Judul: Aplikasi Android Penerjemah Bahasa non-Latin dengan Pengenalan Citra Karakter
Abstrak: Bahasa dengan karakter nonlatin merupakan bahasa yang sulit untuk dipelajari karena penulisannya yang relatif rumit. Beberapa bahasa yang menggunakan karakter nonlatin antara lain Arab, Cina (sederhana), Rusia, Jepang, Korea, dan Thailand. Pada penelitian ini, suatu sistem pengenalan karakter nonlatin berbasis Android dirancang untuk mengenali citra karakter nonlatin menggunakan Tesseract library OCR (Optical Character Recognition) dan menerjemahkannya menjadi bahasa Indonesia dan Inggris menggunakan Microsoft Translator. OCR adalah teknik untuk mengubah teks nondigital menjadi teks digital atau dapat diartikan sebagai pengenalan karakter optik. Pada penelitian ini terdapat 8 kebutuhan fungsional, yaitu memilih bahasa asal, mengambil citra menggunakan kamera dan memotongnya, mengambil citra melalui galeri, melakukan konversi dari citra ke teks, mengedit teks nonlatin hasil OCR, memilih bahasa tujuan, menampilkan hasil terjemahannya, dan me-reset aplikasi. Berdasarkan 650 contoh karakter nonlatin yang terdiri dari 5 bahasa telah diuji, nilai akurasi terbaik yang didapat adalah 95.03% pada kondisi pencahayaan normal. Adapun faktor-faktor yang dapat mempengaruhi akurasi tersebut antara lain: intensitas cahaya, kemiringan, fokus, dan penulisan secara vertikal. Evaluasi usability menghasilkan nilai 82.4%. Kata
Keyword: Android, citra, nonlatin, OCR, teks, Tesseract

Judul: Aplikasi Pencari Info Obat dengan Masukan Citra Teks Kemasan Obat Berbasis Android Menggunakan Tesseract OCR Engine
Abstrak: Detailed information on drug is usually written on a leaflet that can only be read when the package has been opened. It is difficult for consumers who just want to know the detailed information of certain drug to decide whether the drug will be bought or not. A solution is needed to convert drug brand text image into editable text, so that it can be used as a keyword query for drug info searching on the internet. Optical Character Recognition (OCR) is a process to convert image into editable text. Tesseract performs several processes to identify drug brand text image. The processes are image preprocessing, feature extraction, segmentation, and word recognition. This research developed an Android application to recognize drug brand text image. Tesseract is used because it has good accuracy in recognizing text with serif and sans serif font which have far density between characters. Drug packaging input image of the application can be taken from a camera or gallery. The best accuracy of this application in recognizing characters with 70 drug packaging images reached 96.80%.
Keyword: Bogor Agricultural University, Tessera, optical character recognition, drug, Android

Judul: Thermal Characteristics and Dynamics of Tropical Cyclone over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng) 2011
Abstrak: The frequent occasion of Tropical Cyclone (TC) over Western North Pacific (WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC development come from warm ocean temperature where latent heat is released during condensation processes and subsequently concentrated in the boundary layer. Relative humidity at 850-700 hPa is responsible to produce the most intense storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the dynamical factors that lead to the development of TC. Pressure level of 850-200 hPa is chosen to minimize the thermodynamic effect in the lower troposphere. Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to 30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th and 27th. Long curving track and the exhibition of all sequences of TC life cycle, TSC is then considered as an ideal case of TC. The objective of the study with case of TSC is to investigate the role of thermal characteristics and dynamics on TC intensity. The research is carried out by using Advanced Research of Weather Research and Forecasting model (WRF ARW model) version 3.3. Two domains are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E to 149˚E and cover spatial resolution () of 33.1 km. The second domain situate from 09˚N to 27˚N and 119˚E to 132˚E with of 11 km. Timestep of the model () is 120 seconds. The model is supported by the following physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class scheme in the microphysics. Initial meteorological condition prior to the formation of the cyclone is generated using WRF ARW standard-release model. Sensitivity of the model output is obtained from a selected single-parameter change scenarios, namely, 10 % to 20 % decrease and increase of wind shear initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity initial data at 850-700 hPa. The result showed that the negative correlations between wind shear and intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to strengthening of the wind intensity in the early period of Typhoon development are found in wind shear scenarios. The effect of wind shear changes on wind intensity is statistically significant in the 20 % wind shear scenarios. During mature stage, weak wind intensity occurred when wind shear increase as given in the WRF standard-release and the 20 % decreasing scenario. Different situation is found in the 20 % increasing scenario where wind shear tend to weak and lead to strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at 850-700 hPa resulting from 20 % decreasing relative humidity play a major role in the weakening of wind intensity and reduces mechanical energy of the cycle process as much as 300 J kg-1.
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