Narto, Edwin (2022) Analisis prediksi keputusan dalam stok produk pada toko online Angel Yap Bunny dengan metode CART (classification and regression tree). Bachelor thesis, Universitas Pelita Harapan.
Preview
Title.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (33kB) | Preview
Preview
Abstract.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (404kB) | Preview
Preview
ToC.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (897kB) | Preview
Preview
Chapter1.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (831kB) | Preview
![Chapter2 [thumbnail of Chapter2]](http://repository.uph.edu/style/images/fileicons/text.png)
Chapter2.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (1MB)
![Chapter3 [thumbnail of Chapter3]](http://repository.uph.edu/style/images/fileicons/text.png)
Chapter3.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (6MB)
![Chapter4 [thumbnail of Chapter4]](http://repository.uph.edu/style/images/fileicons/text.png)
Chapter4.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (4MB)
![Chapter5 [thumbnail of Chapter5]](http://repository.uph.edu/style/images/fileicons/text.png)
Chapter5.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (440kB)
Preview
Bibliography.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (729kB) | Preview
![Appendices [thumbnail of Appendices]](http://repository.uph.edu/style/images/fileicons/text.png)
Appendices.pdf
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial Share Alike.
Download (3MB)
Abstract
CART (Classification and Regression Tree) is a decision tree algorithm that is widely used to determine a decision from a large number of data sets provided by classification and regression processes. In this study, it was carried out by determining decisions with a classification process (Classification Tree), which will determine decisions in the form of reducing stock or adding stock, because one of the problems experienced at Angel Yap Bunny's online store is determining stock levels according to a number of datasets from store sales. Angel Yap Bunny online and still uses the manual method, which results in online shop owners often forgetting to add stock or reduce stock and hesitating in making decisions. Therefore, assistance from the CART data mining method is used to make the problem into a solution. In the CART calculation, 6 experiments were carried out from 17 data to 900 data, then each data from the experiment was divided into 70% as training data and 30% as testing data, and the average accuracy of 6 experiments was calculated. The experiment resulted in an accuracy of 96.78% with the hold- out accuracy measurement method, which means that the results of the decision prediction research in product stock at the Angel Yap Bunny online store were successful in this study and the use of./ CART (Classification and Regression Tree) adalah algoritma decision tree yang banyak digunakan untuk menentukan suatu keputusan dari sejumlah banyak data yang disediakan dengan proses klasifikasi dan regresi. Pada penelitian ini dilakukan dengan menentukan keputusan dengan proses klasifikasi (Classification Tree) yang dimana akan menentukan keputusan berupa kurangi stok atau tambah stok, karena salah satu masalah yang dialami pada toko online Angel Yap Bunny yaitu menentukan stok masih belum menurut dari sejumlah dataset dari penjualan toko online Angel Yap Bunny dan masih menggunakan cara manual yang mengakibatkan pemilik toko online sering lupa untuk melakukan penambahan stok maupun pengurangan stok dan ragu dalam menentukan keputusan. Oleh karena itu digunakan bantuan dari metode data mining CART untuk menjadikan permasalahan tersebut menjadi sebuah solusi. Dalam perhitungan CART tersebut, dilakukan 6 percobaan dari data yang berjumlah 17 data sampai dengan data yang berjumlah 900 data, kemudian masing-masing data dari percobaan tersebut dibagi dalam 70% sebagai data training dan 30% data testing, dan rata-rata akurasi dari 6 percobaan tersebut menghasilkan akurasi sebesar 96.78% dengan metode pengukuran akurasi hold-out yang artinya hasil penelitian prediksi keputusan dalam stok produk pada toko online Angel Yap Bunny berhasil dalam penelitian ini dan penggunaan hold-out method dengan menerapkan random statement berhasil dilakukan.
Item Type: | Thesis (Bachelor) |
---|---|
Creators: | Creators NIM Email ORCID Narto, Edwin NIM03081180003 edwinnarto.en@gmail.com UNSPECIFIED |
Contributors: | Contribution Contributors NIDN/NIDK Email Thesis advisor Ferawaty, Ferawaty NIDN0127047701 ferawaty.fik@uph.edu |
Uncontrolled Keywords: | data mining; cart; algoritma decision tree; angel yap bunny |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | University Subject > Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems |
Depositing User: | Users 23998 not found. |
Date Deposited: | 15 Aug 2022 06:08 |
Last Modified: | 15 Aug 2022 06:08 |
URI: | http://repository.uph.edu/id/eprint/49591 |