Setyobudi, Indana Lazulfa (2019) Peramalan Produktivitas Buah Yang Dipengaruhi Suhu, Curah Hujan, Dan Kelembaban Di Kota Batu Dengan Metode Statistik Dan Machine Learning. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kota Batu juga dikenal sebagai kota penghasil buah, dimana produksi buah apel menurun akhi-akhir ini. Namun buah lain mengalami kenaikan diantaranya jeruk siam/keprok, alpukat, jambu biji, dan pisang. Penurunan produksi apel tersebut diduga akibat berubahnya iklim dan hujan yang terus menerus. Tujuan penelitian ini adalah meramalkan produktivitas buah yang diduga dipengaruhi suhu, curah hujan, dan kelembaban di Kota Batu. Metode yang digunakan pada penelitian ini adalah ARIMA, fungsi transfer, dan FFNN. Variabel dependen yang digunakan yaitu produktivitas buah, sedangkan variabel independen yang digunakan adalah suhu, curah hujan, dan kelembaban. Data yang digunakan berupa data triwulan pada periode Januari 2008 sampai Desember 2018. Berdasarkan hasil analisis diperoleh bahwa model terbaik untuk meramalkan produktivitas buah adalah dengan metode FFNN. Hasil analisis juga menunjukkan bahwa produktivitas apel, jambu biji, dan alpukat dipengaruhi oleh curah hujan. Sedangkan produktivitas jeruk dipengaruhi suhu. Hasil peramalan menunjukkan bahwa produktivitas jeruk, alpukat, dan pisang di Kota Batu diprediksi mengalami peningkatan di tahun 2019, sedangkan produktivitas apel dan jambu biji mengalami penurunan.
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Batu City also known as apples producer, where the apples production is decreasing recently. But,another fruits are increasing, there are oranges, avocadoes, guavas, and bananas. Decrease of apples production is suspected because climate change and unstinting rain. The purpose of this research is predicting fruits productivity which depends on temperature, rainfall,and humidity in Batu. The methods which are used in this research is ARIMA, transfer function, and FFNN. Fruits productivity is used to be dependent variabel, while the used independent variabel is temperature, rainfall, and humidity. The used data is quarterly data on January 2008 until December 2018. Based on analysis can be inferred that the best model for predicting fruits productivity is FFNN mode. The result of analysis shows that rainfall influence apples, avocadoes, and guavas productivity. While oranges productivity is influenced by temperature. The results of prediction shows that oranges, avocadoes, and bananas productivity in Batu City are predicted to have increase in 2019, meanwhile apples and guavas productivity has decrease.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.535 Set p-1 2019 |
| Uncontrolled Keywords: | Forecasting, productivity, temperature, rainfall, humidity, ARIMA, transfer function, FFNN. |
| Subjects: | H Social Sciences > HA Statistics > HA30.3 Time-series analysis Q Science > QA Mathematics > QA280 Box-Jenkins forecasting |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Setyobudi Indana Lazulfa |
| Date Deposited: | 27 Dec 2022 03:01 |
| Last Modified: | 27 Dec 2022 03:01 |
| URI: | http://repository.its.ac.id/id/eprint/64414 |
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