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All Journal Jurnal Ilmu Dasar Jurnal Sains dan Seni ITS Journal of Civil Engineering Mandalika Mathematics and Educations Journal Enthusiastic : International Journal of Applied Statistics and Data Science

Vita Ratnasari

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Author-ID : 2570304

Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Articles

Pemodelan Persentase Kriminalitas Dan Faktor-Faktor Yang Mempengaruhi Di Jawa Timur Dengan Pendekatan Geographically Weighted Regression (GWR) Panji Anugrah Simamora; Vita Ratnasari
Jurnal Sains dan Seni ITS Vol 3, No 1 (2014)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Kejahatan atau kriminalitas merupakan perbuatan seseorang yang dapat diancam hukuman berdasarkan KUHP atau undang-undang serta peraturan lainnya di Indonesia. Pada tahun 2010 Polda Jawa Timur menduduki peringkat keempat jumlah kriminalitas tertinggi di Indonesia setelah Polda Metro Jaya, Polda Sumatera Utara dan Polda Jawa Barat. Perbedaan karakteristik geografis menyebabkan perbedaan atau keterikatan faktor ekonomi, sosial, budaya yang juga berpengaruh pada tindakan kriminalitas di setiap daerah. Karena itu penelitian ini akan memodelkan persentase kriminalitas dan faktor-faktor yang mempengaruhinya di Provinsi Jawa Timur dengan pendekatan Geographically Weighted Regression (GWR). Dari hasil penelitian ini didapatkan bahwa adanya pengaruh spasial dalam pemodelan persentase kriminalitas di Jawa Timur. Pemilihan pembobot dilakukan dengan cara memilih pembobot yang memiliki nilai AIC terkecil yaitu fix gaussian. Wilayah yang berdekatan cenderung memiliki kesamaan faktor-faktor yang mempengaruhi persentase kriminalitas di Jawa Timur. Variabel kepadatan penduduk dan persentase penduduk migran berpengaruh signifikan pada sebagian besar kabupaten/kota di Jawa Timur. Model GWR menghasilkan R2 sebesar 86,95 persen lebih besar dari model OLS yaitu 54,1 persen.`

Pengelompokkan Kelurahan di Kota Surabaya Berdasarkan Kriteria Pembentukan Kampung Keluarga Berencana Khusnul Khotimah; Vita Ratnasari; Madu Ratna
Jurnal Sains dan Seni ITS Vol 7, No 2 (2018)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Salah satu upaya yang dilakukan BKKBN untuk membumikan kembali program KKBPK adalah dengan terus membangun Kampung KB di seluruh wilayah Indonesia. Kampung KB merupakan satuan wilayah setingkat RW, dusun atau setara, yang memiliki kriteria tertentu, dimana terdapat keterpaduan program kependudukan, keluarga berencana, dan pembangunan keluarga dan pembangunan sektor terkait. Penelitian ini bertujuan untuk mengelompokkan kelurahan di Kota Surabaya berdasarkan kriteria pembentukan Kampung KB menggunakan analisis klaster sehingga diharapkan dapat membantu untuk menentukan wilayah yang akan dijadikan Kampung KB. Pengelompokkan yang dihasilkan, selanjutnya akan dilakukan analisis One Way MANOVA untuk mengetahui apakah terdapat perbedaan antar kelompok yang terbentuk berdasarkan kriteria pembentukan Kampung KB. Hasil analisis klaster menunjukkan bahwa terbentuk lima kelompok kelurahan di Kota Surabaya berdasarkan kriteria pembentukan Kampung KB serta metode pengelompokkan yang terbaik adalah metode ward’s. One Way MANOVA memberikan hasil bahwa terdapat perbedaan rata-rata antar kelompok kelurahan yang terbentuk berdasarkan kriteria pembentukan Kampung KB.

ANALISIS BIAYA UNTUK PEMILIHAN SUMBER DAYA LISTRIK UTAMA RUMAH POMPA GREGES Yudiono Yudiono; Umboro Lasminto; Vita Ratnasari
Journal of Civil Engineering Vol 33, No 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

The central government through the Directorate of Environmental Sanitation Development (PPLP) of the Directorate General of Human Settlements of the Ministry of Public Works and Public Housing participated in the implementation of drainage of Surabaya by providing assistance for the construction of Greges pump house. The pump house Greges as one of the pump house located in Surabaya, is one of the drainage system controllers around Bozem Morokrembangan area especially the flow of water along the Greges channel which is also an outlet for several channels. In the aid of the pump house choose to use Genset as the main power source (SDL). While the Government of Surabaya always wants the use of SDL from PLN. The purpose of this study was to analyze the use of SDL to meet the needs of the Greges Pump House by performing the cost analysis required for the Greges pump house for the use of Genset and PLN power sources, and determining the better SDL selection that would be used to meet the needs of the Greges pump house. Based on the analysis of costs, the use of generators is better than PLN in the investment cost analysis. Based on PLN operational cost analysis is better than generator. In the first year period the total cost for the use of PLN is Rp. 5.102.223.905 greater than the generator Rp. 4.789.084.970,16,, in the second year the cost of using PLN approaches the generator cost, and on the third and so the use of generator is higher than the PLN.

Estimation and Statistical Test in Bivariate Binary Probit Model Vita Ratnasari; Purhadi Purhadi; Ismaini Ismaini; Suhartono Suhartono
Jurnal ILMU DASAR Vol 12 No 1 (2011)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (191.357 KB)

One of the models that can be used to analyze two binary response variables data is bivariate binary probit model. This paper tried to estimate the parameters of bivariate binary probit model using Maximum Likelihood Estimationmethod, whereastoget the statistical test using Maximum Likelihood Ratio Test method.

The Curve Estimation Nonparametric Regression Multiresponse Mixed with Truncated Spline, Fourier Series, and Kernel Sukran, Ade Matao; I Nyoman Budiantara; Vita Ratnasari
Mandalika Mathematics and Educations Journal Vol 7 No 2 (2025): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i2.9188

This study formulates a nonparametric regression model for multiresponse data by combining three estimators: truncated spline, Fourier series, and kernel function. Each estimator captures specific characteristics. Truncated spline capture local traits with knot points, while fourier series capture periodic patterns and kernel estimators provide flexible smoothing for unknown functional forms. The model proposed is under an additive assumption where each predictor contributes independently to each response. Estimation is done with Weighted Least Squares (WLS) method which is efficient in managing the correlations between the multiresponse variables. The final multiresponse nonparametric regression curve estimator combining truncated spline, Fourier series, and kernel is given by \\hat{\mu} = \hat{f} + \hat{g} + \hat{h}\] obtained by solving the WLS optimization problem: [\min_{\boldsymbol{\beta}, \boldsymbol{\alpha}} \{ \boldsymbol{\varepsilon}' W \boldsymbol{\varepsilon} \} =\min_{\boldsymbol{\beta}, \boldsymbol{\alpha}} \left\{ (\mathbf{y}^* - U \boldsymbol{\beta} - Z \boldsymbol{\alpha})' W (\mathbf{y}^* - U \boldsymbol{\beta} - Z \boldsymbol{\alpha}) \right\}.\]. The solution to this problem results in the mixed estimator, which can be expressed as: \[\hat{\boldsymbol{\mu}} = E \mathbf{y} \quad \text{with} \quad E = UB + ZA + T.\]

A Zero-Inflated Ordered Probit Approach to Modeling Household Poverty Levels Yudhani, Nidya Putri; Vita Ratnasari; Santi Puteri Rahayu
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 1, April 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss1.art6

This research addressed the limitations of the ordered probit (OP) regression model in handling data that contains an excessive number of zero responses. The zero-inflated ordered probit (ZIOP) model was employed to overcome this issue. This model separates the estimation of structural zeros and ordinal outcomes through two distinct components: a binary probit for zero inflation and an OP for ordered categories. Due to the absence of closed-form solutions, parameter estimation was conducted using the maximum likelihood estimation (MLE) method with the Berndt-Hall-Hall-Hausman (BHHH) iterative algorithm. The analysis was based on 4,067 household-level observations from Indonesia’s National Socio-Economic Survey, incorporating indicators of health, education, and standard of living derived from the multidimensional poverty index (MPI) framework. The result of the Vuong test (4.56) confirmed that the ZIOP model significantly outperformed the conventional OP model for zero-inflated ordinal data. Therefore, the ZIOP model is considered more appropriate for analyzing household poverty classifications with a high prevalence of zero observations.

Co-Authors Ali Djamhuri I Nyoman Budiantara Ismaini Ismaini Khusnul Khotimah Madu Ratna Panji Anugrah Simamora Purhadi Purhadi Santi Puteri Rahayu Sukran, Ade Matao Umboro Lasminto Yudhani, Nidya Putri Yudiono Yudiono

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