The document discusses information extraction from text documents to make the data easier to maintain and process. It aims to create a system that can gather information from sources like newspapers and provide it to users simply. The system would classify documents in a database and use algorithms like optical character recognition and document classification to extract structured data from unstructured documents. It involves steps like cropping images, OCR, summarization, and classification to digitize newspaper content and extract useful information for users.

1. POWERED BY : GROUP 1
NIA/DESI/POPON/JIMMY/RASYID

2. -Information Extraction (IE) as an important thing for archievingdata from text paper document to be easily maintain and reprocess data
-The manual process of gathering the information consuming too much time and energy

3. -To create a system that can gathering and also provide an information to user with a simple way
-To classify documents in database
-To provide the good algorithm in information extraction
-To provide application that make SubDirectoratePublic Opinion, BPS to archievingdata from newspaper

4. -Informationextraction(IE)isthetaskofautomaticallyextractingstructuredinformationfromunstructeredand/orsemi-structureddocuments
-OCRisaspecialsystemisusedtoidentifyprintedtextpapertypedandprintedusingaprinterwhichisthenfurtherprocessedbyusingaparticularalgorithmintoacharacterthatcanberecognizedandprocessedintoinformation
-Documentclassificationonthelaststep

5. 1. Input(Newspaper/epaper)
2. Cropping+ Image Processing
3. OCR
4. Summarizing
5. Classification
Newspaper,etc
OCR
Plain text
Input
Proses
(get information)
Output
e-paper

7. Gerbawani, R. A. Somadi. 2013. “Peringkasan Dokumen Bahasa Indonesia Menggunakan Logika Fuzzy”. Bogor : Fakultas Matematika dan Ilmu Pengetahuan Alam IPB.
Trisedya, Bayu Distiawan & Jais, Hardinal. 2009. “Klasifikasi Dokumen Menggunakan Algoritma Naive Bayes dengan Penambahan Parameter Probabilitas Parent Category”. Jakarta: Fakultas Ilmu Komputer Universitas Indonesia.
Pramesti, TitisH.W. 2014. “PengenalanKarakterTeksMenggunakanMetodeNeural Network Backpropagation”. Malang: JurusanTeknikElektro, FakultasTeknikUniversitasBrawijaya.

8. THANK YOU
FOR YOUR ATTENTION