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PENERAPAN ALGORITMA AGGLOMERATIVE HIERARCHICAL CLUSTERING (AHC) PADA DATA PERTANIAN DI JAWA TENGAH

Lestari, Sami (2020) PENERAPAN ALGORITMA AGGLOMERATIVE HIERARCHICAL CLUSTERING (AHC) PADA DATA PERTANIAN DI JAWA TENGAH. Undergraduate thesis, Universitas Stikubank.

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Abstract

Data tanaman hasil hortikultura maupun hasil peternakan dari data Badan Pusat Statistik Provinsi Jawa Tengah menampilkan beberapa kabupaten atau kota yang berpotensi menghasilkan tanaman hortikultura mapupun hasil peternakan. Untuk mengetahui wilayah atau daerah mana saja yang mempunyai potensi penghasil panen tertinggi maupun yang terendah maka diperlukan metode untuk mempermudah identifikasi. Dengan menggunakan agglomerative hierarchical clusteting maka akan dengan mudah dilakukan pengelompokan berdasar potensi hasil penen tiap daerah. Penelitian ini bertujuan untuk melakukan pengklasteran yang diterapkan pada hasil pertanian di Jawa Tengah (Data BPS tahun 2017 yang diterbitkan pada tahun 2018). Pengelompokan atau clustering penulis menggunakan algoritma agglomerative hierarchical clustering dengan tiga metode yaitu single lingkage, complete lingkage dan average lingkage yang ditampilkan dalam bentuk dendogram. Clustering bertujuan untuk mengelompokan objek-objek yang mempunyai kemiripan yang sama sehingga bisa dijadikan acuan penanganan yang hampir sama terhadap objek-objek yang mirip. Data on horticultural and livestock products from Central Java Provincial Statistics Agency data shows several regencies or cities that have the potential to produce horticultural crops as well as livestock products. To find out which regions or regions have the highest or lowest potential harvesting, methods are needed to facilitate identification. By using agglomerative hierarchical clusteting, it will be easy to do groupings based on the potential yields of each region. This study aims to conduct clustering that is applied to agricultural products in Central Java (BPS data for 2017 published in 2018). The grouping or clustering of the authors uses the agglomerative hierarchical clustering algorithm with three methods, namely single circumference, complete circumference and average circumference which are displayed in the form of dendogram. Clustering aims to group objects that have the same similarity so that it can be used as a reference for handling almost the same for similar objects.

Item Type: Thesis (Undergraduate)
Additional Information: SKR.I.05.02.1869 NIM : 17.01.55.5007
Uncontrolled Keywords: Algoritma Agglomerative Hierarchical Clustering, algoritma AHC, Data Mining
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Institution: Fakultas Teknologi Informasi > Program Studi Sistem Informasi
Depositing User: Yuliana Eliza
Date Deposited: 08 May 2020 01:41
Last Modified: 08 May 2020 01:41
URI: http://eprints.unisbank.ac.id/id/eprint/6682

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