PREDIKSI POTONGAN SORTASI TANDAN BUAH SEGAR KELAPA SAWIT MENGGUNAKAN ALGORITMA LINEAR REGRESSION

ASLAMATURRIZKI, ASLAMATURRIZKI and Jambak, Muhammad Ihsan (2022) PREDIKSI POTONGAN SORTASI TANDAN BUAH SEGAR KELAPA SAWIT MENGGUNAKAN ALGORITMA LINEAR REGRESSION. Undergraduate thesis, Sriwijaya University.

	Text RAMA_57201_09031181823022.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (4MB) | Request a copy
	Text RAMA_57201_09031181823022_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy
Preview	Text RAMA_57201_09031181823022_0205046801_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (1MB) | Preview
	Text RAMA_57201_09031181823022_0205046801_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (459kB) | Request a copy
	Text RAMA_57201_09031181823022_0205046801_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_57201_09031181823022_0205046801_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (493kB) | Request a copy
	Text RAMA_57201_09031181823022_0205046801_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (238kB) | Request a copy
	Text RAMA_57201_09031181823022_0205046801_06_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (237kB) | Request a copy
	Text RAMA_57201_09031181823022_0205046801_07_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy

Abstract

Fresh fruit bunches of oil palm are oil palm fruits that are still on the tree or that have been harvested, still complete with bunches. Sorting of fresh fruit bunches of oil palm is carried out to observe the quality of the fruit received in the palm oil mill. The sorting aims to separate good and bad fruits, so as to produce products that meet production standards in terms of quality, quantity, and continuity of production tools. There is often a transportation of palm fruit that cannot be processed by mills that are categorized as pieces. Companies can experience indications of losses due to poor harvesting of fresh fruit bunches so that it requires a predictive pattern and which factors affect the cut to minimize the event. The data mining technique or model applied is the Linear Regression algorithm which uses data on sorting pieces of fresh fruit bunches of palm oil in January-July 2021 with cross validation data sharing carried out on the RapidMiner application. The results obtained, the Linear Regression test showed an excellent prediction pattern with an RMSE error value of 0.000 +/- 0.000 (micro average: 0.000 +/- 0.000). And one of the factors that most affects the cut is Dirt/Penalty.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Linear Regression, Prediksi, Cross Validation, RapidMiner, Kelapa Sawit
Subjects:	Q Science > Q Science (General) > Q1-295 General
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Mrs Aslamaturrizki Aslamaturrizki
Date Deposited:	22 Jul 2022 06:49
Last Modified:	22 Jul 2022 06:49
URI:	http://repository.unsri.ac.id/id/eprint/74503

Actions (login required)

View Item