PENERAPAN METODE ENTROPY DAN METODE TOPSIS PADA TINGKAT KESESUAIAN LAHAN TANAMAN KOPI DI PROVINSI BENGKULU (Jurnal Edik Informatika Penelitian Bidang Komputer Sains dan Pendidikan Informatika, 2022)
Coffea sp (coffee plant) is one of Indonesia's mainstay export commodities which has an important role as the third-largest foreign exchange earner after wood and rubber in the agricultural sub-sector. Coffee is one of the most popular beverage offerings in the world, as evidenced by the fact that coffee consumption has soared to 174 percent in 2016 (International Coffee Organization/ICO data). Bengkulu also produces a lot of coffee production including pickled red Robusta, Arabica super, and Arabica luak which usually the farmers also keep badgers in their cages. Bengkulu, which is known as the golden triangle, is the largest Robusta producer on the island of Sumatra. Land use that is by the potential of the land makes the quality of the land maintained and can optimize production results. Therefore, a Decision Support System is needed to provide recommendations for Robusta coffee farmers in determining the lands to be planted. This research uses the entropy weighting method and TOPSIS ranking. The resulting output is in the form of ranking from the highest to the lowest value of each land contained in 28 sub-districts in 4 districts of Bengkulu Province, namely Rejang Lebong, Lebong, Kepahiang, and Seluma from the highest to the lowest value. This system was built using the PHP programming language and system design with the Unified Modeling Language (UML). The development of this system uses the waterfall method. The accuracy of this system based on the tested data is 100%. Based on the results of calculations using a combination of the entropy weighting method and the TOPSIS ranking method, the results of the largest preference value of 0.815 are in the Seberang Musi and Tebat Karai sub-districts, Kepahiang Regency.