Judul: Menangani Overdispersion dengan Model Regresi Poisson Umum
Abstrak: Pada perusahaan asuransi, penentuan tarif premi asuransi harus berdasarkan prinsip adil. Penentuan tingkat premi asuransi disesuaikan dengan besarnya klasifikasi risiko. Semakin tinggi klasifikasi risiko, maka besarnya premi asuransi semakin tinggi. Pendugaan klasifikasi risiko tersebut dapat diduga dari data klaim asuransi. Pada literatur aktuaria, para peneliti menyarankan prosedur statistika untuk pendugaan parameter dalam model klaim asuransi, di antaranya model regresi Poisson dan Negative binomial. Dalam praktik asuransi, penghitungan data asuransi sering menggambarkan ragam lebih besar dari rata-rata yang dalam model regresi Poisson disebut sebagai overdispersion. Karya ilmiah ini membahas penggunaan model regresi Poisson umum untuk menangani permasalahan overdispersion. Model regresi Poisson umum memberikan solusi suatu nilai konstanta yang dapat digunakan untuk mendeteksi ada atau tidaknya overdispersion dalam data, dan dapat memberikan hasil pendugaan parameter regresi untuk data ketika overdispersion tersebut ada.
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Judul: Kajian Perbandingan Regresi Conway-Maxwell-Poisson dan Poisson-Tweedie dalam Mengatasi Overdispersi pada Regresi Poisson
Abstrak: Regresi Poisson adalah model yang umum digunakan untuk memodelkan data cacah. Memodelkan data cacah sering terjadi overdispersi sehingga regresi Poisson kurang tepat digunakan karena regresi Poisson mengasumsikan data equidispersi. Overdispersi dapat diatasi menggunakan regresi Conway-Maxwell-Poisson (COM-Poisson) dan Poisson Tweedie (Poisson-Tw). Model terbaik ditentukan berdasarkan RMSE, absolute bias, ragam penduga parameter, AIC, dan BIC terkecil. Penelitian ini menggunakan data simulasi dan data riil. Peubah respon pada data simulasi dibangkitkan menyebar Generalized Poisson dengan berbagai kombinasi parameter ϕ dan n. Kajian data simulasi menunjukkan bahwa regresi COM-Poisson dan Compound Poisson-Tw adalah model alternatif untuk memodelkan data cacah overdispersi, tetapi COM-Poisson lebih baik digunakan untuk tingkatan dispersi yang tinggi. Kajian data riil menunjukkan bahwa regresi COM-Poisson lebih baik digunakan dengan peubah yang berpengaruh terhadap kasus kusta di Jawa Timur tahun 2020 adalah jumlah penduduk miskin (X3) pada taraf nyata 0,05., Poisson regression is a standard method to model count data. Modeling count data frequently causes overdispersion which means that Poisson regression is less precise to model it as Poisson regression has the assumption of equidispersion. Overdispersion can be overcome by using Conway-Maxwell-Poisson (COM-Poisson) and Poisson Tweedie (Poisson-Tw) regression. The best model is determined based on the lowest value of RMSE, absolute bias, variance of parameter estimator, AIC, and BIC. This research uses both simulation and real data. The response variable of simulation data is generated to follow Generalized Poisson distribution with combinations of ϕ and n. The result of simulation study shows that COM-Poisson and Compound Poisson-Tw are the alternatives to model overdispersed count data, but COM-Poisson is better to overcome overdispersion with higher dispersion parameter level. Real data is modeled using COM-Poisson regression to analyze the number of leprosy cases in East Java 2020 and shows that the number of people living in poverty (X3) affects the number of leprosy cases in East Java 2020 at a 0,05 level of significance.
Keyword: COM-Poisson, Compound Poisson-Tw, overdispersion, Poisson

Judul: Kandungan Mineral Kalakai (Stenochlaena Palustris) yang Tumbuh pada Jenis Tanah Berbeda serta Dimasak dengan Cara Berbeda
Abstrak: Kalakai (Stenochlaena palustris) is one of the local vegetables commonly available in the Palangkaraya. Previous research states that kalakai has a relatively high content of nutrients like beta carotene, folic acid, as well as some important minerals. Local communities (Dayak people) in Central Kalimantan and surrounding used to consume kalakai, especially mothers after child-birth.Kalakai has been recognized as an important vegetable to boost milk supplies for mothers who are breast-feeding. Kalakai was unique, because it can grow on various soil types, even on nutrient-poor soil. Therefore, this research aims to determine the effect of different types of soil on the mineral content of kalakai, and influence of processing on the mineral content. The sampling was conducted at five sites with different soil. They are peaty soil, sulphate acid soils, quartz sand soil, and alluvial soil in January and February. All of the samples were given four different treatments, boiling, frying, steaming and fresh (no treatment). Samples were analyzed moisture, ash, and minerals. Analysis of mineral content using Atomic Absorption Spectrophotometer (AAS) Perkin Elmer 1100B. The type of soil affect the content of minerals in the tip of kalakai leaf. It which grown on peaty soil containing a rather high of mineral Mg, Ca, Zn, Mn, which continuously reach to 5160, 6399, 134.6, 158 ppm, while Fe, Cu, and Al with a low successive level of 117.2, 4.5, 20.5 ppm. The pH of peaty soil in this study was 6.08, allegedly still quite a lot of minerals which can be absorbed by plants. Kalakai which grown on acid-suphate soil contains high Fe and Al i.e. 336.4 and 76.4 ppm. The high micro-mineral Al and Fe in acid-sulphate soils due to soil pH is low. Kalakai grown on quartz sand soil containing high minerals Ca, Cu, and Al, namely 6299, 25.1, and 58.1 ppm, respectively, while other minerals such as Mg, Fe, Zn, and Mn were low, it implies in the amount of 4598, 65, 86.8, and 65.9 ppm, respectively. Kalakai grown on alluvial soil is found that the content of Cu quite high, i.e. 7.26 ppm, whereas Fe, Mn, and Al content were low respectively 52, 63.4, and 5.3 ppm. Relatively low mineral content on kalakai of quartz sand and alluvial soil allegedly because of the low element nutrients contained in these soil types. Results of analysis of total mineral or ash content in various ways of cooking show that kalakai has a different total mineral content. Total minerals from the lowest to the highest were kalakai cooked by boiling, frying, steaming and fresh or without treatment of cooking. Cooking process give an effect to mineral content of kalakai. The process of boiling is the highest role in decreasing Mg (21-68%), Cu (11-60%), Ca (39%) and Mn (8- 38%). Other minerals such as Zn and Fe decreased by frying in the amount of 14-37% and 9-43%, respectively. The whole minerals, except Cu, still in the recommended daily intake limit, if assumed that one portion of kalakai is 50 gram dry basis.
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