OPTIMALISASI PENENTUAN SUMBER PASOKAN KOPI ARABIKA GAYO MELALUI PENDEKATAN HIRARCHICAL CLUSTERING DATA MINING - Arie Saputra (Universitas Teuku Umar, 2017)
Gayo coffee scattered in the mountains and being in two districts of the central highlands and Central Aceh district has become the center of world attention. Gayo Arabica coffee has a unique manifold and the added value created by the mountainous nature Gayo. This factor makes Gayo Arabica coffee has the added value that is not replaceable by other similar commodities. The success of the stakeholders Gayo coffee obtain certification which is organic, fairtrade, coffee practice and Geographic indication that can be a proof of the worldwide recognition of the quality and added value of this coffee. The average price of the last on the coffee harvest season in March 2012 ranged between Rp 100.000,- until Rp 110.000,- in each Kg grean bean on exporter level. Determination of clusters of farmers the right so that the quality and price of supplies could be predicted well by the cooperative as exporters are very important. These routes and ketelusuran origin coffee blend in one location with other location mebuat coffee quality decreases. Mapping the supply of unclear origin uniformity of the quality of the coffee making is difficult to determine. This effect on selling prices decreased overall coffee farmers to the detriment of farmers with good quality coffee. The good name of the cooperative from the viewpoint of importers deteriorate as evidenced by a decrease in the purchase price of the importer in the contract.The sampling process quality coffee supply also becomes difficult because unhomogenity supply region. Supply region is crucial to the quality of the coffee due influenced the position and height of the land. Thus, this research is expected to help formulate clusters of farmers so that the quality and price of coffee could be improved both in terms of farmers and exporters. The last hope of course the welfare of farmers and other stakeholders could be better.Keywords: Data Mining, Optimization, Gayo Arabica Coffee, Supply Chain