SIREUBOH: KLASIFIKASI DATA LOKASI BARANG MENGGUNAKAN REGION OF INTEREST (ROI) DAN ALGORITMA RANSAC

Jurnal Tekno Insentif

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Title SIREUBOH: KLASIFIKASI DATA LOKASI BARANG MENGGUNAKAN REGION OF INTEREST (ROI) DAN ALGORITMA RANSAC
 
Creator Pane, Syafrial Fachri
Awangga, Rolly Maulana
., Maulyanda
 
Description Abstrak - Perusahaan yang bergerak pada bidang logistik membutuhkan inovasi untuk meningkatkan daya saing dalam memberikan layanan terbaik mereka kepada konsumen, salah satunya pada Warehouse Management System (WMS) karena sistem tersebut masih kesulitan dalam mencocokkan data lokasi dengan sistem Logistics Execution System (LES) yang dipakai konsumen. sehingga pada bagian operation system management masih kesulitan dalam proses penempatan barang. Penelitian ini menggunakan algoritma RANSAC untuk mengukur keakuratan data lokasi barang pada proses penempatan barang yang sesuai, Region Of Interest (ROI) untuk memperkecil ruang lingkup data lokasi barang. Hasil analisis yang telah dilakukan dengan melakukan pencocokan data WMS dan LES didapatkan nilai persentase sebesar 87% untuk tingkat keakuratan data lokasi barang dengan mengolah 100 sample data lokasi barang yang dimiliki perusahaan. Hasil penelitian ini menunjukkan sangat bermanfaat karena dapat melakukan pencocokan data berdasarkan lokasi barang.
 
Abstract -  Companies that are engaged in logistics need innovation to improve competitiveness in providing their best services to consumers, one of which is the Warehouse Management System (WMS) because the system is still having difficulty matching location data with the Logistics Execution System (LES) system used by consumers. so that in the operation system management section there are still difficulties in the process of placing goods. This study uses the RANSAC algorithm to measure the accuracy of item location data in the process of placing the appropriate goods, Region of Interest (ROI) to reduce the scope of the location data of goods. The results of the analysis that have been done by matching WMS and LES data obtained a percentage value of 87% for the level of accuracy of the location data of goods by processing 100 samples of location data of goods owned by the company. The results of this study indicate that it is very useful because it can do data matching based on the location of the item.
 
Publisher Lembaga Layanan Pendidikan Tinggi Wilayah IV
 
Date 2019-04-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artikel Peer-review
 
Format application/pdf
 
Identifier https://jurnal.lldikti4.or.id/index.php/jurnaltekno/article/view/98
10.36787/jti.v12i2.98
 
Source Jurnal Tekno Insentif; Vol 12 No 2 (2018): Jurnal Tekno Insentif; 36-40
Jurnal Tekno Insentif; Vol 12 No 2 (2018): Jurnal Tekno Insentif; 36-40
2655-089X
1907-4964
10.36787/jti.v12i2
 
Language ind
 
Relation https://jurnal.lldikti4.or.id/index.php/jurnaltekno/article/view/98/63
 
Rights Hak Cipta (c) 2019 Jurnal Tekno Insentif
http://creativecommons.org/licenses/by-nc-sa/4.0
 

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