Prayoga, Ilham (2026) Sistem Prediksi Pengeluaran Keuangan Menggunakan Metode Long Short-Term Memory (LSTM) Berbasis Android. S1 thesis, Universitas PGRI Madiun.
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Abstract
This research is motivated by financial management issues at Bengkel Mobil Ilham Putra, where records are still kept manually, making it difficult for the owner to monitor expenditure trends and estimate future operational costs. The objective of this study is to design and develop an Android-based financial analysis support system by implementing the Long Short-Term Memory (LSTM) method for time series forecasting. System development follows the V-Model methodology using the Kotlin programming language and Firebase Firestore as a real-time database. The LSTM model was trained using a dataset of 1,043 historical transaction records from February 2025 to April 2026. The results indicate that the LSTM model successfully learned data patterns, as evidenced by the decrease in Mean Absolute Error (MAE) from 0.515 to 0.024 by the end of the training phase. A comparison with manual calculations yielded a Mean Absolute Percentage Error (MAPE) of 4.77%, which is categorized as "very good". Furthermore, functional testing using the Black Box Testing method showed that all application features, including inventory management and AI prediction, performed 100% optimally. Consequently, this application is a viable tool for financial planning and decision making for business owners.
| Item Type: | Thesis/Skripsi/Tugas Akhir (S1) |
|---|---|
| Kata Kunci: | Android; Long Short-Term Memory (LSTM); Time Series Forecasting; Financial Expenditure; Workshop. |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Teknik > Teknik Informatika |
| Depositing User: | ILHAM PRAYOGA |
| Date Deposited: | 18 Aug 2026 06:08 |
| Last Modified: | 18 Aug 2026 06:08 |
| URI: | http://eprint.unipma.ac.id/id/eprint/8471 |
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