MUHAMMAD RIZKI ANANDA, NPM 2109100048 (2025) ANALISIS DATA LAPORAN PENJUALAN PADA TOKO BOLEN ONE CAKE RANTAU PRAPAT MENGGUNAKAN METODE NAÏVE BAYES. Skripsi thesis, Universitas Labuhanbatu.
![[img]](http://repository.ulb.ac.id/style/images/fileicons/text.png) |
Text
COVER FULL.pdf Download (1MB) |
|
Text
BAB I.pdf Download (459kB) |
|
Text
BAB II.pdf Download (824kB) |
|
Text
BAB III.pdf Download (1MB) |
|
Text
BAB IV.pdf Download (1MB) |
|
Text
BAB V.pdf Download (428kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (602kB) |
Abstract
Dalam era digitalisasi, pemanfaatan data penjualan sangat penting dalam mendukung pengambilan keputusan strategis, terutama bagi usaha kecil dan menengah (UKM). Metode Naive Bayes dipilih karena keunggulannya dalam efisiensi komputasi dan kemampuannya mengolah data berskala besar dengan akurasi yang memadai. Penelitian ini menggunakan data penjualan selama empat bulan, dari November 2024 hingga Februari 2025, yang kemudian diproses melalui tahapan pra-pemrosesan, pembagian data training dan testing, serta pengujian menggunakan aplikasi Orange. Hasil pengujian menunjukkan tingkat akurasi model sebesar 80%, F1-score 81,8%, dan AUC sebesar 90%, yang menunjukkan bahwa metode ini cukup efektif dalam klasifikasi produk. Dengan hasil tersebut, toko dapat mengoptimalkan strategi pemasaran, pengelolaan stok, dan pengambilan keputusan bisnis secara lebih tepat. Penelitian ini juga menyarankan untuk menambahkan variabel eksternal dan membandingkan dengan metode klasifikasi lain di penelitian selanjutnya. Kata Kunci: Data Penjualan, Naive Bayes, Klasifikasi, Orange, Toko Kue, UMKM ================================================================================================== In the digitalization era, utilizing sales data is essential to support strategic decision-making, especially for small and medium-sized enterprises (SMEs). The Naive Bayes algorithm was chosen due to its computational efficiency and ability to handle large-scale data with reliable accuracy. The research used four months of sales data, from November 2024 to February 2025, which was processed through data preprocessing, training and testing dataset division, and evaluation using the Orange application. The testing results showed a model accuracy of 80%, an F1-score of 81.8%, and an AUC of 90%, indicating that the method is effective for product classification. These findings help the store optimize marketing strategies, stock management, and business decision-making. The study also suggests incorporating external variables and comparing Naive Bayes with other classification algorithms for future research. Keywords: Sales Data, Naive Bayes, Classification, Orange, Cake Store, SME
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Data Penjualan, Naive Bayes, Klasifikasi, Orange, Toko Kue, UMKM==============Sales Data, Naive Bayes, Classification, Orange, Cake Store, SME |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 06 Nov 2025 02:30 |
| Last Modified: | 06 Nov 2025 02:30 |
| URI: | http://repository.ulb.ac.id/id/eprint/1927 |
Actions (login required)
 |
View Item |
