scholarly journals Artificial Neural Network Model Development to Predict Theft Types in Consideration of Environmental Factors

2021 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
Eunseo Kwon ◽  
Sungwon Jung ◽  
Jaewook Lee
Keyword(s):  
Environmental Factors ◽  
Linear Regression Analysis ◽  
Model Development ◽  
Multiple Linear Regression Analysis ◽  
Target Area ◽  
Ann Model ◽  
Factors Affecting ◽  
Crime Prediction ◽  
Model Training ◽  
Input Variables

Crime prediction research using AI has been actively conducted to predict potential crimes—generally, crime locations or time series flows. It is possible to predict these potential crimes in detail if crime characteristics, such as detailed techniques, targets, and environmental factors affecting the crime’s occurrence, are considered simultaneously. Therefore, this study aims to categorize theft by performing k-modes clustering using crime-related characteristics as variables and to propose an ANN model that predicts the derived categorizations. As the prediction of theft types allows people to estimate the features of the possibly most frequent thefts in random areas in advance, it enables the efficient deployment of police and the most appropriate tactical measures. Dongjak District was selected as the target area for analysis; thefts in the district showed four types of clusters. Environmental factors, representative elements affecting theft occurrence, were used as input data for a prediction model, while the factors affecting each cluster were derived through multiple linear regression analysis. Based on the results, input variables were selected for the ANN model training per cluster, and the model was implemented to predict theft type based on environmental factors. This study is significant for providing diversity to prediction methods using ANN.

Factors Affecting the Production of the Coffee Farming in Uluway Village Mengkendek Sub District Tana Toraja District

2021 ◽  
Vol 6 (1) ◽  
pp. 37
Author(s):  
Renatha Mersi ◽  
Ayub Manggala Padangaran ◽  
Fahria Nadiryati Sadimantara
Keyword(s):  
Data Analysis ◽  
Qualitative Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Land Area ◽  
Coffee Production ◽  
Factors Affecting ◽  
Land Preparation ◽  
Processing Techniques ◽  
Coffee Farming

This study aimed to determine what factors influence coffee production in Uluway Village, Mengkendek Sub District of Tana Toraja District. The research was conducted from March to May 2020 where these factors include land area, labor, fertilizers, and pesticides. This study aimed to determine what factors influence the people's coffee production in Uluway Village, Mengkendek Sub District of Tana Toraja District. The population of this study was all the farmers who cultivated coffee in Uluway Village, Mengkendek Sub District of Tana Toraja District. The sample of this study was 78 respondents who were determined by using the census method. The analytical method used is descriptive qualitative data analysis, the second data analysis using multiple linear regression analysis, and the third. The research results can be drawn from several conclusions, including the coffee farming processing techniques in Uluway Village, namely land preparation, planting, maintenance, harvesting, and postharvest. Factors that have a real effect include land area, fertilizers, and pesticides, while factors that do not affect coffee production are labor

scholarly journals Can chlorophyll-a in meso-oligotrophic shallow waters be estimated using statistical approaches and empirical models from MODIS imagery?

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Andres Mauricio Munar ◽  
José Rafael Cavalcanti ◽  
Juan Martin Bravo ◽  
David Manuel Lelinho Da Motta Marques ◽  
Carlos Ruberto Fragoso Júnior
Keyword(s):  
Linear Regression ◽  
Spatial Heterogeneity ◽  
Multiple Linear Regression ◽  
Chlorophyll A ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Accurate Estimation ◽  
Shallow Waters ◽  
Chl A ◽  
Input Variables

ABSTRACT Accurate estimation of chlorophyll-a (Chl-a) concentration in inland waters through remote-sensing techniques is complicated by local differences in the optical properties of water. In this study, we applied multiple linear regression (MLR), artificial neural network (ANN), nonparametric multiplicative regression (NPMR) and four models (Appel, Kahru, FAI and O14a) to estimate the Chl -a concentration from combinations of spectral bands from the MODIS sensor. The MLR, NPMR and ANN models were calibrated and validated using in-situ Chl -a measurements. The results showed that a simple and efficient model, developed and validated through multiple linear regression analysis, offered advantages (i.e., better performance and fewer input variables) in comparison with ANN, NPMR and four models (Appel, Kahru, FAI and O14a). In addition, we observed that in a large shallow subtropical lake, where the wind and hydrodynamics are essential factors in the spatial heterogeneity (Chl-a distribution), the MLR model adjusted using the specific point dataset, performed better than using the total dataset, which suggest that would not be appropriate to generalize a single model to estimate Chl-a in these large shallow lakes from total datasets. Our approach is a useful tool to estimate Chl -a concentration in meso-oligotrophic shallow waters and corroborates the spatial heterogeneity in these ecosystems.

scholarly journals FACTORS AFFECTING ENTREPRENEURIAL INTENTIONS AMONG COLLEGE STUDENT

2021 ◽  
Vol 5 (2) ◽  
pp. 79-86
Author(s):  
Trisna Sary Lewaru
Keyword(s):  
College Student ◽  
Locus Of Control ◽  
Self Efficacy ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Entrepreneurial Intention ◽  
Entrepreneurial Intentions ◽  
Need For Achievement ◽  
Factors Affecting ◽  
Independent Variables

ABSTRACT This study aims to analyze the factors that influence entrepreneurial intentions among college student. The five independent variables was used include need for achievement, locus of control, self-efficacy, instrumental readiness, entrepreneurship experience. Sample in this research is students on Pattimura University totaling 160 people. Multiple linear regression analysis was used to measure this study. The results of this study indicate that need for achievement, locus of control, entrepreneurship experience have no effect on the intentions of entrepreneurial among students. Whereas instrumental readiness and self-efficacy variable has positive and significant effect on entrepreneurial intention between students of Pattimura University. Keywords : Entrepreneurship, Intentions

scholarly journals Konversi Lahan Sawah di Kota Bogor dan Strategi Anggaran dalam Mengendalikannya

2017 ◽  
Vol 1 (2) ◽  
pp. 217
Author(s):  
Oni Hidayati ◽  
Hermanto Siregar ◽  
A. Faroby Falatehan
Keyword(s):  
Urban Areas ◽  
Agricultural Land ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Provincial Government ◽  
Wetland Area ◽  
Local Regulation ◽  
Factors Affecting ◽  
Land Banking ◽  
Wetland Conversion

Conversion of agricultural land in urban areas is most prevalent in wetlands, thus threatening food availability and loss of multifunctional land. In the last five years, the wetland area in Bogor City has dropped dramatically to 321 ha (BPS of Bogor City, 2016). Control of the rate of conversion of wetland in Bogor City is regulated by Local Regulation number 8 year 2011 concerning Bogor City Spatial Plan (RTRW Kota Bogor) 2011-2031. However, its implementation is less effective so that there is a need for economic instruments to support it. The purpose of this study is to describe the wetland conversion in Bogor City and budgetary strategies in order to control it. Spatial analysis with overlay method was used to and resulted in a land conversion pattern which was dominated by housing area of 1 137.33 ha (47.08%) and garden 254.28 ha (10.53%). The conversion pattern was used as the basis of multiple linear regression analysis of factors affecting wetland area in Bogor City during 2000-2015 which results were: production amount (significant at α 1%); building area (significant at α 5 %); realization of Bogor City Agricultural Service budget (not significant) with R2 value = 86.6%. Wetland conversion control was conducted through budget strategies which are analyzed with Analitycal Hierrachy Process (AHP) calculation, resulting as follows: (1) socialization budget; (2) budget for formulating local regulation; (3)budget sharing with the central/provincial government; (4) streamlining the role of the private; (5) budget supervision; (6)budget for (land banking); (7) incentives and disincentives for farmers.

scholarly journals ANALYSIS OF FACTORS AFFECTING GENERAL SUPPLIERS TO SELL FFB WITH A AND B QUALITY TO PT. SANDABI INDAH LESTARI AND RISK ANALYSIS OF THE RESOURCES

2019 ◽  
Vol 2 (1) ◽  
pp. 1-12
Author(s):  
Ali Setia Iskandar ◽  
Yuwana Yuwana ◽  
Bambang Sumantri
Keyword(s):  
Regression Analysis ◽  
Risk Analysis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Analytical Tool ◽  
Fresh Fruit ◽  
Factors Affecting ◽  
Long Period ◽  
Average Factor ◽  
Fresh Fruit Bunches

This study studies to analyze the factors that influence general suppliers to choose FFB (Fresh Fruit Bunches) on quality and quality B and calculate the business expenses to be received. This research was conducted in the period August - September 2018 at PT. Sandabi Indah Lestari (SIL). The analytical tool used in this study is multiple linear regression analysis and risk analysis. Based on the results of the analysis, the factors that influence general suppliers choose to sell FFB at quality A and quality B at PT. SIL is the average factor of the weight of FFB supplied, the weight of FFB sorted, the distance to the plant and transportation costs, while the factors that do not significantly affect the long period of receiving FFB at the plant then for the risks received are known that the risk of selling FFB quality A is greater because of loss while FFB that sells quality B is smaller because it avoids losses.Keyword: Suppliers, FFB (Fresh Fruit Bunches), quality A and B, risk

scholarly journals Factors Affecting Company's Capability in Performing Integrated Reporting: An Empirical Evidence From Indonesian Companies

2018 ◽  
Vol 7 (2) ◽  
pp. 141
Author(s):  
Putu Sukma Kurniawan ◽  
Made Arie Wahyuni
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Institutional Ownership ◽  
Multiple Linear Regression Analysis ◽  
Managerial Ownership ◽  
Contrast Level ◽  
Integrated Reporting ◽  
Factors Affecting

<p>This study examines the factors that affect the company's capability to perform integrated reporting. The analysis used in testing the hypothesis is multiple linear regression analysis. Results show that company’s size has positive and significant connection and stakeholder’s pressure has negative and significant connection with the company’s capability in performing integrated reporting. In contrast, level of company’s profitability, company’s managerial ownership, and company’s institutional ownership did not have enough connection with company’s capability in performing integrated reporting.</p><p> </p>

scholarly journals Factors Affecting Tax Aggressiveness In Plantation Companies Listed 2014-2017

2019 ◽  
Vol 3 (1) ◽  
pp. 49
Author(s):  
Linda Ramadhani ◽  
Fika Azmi
Keyword(s):  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Multiple Linear Regression Analysis ◽  
Managerial Ownership ◽  
Factors Affecting ◽  
Tax Aggressiveness ◽  
Analysis Technique ◽  
Fixed Assets ◽  
Positive Effect

This study aims to obtain empirical evidence about the factors that influence tax aggressiveness. The independent variables in this study are Corporate governance, Inventory Intensity and Fixed Assets Intensity. The sample in this study were plantation sector companies listed on the Indonesia Stock Exchange in 2014-2017. The sampling technique used purposive sampling method, and obtained data as many as 32 samples. The data analysis technique uses multiple linear regression analysis. The results showed that independent commissioners and inventory intensity did not affect to tax aggressiveness, institutional ownership had a positive effect to tax aggressiveness and managerial ownership and the intensity of fixed assets negatively affected to tax aggressiveness.

Faktor-Faktor Yang Mempengaruhi Minat Wajib Pajak Dalam Menggunakan Sistem E-Filling

IJAcc ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 53-59
Author(s):  
Mardiana Mardiana ◽  
Pipit Nursaputri ◽  
Ria Dwi I’zzaty
Keyword(s):  
Human Resources ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Security And Privacy ◽  
Primary Data ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Factors Affecting

The purpose of this research is to examine the factors affecting interests of taxpayers in using efiling facility. The independent variables of this research are perceived usefulness, perceived ease of use, security and privacy, complexity, readiness technology taxpayers information and human resources. Data used in this research is primary data by using questionnaires. Respondent are the Individual Taxpayers who used e-filing.This research used multiple linear regression analysis that involved 108 respondents. The results show that: (1) perceived usefulness affects positively the intention to use E-filing, (2) perceived ease of use affects positively the intention to use E-Filing, (3) security and privacy affects positively the intention to use E-Filing, (4) complexity affects negatively the intention to use E-filing, (5) Readiness Technology Taxpayers Information affects positively the intention to use E-Filing (6) Human Resources affects positively the intention to use E-Filing

scholarly journals Poorly recognized age-related downward deviation of the inguinal ligament

2016 ◽  
Vol 4 ◽  
pp. 205031211667556 ◽  
Author(s):  
Yassir Nawaz ◽  
Mihir Barvalia ◽  
Gurinder Rana ◽  
M Zain Khakwani ◽  
Khizr Azim ◽  
...  
Keyword(s):  
Human Subjects ◽  
A Priori ◽  
Linear Regression Analysis ◽  
Age Groups ◽  
Vascular Complications ◽  
Multiple Linear Regression Analysis ◽  
Inguinal Ligament ◽  
Mean Deviation ◽  
Factors Affecting ◽  
Age Related

Objective: To determine factors affecting actual inguinal ligament course in live human subjects. Introduction and hypothesis: Although the expected inguinal ligament course is supposedly a straight line extending from anterior superior iliac spine to pubic tubercle, the actual inguinal ligament course is frequently depicted a priori by a downward bowing dotted line. There are no studies in a live subject supporting this assumption. We hypothesized this assumption is indeed valid and is related to among other factors a lifelong effect of gravity and lax abdominal musculature on the inguinal ligament course. Methods: We retrospectively reviewed 54 consecutive computed tomography scans of the abdomen and pelvis randomly distributed across all age groups. Actual inguinal ligament course was visualized by reconstructing images using Terracon software. Vertical distance from the lowest point of actual inguinal ligament course to the expected inguinal ligament course was measured. We used multiple linear regression analysis to study the correlation between degree of inguinal ligament deviation and several variables. Results: Actual inguinal ligament course was below the expected inguinal ligament course in 52 of 54 patients. The mean deviation was 8.2 ± 5.9 mm. Advanced age was significantly associated with greater downward bowing of the inguinal ligament (p = 0.001). Conclusion: Actual inguinal ligament course is often well below the expected inguinal ligament course; this downward bowing of the inguinal ligament is especially pronounced with advancing age. Operators need to be mindful as this downward bowing can lead to supra-inguinal sticks causing vascular complications.

Dry Density Based on Soil Index Properties by Using Expert System

2020 ◽  
Vol 857 ◽  
pp. 266-272
Author(s):  
Bushra S. Albusoda ◽  
Dhurgham A. Al-Hamdani ◽  
Mohammed F. Abbas
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Liquid Limit ◽  
Dry Density ◽  
Great Success ◽  
Ann Model ◽  
Model Liquid

Dry density modeling is a valuable issue. Artificial neural networks (ANNs) have been used in many problems in geotechnical engineering and have demonstrated great success. In this paper, the ANN model is proposed to predict the dry density of the soil. The developed model is managed by the Matlab Neural Network Interface (R2016a). To create the ANN model, liquid limit, plastic limit, plasticity index, moisture content, specific gravity, finer accuracy than sieve 200, total suspended solids, organic and SO3 were selected and used as input parameters. There are (9, 6,5 and 3) nodes, (10) nodes and (1) node used for input, hidden layers and output layers, respectively. The value of dry density obtained from three sources was sympathetic. The first source is the experimental results of 99 soil samples conducted in Al-Najaf Institution laboratory for this study. The second source was to propose the expected dry density using multiple linear regression analysis (MLRA) on the samples used in the first source; The results show, that the prediction of the use of ANNs was closely consistent with the experimental data. Correlation coefficient (R2) and mean square error (MSE) were 0.97368 and 3.19474 10-3, respectively. The observed results of the proposed system were very comparable with those obtained from empirical analysis and the prediction obtained from multiple linear regression analysis, where the advanced ANN approach is applicable.

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