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Analysis of Insurance Customer Factors to Renewal Using Hybrid AHP-FTOPSIS Andawaningtyas, Kwardiniya; Ardiyani, Evi; Karim, Corina
CAUCHY Vol 7, No 2 (2022): CAUCHY: Jurnal Matematika Murni dan Aplikasi (May 2022) (Issue in Progress)
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i2.13356

Abstract

Human life is full of uncertainty that has enormous risks. Insurance is a one of methods that can help humans reduce those risks. Human needs for insurance causes competition among insurance companies in Indonesia to become very competitive. One factor that makes insurance companies to compete is to have its customers who make insurance renewals. Thesis discusses analysis of factors that influence insurance renewal using Analytical Hierarchy Process (AHP) method and the ranking of customer’s favorite insurance for renewal using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method. Five criteria have been determined with each criterion having subcriteria in this study. AHP method is used to calculate the weight of criteria and to determine the factors that influence customers the most to do renewal. The  FTOPSIS method is used to determine the best alternative. The results of the analysis using these methods conclude was the main factor that influences the customers in conducting renewals is feature with the subcriteria of health protection needs. Meanwhile, the ranking of customer’s favorite insurance in conducting renewal is Takafulink Salam Cendikia with proximity coefficient value of 0,645, Takaful Al-Khairat with value 0,563, Takaful Dana Pendidikan with value 0,552, and Takafulink Salam with value 0,341
HIV/AIDS Dynamics Epidemic Analysis Through Age Group and Internal Competition Influence Marsudi Marsudi; Kwardiniya Andawaningtyas
Natural B, Journal of Health and Environmental Sciences Vol 1, No 1 (2011)
Publisher : Natural B, Journal of Health and Environmental Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (60.347 KB) | DOI: 10.21776/ub.natural-b.2011.001.01.9

Abstract

Transmission of HIV/AIDS in Indonesia has potential rounding into very hard. How situation of HIV/AIDS epidemics in Indonesia in future still is unclear. This research aims to analyze of HIV/AIDS epidemics dynamics with influence of age group and internal competition through the simple mathematics model. The SI compartment model is obtained by translating mechanism spreading of disease to be presented in the form of system of nonlinear differential equations. The model parameters obtained by estimation use data of HIV/AIDS in Indonesia from relevant literatures. The local and global stability for the equilibrium point is described use analysis of eigenvalues of Jacobian matrix and Lyapunov-LaSalle’s invariant principle. For the case of data of HIV/AIDS in Indonesia 2007, threshold values of infected reproduced ratio, R0= 0.000035 susceptible reproduced ratio, R1= 100.60235 and infection contact rate, R2=3.50192 The HIV/AIDS dynamics model with two age groups and internal competition has a unique disease-free equilibrium point. The disease-free equilibrium point E0*= (34258263.6455834, 0, 0) is locally asymptotically stable and global unstable.
Effect of Birth Rate Simulation and Vaccination on Dynamics Measles Epidemic Patterns Kwardiniya Andawaningtyas; Marsudi Marsudi
Natural B, Journal of Health and Environmental Sciences Vol 1, No 1 (2011)
Publisher : Natural B, Journal of Health and Environmental Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (75.689 KB) | DOI: 10.21776/ub.natural-b.2011.001.01.12

Abstract

The purpose of this research is to get description about influence of birth rates to the epidemic dynamics pattern of measles is presented as system of nonlinear differential equations. In this case, the epidemic dynamics of measles is of the form of the SEIR model with births which is obtained from four compartments: susceptible, exposed, infectious, and recovered. Then we analyze parameter model (α) to know the influence of change of birth rates to the epidemic dynamics pattern of measles. The changes of birth rates do not alter common pattern of epidemic measles, but the number of epidemic cycle, epidemic process, oscillation process, epidemic size, and time of epidemic convergent changes significantly. If the birth rate increases so does the epidemic cycle, but the epidemic process decreases, the oscillation is faster, and epidemic size converges to higher level value. If the birth rate decreases, the number of epidemic cycle decreases, epidemic process and oscillation take a longer, the epidemic size decreases with higher variance and converges to lower value.
Prediksi Profil Asam Amino Pada Family Protein Menggunakan Hidden Markov Model Endang Wahyu Handamari; Kwardiniya A; Mila Kurniawaty; Emilia S I
Jurnal POINTER Vol 2, No 2 (2011): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRAK Sequence  alignment adalah metode dasar dalam analisis sekuens, yang  merupakan proses penyusunan atau penjajaran dua atau lebih sequence primer sehingga persamaan sequence - sequence tersebut tampak nyata. Salah satu kegunaan  metode ini adalah untuk  memprediksi karakteristik dari suatu protein, yaitu memprediksi struktur atau fungsi protein yang belum diketahui menggunakan protein yang telah diketahui informasi struktur atau informasi fungsinya jika protein tersebut memiliki kesamaan sequence dengan sequence yang terdapat dalam database. Protein merupakan makromolekul yang menyusun lebih dari separuh bagian dari sel.  Protein merupakan  rantai dari gabungan 20 jenis asam amino, di mana setiap jenis protein mempunyai jumlah dan sequence asam amino yang khas. Metode yang dapat diterapkan untuk sequence  alignment di samping algoritma genetika adalah  metode yang berhubungan dengan Hidden Markov Model (HMM). Hidden Markov Model (HMM)  merupakan bentuk pengembangan dari rantai Markov, yang dapat diterapkan dalam kasus yang tidak dapat diamati secara langsung. Sebagai observed state untuk sequence  alignment adalah sequence asam amino dalam tiga kategori yaitu : deletion(1), insertion(2) dan match(3),  sedangkan  untuk hidden state adalah residu asam amino, yang  dapat menentukan  family protein  bersesuaian dengan observasi O .               Implementasi melalui perangkat lunak HMM terhadap sequence asam amino telah dilakukan namun perlu diuji keakuratan  terhadap data sebenarnya melalui PDB (Protein Data Bank). ABSTRACT Sequence alignment is the basic method in sequence analysis,  which is the process of  two or more primer  sequences  so  that  the  equation sequences are apparent.  One of  the  usefulness  of  this  method to predict the characteristics of a protein, which predicts the structure or function of unknown proteins using known protein structure information  if the information  these proteins have sequence similarity to sequences contained in the data base. Proteins are  macromolecules  which  make up more  than half of  the cell. Proteins  are  chains  of a combination of  20 kinds of amino acids,  where each type protein  has  a number of proteins and amino acid sequences are typical.   The  method  can be  applied  to sequence  alignment besides  the genetic algorithm is a method associated with the Hidden Markov Model  (HMM). Hidden Markov Model (HMM) is a form of development of Markov chains, which can be applied in cases that can not be observed directly. As observed state for sequence alignment is the sequence of amino acids into three categories namely: deletion (1), insertion (2) and match (3), while for the hidden state is an amino acid residue, which can determine the family of proteins corresponding to the observation O. Implementation through HMM software for  the amino acid sequence has been done but needs to be tested against actual data accuracy through the PDB  (Protein Data Bank).
TRAINING OF MICROSOFT MATHEMATICS TO IMPROVE THE QUALITY OF LEARNING METHODS FOR TEACHERS IN JUNIOR SECONDARY SCHOOLS (SMP AND MTs) AT PONOROGO EAST JAVA INDONESIA Kwardiniya Andawaningtyas; Wuryansari Muharini Kusumawinahyu; Ani Budi Astuti
Journal of Innovation and Applied Technology Vol 3, No 1 (2017)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1069.821 KB) | DOI: 10.21776/ub.jiat.2017.003.01.8

Abstract

All this time, mathematics has become the scourge for elementary and junior high school students, so that students are not well motivated to learn the material of Mathematics. Along with the development of computer technology, it can be used as one tool that can help the learning process. Mathematics software can be used to explain the difficult concepts in mathematics becomes easily, clearer, more interesting and fun. In Ponorogo, mathematics teachers have a meeting forum called the Subject Teacher Council (MGMP) of Mathematics. The general problems of the council is the less equality in opportunities of MGMP Mathematics teachers in Junior Secondary Schools (SMP and MTs) at Ponorogo to attain trainings for improving students skills in understanding the material of Mathematics and the limited insight of mathematics teachers about mathematics software that can be used as an instructional media of mathematics material. Therefore, the activity of microsoft mathematics training for mathematics teachers in Junior Secondary Schools at Ponorogo has been necessarily and urgently needed to improve the quality of learning methods. These software is open source software with less space requirement in the computer and easy installation.
Seleksi Nilai Fuzziness Exponent Optimal pada Algoritma Fuzzy c-Means untuk Mengelompokkan Provinsi di Indonesia Berdasarkan Indikator Pembangunan Ekonomi Sa'adah, Umu; Handamari, Endang Wahyu; Andawaningtyas, Kwardiniya; Setyowati, Nur Fitriana
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 17 No. 2: December 2022
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v17i2.54897

Abstract

Pada tahun 2015, PBB merancang 17 Tujuan Pembangunan Berkelanjutan (SDGs) untuk mencapai kesejahteraan manusia pada tahun 2030 dengan mengintegrasikan tiga dimensi pembangunan berkelanjutan: ekonomi, sosial, dan lingkungan. Salah satu faktor yang digunakan untuk menilai keberhasilan sebuah wilayah atau pemerintahan dalam mengelola kesejahteraan dan kemakmuran masyarakat adalah tingkat perekonomian. Untuk mewujudkan kondisi tersebut diperlukan strategi dalam pembangunan pada sektor ekonomi. Penelitian ini bertujuan untuk mengelompokkan Provinsi di Indonesia menjadi 3 klaster berdasarkan indikator pembangunan ekonomi menggunakan algoritma fuzzy c-means. Penentuan 3 klaster dimaksudkan untuk klaster provinsi dengan tingkat pembangunan ekonomi rendah, sedang dan tinggi. Data yang digunakan dalam penelitian ini merupakan data sekunder yang diperoleh dari laman resmi Badan Pusat Statistika. Dengan mengetahui karakteristik provinsi berdasarkan indikator pembangunan ekonomi (IPE), maka pengambil keputusan dapat menyusun strategi perencanaan program pembangunan ekonomi berdasarkan skala prioritas pada masing-masing provinsi. Hasil pengelompokan menunjukkan bahwa Provinsi Papua sangat membutuhkan prioritas pembangunan khususnya dalam sektor ekonomi guna peningkatan indeks pembangunan manusia, angka partisipasi sekolah berusia 7 sampai 12 tahun, angka partisipasi sekolah berusia 13 sampai 15 tahun, angka partisipasi sekolah berusia 16 sampai 18 tahun, sumber air minum yang layak, sumber penerangan listrik, dan sanitasi yang layak, karena indikator-indikator tersebut memiliki nilai rendah.
VALUE AT RISK ESTIMATION FOR STOCK PORTFOLIO USING THE ARCHIMEDEAN COPULA APPROACH Saifullah, Mohammad Dicky; Sa'adah, Umu; Andawaningtyas, Kwardiniya; Handamari, Endang Wahyu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1779-1790

Abstract

Investment is one of the many ways to achieve future profits. One form of investment that is widely made is stocks. The return obtained in investing in stocks is potentially higher than other investment alternatives, but the risks borne are amplified, so it is necessary to analyze these risks that may occur. In this study, the Archimedean copula method is used to estimate the Value at Risk on shares of PT Bank Rakyat Indonesia Tbk (BBRI) and PT Telekomunikasi Indonesia Tbk (TLKM) for the period September 1, 2021, to August 31, 2023. The stock data is used to determine the Archimedean copula model and calculate the estimated value of Value at Risk (VaR) on the stock return portfolio using the Archimedean copula approach. The Archimedean copula models used are the Clayton copula model, Gumbel copula, and Frank copula. Of the three Archimedean copula models, the best model was selected by looking at the largest Maximum Likelihood Estimation (MLE) value. In this study, the log-likelihood value of Clayton copula is 7.958, Gumbel copula is 6.663, and Frank copula is 8.398. Therefore, Frank copula is the best Archimedean copula model with the largest log-likelihood value of 8.398 for the said data. Then the VaR estimation is done with the Frank copula model. The Value at Risk estimation results based on the Frank copula model show maximum loss rates of -0.0277 at the 90% confidence level, -0.0363 at the 95% confidence level, and -0.0516 at the 99% confidence level.