Model Asuransi Kendaraan Bermotor Menggunakan Distribusi Mixed Poisson

Motor vehicle insurance is a form of protection of motor vehicles owned by the insured. One of the activities in insurance companies is claim. Claim is risk of loss claim is paid by the insurance company to the insured. Analysis of motor vehicle insurance claims typically uses poisson distribution approach. Nevertheless in many cases of motor vehicle insurance claim, the value of variance greater than the mean value. In this case overdispersed has been going on the assumption poisson distribution. If the poisson distribution continued to be used when going overdispersed, so the poisson distribution is inefficient because it affects the error standard. To solve the problem can be used mixed Poisson distribution. This final project used two mixed Poisson distribution which is a mixture of gamma poison known as negative binomial distribution and poisson-exponential mixture known as a geometric distribution. Carried out on the data motor vehicle claim in PT. Jasa Asuransi Indonesia, Semarang branch year 2010 to 2011 it is estimated that of the 100 vehicle type Car policyholders aged <1 year will be 2 claims per year

Komputasi Metode Exponentially Weighted Moving Average Untuk Pengendalian Kualitas Proses Produksimenggunakan Gui Matlab (Studi Kasus : PT Djarum Kudus Skt Brak Megawon III)

Control chart is one of tools for quality control of production. control chart is one of tool that can be used to control the quality of production for variable data such as weight of product. However, there is a weakness of control chart, which is sensitivless in detecting small shift of the mean process. Exponentially Weighted Moving Average (EWMA) control chart is one of the quality control tool that can improve the weakness of control chart. EWMA control chart has a weight smoothing parameter (λ) which makes EWMA control chart more sensitive in detecting small shifts the process mean. Each production data will be weighted and past production data will be affected by present production data. EWMA control chart will be used to make a control chart by weight of cigarette data in Brak Megawon III PT Djarum Kudus. In this study, will be established to assist in the GUI Matlab computational EWMA methods chart controller to control the quality of production at PT Djarum Kudus.In this study showed that the most optimum weight refiner which is at a value of 0.6

Analisis Grafik Pengendali Nonparametrik Dengan Estimasi Fungsi Densitas Kernel Pada Kasus Waktu Pelorotan Batik Tulis

The quality of the product becomes one of the basic factors in the decisions of consumers in selecting products. A companny needs a quality control for keeping the consistency of product quality. One of statistic tools which can be used in quality control is a control chart. If the obtained data do not have a specific distribution assumption, it is needs to use nonparametric control chart as the solution. One of ways to describe the nonparametric control chart is a kernel density estimation. The most important point in the kernel density estimation is optimal bandwidth selection and one of the method that can be used is Least Squares Cross Validation. In this case, will be described a nonparametric control chart to data of vanishing candle at batik in Pekalongan using Rectangular, Triangular, Biweight and Epanechnikov kernel density estimation. Based on the data processing using R.2.14, the result was obtained that from the four kernel estimatios which were used, the obtained control chart by the Rectangular kernel density estimation which have the largest value of variance. It shows that the control chart by the Rectangular kernel density estimation is the widest control chart. While, the obtained control chart by the Epanechnikov kernel density estimation which have the smallest value of variance. It shows that the control chart by the Epanechnikov kernel density estimation is the narrowest control char

Klasifikasi Calon Pendonor Darah Menggunakan Metode Naïve Bayes Classifier (Studi Kasus : Calon Pendonor Darah Di Kota Semarang)

Classification is the process of finding a model or function that describes and distinguishes data classes or concepts, for the purpose of being able to use the model to predict the class of objects whose class label is unknown. There are some methods that are included in the classification methods, one of them is Naïve Bayes. Naïve Bayes is a prediction technique that based simple probabilistic are based on the application of Bayes theorem with strong independence assumption. On this study carried out correction to the Naïve Bayes method in calculating the conditional probability of each feature using two approaches, normal density function and cumulative distribution function approaches. These two approaches are used to classify prospective blood donors in Semarang City. The predictor variables used are hemoglobin level, upper blood pressure, lower blood pressure, and weight. The result of this study shows that both approaches have the same Matthews Correlation Coefficient (MCC) values, 0.8985841 or close to +1. It means that both approaches equally well doing classification

Komputasi Metode Saw Dan Topsis Menggunakan Gui Matlab Untuk Pemilihan Jenis Objek Wisata Terbaik (Studi Kasus : Pesona Wisata Jawa Tengah)

Multi-Attribute Decision Making (MADM) is a method of decision-making to establish the best alternative from a number of alternatives based on certain criteria. Some of the methods that can be used to solve MADM problems are Simple Additive Weighting (SAW) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). SAW works by finding the sum of the weighted performance rating for each alternative in all criteria. While TOPSIS uses the principle that the alternative selected must have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Both of these methods were applied in making the selection of the best tourist attractions in Central Java. There are 15 tourist attractions and 7 criteria: location, infrastructure, beauty, atmosphere, tourist interest, promotion, and cost. This primary research employed a questionnaire that passed the questionnaire testing, namely its validity and reliability test. The result of this study shows that the best type of tourism according to the government is temple tour. While water sports tourism is favored by tourism observers. As for college students, the preferred tourist destination is religious tourism. This study also produced a GUI Matlab programming application that can help users in performing data processing using SAW and TOPSIS to select the best attraction in Central Java

Peramalan Outflow Uang Kartal Di Bank Indonesia Wilayah Jawa Tengah Dengan Metode Generalized Space TIME Autoregressive (Gstar)

Generalized Space Time Autoregressive (GSTAR) model is a method that has interrelation between time and location or called with space time data. This model is generalization of Space Time Autoregressive (STAR) model where GSTAR more flexible for data with heterogeneous location characteristics. The purposes of this research are to get the best GSTAR model that will be used to forecast the outflow in the Bank Indonesia Office (BIO) Semarang, Solo, Purwokerto and Tegal. The best model obtained in this study is GSTAR (11) I(1) using the inverse distance weighting locations. This model has an average value of MAPE 35.732% and RMSE 440.52. The best model obtained explains that the outflow in BIO Semarang, Solo and Purwokerto are affected by two time lag before while for outflow in BIO Tegal is affected by two time lag befor and outflows in three other BIO