| dc.contributor |
Fakultas Matematika dan Ilmu Pengetahuan Alam |
|
| dc.creator |
Prasetia, Muhammad Wisnu |
|
| dc.creator |
Sunendiari, Siti |
|
| dc.date |
2019-01-25 |
|
| dc.date.accessioned |
2019-09-11T01:59:26Z |
|
| dc.date.available |
2019-09-11T01:59:26Z |
|
| dc.identifier |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/14389 |
|
| dc.identifier.uri |
http://hdl.handle.net/123456789/22037 |
|
| dc.description |
Abstract. In statistics how to control quality can be done using a control diagram. The use of control diagrams depends on the number of variables observed. If the variable is only one, then univariate control diagrams are used, but if the variables are more than one, multivariate control diagrams are used. A multivariate control diagram is a diagram that controls variables that correlate together to influence a process. The assumption that must be fulfilled in a multivariate control diagram is that the data must follow a multivariate normal distribution. One of the multivariate control diagrams is the multivariate Generalized variance control diagram. Generalized variance control diagrams are used to monitor the variability of the production process simultaneously. In this thesis will discuss the Generalized Variance control diagram using secondary data from Agus Heryandri (1997) thesis in the production process of making Plywood on the Ketapang Indah Plywood P. Pontianak Industry. The results of monitoring the variability of the Plywood production process are out of control.Keywords: Multivariate normal distribution, process variability, Generalized Variance control diagram.Abstrak. Dalam statistika cara mengendalikan kualitas bisa dilakukan dengan menggunakan diagram kendali. Penggunaan diagram kendali tergantung dari banyaknya variabel yang diamati. Apabila variabelnya hanya satu maka digunakan diagram kendali univariat, tetapi jika variabelnya lebih dari satu maka digunakan diagram kendali multivariat. Diagram kendali multivariat merupakan diagram yang mengendalikan variabel yang saling berkorelasi secara bersama-sama mempengaruhi suatu proses. Asumsi yang harus terpenuhi dalam diagram kendali multivariat adalah data harus mengikuti distribusi normal multivariat. Salah satu diagram kendali multivariat yaitu diagram kendali multivariat Generalized variance. Diagram kendali Generalized variance digunakan untuk memantau variabilitas proses produksi secara simultan. Dalam skripsi ini akan membahas diagram kendali Generalized Variance dengan menggunakan data sekunder dari skripsi Agus Heryandri (1997) pada proses produksi pembuatan Plywood di P.T Ketapang Indah Plywood Industri Pontianak. Hasil dari pemantuan variabilitas proses produksi Plywood tidak terkendali.Kata Kunci: Distribusi normal multivariat, Variabilitas Proses, Diagram Kendali Generalized Variance. |
|
| dc.format |
application/pdf |
|
| dc.format |
application/pdf |
|
| dc.language |
eng |
|
| dc.publisher |
Universitas islam Bandung |
|
| dc.relation |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/14389/pdf |
|
| dc.relation |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/14389/pdf_1 |
|
| dc.rights |
Copyright (c) 2019 Prosiding Statistika |
|
| dc.source |
Prosiding Statistika; Vol 5, No 1, Prosiding Statistika (Februari, 2019); 10-15 |
|
| dc.source |
Prosiding Statistika; Vol 5, No 1, Prosiding Statistika (Februari, 2019); 10-15 |
|
| dc.source |
2460-6456 |
|
| dc.subject |
Statistika |
|
| dc.subject |
Distribusi normal multivariat, Variabilitas Proses, Diagram Kendali Generalized Variance |
|
| dc.title |
Diagram Kendali Generalized Variance |
|
| dc.type |
info:eu-repo/semantics/article |
|
| dc.type |
info:eu-repo/semantics/publishedVersion |
|
| dc.type |
Peer-reviewed Article |
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| dc.type |
kuantitatif |
|