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Articles by Anggunmeka Luhur Prasasti
Total Records ( 5 ) for Anggunmeka Luhur Prasasti
  Nashar Luthfi Sugara , Tito Waluyo Purboyo and and Anggunmeka Luhur Prasasti
  Today, the information exchange has become faster than before. The speed of an information exchange is given by the smallest data sent. The compression method is the solution for making the information smaller than before. The information we discuss in this study is an image data. The image compression is one of the multimedia field which is used by people from past until now, even forever. The purpose of the image compression is to make the size of the image smaller than the original image size. The image compression has several methods, these are Huffman, DCT, DWT, LZW, EZW and much more. The image, we use for the experiment is JPG format. We will use three images for the sample. In this study, we compare the compression size and the compression ratio using Huffman and DCT methods.
  Mohamad Nurfakhrian Aziz , Anggunmeka Luhur Prasasti and Tito Waluyo Purboyo
  Face recognition using infrared technology is increasingly being used for the security purpose, it is Closed Circuit Television (CCTV) camera. CCTV camera is generally using infrared technology to monitor the surrounding environment in every condition whether it’s clear or even dark one without any lighting. Any evidence of crime captured by CCTV camera will be used for legal purposes. As we know that the image from infrared camera has poor quality, especially in terms of illumination and image detail, so, it’s hard to recognize someone from infrared camera. Therefore, the image quality from infrared camera needs to be enhanced. Retinex algorithm works like retina (in the eyes) and cortex (in the brain) to adapt the illumination. SSR (Single-Scale Retinex) and MSR (Multi-Scale Retinex) methods has been used in this research to be analyzed their effectiveness in face recognition using LDA (Linear Discriminant Analysis) method. In the tests that have been done, people face recognition in very dark conditions can still be recognized compared to face recognition without retinex and MSR has better accuracy than SSR one.
  Salma asti Shofia Rosyda , Budhi Irawan and Anggunmeka Luhur Prasasti
  Arabic is one of the languages which attracted, needed and used by a lot of people in the world. Many countries have used Arabic language in courses which related to the international world. Arabic also used by Muslim people, beacause Arabic is the main language of the hooly book of Muslim (Quran). The importance to know and to understand the basic of Arabic language for the temporary needs like when we travel to a country which use Arabic as their main language include during Hajj and Umrah. At this time the smartphone has become a major need for humans, based on that then made Arabic writing recognition application which aims to help pilgrims of Hajj and Umrah who can not speak Arabic. In this study, the method used is the method of Convolutional Neural Network (CNN). Test results from Arabic handwritten image classification using CNN resulted in an average accuracy of 60%. It can be concluded that the CNN method used in this application is able to do a good classification.
  Mohammad Rizky Adhiguna , Budhi Irawan and Anggunmeka Luhur Prasasti
  Money is the most commonly used means of payment by the public. But without denying fake money is widely circulated and there are still many people who are less accurate in recognizing the authenticity of the money. This will be bad for social life as we known that money is main payment that can use by everyone. For people with disabilities that lack of visual itself will be hard to know the identity from the money. With this problem in this research will be designed and implemented an Android based mobile application that can recognize currency with image. Applications designed using the Scale Invariant Feature Transform (SIFT) method that can provide information to users about their nominal and authenticity of the money using Indonesian. This application can help people who are less aware of information about genuine money and people with disabilities to find informations about authenticity of Foreign currency. With this application people with disabilities, also can tell the identity of the money itself with more accurate considering this app has implemented by SIFT method on feature extraction but the process time will be longer because the SIFT method itself has a fairly complicated calculation process. From these complex calculations will also produce better accuracy.
  Indrawan Risangaji , Muhammad Nasrun and Anggunmeka Luhur Prasasti
  The need for people to consume rice continues to increase which causes the price of rice in the market to rise and fall in the Yogyakarta Special Region while the government still lacks attention to rice production in each year. This research focuses on making regional groupings in Yogyakarta Special Region based on the level of rice productivity. Data mining process is done by clustering using k-means to classify sub-districts based on production data and land area. Evaluation of the results of clusters uses elbow method and comparison of cluster results with other programs. Regional grouping based on the level of rice productivity produces 3 optimal clusters which are divided into low productivity, medium productivity and high productivity. With the results of this study, it is expected to help the Yogyakarta agricultural service in an effort to increase rice productivity more evenly in each region.
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