SISTEM VERIFIKASI MENGGUNAKAN GARIS-GARIS TELAPAK TANGAN

Telapak tangan merupakan biometrika yang masih relatif baru, yang memiliki karakteristika unik berupa garis-garis (rajah) telapak tangan dan bersifat stabil. Keunikan dan kestabilan rajah tersebut merupakan ciri handal setiap telapak tangan.Sistem verifikasi telapak tangan merupakan proses pencocokan telapak tangan yang diuji dengan suatu telapak tangan yang diklaim. Hasilnya adalah suatu keputusan apakah telapak tangan yang diuji milik pengguna sah (genuine user) atau tidak sah (imposter user). Proses perolehan ciri rajah telapak tangan memegang peranan penting terhadap keberhasilan verifikasi. Pada tulisan ini, ciri-ciri rajah telapak tangan diperoleh dengan menggunakan metode deteksi garis dan operasi blok. Sedangkan proses pencocokan menggunakan metrika korelasi.Sistem yang dibuat diuji menggunakan sekitar 1000 citra telapak tangan milik 200 orang, setiap orang diwakili 5 sampel telapak tangan. Dua dari 5 citra sampel tersebut digunakan sebagai citra uji, sedangkan sisanya (3) untuk citra acuan. Hasil pengujian menunjukkan sistem ini mampu memberikan unjukkerja tinggi yaitu sekitar 97% tepat, atau memiliki EER sekitar 1.42%.</p

SEGMENTASI CITRA RETINA DIGITAL RETINOPATI DIABETES UNTUK MEMBANTU PENDETEKSIAN MIKROANEURISMA

Retinopati diabetes merupakan komplikasi mikro vaskuler yang dapat terjadi pada penderita diabetes dan menyerang fungsi penglihatan. Gejala klinis dari penyakit ini adalah munculnya mikroaneurisma yang merupakan pembengkakan pembuluh darah berukuran mikro dan dapat terlihat sebagai titik-titik kemerahan pada retina. Sistem segmentasi citra retina digital untuk membantu pendeteksian mikroaneurisma adalah sistem yang dikembangkan untuk melakukan segmentasi terhadap citra retina sehingga citra retina yang dihasilkan layak digunakan sebagai masukan pada sistem identifikasi mikroaneurisma. Pada penelitian ini dilakukan kombinasi terhadap metode-metode seperti variasi grayscale (grayscale biasa, red channel, green channel, blue channel), filter Gaussian, histogram modifikasi (histogram ekualisasi dan adaptif histogram ekualisasi), binerisasi (iterasi dan threshold ganda), filter median dan pelabelan komponen terhubung. Pengujian masing-masing kombinasi dilakukan pada citra retina yang berasal dari basis data Departement of Ophthamology, Faculty of Medicine,University of Kuopio, Finland dan dihitung akurasi dengan membandingkan hasil penandaan dokter antara citra asli dan citra hasil segmentasi. Hasilnya kombinasi metode dengan grayscale green channel, filter Gaussian, adaptif histogram ekualisasi 9 x 9, Threshold ganda dengan T1=70 dan T2=90, dan filter median memberikan akurasi sistem yang paling tinggi yaitu sebesar 94%.</p

Fuzzy Expert System for Tropical Infectious Disease by Certainty Factor

Communication between doctor and patient play an important role in determining the diagnosis of the illness suffered by the patient. Consultation time constraints led to insufficient information obtained to produce a diagnosis. This limitation is overcome by developing an expert system using fuzzy logic to represent the vagueness of symptoms experienced by patients and the certainty factor represents a relationship between the symptoms and disease. Fuzzy logic method begins with the acquisition of knowledge to produce the facts and rules, implication process, composition and defuzzification. The result of defuzzification used in the calculation of sequential and combined certainty factor which represent the belief percentage of diseases diagnosis that suffered by the patient. The results of the expert diagnosis with expert system for the given cases indicates the system, has the similarity diagnosis with the expert at 93.99%

Low-Cost Based Eye Tracking and Eye Gaze Estimation

The costs of current gaze tracking systems remain too high for general public use. The main reason for this is the cost of parts, especially high-quality cameras and lenses and cost development. This research build the low cost based for gaze tracking system. The device is built by utilizing of modified web camera in infrared spectrum. A new technique is also proposed here in order to detect the center pupil coordinate based on connected component labeling. By combination the pupils coordinate detection method with third order polynomial regression in calibration process to determine the gaze point. The experiment results show our system has an acceptable accuracy rate with error pixel 0.39o in visual degree

Hate Speech Classification in Indonesian Language Tweets by Using Convolutional Neural Network

The rapid development of social media, added with the freedom of social media users to express their opinions, has influenced the spread of hate speech aimed at certain groups. Online based hate speech can be identified by the used of derogatory words in social media posts. Various studies on hate speech classification have been done, however, very few researches have been conducted on hate speech classification in the Indonesian language. This paper proposes a convolutional neural network method for classifying hate speech in tweets in the Indonesian language. Datasets for both the training and testing stages were collected from Twitter. The collected tweets were categorized into hate speech and non-hate speech. We used TF-IDF as the term weighting method for feature extraction. The most optimal training accuracy and validation accuracy gained were 90.85% and 88.34% at 45 epochs. For the testing stage, experiments were conducted with different amounts of testing data. The highest testing accuracy was 82.5%, achieved by the dataset with 50 tweets in each category

A New Framework for Information System Development on Instant Messaging for Low Cost Solution

The increasingly inexpensive Internet has spurred the growth of online information system services in various companies. Almost all services are available in forms on web or mobile applications. For small companies, this particular system is more difficult to implement as it requires a substantial cost allocated for hosting, domain and server devices. The solution is to develop a framework for building information system services through Instant Messaging (IM) such as Telegram, Line or XMPP / Jabber using the Design Science Research Methodology. This proposed framework has the ability to transform the existing information system services into chat services with RBAC role, session, validation and natural interaction using Indonesian-language conversations. The framework that consists of Initiate layers, business process and communication, memory group and OLTP DBMS will produce low-cost solution for the development of integrated information systems service

PEMBENTUKAN KODE TELAPAK TANGAN (PALM CODE) BERBASIS METODE GABOR 2D

Establishment Code Hand Palm (Palm Code) 2D Gabor-Based Method. Palmprint is relatively new in physiological biometrics. Palmprint ROI segmentation and feature extraction are two important issues in palm print recognition. This paper introduces two steps in the center of mass moment method for ROI segmentation that will be applied in the Gabor 2D filter to obtain palm code as palmprint feature vector. Normalized Hamming distance was used to measure the similarity degrees of two feature vectors of palmprint. The system was tested using database 1000 palmprint images generated from 5 samples from each of the 200 persons randomly selected with ROI 64 x 64 and 128 x 128 pixel. Experiment results show that this system can achieve high performance with a success rate about 98.7% (FRR = 1.17%, FAR = 0.11%, T = 0.376) with ROI 64 x 64 pixel.Keywords: biometrics, Gabor filter, Hamming distance, identification, palmprin

Foreign Tourist Arrivals Forecasting Using Recurrent Neural Network Backpropagation through Time

Bali as an icon of tourism in Indonesia has been visited by many foreign tourists. Thus, Bali is one of the provinces that contribute huge foreign exchange for Indonesia. However, this potential could be threatened by the effectuation of the ASEAN Economic Community as it causes stricter competition among ASEAN countries including in tourism field. To resolve this issue, Balinese government need to forecast the arrival of foreign tourist to Bali in order to help them strategizing tourism plan. However, they do not have an appropriate method to do this. To overcome this problem, this study contributed a forecasting method using Recurrent Neural Network Backpropagation Through Time. We also compare this method with Single Moving Average method. The results showed that proposed method outperformed Single Moving Average in 10 countries tested with 80%, 70%, and 70% better MSE results for 1, 3 and 6 months ahead forecast respectively

Augmented Reality Using Real-Object Tracking Development

Augmented reality applications in tourism usually use images as markers, such as brochures or information boards. However, it is still ineffective because users cannot interact directly with real-objects. This study aims to create applications that more interesting and interactive way which can be used by interacting directly with real-object. This research is located in Taman Ayun Temple, one of the tourism objects that are world cultural heritage in Bali. The application is designed with the real-object tracking augmented reality method using the Wikitude Android SDK platform. The application is built in Indonesian and English. The test results show that the percentage of the recognition of 40 objects from various directions is more than 80%, from a distance of 10 to 40 meters is more than 70%, from a good and moderate lighting condition is more than 80%, and recognize similar objects as a different object

The Impact of Color Space and Intensity Normalization to Face Detection Performance

In this study, human face detection have been widely conducted and it is still interesting to be research. In this research, strong impact of color space for face i.e., many and multi faces detection by using YIQ, YCbCr, HSV, HSL, CIELAB, and CIELUV are proposed. In this experiment, intensity normality method in one of the color space channel and tested the faces using Android based have been developed. The faces multi image datasets came from social media, mobile phone and digital camera. In this experiment, the color space YCbCr percentage value with the image initial value detection before processing are 67.15%, 75.00%, and 64.58% have been reached. Then, after the normalization process are 83.21%, 87.12%, and 80.21% have been increased. Furthermore, this study showed that color space of YCbCr have reached improvement percentag