Arifa, Salsabila (2025) Rancang Bangun Aplikasi Website dan Mobile Pengelolaan Proyek Perumahan dengan Metode KNN untuk Prediksi Penjualan Rumah (Studi Kasus: PT. Bakti Luhur Abadi). Undergraduate thesis, UPN Veteran Jawa Timur.
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (Cover)
21081010067-cover.pdf Download (2MB) |
|
Text (Bab 1)
21081010067-bab1.pdf Download (189kB) |
|
Text (Bab 2)
21081010067-bab2.pdf Restricted to Repository staff only until 19 June 2027. Download (276kB) |
|
Text (Bab 3)
21081010067-bab3.pdf Restricted to Repository staff only until 19 June 2027. Download (3MB) |
|
Text (Bab 4)
21081010067-bab4.pdf Restricted to Repository staff only until 19 June 2027. Download (1MB) |
|
Text (Bab 5)
21081010067-bab5.pdf Download (168kB) |
|
Text (Daftar Pustaka)
21081010067-daftarpustaka.pdf Download (165kB) |
|
Text (Lampiran)
21081010067-lampiran.pdf Restricted to Repository staff only until 19 June 2027. Download (102kB) |
Abstract
PT Bakti Luhur Abadi is a property development company that manages projects independently. Currently, project progress monitoring is still done manually and sales reports are generated using Microsoft Excel. The solution implemented is to develop an application that functions as a project management tool equipped with predictive technology to support more effective sales planning and strategies by utilizing the K-Nearest Neighbors (KNN) method. The research methods include needs analysis, system design, implementation, and testing. The application has three access levels: the Website Application is fully managed by the Admin, while the Mobile Application is managed by the Director and Field Team. The website application was built using CodeIgniter 3, while the mobile application was built using React Native. The result is a website with the main feature of website management.. The mobile application's main features include progress reporting and procurement requests. Application testing was conducted using the Blackbox method with several testing scenarios for each feature. The website application was tested with 17 features, while the mobile application was tested with 12 features. KNN testing was conducted using 30 test data and 114 training data with varying K values. The testing results with different K values showed varying accuracy levels. The testing results indicated that K = 7 yielded the highest accuracy, at 86.7%.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||||||
| Subjects: | Q Science > QA Mathematics > QA76 Computer software Q Science > QA Mathematics > QA76.6 Computer Programming |
||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Salsabila Arifa | ||||||||||||
| Date Deposited: | 19 Jun 2025 02:09 | ||||||||||||
| Last Modified: | 19 Jun 2025 02:09 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/38587 |
Actions (login required)
 |
View Item |