabon Doni, Rikardus Sianturi, Shine Crossifixio Sisilia Daeng Bakka Mau Sisilia Daeng Bakka Mau Sisilia Daeng Bakka Mau Sisilia Daeng Bakka Mau Talo, Martinus Coreia Thomas Boris Asalodan Tokan Tualaka, Nugrah Salmo William S. Na Yansen Nurak, Eugenius Yohan Yefta Novemphi Nahak Yohanes LIm, Irvan Yohanes Mada Masa Yulianti Paula Bria