Judul: Receipt Recorder Application Development Using Tesseract OCR Engine
Abstrak: Dalam kegiatan transaksi harian yang kita lakukan, kegiatan pencatatan pengeluaran adalah hal yang penting dilakukan untuk mengatur anggaran belanja. Oleh karena itu, dibutuhkan suatu alat untuk mencatat pengeluaran tersebut. Penelitian ini merancang sebuah aplikasi web pencatat belanja dengan mengimplementasikan teknologi Optical Character Recognition (OCR) Tesseract yang mampu mengekstrak tulisan pada gambar nota belanja menjadi teks yang dapat diedit. Aplikasi yang diberi nama “Receipt Recorder” ini dibangun dengan metode pengembangan Waterfall menggunakan framework Angular untuk front end, ExpressJS untuk back-end, dan MongoDB sebagai database. Dengan adanya aplikasi ini, pengguna dapat mencatat pengeluaran belanjanya tanpa perlu melakukan input nominal total secara manual. Hasil dari penelitian ini menunjukkan bahwa teknologi OCR Tesseract cocok digunakan untuk mengekstrak data dari struk bertipe cetak.
Keyword: Angular, Express JS, MongoDB, Pencatat Pengeluaran, Tesseract, Optical Character Recognition

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: Pengaruh Ph Terhadap IgG Anti H5N1 Asal Kolostrum Sapi Yang Divaksin Dengan Vaksin Avian Influenza H5N1
Abstrak: The aims of this study is to determine the stability of IgG anti-H5 from bovine colostrum (BC) after exposure to acid and basic pH. Two samples of BC, whole colostrum and whey colostrum incubated at pH 4, 5, 9, and 10 for 30 and 60 minutes. Haemagglutination Inhibition (HI) test is used to determine IgG titer after incubation. IgG titers decreased after exposure to acid or basic pH. Acid exposure (pH 5) decreased antibodi titer of whole colostrum as much as 3,75% and 16,25% after incubation 30 and 60 minutes respectively. Antibody titer to pH 4 also decreased until 12,5% and 16,5% after for 30 and 60 minutes respectively. In whey colostrum, both pH 4 and pH 5 reduce 18,75% antibody titer. On other hand, IgG titers is decreased until 100% at basic pH (pH 9-10). In conclusion, IgG from BC is degraded in acidic and alkaline conditions.
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