Judul: Sistem Identifikasi Famili Secara Otomatis Berbasis Teks Menggunakan Dokumen Etnofitomedika
Abstrak: This research represents a text-based system that can be used for automatic identification of plant families according to the taxonomy of plants. The identification was done by utilizing information from etnofitomedika documents on plant characteristics that can represent the family of each plant including morphology, habitats, habitus, and biochemical compounds. The method used in this research is Chi-Square method to select important words in each document and Naïve Bayes method to classify the words. The experimental results showed that the critical value using significance level of 0,001 had better accuracy than the critical value using significance level of 0,01. The accuracy of classification systems based on family category using K-fold cross validation with significance value of 0,001 was 85,5%. It was found this system is useful in helping users especially researchers and taxonomists for plant family identification. Furthermore, it can help strengthening the knowledge on biodiversity and the use of medical plants.
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Judul: Klasifikasi Dokumen Tumbuhan Obat Berbasis Famili Menggunakan Probalistic Neural Network
Abstrak: This research presents a system for the extraction of features and classification of the document medicinal plants using the chi-square method and neural network classification probalistic. Automation family identification by grouping characteristics medicinal plants contained in the document. In this research, the phase consists of collecting documents, doing conversion from hardcopy documents to softcopy into XML format, pre-process the document, featuring selection using the chi-square, document classification using PNN and evaluation using Confusion Matrix. Classification results are influenced by the number of family identifier words. Number of words identifier of a family affected by the same number of words in each document training. The more same words in each document training, the greater probability of the word being said identifier. In this research, identifier of a family does not describe the characteristics of plant taxonomy. This is due to the same number of words in each document has not practically described the characteristics of plant taxonomy. The evaluation research of classification algorithm Probalistic Neural Network (PNN) with weight value 1 and layer patterns using feature extraction using the chi-square values of alpha (α) value of 0.1 overall result of classification is 82.14%. This research represents a medical plant document system that can be used for automatic identification of families according to the taxonomy of plants.This system is useful to help users especially researchers and taxonomists in the identification document through labeling family automatically on each document, with the existing system, therefoe the users dont need to bring a book or a guide book to identify the field. Furthermore, it can overcome the limitations of people's knowledge of the diversity and the use of medicinal plants. That is because there are a lot of documents to train the same word in each document which is not characteristic of plant taxonomy.
Keyword: probalistic neural network classifier, medical plant document, document identification, document classification, chi-square

Judul: Sludi Tala Lelak Fasililas Pangkalan Pendaralan Ikan (PPI) Muara Angke Jakarta
Abstrak: Berdasarkan Rencana Umum Tata Ruang (KUTR) Oaerah Khusus IbukOla Jakarta tahun 1985-2005 dan dikaitkan dengan Mah Kebijaksanaan Pengembangan Kawasan Pantura yang tertera dl Keppres No. 52 tahun 1995 tentang Reklamasi Pantura Jakarta serta Peraturan Oaerah Tata Ruang Kawasan Pantura maka kegiatan perikanan khususnya perikanan laut dipusatkan di dua lokasi yaitu dl Muara Angke dan Muara Saru. PPI Muara Angke sebagai tempat pendaratan armada perikanan rakyat, sedang Pelabuhan Perikanan Samudera Jakarta (PPSJ) Muara Saru diperuntukkan bagi armada perikanan skala besar atau berorientasi ekspor. Sejak tahun 1977, PPI Muara Angke ditetapkan sebagai satu-satunya tempat pendaratan ikan tradisional di Pantai Utara Jakarta, dibangun oleh Pemda OKI Jakarta lengkap dengan sarana dan prasarana perikanan, pemukiman nelayan dan fasilitasnya (Oinas Perikanan, 1997). Tujuannya untuk merelokasi tempat-tempat pendaratan ikan lain yang banyak tersebar di Pantai Utara wilayah OKI Jakarta dan saat ini belum tertata secara baik. Oalam kurun waktu ± 22 tahun (1977-1999), kawasan Muara Angke telah mengalami peningkatan pembangunan yang pesat, seperti adanya pasar pengecer, unit pengepakan ikan, Pusat Jajan Serba lkan, Pengolahan Hasil Perikanan Tradisional (PHPT), pemukiman nelayan dan fasilitas umum lainnya; juga mengalami peningkatan armada kapal perikanan yang melakukan bongkar muat dan kegiatan-kegiatan lainnya. Meskipun sejak tahun 1996/1997 kawasan Muara Angke telah memiliki Master Plan, namun dalam pelaksanaannya belum diterapkan sesuai tahapan pengembangannya sebagai akibat alokasi dana dari Pemerintah yang terbatas. Hal ini menyebabkan pembangunan kawasan tersebut dilakukan secara parsial tergantung alokasi anggaran dan sektor-sektor yang memiliki dana. Pengembangan yang parsial menyebabkan kondisi kawasan Muara Angke saat ini kumuh dan tidak tertata dengan baik. Selain itu terlihat ketidakteraturan pada beberapa aktifitas dan kemacetan lalulintas pada jalan-jalan yang terdapat di dalam kawasan PPI.
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