Rekomendasi stok UMKM sektor peternakan dengan menggunakan metode Naïve Bayes di 786 NS Farm

Dennison, Shendy (2023) Rekomendasi stok UMKM sektor peternakan dengan menggunakan metode Naïve Bayes di 786 NS Farm. Bachelor thesis, Universitas Pelita Harapan.

[img]
Preview
Text (Title)
Title.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (87kB) | Preview
[img]
Preview
Text (Abstract)
Abstract.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (254kB) | Preview
[img]
Preview
Text (ToC)
ToC.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (344kB) | Preview
[img]
Preview
Text (Chapter1)
Chapter 1.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (223kB) | Preview
[img] Text (Chapter2)
Chapter 2.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (756kB)
[img] Text (Chapter3)
Chapter 3.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB)
[img] Text (Chapter4)
Chapter 4.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (868kB)
[img] Text (Chapter5)
Chapter 5.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (197kB)
[img]
Preview
Text (Bibliography)
Biblio.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (345kB) | Preview
[img] Text (Appendices)
Appendices.pdf
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (5MB)

Abstract

Transformasi digital telah menjadi fokus, dan Presiden telah menghimbau para pelaku UMKM untuk bergerak menuju platform digital pada tahun 2024 untuk mendukung ekspansi dan perdagangan global. Dengan dorongan untuk digitalisasi, tantangan yang dihadapi adalah penentuan perencanaan stok yang optimal. Penelitian ini mengusulkan metode Naïve Bayes dalam perencanaan stok. Metode ini dipilih karena kemampuannya dalam mengolah nilai atribut terhubung atau bebas dengan probabilitas yang lebih sederhana dan telah terbukti mencapai akurasi yang lebih tinggi dibandingkan model pengklasifikasi lainnya. Selain itu, pengembangan aplikasi yang dilakukan menggunakan metode pengembangan Agile, yang melibatkan tahap planning, design, develop, testing, deploy, dan review. Hasil dari pengujian Black Box yang dilakukan untuk mengevaluasi kinerja sistem sesuai kebutuhan pengguna, menunjukkan pencapaian 100% pada 4 aktivitas pengujian. Pengujian ini mengindikasikan bahwa fitur dalam perancangan ini memberikan solusi optimal untuk pengadaan barang. Dengan demikian, sistem ini dianggap berhasil dan dapat diimplementasikan oleh pelaku usaha di 786 NS Farm untuk menganalisis dan membuat keputusan dalam proses penambahan stok./ Digital transformation has become a focal point, with the President urging micro, small, and medium-sized enterprises (MSMEs) to embrace digital platforms by 2024 to support global expansion and trade. With the drive for digitalization, the challenge lies in determining optimal stock planning. This research proposes the use of data mining, specifically the Naïve Bayes method in stock planning. This method was chosen for its ability to process linked or independent attribute values with simpler probabilities and has been proven to achieve higher accuracy compared to other classifier models. Furthermore, the application development was conducted using the Agile development method, involving stages of planning, design, development, testing, deployment, and review. The results of the Black Box testing conducted to evaluate system performance according to user needs show a 100% achievement in 4 testing activities. These tests indicate that the features in this design provide an optimal solution for procurement. Thus, the system is considered successful and can be implemented by business players at 786 NS Farm to analyze and make decisions in the stock replenishment process.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Dennison, ShendyNIM03081200024shendydennison@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorPangaribuan, Jefri JuniferNIDN0130108901jefri.pangaribuan@uph.edu
Uncontrolled Keywords: UMKM; perencanaan stok, Naïve Bayes, agile
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
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: Shendy Dennison
Date Deposited: 06 Feb 2024 04:14
Last Modified: 06 Feb 2024 04:14
URI: http://repository.uph.edu/id/eprint/61526

Actions (login required)

View Item View Item