Bima Putra Efendi, . (2025) IMPLEMENTASI RANDOM FOREST REGRESSOR UNTUK PREDIKSI BIAYA PENGIRIMAN BARANG PADA PT. WIDYA TRANS CARGO. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (224kB) |
|
Text
AWAL.pdf Download (658kB) |
|
Text
BAB I.pdf Restricted to Repository UPNVJ Only Download (404kB) |
|
Text
BAB II.pdf Restricted to Repository UPNVJ Only Download (408kB) |
|
Text
BAB III.pdf Restricted to Repository UPNVJ Only Download (330kB) |
|
Text
BAB IV.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
BAB V.pdf Download (265kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (232kB) |
|
Text
DAFTAR RIWAYAT HIDUP.pdf Restricted to Repository UPNVJ Only Download (161kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (9MB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (820kB) |
Abstract
PT. Widya Trans Cargo as a company engaged in logistics faces challenges in determining the estimated shipping price quickly and accurately to customers. In some situations, the company must check historical data to provide an estimate of shipping costs to customers. This certainly takes a long time because the company must match new customer data with historical data. To overcome this, this study developed a web-based shipping price prediction system using the Random Forest algorithm. The model is built based on historical shipping data that includes attributes of the destination city, shipping distance, and weight of the goods. The evaluation results show that the model with a training data and test data ratio of 90:10 provides the best performance with an accuracy level of 96.86% and a Mean Absolute Percentage Error (MAPE) value of 3.14%. This system is implemented using the Streamlit framework which allows users to make interactive price predictions through manual input. With this prediction system, the company can provide faster price estimates to customers and support operational efficiency and strategic decision making in shipping management.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2110512027] [Pembimbing 1: Nur Hafifah Matondang] [Pembimbing 2 : M. Octaviano Pratama] [Penguji 1: Kraugusteeliana] [Penguji 2: Sarika] |
| Uncontrolled Keywords: | Logistics, Random Forest, Prediction System, Price Prediction |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | BIMA PUTRA EFENDI |
| Date Deposited: | 07 Aug 2025 07:07 |
| Last Modified: | 07 Aug 2025 07:07 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37506 |
Actions (login required)
 |
View Item |