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Sutikno, Dr., S.Si., M.Si.
Community Engagement Center for Regional Potential and Community Empowerment (PDPM)
Department of Statistics
,
Laboratory of Environmental and Health Statistics
h-index
193
Citations
7
h-index
Calculated based on number of publications stored in Pure and citations from Scopus
2012
2024
Research activity per year
Overview
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Research output
(64)
Similar Profiles
(6)
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Dive into the research topics where Sutikno is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Mathematics
Auto Regressive Integrated Moving Average
9%
Autoregressive Integrated Moving Average
9%
Bayesian
18%
Bayesian Approach
11%
Bivariate
75%
Closed Form
11%
Copula
10%
Covariate
20%
Cox Point Process
9%
Cross-Validation
9%
Dependent Variable
9%
Ensemble Model
9%
Estimation Method
14%
Filter Method
9%
Gaussian Copula
9%
Generalized Cross
9%
Global Method
11%
Inverse Gaussian
28%
Likelihood Ratio Test
23%
Logistic Regression
9%
Logistic Regression Model
14%
Marginals
9%
Maximum Likelihood
31%
Maximum Likelihood
25%
Mean Square
11%
Mean Square Error
11%
Mixed Model
9%
Multivariate Adaptive Regression Spline
28%
Negative Binomial
18%
Newton-Raphson
10%
Overdispersion
17%
Parameter Estimation
92%
Poisson Regression
55%
Poisson Regression Model
19%
Predictor Variable
32%
Principal Component Analysis
9%
Regression Model
100%
Regression Parameter
26%
Regularization
9%
Relative Risk
9%
Response Variable
60%
Ridge
9%
Risk Analysis
18%
Space Model
11%
Spline Model
11%
Statistical Hypothesis Testing
72%
Statistical Modeling
9%
Statistical Test
13%
Statistics
28%
Test Statistic
30%
Engineering
Actual Condition
6%
Air Transport
18%
Aircraft
8%
Back Face
7%
Basis Function
6%
Carbon Fibre Reinforced Polymer
18%
Carbon Fibre-Reinforced Polymer Composite
6%
Composite Material
10%
Computational Time
9%
Cutting Force
18%
Delamination
11%
Delay Time
9%
Design Model
9%
Distribution Model
9%
Electric Power Plant
9%
End Milling
18%
Energy Engineering
9%
Feedforward
7%
Fibre-Reinforced Polymer Composite
9%
Fuzzy Inference System
9%
Fuzzy System
9%
Gaussians
18%
Genetic Algorithm
16%
Genetic Algorithm Method
9%
Hidden Layer
13%
Impact Energy
11%
Input Layer
7%
Least Square
13%
Lifecycle Cost
9%
Marginals
18%
Output Layer
9%
Parameter Estimation
6%
Particle Swarm Optimization
9%
Performance Test
9%
Potential Loss
9%
Predictor Variable
20%
Process Parameter
7%
Quality Characteristic
14%
Quality Loss
9%
Railway
9%
Rainfall Intensity
9%
Risk Level
18%
Root Mean Square
9%
Spindle Speed
6%
Support System
14%
Thematic Map
9%
Thrust Force
9%
Traffic Volume
9%
Vehicle Operation
9%
Vulcanization Process
9%
