| dc.contributor.advisor | Aziezah, Nur | |
| dc.contributor.author | JUHENDRA, GANDI | |
| dc.date.accessioned | 2024-08-07T02:39:26Z | |
| dc.date.available | 2024-08-07T02:39:26Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/156415 | |
| dc.description.abstract | Welding merupakan proses menyatukan bagian atas dan bawah bodi mobil dengan ribuan jenis pengelasan. Proses welding di PT XYZ memiliki peran penting dalam produksi mobil, dengan dua bagian utama yaitu Welding 1 dan Welding 2. Penelitian ini bertujuan untuk menganalisis working hour dan tingkat produksi menggunakan algoritma K-Means Clustering. Data working hour dari April hingga Desember 2023 dikelompokkan menjadi tiga cluster: working hour rendah (kurang dari 390 menit), working hour sedang (390-560 menit), dan working hour tinggi (lebih dari 560 menit). Hasil analisis menunjukkan bahwa produk dari Welding 1
(mobil A, B, dan C) memiliki permintaan yang lebih tinggi dibandingkan produk dari Welding 2 (mobil D, E, F, dan G). Rata-rata produksi harian di Welding 1 adalah 241 hingga 264 mobil, sementara di Welding 2 adalah 187 hingga 247 mobil. Berdasarkan temuan ini, disarankan agar PT XYZ meningkatkan strategi pemasaran dan efisiensi produksi terutama di Welding 2 untuk memenuhi
permintaan pasar. | |
| dc.description.abstract | Welding unites the upper and lower parts of a car body with thousands of welding types. The welding process at PT XYZ plays a crucial role in car production, with two main divisions: Welding 1 and Welding 2. This study aims to analyze working hours and production levels using the K-Means Clustering algorithm. Working hour data from April to December 2023 was grouped into three clusters: low working hours (less than 390 minutes), medium working hours (390-560 minutes), and high working hours (more than 560 minutes). The analysis results show that products from Welding 1 (cars A, B, and C) have higher demand compared to products from Welding 2 (cars D, E, F, and G). The average daily production in Welding 1 is 241 to 264 cars, while in Welding 2 it is 187 to 247 cars. Based on these findings, it is recommended that PT XYZ enhance its marketing
strategies and production efficiency, particularly in Welding 2, to meet market demand. | |
| dc.description.sponsorship | | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Penerapan K-Means untuk Clustering Data Working Hour pada Bagian Welding Perusahaan Manufaktur | id |
| dc.title.alternative | Application of K-Means Clustering for Working Hour Data in the Welding Department of Manufacturing Companies | |
| dc.type | Tugas Akhir | |
| dc.subject.keyword | clustering | id |
| dc.subject.keyword | k-means clustering | id |
| dc.subject.keyword | production analysis | id |
| dc.subject.keyword | welding | id |
| dc.subject.keyword | working hour | id |
