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All Journal Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknologi dan Rekayasa Techno.Com: Jurnal Teknologi Informasi Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Ilmiah Matrik Jurnal Teknik Informatika (JUTIF) Jurnal Teknik dan Science (JTS) Jurnal Pengabdian Masyarakat Tapis Berseri Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat SOROT: Jurnal Pengabdian Kepada Masyarakat
Condro Wibawa
Universitas Gunadarma
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Other

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Journal : Jurnal Ilmiah Matrik

 1 
KOMPARASI KECEPATAN HADOOP MAPREDUCE DAN APACHE SPARK DALAM MENGOLAH DATA TEKS Condro Wibawa; Setia Wirawan; Metty Mustikasari; Dessy Tri Anggraeni
Jurnal Ilmiah Matrik Vol 24 No 1 (2022): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v24i1.1649

Abstract

Istilah Big Data saat ini bukanlah hal yang baru lagi. Salah satu komponen Big Data adalah jumlah data yang masif, yang membuat data tidak bisa diproses dengan cara-cara tradicional. Untuk menyelesaikan masalah ini, dikembangkanlah metode Map Reduce. Map Reduce adalah metode pengolahan data dengan memecah data menjadi bagian-bagian kecil (mapping) dan kemudian hasilnya dijadikan satu kembali (reducing). Framework Map Reduce yang banyak digunakan adalah Hadoop MapReduce dan Apache Spark. Konsep kedua framework ini sama akan tetapi berbeda dalam pengelolaan sumber data. Hadoop MapReduce menggunakan pendekatan HDFS (disk), sedangkan Apache Spark menggunakan RDD (in-memory). Penggunaan RDD pada Apache Spark membuat kinerja framework ini lebih cepat dibandingkan Hadoop MapReduce. Hal ini dibutktikan dalam penelitian ini, dimana untuk mengolah data teks yang sama, kecepatan rata-rata Apache Spark adalah 4,99 kali lebih cepat dibandingkan Hadoop MapReduce.
Perbaikan Citra Tanda Tangan Digital Menggunakan Metode Otsu Thressholding dan Sauvola Dessy Tri Anggraeni; Condro Wibawa
Jurnal Ilmiah Matrik Vol 25 No 1 (2023): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v25i1.2324

Abstract

Abstract : The digital era forces people to digitize in all fields. Digital product that is often found is digital image. One kind of digital image application is the use of a digital image signature embedded in a document. However, often the results are unsatisfactory, such as background color problems, noise, lack of clarity, etc. The quality of digital image signatures can be improved by implementing the Otsu Thresholding and Sauvola methods. These two methods were chosen because they are widely used in document image quality improvement. The purpose of this study is to produce a better digital image signature and to compare the performance of these two methods. The results showed that the quality of the images produced by these two methods was better than the original image or by using standard filters from a word processing application. Meanwhile, from the two methods used, Sauvola's method was slightly better than Otsu's method. In terms of visual evaluations, the Sauvola method total score is 13 compare to Otsu method score that is 11. Meanwhile, the PSNR ratio show that the two methods give the same results, that is 34,571 db.
Perbaikan Citra Tanda Tangan Digital Menggunakan Metode Otsu Thressholding dan Sauvola Dessy Tri Anggraeni; Condro Wibawa
Jurnal Ilmiah Matrik Vol 25 No 1 (2023): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v25i1.2324

Abstract

Abstract : The digital era forces people to digitize in all fields. Digital product that is often found is digital image. One kind of digital image application is the use of a digital image signature embedded in a document. However, often the results are unsatisfactory, such as background color problems, noise, lack of clarity, etc. The quality of digital image signatures can be improved by implementing the Otsu Thresholding and Sauvola methods. These two methods were chosen because they are widely used in document image quality improvement. The purpose of this study is to produce a better digital image signature and to compare the performance of these two methods. The results showed that the quality of the images produced by these two methods was better than the original image or by using standard filters from a word processing application. Meanwhile, from the two methods used, Sauvola's method was slightly better than Otsu's method. In terms of visual evaluations, the Sauvola method total score is 13 compare to Otsu method score that is 11. Meanwhile, the PSNR ratio show that the two methods give the same results, that is 34,571 db.
Co-Authors Ahmad MAULANA Alamsyah, Rafly Dessy Tri Anggraeni Mariska, Vinna Metty Mustikasari Metty Mustikasari Setia Wirawan Tri Anggraeni, Dessy Tri Anggraeni, Dessy Wijaya Kusuma