scholarly journals Sistem Pendukung Keputusan Dengan Metode Chi-Squared Automatic Interaction Detection Analysis (CHAID) Untuk Memprediksi Mahasiswa Putus

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Yudi Fadli ◽  
Fenty Ariani ◽  
Usman Rizal
Keyword(s):  
Interaction Detection ◽  
Detection Analysis ◽  
Chi Squared

scholarly journals Exploring the Negotiation Thesis Application Among Ski Resort Tourists: A Segmentation Approach

2015 ◽  
Vol 42 (5) ◽  
pp. 716-739
Author(s):  
Chris A. Vassiliadis ◽  
Victoria Bellou ◽  
Constantinos-Vasilios Priporas ◽  
Andreas Andronikidis
Keyword(s):  
Decision Making ◽  
Relative Strength ◽  
Decision Making Process ◽  
Structural Constraints ◽  
Interaction Detection ◽  
Ski Resorts ◽  
Participation Decision ◽  
Detection Analysis ◽  
Revisit Intention ◽  
Chi Squared

The negotiation thesis offers a framework for understanding the participation decision making of tourists. Unlike previous studies that investigate the causal relationship between constraints and tourists’ revisit intention, this study identified distinct segments of ski tourist based on the relative strength of constraints experienced and then investigated their decision-making process across a sample of 1,348 tourists of ski resorts. Chi-squared automated interaction detection analysis revealed that the decision-making process regarding intention to revisit a ski destination varies between highly versus less constrained ski tourists, indicating different relative strengths of interpersonal, intrapersonal, and structural constraints and different interactions among them when predicting revisit intention. On a practical basis, albeit the vast majority of participants were willing to repeat its visit, we offer customized per segment recommendations on increasing frequency of visitation and spending levels.

scholarly journals Predictors of the Level of Knowledge about Sexual Harassment and Assault among College Students: A Chi-Squared Automatic Interaction Detection Analysis

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Erol Esen ◽  
◽  
Yağmur Soylu ◽  
Diğdem Müge Siyez ◽  
◽  
...  
Keyword(s):  
College Students ◽  
Sexual Harassment ◽  
Interaction Detection ◽  
State College ◽  
Detection Analysis ◽  
Chaid Analysis ◽  
Multi Stage ◽  
Chi Squared ◽  
Level Of Knowledge ◽  
High Level

This study aims to determine college students’ levels of knowledge about sexual harassment and assault, and to identify the predictors of this level of knowledge. Participants have been selected using a multi-stage sampling method and consist of 7,302 college students from a state college in Turkey. The age of participants ranged from 17 years to 29 years with a mean age of 21.33 years (SD = 2.04). The Sexual Harassment and Assault Knowledge Test, the Survey of College Students’ Exposure to Sexual Harassment and Assault, and a socio-demographic form were used to obtain data from the sample. The two-steps cluster analysis revealed that 70.2 % of the all participants had moderate level of knowledge about sexual harassment and assault, while 13.6 % had a low level of knowledge and 16.2 % had high level of knowledge. The CHAID analysis indicated that sex was the main predictor of level of knowledge about sexual harassment and assault. Also, exposure to sexual harassment or assault, dating experience, and having gender-equality education were found as other predictor variables. Finally, classification accuracy of the CHAID model was found 79.5 % within the sample.

scholarly journals Predictors of the Level of Knowledge about Sexual Harassment and Assault among College Students: A Chi-Squared Automatic Interaction Detection Analysis

2021 ◽  
Author(s):  
Erol Esen ◽  
Yağmur Soylu ◽  
Diğdem Müge Siyez
Keyword(s):  
College Students ◽  
Sexual Harassment ◽  
Interaction Detection ◽  
State College ◽  
Detection Analysis ◽  
Chaid Analysis ◽  
Multi Stage ◽  
Chi Squared ◽  
Level Of Knowledge ◽  
High Level

This study aims to determine college students’ levels of knowledge about sexual harassment and assault, and to identify the predictors of this level of knowledge. Participants have been selected using a multi-stage sampling method and consist of 7,302 college students from a state college in Turkey. The age of participants ranged from 17 years to 29 years with a mean age of 21.33 years (SD = 2.04). The Sexual Harassment and Assault Knowledge Test, the Survey of College Students’ Exposure to Sexual Harassment and Assault, and a socio-demographic form were used to obtain data from the sample. The two-steps cluster analysis revealed that 70.2 % of the all participants had moderate level of knowledge about sexual harassment and assault, while 13.6 % had a low level of knowledge and 16.2 % had high level of knowledge. The CHAID analysis indicated that sex was the main predictor of level of knowledge about sexual harassment and assault. Also, exposure to sexual harassment or assault, dating experience, and having gender-equality education were found as other predictor variables. Finally, classification accuracy of the CHAID model was found 79.5 % within the sample.

scholarly journals PEMODELAN PREFERENSI PENGAJUAN KREDIT USAHA MIKRO (KUM) DI BANK X OLEH PEMILIK USAHA MIKRO DI SURABAYA DENGAN METODE CHAID

2019 ◽  
Vol 3 (3) ◽  
pp. 34
Author(s):  
Niken Ariestanti ◽  
Kestrilia Rega Prilianti
Keyword(s):  
Small And Medium Enterprises ◽  
Classification Tree ◽  
Interaction Detection ◽  
Detection Analysis ◽  
Chi Squared ◽  
National Bank ◽  
Commercial Loans ◽  
The Government ◽  
The Right ◽  
Medium Enterprises

In the aim of developing and strengthening  the micro, small and medium enterprises (MSMEs), the government of Indonesia provide financial support for MSMEs enterpreneur through commercial loans which is held by several national bank. In order to assure that the loan goes to the right enterpreneur, those banks need some information about the MSMEs entepreneur’s preference in applying the MSMEs loan. These preference could be predicted by exploring the enterpreneur’s characteristics. One of the quantitative method called CHAID (Chi-Squared Automatic Interaction Detection Analysis) has been used in this research to provide that prediction. With this method, the MSMEs enterpreneur’s preferences on loan application and loan products were modeled by two classification tree.   

PENERAPAN CHAID DENGAN PENDEKATAN SMOTE PADA KEMATIAN BALITA DI KAWASAN TIMUR INDONESIA TAHUN 2017

2020 ◽  
Vol 2019 (1) ◽  
pp. 357-367
Author(s):  
Isti Samrotul Hidayati ◽  
I Made Arcana
Keyword(s):  
Sampling Technique ◽  
Chi Square ◽  
Interaction Detection ◽  
Chi Squared

Metode Chi-squared Automatic Interaction Detection (CHAID) merupakan metode segmentasi berdasarkan hubungan variabel respon dan penjelas menggunakan uji chi-square, yang dalam penerapannya perlu memperhatikan keseimbangan data untuk meminimalkan kesalahan dalam klasifikasi. Salah satu pendekatan yang dapat digunakan pada data yang tidak seimbang adalah metode Synthetic Minority Over-sampling Technique (SMOTE). Dalam penelitian ini, metode CHAID dengan pendekatan SMOTE diterapkan pada Angka Kematian Balita (AKBa) di Kawasan Timur Indonesia (KTI). Tujuannya adalah untuk mengetahui variabel-variabel yang mencirikan kematian balita berdasarkan metode analisis CHAID yang diterapkan dan membandingkannya dengan pendekatan SMOTE. Hasil perbandingan menunjukkan bahwa pendekatan SMOTE lebih baik digunakan dengan nilai sensitivitas sebesar 48,3% dan nilai presisi sebesar 75,9%. Variabel yang signifikan mencirikan kematian balita di KTI adalah berat badan saat lahir, jenis kelahiran, status bekerja ibu dan kekayaan rumah tangga, dengan karakteristik utama adalah balita yang memiliki berat badan lahir rendah dan terlahir kembar.

scholarly journals Probability of Roadside Accidents for Curved Sections on Highways

2020 ◽  
Vol 2020 ◽  
pp. 1-18 ◽  
Author(s):  
Guozhu Cheng ◽  
Rui Cheng ◽  
Yulong Pei ◽  
Liang Xu
Keyword(s):  
Risk Factors ◽  
Decision Rules ◽  
Significant Risk ◽  
Vehicle Speed ◽  
Probabilistic Prediction ◽  
Interaction Detection ◽  
Probability Prediction ◽  
Chi Squared ◽  
Longitudinal Slope ◽  
Curve Radius

To predict the probability of roadside accidents for curved sections on highways, we chose eight risk factors that may contribute to the probability of roadside accidents to conduct simulation tests and collected a total of 12,800 data obtained from the PC-crash software. The chi-squared automatic interaction detection (CHAID) decision tree technique was employed to identify significant risk factors and explore the influence of different combinations of significant risk factors on roadside accidents according to the generated decision rules, so as to propose specific improved countermeasures as the reference for the revision of the Design Specification for Highway Alignment (JTG D20-2017) of China. Considering the effects of related interactions among different risk factors on roadside accidents, path analysis was applied to investigate the importance of the significant risk factors. The results showed that the significant risk factors were in decreasing order of importance, vehicle speed, horizontal curve radius, vehicle type, adhesion coefficient, hard shoulder width, and longitudinal slope. The first five important factors were chosen as predictors of the probability of roadside accidents in the Bayesian network analysis to establish the probability prediction model of roadside accidents. Eventually, the thresholds of the various factors for roadside accident blackspot identification were given according to probabilistic prediction results.

scholarly journals Determinants of Nutrition Facts Table Use by Chinese Consumers for Nutritional Value Comparisons

2022 ◽  
Vol 19 (2) ◽  
pp. 673
Author(s):  
Zeying Huang ◽  
Haijun Li ◽  
Jiazhang Huang
Keyword(s):  
Nutritional Value ◽  
Online Survey ◽  
Nutrition Labeling ◽  
Chinese Consumers ◽  
Nutritional Values ◽  
Factors Associated ◽  
Interaction Detection ◽  
Chi Squared ◽  
Nationally Representative ◽  
Adoption Level

The nutrition facts table is a nutrition labeling tool designed to inform consumers of food nutritional contents and enable them to make healthier choices by comparing the nutritional values of similar foods. However, its adoption level is considerably low in China. This study employed the Chi-squared Automatic Interaction Detection (CHAID) algorithm to explore the factors associated with respondents’ adoption of nutrition facts table to compare the nutritional values of similar foods. Data were gathered through a nationally representative online survey of 1500 samples. Results suggested that consumers’ comprehension of the nutrition facts table was a direct explanatory factor for its use. The usage was also indirectly explained by people’s nutrition knowledge, the usage of nutrition facts table by their relatives and friends, and their focus on a healthy diet. Therefore, to increase the use of nutrition facts table by Chinese consumers, the first consideration should be given to enhancing consumers’ comprehension of the labeling

scholarly journals Data mining untuk memprediksi prestasi siswa berdasarkan sosial ekonomi, motivasi, kedisiplinan dan prestasi masa lalu

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Heri Susanto ◽  
Sudiyatno Sudiyatno
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Multiple Regression ◽  
Economic Status ◽  
Predictive Analysis ◽  
Research Approach ◽  
Significance Level ◽  
Achievement Prediction ◽  
Interaction Detection ◽  
Chi Squared

Penelitian ini bertujuan untuk membuat prediksi prestasi belajar siswa berdasarkan status sosial ekonomi orang tua, motivasi, kedisiplinan siswa dan prestasi masa lalu menggunakan metode data mining dengan algoritma J48. Sebagai perbandingan, data penelitian dianalisis juga dengan CHAID (Chi Squared Automatic Interaction Detection) dan regresi ganda. Pendekatan penelitian yang digunakan adalah kuantitatif. Subyek penelitian ini adalah siswa tingkat X SMK Negeri 4 Surakarta berjumlah 416 siswa. Teknik pengumpulan data yang digunakan adalah dokumentasi dan angket. Hasil penelitian menunjukkan bahwa analisis prediksi menggunakan decision tree algoritma J48 memiliki akurasi sebesar 95,7%, sedangkan analisis prediksi menggunakan CHAID memiliki tingat akurasi 82,1% dan analisis regresi ganda menghasilkan tingkat signifikansi sebesar 90,6%. Berdasarkan hasil tersebut bisa disimpulkan bahwa metode J48 lebih baik dibandingkan dengan metode CHAID dan regresi ganda. DATA MINING TO PREDICT STUDENT’S ACHIEVEMENT BASED ON SOCIO-ECONOMIC, MOTIVATION, DISCIPLINE AND ACHIEVEMENT OF THE PASTAbstractThis study aims to make student achievement prediction based on socio-economic status of parents, motivation, discipline students and past achievements using data mining methods with the J48 algorithm. For comparison, the data were analyzed also with CHAID (Chi Squared Automatic Interaction Detection) and multiple regression. The research approach is quantitative. The subjects of this study were student-first level at SMK Negeri 4 Surakarta totaled 416 students. Data collection techniques used are documentation and questionnaires. The results showed that the predictive analysis using J48 decision tree algorithm has an accuracy of 95.7%, while the predictive analysis using CHAID has the rank of an accuracy of 82.1% and a multiple regression analysis resulted in a significance level of 90.6%. Based on these results it can be concluded that the J48 method is better than the CHAID and multiple regression methods.

scholarly journals Aplikasi Data Mining Dengan Metode CHAID Dalam Menentukan Status Kredit

2020 ◽  
Vol 18 (1) ◽  
pp. 29
Author(s):  
Muhammad Rizki ◽  
Muhammad Isnaini Hadiyul Umam ◽  
Muhammad Luthfi Hamzah
Keyword(s):  
Data Mining ◽  
Chi Square ◽  
Interaction Detection ◽  
Detection Analysis

Seiring dengan digalakkannya Industrial 4.0, data mining menjadi topik yang hangat untuk bahas dikalangan peneliti. Perkembangan teknologi yang begitu cepat memaksa kita untuk dapat mengambil keputusan dengan cepat pula. Kredit macet menjadi salah satu resiko terbesar lembaga keuangan. Resiko kredit macet ini wajib diminimalisir dengan menganalisa faktor status nasabah berdasarkan data personalnya, sehingga dapat dilakukan klasifikasi berdasarkan  hubungan antar faktor tersebut. Salah satu kunci utama memenangkan persaingan pasar yaitu dengan menentukan target pasar. Data mining menyediakan banyak alat bantu untuk klasifikasi, salah satunya dengan menggunakan metode analisis CHAID (Chi-square Automatic Interaction Detection Analysis). Diagram pohon keputusan yang dihasilan dari Analisis CHAID dapat memberikan informasi tentang derajat hubungan antara variable independent dan dependent, serta informasi tentang karakteristik masing-masing kategori. Dalam hal ini, analisis CHAID digunakan untuk menentukan klasifikasi nasabah berdasarkan status kredit nasabah sebagai variable terikat dan data pribadi nasabah sebagai variable bebas. Dengan menggunakan uji Chi-square, dari total 7 variables independent, hanya 5 variable yang signifikan dengan variable dependent. Variable-variable tersebut adalah variable independent usia, pekerjaan, pendidikan, jangka waktu dan jumlah pinjaman. Berdasarkan hasil analisis CHAID didapatkan empat kelas. Kelas nasabah dengan pekerjaan sebagai (Aparatur Sipil Negara) ASN merupakan kelas yang memiliki resiko kredit macet yang paling minimal.

Air Quality Modeling and Metamodeling Approach

2011 ◽  
pp. 144-161 ◽  
Author(s):  
Miloslava Kašparová ◽  
Jirí Krupka
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Classification Problem ◽  
Air Quality Modeling ◽  
Point Of View ◽  
Interaction Detection ◽  
Power Stations ◽  
Quality Modeling ◽  
Chi Squared ◽  
Problematic Area

This chapter deals with modeling and metamodeling of air quality in the Pardubice region of the Czech Republic. From a regional point of view, the Pardubice district is the most problematic area in regards to air pollution. Concentrations of traffic, industry and power stations (Opatovice and Chvaletice) activities are the cause of this situation, although emissions of all pollutants have markedly decreased within the last ten years. A decrease in air pollution was achieved particularly by restriction and restructuring of industrial production, use of emission standards, changes in legislation in the area of air protection, etc. The mentioned air quality modeling belongs to classification tasks. It means the authors deal with the classification problem, with the creation of classification models (classifiers) and they focus on metamodeling (combining classifiers). Through the application of modeling and metamodeling the authors use selected algorithms of decision trees (C5.0, chi-squared automatic interaction detection and classification and regression trees) that belong to useful explanatory techniques.

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