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Penerapan Metode Empirical Best Linear Unbiased Prediction (EBLUP) pada Model Fay-Herriot Small Area Estimation (SAE) Luthfatul Amaliana; Evellin Dewi Lusiana
Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Vol 1 No 1 (2017): Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai Islami )
Publisher : Mathematics Department

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.784 KB)

Abstract

Small area digambarkan sebagai suatu area geografis kecil, seperti desa/kelurahan, kecamatan, atau kabupaten. Ukuran sampel yang kecil dari small area menyebabkan estimasi parameter secara langsung tidak mampu menghasilkan ketelitian yang cukup baik. Metode Empirical Best Linear Unbiased Prediction (EBLUP) pada Small Area Estimation (SAE) menjadi salah satu solusi untuk permasalahan estimasi pada model small area, yaitu model Fay-Herriot. Tujuan dari penelitian ini adalah mencari estimator model Fay-Herriot yang bersifat linier, unbiased, dan terbaik serta diaplikasikan pada kasus kemiskinan di Kabupaten Jember. Salah satu ukuran kebaikan estimator yaitu dari Mean Square Error (MSE) hasil estimasi. Dalam penelitian ini, metode Lagrange digunakan untuk memperoleh MSE EBLUP yang minimum. Hasil estimasi pengeluaran rumah tangga per kapita di desa di Kabupaten Jember menunjukkan bahwa hasil estimasi EBLUP lebih baik dibandingkan hasil estimasi langsung.
THE EFFECTIVENESS OF DEMONSTRATION AND EXPERIMENTATION LEARNING METHODS FOR EMPOWERING PINE FOREST COFFEE FARMERS BENDOSARI VILLAGE PUJON-MALANG INDONESIA Ani Budi Astuti; N Nurjannah; Luthfatul Amaliana; Wenny Bekti Sunarharum
Erudio Journal of Educational Innovation Vol 6, No 2 (2019): Erudio Journal of Educational Innovation
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18551/erudio.6-2.4

Abstract

An effective learning method is very important for the success of a learning goal, especially for the success of learning that involves the village community. The village communities have very diverse abilities and knowledge, in general an activity is carried out in accordance with daily habits, so it is not easily changed. However, the villagers already have a lot of experience, especially related to their daily livelihoods. The characteristics of such objects require an effective learning innovation in order to increase the knowledge they do not yet have. An effective learning method is a form of activity to improve the culture of literacy in the community. The demonstration learning methods and field experiments proposed as learning methods are expected to be in accordance with the characteristics of coffee farmers in Bendosari Village in the context of empowering coffee farmers in Bendosari Village. The purpose of this study is to identify how effective the demonstration learning methods and field experiments for empowering coffee farmers in Bendosari Village, Pujon-Malang Indonesia. The results showed that the demonstration learning method and field experiment very effective in increasing the knowledge and field ability of coffee farmers in Bendosari Village. Increase farmers knowledge and ability by 20%.
PERFORMA PROPORSI ZERO-INFLATION PADA REGRESI ZERO-INFLATED NEGATIVE BINOMIAL (STUDI KASUS: DATA TETANUS NEONATORUM DI JAWA TIMUR) LUTHFATUL AMALIANA; UMU SA’ADAH; NI WAYAN SURYA WARDHANI
E-Jurnal Matematika Vol 7 No 1 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2018.v07.i01.p183

Abstract

Tetanus Neonatorum (TN) is an infectious disease that could be prevented by immunization. East Java Province is the highest numbers of TN case in Indonesia. TN data in East Java contain overdispersion and big proportion of zero-inflation (71,05%). The data containing overdispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The aim of this study are: (1) to know the perform of proportion of zero-inflation for ZINB model and (2) to obtain the optimal proportion of zero-inflation for TN data. The result of this study indicates that the optimal proportion of ZINB model is 64,52%.
EBLUP-SMALL AREA ESTIMATION METHOD FOR PER CAPITA EXPENDITURES IN BALI LUTHFATUL AMALIANA; MADE LARAS SETYANA DEWI
E-Jurnal Matematika Vol 11 No 1 (2022)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2022.v11.i01.p361

Abstract

Small Area Estimation (SAE) is a statistical technique for estimating the parameters of a sub-population with a small sample size. SAE aims to improve the accuracy of parameter estimation, with indirect estimation. This study aims to determine the best method between empirical best linear unbiased prediction (EBLUP) and spatial EBLUP methods (with a queen contiguity weighted matrix) in estimating per capita expenditure per sub-district in Bali. The results of this study indicate that the best SAE method in estimating per capita expenditure per sub-district in Bali is the EBLUP method with the smaller mean squared error. The EBLUP estimation results are significantly influenced by three variables, namely the population, public primary schools, and families using PLN. The sub-district with the highest per capita expenditure in Bali is Denpasar Selatan sub-district. Meanwhile, the sub-district with the lowest per capita expenditure was Abang sub-district. Since the EBLUP model is better than SEBLUP model, this indicates that per capita expenditure per sub-district in Bali is not influenced by its neighbors.
Model Geographically Weighted Regression dengan Fungsi Pembobot Adaptive dan Fixed Kernel pada Kasus Kematian Ibu di Jawa Timur Ulfie Safitri; Luthfatul Amaliana
Jurnal Statistika dan Aplikasinya Vol 5 No 2 (2021): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.05209

Abstract

Model Geographically Weighted Regression (GWR) merupakan pengembangan dari model regresi linier berganda yang dapat menghasilkan penduga parameter model yang bersifat lokal untuk setiap titik atau lokasi di mana data diamati. Model GWR dapat digunakan apabila data memenuhi asumsi heterogenitas spasial yang diakibatkan oleh perbedaan kondisi data antara satu lokasi dengan lokasi lain. Penelitian ini bertujuan untuk menentukan model GWR terbaik dengan pembobot adaptive kernel dan fixed kernel pada kasus kematian ibu di Jawa Timur tahun 2018. Data yang digunakan pada penelitian ini adalah data kematian ibu sebagai variabel respon dan rumah tangga berperilaku hidup bersih sehat, kunjungan ibu hamil dengan K4, ibu hamil mendapat tablet Fe3, persalinan yang ditolong tenaga kesehatan, serta jumlah fasilitas kesehatan sebagai variabel prediktor. Berdasarkan kriteria pemilihan model terbaik yang dilihat dari nilai AIC terkecil dapat disimpulkan bahwa model GWR dengan fungsi pembobot adaptive bi- square kernel merupakan model terbaik untuk data kematian ibu. Faktor yang mempengaruhi kasus kematian ibu berdasarkan pengujian parameter secara parsial yaitu kunjungan ibu hamil dengan K4 dan jumlah fasilitas kesehatan.
Confirmatory Factor Analysis pada Indikator Kesembuhan Pasien Isolasi Mandiri Covid-19 di Indonesia Nur Silviyah Rahmi; Luthfatul Amaliana; Laila Masruro Pimada; Reza Yesica; Devi Nur Cahaya Ningsih
Statistika Vol. 22 No. 1 (2022): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v22i1.477

Abstract

ABSTRAK Jumlah kasus terkonfirmasi positif Covid-19 di Indonesia pada September 2021 telah mencapai angka 4.204.116 Jiwa dengan pasien meninggal sebanyak 141 ribu orang atau tingkat kematian sebesar 3,4 persen. Kementerian Kesehatan Republik Indonesia melalui Satgas Penanganan Covid-19 telah menerbitkan pedoman pencegahan dan pengendalian Covid-19 untuk menekan angka kematian dan meningkatkan angka kesembuhan. Menurut pedoman tersebut, seseorang yang menjalani isolasi mandiri perlu diberikan perawatan kesehatan, dukungan sosial dan psikososial, serta kebutuhan dasar termasuk makanan, air dan kebutuhan pokok lainnya. Penelitian ini berusaha mengidentifikasi pengaruh faktor eksternal yang meliputi dukungan, serta faktor internal yang meliputi motivasi dan pengetahuan pasien terhadap tingkat kesembuhan penyintas Covid-19 isolasi mandiri. CFA digunakan apabila pengetahuan mengenai struktur suatu faktor laten diketahui. Struktur tersebut diperoleh berdasarkan kajian teoritis, hasil penelitian mengenai hubungan antara variabel yang diobservasi dengan variabel laten. Pendekatan CFA diterapkan untuk mengetahui indikator yang paling besar berpengaruh terhadap variabel laten dukungan sosial, pengetahuan dan motivasi kesembuhan. Pengambilan data primer dilakukan secara online dengan jumlah sampel sebanyak 148 responden penyintas Covid-19 di seluruh Indonesia pada bulan Agustus 2021. Hasil analisis CFA menunjukkan bahwa indikator DS1 (mendapatkan ungkapan empati, kepedulian, dan perhatian yang diberikan petugas terhadap penderita Covid-19) memiliki nilai loading factor terbesar yaitu 0,741. Pada variabel laten pengetahuan, indikator P7 (Tujuan pengobatan Covid-19 adalah menyembuhkan penderita, mencegah penularan dan kematian serta menurunkan tingkat penularan) memiliki nilai loading factor terbesar yaitu 0,767. Sedangkan pada variabel laten tindakan sembuh Indikator TS1 (Bersedia menjalani masa pengobatan dengan pemberian dalam waku pengobatan kurang lebih 14 hari) memiliki nilai loading factor terbesar yaitu 0,924. ABSTRACT The number of positive confirmed cases of Covid-19 in Indonesia in September 2021 has touched 4,204,116 people with the number of patients dying as many as 141,000 people or a death rate of 3.4 percent. The Ministry of Health of the Republic of Indonesia through the Covid-19 Handling Task Force has issued guidelines for the prevention and control of Covid-19 to reduce mortality and increase recovery rates. Based on these guidelines, people who are in self-isolation need to be provided with health care, social and psychosocial support, as well as basic needs including food, water and other basic needs. This study seeks to identify the influence of external factors which include support, as well as internal factors which include the motivation and knowledge of patients on the recovery rate of Covid-19 survivors in self-isolation. CFA can be used when knowledge of the composition or structure of a latent factor is known. The structure is obtained from theoretical studies, the results of research on the relationship between the variables studied and the latent variables. By using the CFA approach, it can be seen that the indicators that have the greatest influence on the latent variables of social support, knowledge and motivation for healing are known as loading factors. Primary data was collected online with 148 COVID-19 survivors across Indonesia in August 2021 as the sample. From the CFA analysis, it was found that the Social Support 1 (DS1) indicator, which is getting expressions of empathy, concern, and attention given by officers to Covid19 sufferers is the largest loading factor value, which is 0.745. This means that the influence of the DS1 indicator on the latent variable of Social Support is 0.745 or 74.5% is influenced by the DS1 indicator compared to the other 4 indicators, namely DS2, DS3, DS4, DS5. In the knowledge latent variable, the Knowledge 7 (P7) indicator, namely the purpose of Covid-19 treatment is to cure the patient, prevent transmission and death and reduce the transmission rate, which is the largest loading factor value, which is 0.767. Then on the latent variable of healing action, Healing Action Indicator 1 (TS1), namely being willing to undergo a treatment period with administration within a treatment time of approximately 14 days) is the largest loading factor value, which is 0.924.