Sri Pingit Wulandari
Jurusan Statistika Institut Teknologi Sepuluh Nopember (ITS) Surabaya

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PENGEMBANGAN PREFERENSI DALAM PEMILIHAN KONSEP PRODUK KOSMETIK BEDAK BERBASIS ANALISIS KONJOIN Wulandari, Sri Pingit
FORUM STATISTIKA DAN KOMPUTASI Vol. 14 No. 1 (2009)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Perkembangan industri kosmetik yang terus meningkat menyebabkan beragamnya produk bedak yang beredar di pasar, baik dari segi merek, fasilitas, jenis, harga maupun variasi lain yang terkandung dalam produk tersebut. Perusahaan yang bergerak di bidang produksi, baik produksi barang maupun jasa, tidak akan lepas dari mencari keuntungan optimal. Salah satu cara adalah dengan jalan kombinasi suatu produk. Analisis konjoin adalah suatu metode untuk mengoptimalkan keuntungan dengan jalan kombinasi produk. Kombinasi produk yang dimaksudkan adalah memproduksi satu jenis produk dengan ukuran atau kemasan tertentu dengan tujuan khusus agar dapat mencapai pangsa pasar yang lebih luas. Penyusunan konsep produk bedak berdasarkan pertimbangan atribut-atribut paling dipentingkan yang terkandung dalam produk bedak. Analisis konjoin menghasilkan konsep produk baru yang paling diinginkan sesuai preferensi responden. Konsep produk bedak yang terbentuk adalah produk bedak dengan jenis tabur, bahan kemasan melamin, tanpa harus terkandung kandungan UV dan Vitamin, disertai wewangian, bentuk kemasan bulat, dan ukuran harga yang penting.
Pemodelan Faktor-Faktor yang Mempengaruhi Jumlah Kasus Penyakit Tuberkulosis di Jawa Timur dengan Pendekatan Generalized Poisson Regression dan Geographically Weighted Poisson Regression Lestari, Rida Dwi; Wulandari, Sri Pingit; Purhadi, Purhadi
Jurnal Sains dan Seni ITS Vol 3, No 2 (2014)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (554.283 KB) | DOI: 10.12962/j23373520.v3i2.8130

Abstract

Tuberkulosis merupakan salah satu penyakit saluran pernafasan bawah dan menular yang disebabkan oleh kuman Mycrobacterium Tuberculosis. Provinsi Jawa Timur menduduki peringkat terbanyak kedua jumlah kasus penyakit tuberkulosis di Indonesia. Dalam penelitian ini dilakukan pemodelan faktor-faktor yang mempengaruhi jumlah kasus penyakit tuberkulosis di Jawa Timur dengan pendekatan Generalized Poisson Regression (GPR) dan Geographically Weighted Poisson Regressions (GWPR). Pemodelan menggunakan regresi poisson diperoleh hasil bahwa terjadi kasus over dispersi, sehingga digunakan metode GPR untuk mengatasinya. GWPR merupa-kan pengembangan dari regresi Poisson dengan memperhatikan faktor spasial. Hasil pemodelan menunjukkan bahwa dengan metode GWPR variabel yang berpengaruh signifikan terhadap jumlah kasus penyakit tuberkulosis di seluruh kabupaten/kota di Jawa Timur adalah persentase penduduk usia produktif, persentase tenaga kesehatan terdidik tuberkulosis, dan persentase tempat umum dan pengelolaan makanan (TUPM) sehat. Sedangkan metode GPR memberikan hasil bahwa persentase penduduk usia produktif, dan TUPM sehat berpengaruh signifikan terhadap jumlah kasus penyakit tuberkulosis di Jawa Timur.
PEMODELAN RESIKO PENYAKIT KAKI GAJAH (FILARIASIS) DI PROVINSI PAPUA DENGAN REGRESI ZERO-INFLATED POISSON Wulandari, Sri Pingit; Sutijo, Brodjol; Rahmawati, Ika
FORUM STATISTIKA DAN KOMPUTASI Vol. 15 No. 1 (2010)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

The goverment has established elimination of filariasis tropical disease as one of the priority programs. One of the districts that has become a target is Papua. The total amount of  filariasis victim on every regency/city in Papua district can be assumed to follow a Poisson distribution. So Poisson regression method is a suitable method to know the influence factor of filariasis disease. Poisson regression model assumes equidispersion, that is equality of mean and variance of the response variable. Overdispersion test shows that the variance of the response variable exceeds its mean value. So the model is modified into zeroinflated Poisson (ZIP) regression model (logit and log). ZIP logit regression model shows that the quantity of filariasis victim in every regency/city in Papua district with zero count is influenced by the percentage of household members who sleep inside mosquito net, the percentage of household members who sleep inside insecticide musquito net, and the percentage of house-holds who keep pet (dog/cat/rabbit). While ZIP regression on log model shows that the increasing number of percentage household who keeps their pet will enhance the quantity of filariasis victim  in Papua district as many as two people. Regencies/cities which need to get special attention through an elimination program of filariasis are Asmat, Tolikara, Supiori, Yapen Waropen, and Jayapura city.
Hybrid Support Vector Machine to Preterm Birth Prediction Santoso, Noviyanti; Wulandari, Sri Pingit
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 8, No 2 (2018): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.058 KB) | DOI: 10.22146/ijeis.35817

Abstract

Preterm birth is one of the major contributors to perinatal and neonatal mortality. This issue became important in health research area especially human reproduction both in developed and developing country. In 2015 Indonesia rank fifth as the country with the highest number of premature babies in the world. The ability to reduce the number of preterm birth is to reduce risk factors associated with it. This research will be made the prediction model of preterm birth using hybrid multivariate adaptive regression splines (MARS) and Support Vector Machine (SVM). MARS used to select the attributes which suspected to affect premature babies. The result of this research is prediction model based on hybrid MARS-SVM obtains better performance than the other models
DETEKSI DINI RISIKO KREDIT MELALUI RATING TRANSITION STOCHASTIC MATRIX DAN VALUE AT RISK (Early Detection of Credit Risk Through Rating Transition Stochastic Matrix and Value at Risk) Haryono, _; Wulandari, Sri Pingit; Retnaningsih, Sri Mumpuni
FORUM STATISTIKA DAN KOMPUTASI Vol. 17 No. 1 (2012)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Credit risk is the risk occurs when the debtors fail to meet their obligation in accordance with agreed term to the bank. This research is made to analyze the credit risk for industrial and trade sector in Bank X, both sectors contribute about 80% loan credit. The calculation of the VaR 95% used Markov Chain regular and ergodic and adjusted by macro economic variable which significance influence the movement of those quality rating. The result of Markov chain for industrial sector show that the ability debtor increase for repay the loan in the long run but for trade sector became worst. The VaR 95% results for industrial sector is Rp 2,17 billion or about 3,27% and for trade sector is Rp 4,46 billion or about 2,03% from outstanding credit those sectors. This results is not appropriate with the New Basel Capital Accord which recomennded to allocate capital 8% from outstanding credit to cover credit risk. The calculation of the TVaR 95% for industrial sector is Rp 4,89 billion or about 7,38% and for trade sector is Rp 16,60 billion or about 7,55% from outstanding credit both sectors. For the TVaR 95% portofolio give the results is Rp 18,99 billion or about 6,5% from outstanding credit.Keywords : Credit Risk, Markov chain, Regression, Macroeconomics, VaR, TVaR, Portofolio Risk.