Kandowangko NY, Latief M, Yusuf R. 2018. Inventory of traditional medicinal plants and their uses from Atinggola, North Gorontalo District, Gorontalo Province, Indonesia. Biodiversitas 19: 2294-2301. Medicinal plants have been used by the people of Gorontalo as a hereditary tradition. But this knowledge has not spread to the wider community because the traditional wisdom about medicinal plants has not been documented, stored and managed properly by employing digital tools. The purpose of this study is to prepare an inventory of the traditional medicinal plants and the details of their uses in Atinggola, North Gorontalo district, Indonesia. Data has been collected by ethnobotanical survey method and analyzed using the descriptive qualitative method. The study has shown that 38 species of medicinal plants, belonging to 20 families, are used to cure many diseases by the traditional healers of Atinggola. Among them, 6 species are used to treat fever, 5 species to treat skin diseases, 2 species each to treat cancer, gastrointestinal diseases, liver diseases, and as body tonic to restore power; 1 species each to treat toothache, malaria, tonsillitis, allergies, eye irritation, wound infections and tuberculosis (TBC). Plant parts used in the treatment practices are leaf, fruit, flower, rhizome, root, stem, seed, shoots, midribs parts, etc. However, the most dominant part used is the leaf of the plants. Various methods such as boiling, squeezing, scraping, chewing, smashing, brewing, etc. are used to prepare the medicines. 29 species (76.31%) of medicinal plants are collected from cultivated sources such as backyards and gardens while 9 species (23.68%) are still sourced from forests.
Abstract. There is a significant number of unpublished research by university lecturers and students about Gorontalo's local medicinal plants that have contributed to the insufficiency of information to the society regarding the benefits of local medicinal plants. Moreover, the public lacks digital backup and documentation of the medicinal plants referred. This research aims to create a web database of Gorontalo's local medicinal plant, by comprising waterfall method of software engineering approach. The waterfall method involves four steps. The first step is system requirement analysis through preliminary study and observation based on field study and library research. The second is system design, by context diagram and system architecture designs, i.e., use case diagram, class diagram, activity diagram, and database design. The third is coding using PHP programming language by OOP (object oriented programming) concept and MVC (model view controller) architecture. The last step is system test using the black-box testing method. The result shows that the web application designed is able to operate properly.
Kurangnya informasi kepada masyarakat tentang pemanfaatan dan khasiat tanaman obat daerah Gorontalo menyebabkan kurangnya pemanfaatan terhadap tanaman obat daerah ini. Selain murah untuk digunakan sebagai obat tradisional, tanaman obat daerah ini juga dapat mengatasi berbagai macam penyakit. Akan tetapi, data tanaman obat daerah ini belum dikelola dengan baik dan belum tersimpan dan terdokumentasi secara digital. Tujuan penelitian ini adalah membuat sistem informasi berupa aplikasi web dan mobile data tanaman obat daerah Gorontalo. RUP (Rational Unified Proces) dengan menggunakan konsep Unified Modelling Languange (UML) digunakan dalam metode perancangan sistem yang terdiri dari use case diagram, activity diagram, dan class diagram. Untuk bahasa pemrograman menggunakan PHP dengan konsep OOP (object oriented programing) sebagai backend-nya untuk aplikasi web dan IONIC framework sebagai frontend untuk aplikasi mobile. Hasil pengujian menunjukkan bahwa aplikasi dapat mengelola data tanaman obat dan juga menampilkan dan mencari data tanaman obat berdasarkan penyakit tertentu. Kata kunci: aplikasi web dan mobile, tanaman obat Gorontalo
The purpose of this research is to design the application of digital image processing system to identify the image of medicinal plants of Gorontalo region using artificial neural network method using back propagation. This research used a digital image processing method with segmentation and extraction techniques. Segmentation process was carried out using thresholding method. Furthermore, a process of characteristic extraction from medicinal plants drawings was carried out using feature and color feature extractions to obtain the value of metric, eccentricity, hue, saturation and value. these five values were used as parameters for input neurons and one output neuron which denoted the class of the medicinal plants image. Data of this research consisted of 91 images which had been divided into two types, training data and test data. The training data consisted of 80 images and the test data consisted of eleven images. A network architecture was obtained from the training result and it provided the highest accuracy level (100%) and least number of iteration with a number of 50 neurons on hidden layer and 143 epochs. The testing result showed a lower accuracy of 54.54%.
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