Indrawati, Diana (2019) Model Peramalan Jumlah Kriminalitas Pencurian di Wilayah Polrestabes Kota Surabaya dengan Menggunakan Model Poisson GARMA dan Model Binomial Negatif GARMA. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pencurian adalah salah satu tindak kejahatan yang sering terjadi di masyarakat. Berdasarkan Kepolisian pencurian terdiri atas pencurian biasa, pencurian ringan, pencurian pemberatan dan pencurian kekerasan. Menurut BPS, jumlah kejadian pencurian terbanyak terjadi selama tahun 2018 salah satunya di wilayah Polrestabes Kota Surabaya. Berdasarkan fakta tersebut dilakukan peramalan untuk memberikan bahan pertimbangan jumlah kejadian pencurian di masa mendatang. Peramalan umumnya menggunakan model ARMA. Model ARMA kurang cocok digunakan pada peramalan count data. Model ARMA dikembangkan menjadi model GARMA, jika data diasumsikan berdistribusi Poisson disebut Poisson GARMA dan jika data diasumsikan berdistribusi Binomial Negatif disebut Binomial Negatif GARMA. Estimasi model Poisson GARMA dan Binomial Negatif GARMA menggunakan MLE dan dioptimasi menggunakan IRLS. Model ini diterapkan pada kasus kriminalitas pencurian di wilayah Polrestabes Kota Surabaya dan membandingkan tingkat akurasi peramalan antara Poisson GARMA dan Binomial Negatif GARMA. Hasil yang didapatkan model Binomial Negatif GARMA (1,0) lebih baik untuk wilayah Surabaya Pusat, Surabaya Timur, dan Surabaya Selatan daripada model Poisson GARMA (1,0) sedangkan model Binomial Negatif GARMA (0,2) lebih baik untuk wilayah Surabaya Barat daripada model Poisson GARMA (0,2). Model terbaik diantara seluruh wilayah Polretabes Surabaya adalah model Binomial Negatif GARMA (0,2). Pemilihan model terbaik menggunakan nilai AIC yang terendah.
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Theft is a crime that often occurs in the community. According to the Police, theft consists of ordinary theft, minor theft, weight theft, and theft of violence. According to BPS, the highest number of incidents of theft occurred during 2018, one of which was in the Surabaya City Police Region. Based on these facts forecasting is done to provide material for consideration of the number of incidents of theft in the future. Forecasting generally uses the ARMA model. The ARMA model is less suitable for use in count data. The ARMA model was developed into the GARMA model if the data is assumed to be Poisson distribution called Poisson GARMA and if the data is assumed to be Negative Binomial distribution is called Negative Binomial GARMA. Estimation of the Poisson GARMA model and Binomial Negative GARMA model uses MLE and is optimized using IRLS. This model is applied in cases of theft crimes in the Surabaya City Police Region and compares the accuracy of forecasting between Poisson GARMA and Negative Binomial GARMA. Based on the analysis carried out, the Negative Binomial GARMA (1.0) model is better for Central Surabaya, East Surabaya, and South Surabaya than Poisson GARMA (1.0) model and the Negative Binomial GARMA (0.2) model is better for the West Surabaya region rather than the Poisson GARMA (0.2) model. The best model in the Surabaya City Police Region area is the Binomial Negative GARMA (0.2) model in the West Surabaya region. The selection of the best model uses the lowest value of AIC.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSMa 519.535 Ind m-1 2019 |
| Uncontrolled Keywords: | AIC, Binomial Negatif GARMA, Jumlah Pencurian, Poisson GARMA. |
| Subjects: | Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA280 Box-Jenkins forecasting |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Diana Indrawati |
| Date Deposited: | 29 May 2023 01:32 |
| Last Modified: | 29 May 2023 01:32 |
| URI: | http://repository.its.ac.id/id/eprint/66076 |
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