Pemilihan Arsitektur Optimal Model Nn Dengan Metode Kontribusi Increment

Neural Network is an information processing system that has certain characteristic in common with biological neural network. In development NN has been many applied in several surface, one of them is for forecasting. For the best application of NN, architecture has determined. One of methode to get optimal architecture NN is incremental contribution methods. This methods will to determine the size of hidden and input cell in the network with excluding respectively. One of the unit cell with a low incremental contribution will be exclution from network. The result shows that the incremental contribution methods is capable reducing the size of the network is propozed, so getting optimal architecture from network

Model Regresi Cox Proporsional Hazard Pada Data Ketahanan Hidup

A lot of events occured in daily life are connected with survival time, for example a time interval that measure the failure of a product, time duration which is needed to recover from disease, the back pain recurred after treatment. Data about survival time duration of an event is called survival data. Survival data can not be observed completely that is called as sensored data. Cox proportional hazard model is employed to analyze and determine the survival rate from cencored data affected one or more explanatory variables. This model assummed that the hazard rate of group is proportional to the hazard rate of another group. In the paper, wants to the factor that affect the survival of patient with cervical cancer. From the result of data processing that affect are age and stadum with cox proportionl hazard model is hi(t) = exp(-1.848U1i – 1.584U2i – 3.255S2i - 2.108S3i ) h0(t

Uji Hidup Dipercepat Pada Distribusi Eksponensial Tersensor Tipe II Dengan Tegangan Konstan

Accelerated Life Testing (ALT) is used to obtain information quickly on life distribution, failure rates and reliabilities. ALT is achieved by subjecting the test units to conditions such that the failure occur sooner. Prediction of long term reliability can make within a short periode of time. Result from the ALT are used to extrapolate the unit characteristic at any future time and at given normal operating conditions. ALT using a time varying stess application is often used to induce failure in relatively short times. The most basic and useful type of ALT in which the stress on each unit is increased step by step over time, it can substantially shorten the duration of the reliability test. The life distribution which used in reliability test is exponential distribution. By using Maximum Likelihood Estimation is obtained point estimation of parameter on step stress, and povital quantity is obtained confidence interval for parameter. From this estimation Mean Time to Failure (MTTF) and reliability of product under normal operating condition Keysword: Accelerated Life Testing (ALT), Step Stress, Exponential Distribution, Maximum Likelihood Estimation, Povital Quantit

Uji Hidup Dipercepat Pada Distribusi Eksponensial Tersensor Tipe II Dengan Tegangan Konstan

Accelerated Life Testing (ALT) is used to obtain information quickly on life distribution, failure rates and reliabilities. ALT is achieved by subjecting the test units to conditions such that the failure occur sooner. Prediction of long term reliability can make within a short periode of time. Result from the ALT are used to extrapolate the unit characteristic at any future time and at given normal operating conditions. ALT using a time varying stess application is often used to induce failure in relatively short times. The most basic and useful type of ALT in which the stress on each unit is increased step by step over time, it can substantially shorten the duration of the reliability test. The life distribution which used in reliability test is exponential distribution. By using Maximum Likelihood Estimation is obtained point estimation of parameter on step stress, and povital quantity is obtained confidence interval for parameter. From this estimation Mean Time to Failure (MTTF) and reliability of product under normal operating condition Keysword: Accelerated Life Testing (ALT), Step Stress, Exponential Distribution, Maximum Likelihood Estimation, Povital Quantit

Rancangan Strip Plot Model Tetap

The experiment involve the study of the effects of two or more factors can be used the factorial designs. The factorial designs have several advantages. They are more efficient than one factor at a time experints. Furthermore, a factorial designs is necessary when interaction may be present to avoid misleading conclutions. In the Strip Plot design is factorial two factors which random factors aren't based on main plot or the whole plot but the important is it's interaction. There are three error in the Strip plot. They are error caused by factor A, error caused by factor B and error by A and B interaction

Analisis Desain Faktorial Fraksional 2k-p Dengan Metode Lenth

Rancangan faktorial fraksional banyak digunakan dalam percobaan terutama di bidang industri karena dapat menentukan pengaruh faktor utama dan interaksi terhadap respon. Rancangan yang melibatkan k buah faktor dengan dua taraf dan menggunakan 2-p fraksi dari percobaan faktorial lengkap disebut rancangan faktorial fraksional 2k-p. Penentuan faktor signifikan jika data yang diamati tanpa pengulangan dapat diuji dengan menggunakan metode Lenth. Penelitian ini bertujuan untuk menentukan penaksir dan statistik uji untuk mendapatkan faktor signifikan dengan metode Lenth, serta menentukan perbedaan dalam penggunaan metode Lenth dengan metode klasik. Kasus yang digunakan adalah rancangan faktorial fraksional 25-1 dengan faktor A, B, C, D, E. Hasil pengujian dengan metode Lenth diperoleh nilai estimasi S0 dan sebagai penaksir awal dan akhir. Nilai Margin Error dan Simultan Margin Error sebagai batas kesalahan dalam penentuan faktor signifikan. Faktor yang berpengaruh terhadap respon adalah faktor B dan C. Apabila diuji dengan metode klasik diperoleh faktor yang berpengaruh terhadap respon adalah faktor B, C, D, E, AB, AC, dan BC, sehingga dapat dikatakan bahwa metode klasik lebih sensitif daripada metode Lenth

Analisis Regresi Kegagalan Proporsional Dari Cox Pada Data Waktu Tunggu Sarjana Dengan Sensor Tipe I (Studi Kasus Di Fakultas Sains Dan Matematika Universitas Diponegoro)

One of the goals of studying in Higher Education Institutionis to obtain a job as soon as possible. A graduate is not required to be an unemployed. In Indonesia, the average period of waiting time for undergraduate (S1) to get the first job is 0 (zero) to 9 (nine) months. There are several factors have influenced the length of an undergraduate to get a job. They are Grade Point Average (GPA), Length of Study, etc. Therefore, it is important to know the factors influencing the waiting time of undergraduates to get a job. One method that can be used is the analysis of survival. Survival analysis is the analysis of survival time data from the initial time of the study until certain events occur. One method of survival analysis is Cox Proportional Hazard Regression. It is used to determine the relationship between one or more independent variables and the dependent variable. Cases raised in this study were the factors influencing the waiting time of graduates of the Faculty of Science and Mathematics, University of Diponegoro by using Type I data censoring. The conclusions state that the factors influencing the waiting time of graduates are Organization, Department, and Gender