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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2207002268	T74503	T745032022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T745032022

Publisher

Inderalaya : Prodi Sistem Informasi, Fakultas Ilmu Komputer Uniersitas Srwijaya., 2022

Collation

xi, 68 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

003.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem analisis
Prodi Sistem Informasi

Specific Detail Info

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Statement of Responsibility

SEPTA

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