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All Journal JURNAL SISTEM INFORMASI BISNIS JOIV : International Journal on Informatics Visualization Jukung (Jurnal Teknik Lingkungan) Comment: an International Journal of Community Development Jurnal IMPACT: Implementation and Action Musamus Journal Of Research Information and Communication Technology JISKa (Jurnal Informatika Sunan Kalijaga) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Journal of Applied Computer Science and Technology (JACOST)
Nahdi Saubari
Universitas Muhammadiyah Banjarmasin
Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Other

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Journal : JURNAL SISTEM INFORMASI BISNIS

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Deteksi Objek Terapung pada Sungai Martapura dengan Metode Haar Like Feature Menggunakan Kamera Smart Phone Saubari, Nahdi; Ansari, Rudy; Gazali, Mukhaimy
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 2 (2019): Volume 9 Nomor 2 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (539.415 KB) | DOI: 10.21456/vol9iss2pp141-148

Abstract

Martapura river is the center of Banjarmasin’s local life, especially for water transportation and its famous floating market tourism spot. Due to various floating objects in Martapura river, a method to detect those objects is needed to control the condition of the river. In general, there are several methods to detect objects such as Gaussian, Support Vector Machine (SVM), Independent Component Analysis (ICA) and the newest method called Haar Like Feature (HLF). Those first three methods often used to detect moving object, while HLF mostly used to detect human’s face. This research aimed to examine the use of HLF method to detect floating objects in Martapura river by using smartphone’s camera with the specification of 16Megapixel and 1080p resolution. The data collected with random sampling technique in two different spots in Banjarmasin at different times. Images and videos then examined using HLF method. The result shows that HLF method by using smartphone camera cannot be used to identify any floating objec
Jaringan Syaraf Tiruan Perambatan Balik Untuk Pengenalan Wajah Saubari, Nahdi; Isnanto, Rizal; Adi, Kusworo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 6, No 1 (2016): Volume 6 Nomor 1 Tahun 2016
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.153 KB) | DOI: 10.21456/vol6iss1pp30-37

Abstract

This research discusses about face detection and face recognition in an image. Face detection has only two classifications, i.e face and not face. Face recognition is compatible with some classifications of a number individuals who want to be recognized. Face detection and face recognition in thi study using Haar-Like Feature method and Artificial Neural Network Backpropagation. A method Haar-Like Feature used for detection and extraction in an image, because the clasification on this method showed success at used to detect image of the face. Artificial Neural Network Backpropagation is a training algorithm that is used to do training simulated on facial image data training stored in a database. This study uses Ms. Excel 2007 as database with 10 individual sample image, every image in each individuals having three distance with every range has four defferent light intensities, so that the data training stored in the database reached 120 data training. The results shows that the face detection and face recognition which is developed can recognize a face image with an average accuracy rate reaches 80,8% for each distance.
Co-Authors Ahadi Ningrum, Ayu Finki Dona Marleny Gazali, Mukhaimy Hanny Maria Caesarina Kamaruddin Kusworo Adi Mambang Maulida, Ihdalhubbi Muhammad Syahid Febriadi Muhammad Syahid Pebriadi Mukhaimy Gazali Munsyi Munsyi Novriansyah, Irvan R Rizal Isnanto Rudy Ansari Rudy Ansari, Rudy Siti Ratna Sari Windarsyah Windarsyah