Found 3 Documents

Aplikasi Informasi Penyakit Hepatitis Hendra, Hendra; Sevani, Nina; Fredicia, Fredicia
Teknik dan Ilmu Komputer vol. 03 no. 09 Januari-Maret 2014
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar


Pengembangan Model Pengenalan Wajah Manusia dengan Teknik Reduksi Dimensi Bi2DPCA dan Support Vector Machine sebagai Classifier Fredicia, Fredicia; Buono, Agus; Giri, Endang Purnama
Ultimatics : Jurnal Teknik Informatika Vol 8 No 1 (2016): Ultimatics: Jurnal Ilmu Teknik Informatika
Publisher : Program Studi Teknik Informatika UMN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.244 KB) | DOI: 10.31937/ti.v8i1.497


This paper presents the modeling of face recognition using feature extraction based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) as a classifier. Three PCA techniques were compared, they are 1DPCA, 2DPCA and Bi-2DPCA. Meanwhile, three type of SVM kernel functions-linear, polynomial, and radial basis function (RBF) were used. The experiment used the ORL Face Database AT&T Laboratory, which contain 400 images with 10 images per each person. The leave one out method is used for validating each pair of extraction and classifier method. The highest accuracy is obtained by a combination of linear kernel and Bi-2DPCA85%, with 94.25%, and also the fastest computation time, is 15.34 seconds. Index Terms— Face Recognition, Principle Component Analysis, Kernel, Support Vector Machine, Leave-one Out Cross Validation
Aplikasi Smart Investment Planner Berbasis Web K., Prasetya; K., Endah; Fredicia, Fredicia
ComTech: Computer, Mathematics and Engineering Applications Vol 6, No 2 (2015): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v6i2.2272


The lack of knowledge of investment products lead many people decided not to invest for their future. This can be overcome by utilizing the information and communication technology development by making a web application of Smart Investment Planner with the aim to recognize various types of investment product as well as the character investment and tips for users. This application uses a set of data as knowledge base which obtained from the literature, discussions with economic experts, database design, user interface design, as well as tests and evaluations by experts. The result of these applications concluded that this application collect the information as well as investment products that suit into their needs and also encourage them to start invest.