Qur'ana, Ilma Ma'rifatul (2026) SISTEM PREDIKSI PENDAPATAN USAHA BARBERSHOP BERBASIS WEBSITE. Undergraduate thesis, Universitas Nusantara PGRI Kediri.
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Abstract
sistem prediksi pendapatan usaha barbershop berbasis website menggunakan metode Long Short-Term Memory (LSTM). Permasalahan yang dihadapi adalah pencatatan transaksi yang masih dilakukan secara manual sehingga sulit dilakukan analisis dan prediksi pendapatan. Sistem dikembangkan menggunakan bahasa pemrograman Python dengan framework Streamlit dan database SQLite. Fitur utama sistem meliputi input transaksi, riwayat transaksi, prediksi pendapatan, training ulang model, evaluasi model, serta laporan dalam format PDF, Excel, dan CSV. Metode LSTM digunakan untuk mempelajari pola data histori transaksi sehingga mampu menghasilkan prediksi pendapatan berdasarkan data sebelumnya. Hasil penelitian menunjukkan bahwa sistem berhasil berjalan dengan baik sesuai kebutuhan pengguna. Berdasarkan hasil evaluasi model diperoleh nilai RMSE sebesar Rp148.054, MAE sebesar Rp112.921, dan MAPE sebesar 16,86% dengan tingkat akurasi estimasi sebesar 83,1%. Hasil tersebut menunjukkan bahwa metode LSTM cukup baik digunakan untuk memprediksi pendapatan usaha barbershop.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Long Short-Term Memory (LSTM), Deep Learning, Barbershop, prediksi Pendapatan. |
| Subjects: | 410 Engineering science > 457 Computer engineering 410 Engineering science > 459 Computer science 410 Engineering science > 461 Information systems |
| Divisions: | Fakultas Teknik dan Ilmu Komputer > S1-Teknik Informatika |
| Depositing User: | Ilma Ma'rifatul Qur'ana |
| Last Modified: | 05 Aug 2026 05:00 |
| URI: | http://repository.unpkediri.ac.id/id/eprint/26564 |
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SISTEM PREDIKSI PENDAPATAN USAHA
BARBERSHOP BERBASIS WEBSITE. (deposited UNSPECIFIED)
- SISTEM PREDIKSI PENDAPATAN USAHA BARBERSHOP BERBASIS WEBSITE. (deposited UNSPECIFIED) [Currently Displayed]
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