Yuciana Wilandari
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ESTIMASI CADANGAN KLAIM MENGGUNAKAN METODE DETERMINISTIK DAN STOKASTIK Yuciana Wilandari; Gunardi Gunardi; Adhitya Ronnie Effendie
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 1 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.1.2021.56-63

Abstract

The estimated of claims reserve has a very important in insurance companies, because it is the company's liability to policyholders in the future and can also result in the bankruptcy of the insurance company. In general, there are two methods for calculating claims reserves are the deterministic method (Chain Ladder and Bornhuetter Ferguson) and the stochastic method (Benktander Hovinen and Cape Cod). This article compares the two methods and determines the best method. Using the claim payments data that have been paid by an insurance company in Indonesia, the best method is the Benktander Hovinen method.
ANALISIS SEKTOR UNGGULAN MENGGUNAKAN DATA PDRB (Studi Kasus BPS Kabupaten Kendal Tahun 2006-2010) Rosita Wahyuningtyas; Agus Rusgiyono; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (505.722 KB) | DOI: 10.14710/j.gauss.v2i3.3667

Abstract

Gross Domestic Regional Product (GDRP) is total numbers of added values who’s producting by effort unit in that domestic area’s. GDRP can be classified in two form, that is GRDP at Current Market Prices and GRDP at Constant Prices. GRDP at Current Market Prices is calculating with two approaches, those are approach production and approach income. GRDP at Constant Prices can be calculated using two methods, revaluation and deflation. By using GDRP data, then it can be known which sector is  prominent sector in that region. Some methods who using GDRP data as decisive prominent sector is method of Typology Klassen, LQ, MRP, Overlay and Shift Share. These methods classifying the economic sectors into four groups, they are prominent sector, growing sector, potential sector and under developed sector, based on large of contribution and rate of growth. By taking the study area Kendal Regency and reference area is province Central of Java, then by used that methods can be known which sector be prominent sector in Kendal Regency. Based on the result from analysis methods, they are same result about prominent sector: agriculture sector and mining and quarrying sector
KETEPATAN KLASIFIKASI KEIKUTSERTAAN KELUARGA BERENCANA (KB) MENGGUNAKAN ANALISIS REGRESI LOGISTIK BINER DAN FUZZY K-NEAREST NEIGHBOR IN EVERY CLASS DI KABUPATEN KLATEN Dhinda Amalia Timur; Yuciana Wilandari; Diah Safitri
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (430.729 KB) | DOI: 10.14710/j.gauss.v3i4.8072

Abstract

Fertility is one of the factors that affect population growth. High population growth resulted in the emergence of a variety of problems for a country including Indonesia. This requires a treatment that population growth can be controlled, one attempts to handle by using a Keluarga Berencana program. Therefore conducted a study to determine the factors that affect that participation of Keluarga Berencana (KB) by using Binary Logistic Regression analysis in which the participation of KB divided into two, namely join KB and KB did not participate. Based on the results obtained Binary logistic regression analysis predictor variables that significantly affect participation KB is the number of children, father's education, and mother's education. The resulting classification accuracy with training data comparison testing was 90:10 at 84.375%. Furthermore, the data were analyzed by using Fuzzy K-Nearest Neighbor in every Class (FK-NNC) to determine the accuracy of the classification results comparison with FK-NNC Binary Logistic Regression. From the analysis of the classification accuracy using the FK-NNC with a 90:10 ratio of training data and testing the value of K = 7 values obtained tersebesar ie 87.5%. The comparison of classification accuracy of this value indicates if the FK-NNC is better classify participation in Keluarga Berencana in Klaten district  2012. Keywords: Keluarga Berencana, Binary Logistic Regression, Fuzzy K-Nearest Neighbor in every Class (FK-NNC)
PEMODELAN SEASONAL GENERALIZED SPACE TIME AUTOREGRESSIVE (SGSTAR) (Studi Kasus: Produksi Padi di Kabupaten Demak, Kabupaten Boyolali, dan Kabupaten Grobogan) Aisha Shaliha Mansoer; Tarno Tarno; Yuciana Wilandari
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (600.045 KB) | DOI: 10.14710/j.gauss.v5i4.14716

Abstract

Generalized Space Time Autoregressive (GSTAR) model is more flexible as a generalization of Space Time Autoregressive (STAR) model which be able to express the linear relationship of time and location. The purpose of this study is to construct GSTAR model for forecasting the rice plant production in the three districts of Central Java. The data which used to contruct the model is quarterly data of rice plant production in Demak, Boyolali and Grobogan from 1987 through 2014. According to the empirical study result using GSTAR model with uniform weight, binary weight, inverse distance wight, and normalized cross correlation weight, GSTAR (31)-I(1)3 with uniform weight is the optimal model. The model shows that every location is influenced by the location itself. Keywords :  GSTAR, Space Time, uniform weight
ANALISIS PEMBENTUKAN PORTOFOLIO OPTIMAL SAHAM DENGAN PENDEKATAN OPTIMISASI MULTIOBJEKTIF UNTUK PENGUKURAN VALUE AT RISK Fiki Farkhati; Abdul Hoyyi; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v3i3.6448

Abstract

Mean Variance Efficient Portfolio (MVEP) is theory of portfolio which purposed to standard investor  because approach has only one objective that minimize portfolio risk. Portfolio with multi-objective optimization that simultaneously maximize portfolio return and minimize portfolio risk with various weighting coefficient k represents risk aversion index. The purpose of this research is analyze proportion each stock in order that is formed optimal portfolio approach multi-objective optimization and analyze expected return and risk that suitable with preference investor. This research is based on cases stocks ASII, TLKM, SMGR, UNVR and LPKR. As a specific example investment Rp 50.000.000,00 in 20 days with 95% degree of confidence. Optimal portfolio for risk seeker investor is portfolio with     k = 0,01 with expected profit Rp 1.547.392,00 and risk estimation Rp 33.832.562,00. Optimal portfolio for risk indifference investor is portfolio with 1 ≤ k ≤ 100 with expected profit                Rp 965.678,00 until Rp 1.435.038,00 and risk estimation Rp 19.500.464,00 until                  Rp 25.513.351,00. Optimal portfolio for risk averse investor is portfolio with k = 10000 with expected return Rp 950.414,00 and risk estimation Rp 19.495.116,00. 
PEMETAAN PREFERENSI MAHASISWA BARU DALAM MEMILIH JURUSAN MENGGUNAKAN ARTIFICIAL NEURAL NETWORK (ANN) DENGAN ALGORITMA SELF ORGANIZING MAPS (SOM) Muh Najib Hilmi; Yuciana Wilandari; Hasbi Yasin
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.764 KB) | DOI: 10.14710/j.gauss.v4i1.8145

Abstract

College is the highest educational institution and the role the intellectual life of the Indonesian people that the main purpose of academics. Not all colleges into their destination but only college that has a role, credibility and rank the best course of which it is their goal. This makes higher education marketing research approach to get attention and become the main goal of the academics in choosing a college. This research was conducted in order to determine with certainty attribute / emotional reasons academics in choosing college as their academic goals. The method used in this study were self-organizing maps with the Kohonen algorithm is a classification method. Kohonen SOM algorithm with learning rate used 0:05, 0.25, 0:50, 0.75, 0.95 and initialization of initial weight value and the value of the midpoint and 500 iterations with output 3 clusters are formed. Results clustering of SOM validated using Davies-Bouldin index with the best clustering results that DBI minimum (1.7802) with the learning rate is 0.95 and the cluster formed three clusters for the first cluster as many as six members, cluster-2 by 9 members and 3rd cluster as 5 members the results of clustering with top priority contained in the cluster to-2 with a mean (7.434) with the characteristics of each member is an emotional reason in choosing a major. Keywords: Self Organizing Maps, Kohonen algorithm, Learning Rate, Index Davies Bouldin, Cluster.
PEMETAAN CABANG PERUSAHAAN ASURANSI X BERDASARKAN LAPORAN BEBAN KLAIM DAN PENERIMAAN PREMI MENGGUNAKAN BIPLOT Maharani Febriana Putri; Yuciana Wilandari; Rita Rahmawati
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.797 KB) | DOI: 10.14710/j.gauss.v4i2.8580

Abstract

The number of cars currently make everyone aware of the benefits of insurance to protect against financial loss. Insurance products that demand a lot of people are motor vehicle insurance product that car. As an entrepreneur it is necessary to determine whether or not a company healthy in order to determine the condition of the company and what things need to be considered to improve the financial condition of the company. To see healthy or not an insurance company then needs to be analyzed on the income and expenditures of the company. The company has a good insurance premium income is greater than the burden of claims. This makes the company should strive to find that a lot of customers and minimize the burden of the claims that the company is in good financial condition. This study was conducted to find out how the condition of the company by using biplot analysis. This analysis can be applied to determine the company branch mapping, information and determine which branch company has the top achievers. The results obtained from these studies is the premium income report greater than the burden of claims and the top achievers is Surabaya Tunjungan. In addition, mapping that can be explained by a biplot analysis reached 100% which means it can explain the total data properly.Keywords : company branch mapping, biplot analysis, premium income and            burden of claims
PERAMALAN JUMLAH KECELAKAAN DI KOTA SEMARANG TAHUN 2017 MENGGUNAKAN METODE RUNTUN WAKTU (Studi Kasus : Data Jumlah Kecelakaan Lalu Lintas di Kota Semarang Periode Januari 2012 – Desember 2016) Iantazar Rezqitullah Maharsi; Moch. Abdul Mukid; Yuciana Wilandari
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.054 KB) | DOI: 10.14710/j.gauss.v6i3.19308

Abstract

Accident data from Satlantas Polrestabes Semarang City is known that in 2016 there is an increase in the number of traffic accidents in the Semarang city. In the future the impact of accidents is predicted to be bigger so it is necessary to forecasting. Forecasting is one of the most important elements in decision making, because effective or not a decision generally depends on several factors that can not be seen at the time the decision was taken. In this time study the possible time series model is ARMA (2,2), ARMA (2,1), ARMA (1,2), ARMA (1,1), AR (2), AR (1), MA (2), MA (1). However, after testing, the model used is ARMA (1,1). This model is used because it meets all the assumption requirements that are parameter significant , residual indepedent test, residual normality test and the smallest Mean Square Error value. According to data forecasting results showed the highest number of crashes existed in January of 97 accidents and the lowest in December amounted to 93 accidents, So that the necessary to action from the relevant agencies to cope with the increasing number of traffic accidents in the city of Semarang. Keywords : Time Series Method, ARMA (1,1), Traffic Accident.
ANALISIS RANCANGAN BUJUR SANGKAR GRAECO LATIN Yuyun Naifular; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (389.961 KB) | DOI: 10.14710/j.gauss.v3i1.4784

Abstract

The design of the experiment is a test or series of tests, using both descriptive statistics and inferential statistics that aims to transform the input variables into an output which is the response of the experiment. The Graeco Latin Square Design was built to control the diversity of component units of local control experiment of three is a row, column, and Greek letters. Terms the Graeco Latin Square Design is if the rows, columns, Latin letters, and Greek letters have the same level and each Greek letter appears only once in each row, column, and Latin letter. The steps in the analysis of the test Graeco Latin Square Design to test the normality of the error, homogeneity of variance test, determine the degrees of freedom, calculating Sum of Squares and Mean Square every factor. Next calculate the value of F for test row, column, treatments Latin letter, and treatment of Greek letters, draw up a table of variance analysis, and conclude whether there is any effect on the response variance of each source. If there is impact, it is necessary to further test using the Duncan test
PENENTUAN CADANGAN DISESUAIKAN DENGAN METODE ILLINOIS PADA ASURANSI JIWA ENDOWMEN SEMIKONTINU Marlia Aide Revani; Yuciana Wilandari; Dwi Ispriyanti
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.478 KB) | DOI: 10.14710/j.gauss.v1i1.903

Abstract

Semicontinuous endowment insurance is a kind of insurance with a periodic premium payments which gives two benefits, payment of death benefit at the moment of death if the insured dies during a certain period of years or payment of living benefit if the insured survives to the end of the period. The insurer’s obligation of insured’s premium payments, provides net level premium reserves for benefit payment in the future. The insurer needs expenses for it’s operate and in fact, the first year expenses usually exceed the loading. This means that an insurance company have to find funds to cover the first year expenses. The funds can be obtained by modified reserve system. To get information of modified reserve value for semicontinuous life insurance, the study of determination of modified reserve value using Illinois method has been done. The full net level reserves are lesser than the reserves under the Illinois method before the end of min(n, 20) years and both of these reserves will be equal at the the end of min(n, 20) years, with n is premium period.