PENGGUNAAN ALGORITMA K-MEANS DALAM KLASTERISASI POTONGAN TANDAN BUAH SEGAR KELAPA SAWIT

PUTRI, AMARA EKA and Jambak, Muhammad Ihsan (2022) PENGGUNAAN ALGORITMA K-MEANS DALAM KLASTERISASI POTONGAN TANDAN BUAH SEGAR KELAPA SAWIT. Undergraduate thesis, Sriwijaya University.

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Abstract

The process of sorting fresh fruit bunches is the process of selecting palm fruit to be used as Crude Palm Oil (CPO). In the sorting process there are palm fruits that cannot be processed, in this case known as pieces of fresh fruit bunches. Such pieces of fruit consist of unripe fruits, rotten fruits, long petioles, empty bunches, dirt, water and dura. This piece affects the production yield, the more pieces, the production yield will decrease. Given the large number of pieces of fresh fruit bunches produced every day, one of the first steps to find out the characteristic factors of fresh fruit bunch pieces is to group the data owned. Grouping was carried out using clustering techniques using the K-Means algorithm in FFB data for January-July 2021. K-Means works optimally at a value of k=3, modeling rapidminer with a value of k=3 gets a DBI value of 1.087. So that the pieces of fresh fruit bunches are divided into 3 clusters, namely high fresh fruit bunches, medium fresh fruit bunch pieces, and low fresh fruit bunches.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Fresh Fruit Bunch Pieces, Clustering, K-Means, Davies Bouldin Index
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data.
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	- Amara Eka Putri
Date Deposited:	29 Jul 2022 05:18
Last Modified:	29 Jul 2022 05:18
URI:	http://repository.unsri.ac.id/id/eprint/75260

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