Muizzadin, Muizzadin (2025) PREDIKSI CAPAIAN PENDAPATAN PASAR TRADISIONAL DI SURABAYA MENGGUNAKAN METODE BAYESIAN STRUCTURAL TIME SERIES (BSTS) DENGAN IMPLEMENTASI GUI R- SHINY. Undergraduate thesis, Universitas Pemabangunan Nasional Veteran Jawa Timur.
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Abstract
Traditional markets play an important role in supporting the regional economy,including in the city of Surabaya. However, in recent years, the number oftraditional markets has continued to decline due to competition with modernmarkets. In addition, the contribution of traditional markets to Regional OriginalIncome (PAD) shows fluctuations, such as 1.67% in 2013, 1.66% in 2014, andincreasing to 1.76% in 2015. This condition is a challenge in managing regionaleconomic policies, so an accurate prediction method is needed to support strategicdecision making. This study aims to predict the achievement of traditional marketrevenue in Surabaya using the Bayesian Structural Time Series (BSTS) method. Thedata used is the percentage of traditional market revenue achievement over the pastfifteen years. The BSTS model was chosen because of its ability to capture trends,seasonal patterns, and structural changes in data through the application ofcomponents such as Local Level, Local Linear Trend, and Seasonal. Modelperformance evaluation is carried out using two main metrics, namely MeanAbsolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). Theresults of the study showed that the model with Local Level and Seasonalcomponents, as well as 1,000 MCMC iterations, gave the best results with MAPEof 4.036% and RMSE of 5.198. This model proved effective in capturing datapatterns and providing accurate predictions. These findings indicate that the BSTSmethod is a reliable approach and can be used as a basis for decision making indesigning strategies to increase the contribution of traditional markets to theregional economy
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics Q Science > QA Mathematics > QA76.6 Computer Programming |
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| Divisions: | Faculty of Computer Science > Departemen of Data Science | ||||||||||||
| Depositing User: | Muizzadin Muizzadin | ||||||||||||
| Date Deposited: | 19 Jun 2025 07:35 | ||||||||||||
| Last Modified: | 19 Jun 2025 07:35 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/38592 |
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