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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer
Rizal, Reyhan Achmad
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Computer Science & IT Decision Sciences, Operations Research & Management Education

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Klasifikasi Wajah Menggunakan Support Vector Machine (SVM) Rizal, Reyhan achmad; Girsang, Imron Sanjaya; Prasetiyo, Sidik Apriyadi
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 3 No. 2 (2019): Remik Volume 3 Nomor 2 April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.501 KB) | DOI: 10.33395/remik.v3i2.10080

Abstract

Klasifikasi wajah merupakan teknik yang dapat digunakan untuk membedakan karakteristik pola wajah seseorang. Sistem klasifikasi wajah adalah suatu aplikasi yang membuat sebuah mesin dapat mengenali wajah seseorang sesuai dengan citra wajah yang telah ditraining dan disimpan di dalam database mesin tersebut. Klasifikasi wajah sendiri dapat dilakukan dengan berbagai cara, salah satunya adalah menggunakan metode support vector machine (SVM). Penelitian ini dilakukan dengan sampling yang di ambil dalam variasi posisi pada sudut kemiringan subjek (-90°, -70°, -45°, -25°, -5° ) dan (+90°, +70°, +45°, +25°, +5° ) dengan ukuran citra 640x480. Sistem klasifikasi wajah didalam penelitian ini dibangun dengan menggunakan metode support vector machine (SVM) dan bahasa pemograman Matlap. Penelitian ini menghasilkan tingkat true detection 90% dan false detection 10% dari jumlah sampel 200 subjek yang digunakan. Keywords— Klasifikasi wajah, sudut kemiringan, SVM
Klasifikasi Kandungan Boraks Dalam Saos Tomat Melalui Citra Menggunakan GLCM Rizal, Reyhan Achmad; Susanto, Mario; Chandra, Andy
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (208.355 KB) | DOI: 10.33395/sinkron.v4i2.10508

Abstract

One of the food products that need to be reviewed for safety and is the most consumed is tomato sauce, although it contains a large amount of water in the sauce which has a long shelf life because it contains acid, sugar, salt, and is often given preservatives. The purpose of this study was to determine the tomato sauce using harmful preservatives such as the addition of borax. The dataset used in this study is the image of tomato sauce containing borax and not with the number of samples 400 images of tomato sauce with different comparison percentages starting from the image of tomato sauce with 70% borax content, image of tomato sauce with 50% borax content, image tomatoes with 30% borax content and image of tomato sauce that does not contain borax. A sampling of images using a camera phone brand xiaomi note 5 by mixing borax in the original sauce before the sample is used for the training and testing process. The classification results show the gray level co-occurrence matrix (GLCM) method is quite optimal in classifying tomato sauce data containing borax and not with an average percentage of the introduction of 88%.
Comparison of Machine Learning Classification Algorithms in Sentiment Analysis Product Review of North Padang Lawas Regency Yennimar, Yennimar; Rizal, Reyhan Achmad
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.962 KB) | DOI: 10.33395/sinkron.v4i1.10416

Abstract

The growth of SMEs in Indonesia, which has increased by 6% every year, is driven by continued growth by many parties, including the government and private institutions that often conduct business coaching and assistance. Problems that are often encountered are the lack of willingness of MSME business practitioners to apply information technology and the internet, besides that most of them live in rural areas with very limited internet access and many are not yet digital-literate, adequate digital technology utilization capabilities and the will of business people For SMEs to understand customer needs, a service that is consistent with standard service procedures will give a good impression and pay attention to customer feedback. This research was conducted by collecting data on MSME products obtained from the North Padang Lawas District Trade Industry Office followed by the development of a Paluta Market website as a marketplace for media promotion and marketing of MSME products in North Padang Lawas by applying a sentiment analysis approach using machine learning classification algorithm to produce product rating values based on public opinion of MSME products contained on the website, in addition the system is able to classify consumer comment data on MSME products from various sources from the umkm web, so that it becomes useful information for MSME businesses especially in North Padang Lawas Regency and the community at large. The results of the application of sentiment analysis of a product on the Paluta Market website can be used as a reference in improving service and product quality, so as to create a variety of new opportunities that are profitable for MSME businesses.
Analysis of Facial Image Extraction on Facial Recognition using Kohonen SOM for UNPRI SIAKAD Online User Authentication Rizal, Reyhan Achmad; HS, Christnatalis
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.265 KB) | DOI: 10.33395/sinkron.v4i1.10242

Abstract

Academic Information System (Sistem Informasi Akademik aka SIAKAD) Online of Universitas Prima Indonesia (UNPRI) is one of the applications used to facilitate the administration process of lectures which includes the filling process of study plan cards (Kartu Rencana Studi aka KRS), study result cards (Kartu Hasil Studi aka KHS), class schedules, submission of research titles, seminars, and other processes. SIAKAD UNPRI can be accessed by students, lecturers, and academics where every user has a password that has been encrypted to maintain the security of information from people who are not responsible, password security using the encryption method needs to be changed regularly, but there are still many students, lecturers and academic community who are reluctant to change passwords. To improve the security verification stage for SIAKAD users, we propose a face recognition feature approach. Face recognition is a feature that allows the identification of someone from a digital image or video. The way the facial recognition method works is by comparing face data from the camera or images with images that were previously stored in a database. In this study, the Kohonen SOM method is proposed for face identification based on the feature extraction approach of discrete cosine transform (DCT), linear discriminant analysis (LDA) and principal component analysis (PCA) to improve the security of UNPRI SIAKAD users. The analytical framework is done by requiring students to do face taking, where each student will save 5 (five) faces extracted with facial features using the DCT, LDA and PCA model approach, feature extraction results are used as input to the Kohonen SOM network for training and testing facial recognition, then analysis of the effect of DCT, LDA and PCA feature extraction on the Kohonen network on facial recognition accuracy.
Co-Authors Andy Chandra Girsang, Imron Sanjaya HS, Christnatalis Prasetiyo, Sidik Apriyadi Susanto, Mario Yennimar, Yennimar