Judul: Aplikasi Mobile Inventarisasi dan Pemetaan Tumbuhan Obat Menggunakan GPS (Global Positioning System)
Abstrak: This research develops the MedLeaf system which was designed to find information concerning medicinal plants. MedLeaf is the development of biodiversity informatics system which is developed by using Android operating system. Biodiversity informatics examines only the level of species diversity which will be mapped to view the spread of medicinal plants. Several technologies that support this research are Google Maps and GPS. There are two facilities the developed in mobile application, namely the mapping and the inventory of medicinal plants. Mapping is used to find the spread location of medicinal plant and inventory is used to preserve the medicinal plants. The amount of data used in this research are 100 species of medicinal plants and 107 data of medicinal plants that have been found at IPB Dramaga campus. Questionnaire method is used to evaluate the user’s satisfaction. The evaluation result indicates that the system is promising for mapping the medicinal plants.
Keyword: Biodiversity Informatics, Google Maps, GPS, Heuristic Evaluation

Judul: Aplikasi Mobile Untuk Identifikasi Tumbuhan Obat Menggunakan Local Binary Patterndengan Klasifikasi Probabilistic Neural Network
Abstrak: This research proposed a new mobile application for medicinal plants identification. Local Binary Pattern (LBP) is used to extract image features and Probabilistic Neural Network (PNN) is used to classify medicinal plants on mobile phone. LBPP,Rriu2 was used as LBP descriptor in this research, which uses rotation invariant and uniform patterns of image texture. The aim of this research was to implement this application in open source Android 2.3 (Gingerbread) operating system. The data used is the medicinal leaf image from Botanical Garden, Bogor Indonesia which consist of 15 species with 10 variations for each species. The experiment showed that the accuracy of identifications is 31.11% and the computation time is 50.02 seconds.The experimental result show the accuracy is still low, so this research need to be explored further to improve the accuracy. This new mobile application is useful to help user in plant identification.
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Judul: Perubahan Komposisi Lemak, Asam Lemak, Kolesterol, dan Jaringan Skin on Fillet Ikan Ekor Kuning (Caesio cuning) Setelah Proses Deep Frying
Abstrak: Ikan Ekor Kuning (Caesio cuning) merupakan komoditas yang banyak dimanfaatkan di Indonesia. Salah satu cara pengolahan yang umum dilakukan masyarakat pada ikan ekor kuning adalah dengan cara digoreng. Penelitian sebelumnya menunjukkan proses penggorengan mempengaruhi kandungan gizi pada ikan. Tujuan penelitan ini adalah menentukan pengaruh proses penggorengan dengan metode deep frying pada suhu 160 °C dan suhu 180 °C selama 5 menit pada kadar proksimat, asam lemak, kolesterol, dan jaringan ikan ekor kuning. Proses penggorengan menurunkan kadar air, abu, protein, dan karbohidrat serta meningkatkan kadar lemak. Proses penggorengan meningkatkan kadar asam lemak laurat, palmitat, oleat dan linoleat. Asam lemak secara keseluruhan mengalami penurunan setelah proses penggorengan. Fillet segar mengandung 1,67% EPA dan 7,57% DHA. Fillet goreng 160 °C mengandung 0,66% EPA dan 2,59% DHA serta fillet goreng 180 °C mengandung 0,65% EPA dan 2,50% DHA. Rasio asam lemak omega6:omega3 ikan ekor kuning segar sebesar 0,40, goreng 160 °C sebesar 2,38 dan 180 °C sebesar 2,44. Kolesterol ikan ekor kuning segar dan goreng menunjukkan perbedaan, ikan ekor kuning segar memiliki kadar kolesterol sebesar 256,04 mg/100g, goreng 160 °C sebesar 306,64 mg/100g, dan 180 °C memiliki kandungan kolesterol 242,09 mg/100g. Struktur jaringan daging fillet ikan ekor kuning mengalami perubahan akibat proses deep frying. Jaringan sampel yang digoreng dengan suhu 180 °C selama 5 menit menunjukkan struktur yang lebih kompak bila dibandingkan dengan sampel segar dan sampel yang digoreng pada suhu 160 °C selama 5 menit
Keyword: histologi, komposisi kimia, omega 3, omega 6, proses penggorengan