PREDIKSI HASIL PANEN KELAPA SAWIT PADA PT.CITRA MULIA PERKASA ESTATE LAMPASIO MENGGUNAKAN METODE REGRESI LINEAR BERGANDA

Muhammad Febrian Hanafi, . (2026) PREDIKSI HASIL PANEN KELAPA SAWIT PADA PT.CITRA MULIA PERKASA ESTATE LAMPASIO MENGGUNAKAN METODE REGRESI LINEAR BERGANDA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
ABSTRAK.pdf
Download (96kB)
[img] Text
AWAL.pdf
Download (509kB)
[img] Text
BAB 1.pdf
Restricted to Repository UPNVJ Only
Download (134kB)
[img] Text
BAB 2.pdf
Restricted to Repository UPNVJ Only
Download (324kB)
[img] Text
BAB 3.pdf
Restricted to Repository UPNVJ Only
Download (507kB)
[img] Text
BAB 4.pdf
Restricted to Repository UPNVJ Only
Download (697kB)
[img] Text
BAB 5.pdf
Download (98kB)
[img] Text
DAFTAR PUSTAKA.pdf
Download (123kB)
[img] Text
DAFTAR RIWAYAT HIDUP.pdf
Restricted to Repository UPNVJ Only
Download (73kB)
[img] Text
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only
Download (775kB)
[img] Text
HASIL PLAGIARISME.pdf
Restricted to Repository staff only
Download (9MB)
[img] Text
ARTIKEL KI.pdf
Restricted to Repository staff only
Download (399kB)

Abstract

Predicting palm oil production is an important aspect in efforts to improve the efficiency and effectiveness of plantation management. This study aims to predict palm oil yields by applying the Data Mining method using the Multiple Linear Regression algorithm. The data used comes from PT. Citra Mulia Perkasa Estate Lampasio, which includes variables such as Land yield (HA), Harvesting power (HK), and harvest yield (JJG). There is a need to identify key variables such as Land Area (HA)and Harvesting power(HK) that have a significant influence on palm oil production results.The data is analyzed to find significant patterns and relationships between variables that affect production yields. The results show that the Multiple Linear Regression method is able to produce a predictive model with a fairly high level of accuracy, so it can be used as a tool in production planning and managerial decision making. Thus, the application of data mining in predicting palm oil yields makes a real contribution to optimizing productivity and operational efficiency in the plantation sector.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil : 2110512054] [Pembimbing : Ruth Mariana Bunga Wadu] [Penguji 1 : Ika Nurlaili Isnainiyah] [Penguji 2 : Bambang Triwahyono]
Uncontrolled Keywords: Data Mining, Multiple Linear Regression, Palm Oil, Prediction, Harvesting power.
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: MUHAMAD FEBRIAN HANAFI
Date Deposited: 22 Apr 2026 02:00
Last Modified: 22 Apr 2026 02:00
URI: http://repository.upnvj.ac.id/id/eprint/42430

Actions (login required)

View Item View Item