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KEANEKARAGAMAN JENIS ANGGREK (ORCHIDACEAE) DI AREA HUTAN BUKIT KUKUS, BANGKA BARAT Djodi Surya Prawira; Eka Yuliawati; Erika Purba
EKOTONIA: Jurnal Penelitian Biologi, Botani, Zoologi, dan Mikrobiologi Vol 4 No 2 (2019): Ekotonia: Jurnal Penelitian Biologi, Botani, Zoologi dan Mikrobiologi
Publisher : Department of Biology, Faculty of Agriculture, Fisheries and Biology, University of Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.03 KB) | DOI: 10.33019/ekotonia.v4i2.1785

Abstract

Orchid is a group of flowering plants of the Orchidaceae family with a total of 700-800 genera and 25,000-35,000 species. Identification of orchids is a step to determine orchid species by comparing the morphological characteristics of each orchid found. This research was conducted in Bukit Kukus, Air Belo Village, Muntok Subdistrict, West Bangka Regency for four days, from March 9 to March 12, 2018 using exploration methods, including: a preliminary survey, data collection and herbarium making. The results showed that the number of orchids that were found was the conclusion that could be drawn from this exploration is in Bukit Kukus, Air Belo Village, Muntok District, West Bangka Regency, found 15 types of orchids, consisting of 7 genera, namely Agrostophyllum, Arachnis, Bulbophyllum, Coelogyne, Dendrobium, Nephelaphyllum and Poystachya with the most genera Bulbophyllum found, up to 5 species. The most common orchids are found in Zone I, where 12 of the 15 species can be found, while the most common type of orchid is epiphytic orchids with rock substrates.
Analisis Pola Kunjungan pada Objek Wisata Kabupaten Simalungun Dengan Menggunakan Algoritma Apriori Berbasis Website Erika Purba; Andy Paul Harianja
SATESI: Jurnal Sains Teknologi dan Sistem Informasi Vol. 4 No. 2 (2024): Oktober 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian ALGERO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/satesi.v4i2.3244

Abstract

Tourist attractions are places of interest and visited by tourists because they have certain appeals. These attractions can include natural tourism, cultural tourism, artificial tourism, or agro-tourism. Simalungun Regency offers various interesting tourist spots, ranging from natural beauty such as waterfalls and lakes to rich traditional cultures that reflect local history and customs. However, information about tourist visit patterns remains limited. A deeper understanding of these patterns is crucial, especially for tourism managers in designing effective and sustainable development strategies. Therefore, this study aims to identify associations or relationships between tourist attractions based on tourist visit data. The Apriori algorithm was chosen for its ability to discover high-frequency patterns in large datasets. These patterns are expected to provide valuable insights for tourism managers in designing effective promotional strategies. Apriori is a well-known algorithm in data mining, particularly for finding frequent itemsets using association rule techniques. The algorithm is carried out by determining frequent itemsets, from 1-itemset to multi-itemsets, until the association rules are derived from the pre-selected data. To obtain these frequent itemsets, each selected data must meet the minimum support and minimum confidence requirements so that the resulting association rules are relevant and practically applicable.