scholarly journals KARAKTERISTIK SEKTOR PERTANIAN DI PROVINSI BALI MENURUT SUBSEKTOR PENYUSUN

2013 ◽  
Vol 2 (4) ◽  
pp. 23
Author(s):  
PUTU OKA SURYA ARSANA ◽  
MADE SUSILAWATI ◽  
KETUT JAYANEGARA
Keyword(s):  
Factor Analysis ◽  
Principal Component ◽  
Real Variable ◽  
Dominant Factor ◽  
Analysis Method ◽  
Factor Rotation ◽  
Factors Analysis ◽  
Culture Heritage ◽  
Eigen Values ◽  
Largest Eigenvalues

Bali instead of famous for tourism also popular at agriculture. One of them is subak. It is a culture heritage in the world. To cope with this problem the development in agriculture should be increased. The goal for this research are to know the identifiier factors of agriculture devolopment in Bali, the most dominat factors, and the variable which represent the development of agriculture in Bali. The method of analysis used for this research is factors analysis. Factor analysis is used to reduce the data or summary, for variable which is being changed to a new variable called factor and still load many information contained in a real variable. The method used in the factor analysis is principal component analysis method. Many  factors are determined by eigen values. The  factor rotation which used is varimax rotation. Based on the research results, got seven factors with the diversities which can be explained are 76.417%. Factors dryland farming as the most dominant factor identifier with the total value of the largest eigenvalues ??is 4.564 or 25.356% with variables representing these factors are widely planted potatoes and pulses.

scholarly journals Student Attendance Management System using Principal Component Analysis Method

2020 ◽  
Vol 9 (4S2) ◽  
pp. 9-15
Keyword(s):  
Management System ◽  
Iris Recognition ◽  
Principal Component ◽  
Cost Effective ◽  
Analysis Method ◽  
Academic Institutions ◽  
Student Attendance ◽  
Eigen Values ◽  
Cost Effective Technique ◽  
Day By Day

Attendance taking and maintaining is a tedious job in the academic institutions where the time of class is restricted. The manual attendance i.e., roll call or paper-based signature systems usually consumes more time and error prone and also possibility of recording proxy attendance is more. Attendance is one of the criteria in considering students’ eligibility for attending the external examinations and also for the promotion to the next semester / year, where these kinds of problems may cause severe effect on the academic institutions. As the strength of students in a class is increasing day by day; monitoring, awarding and maintenance of attendance has becoming a challenge for the academic institutions. As a solution, attendance can be recorded using anyone of the existing biometric techniques like fingerprinting, iris recognition, signature, face recognition etc. Face identification is the best method among all the earlier mentioned methods for implementing in the academic institutions as it does not require human intervention and it is a cost-effective technique. A novel student attendance recording and management system using a MATLAB application, LabVIEW, Camera interface and GSM is proposed in this paper. Students’ faces will be captured with the help of a camera connected to a computer and Eigen values of the captured images will be detected with the help of MATLAB executed by LabVIEW Mathscript node. LabVIEW, a graphical programming environment is adopted for acquiring face, processing and authenticating the student once the match is found. Authenticated student attendance will be updated, and a message will be sent with the help of GSM module interface to myRIO. Proposed system replaces the manual attendance system which improves the performance of existing system.

scholarly journals FAKTOR - FAKTOR YANG MEMPENGARUHI MINAT KONSUMEN DALAM MENGGUNAKAN JASA TRANSPORTASI KRL / COMMUTER LINE DENGAN METODE ANALISIS FAKTOR

2019 ◽  
Vol 2 (1) ◽  
pp. 38
Author(s):  
Besse Arnawisuda Ningsi ◽  
Ani Putriyani
Keyword(s):  
Factor Analysis ◽  
Reduction Process ◽  
Principal Component ◽  
Dominant Factor ◽  
Transportation Services ◽  
Consumer Interest ◽  
Number Of Factors ◽  
Interference Test ◽  
Spss Software ◽  
Determining Factor

The purpose of this study was to find out how many factors were formed through the reduction process, to determine which factors most dominantly influence consumer interest in using KRL Commuter Line transportation services, to find out how much influence the most dominant factors influence consumer interest in using KRL Commuter transportation services Line. In this study, the Factor Analysis method was used with principal component analysis techniques using SPSS software. 7 stages of factor analysis, namely: (1) formulating a problem, (2) Variable Interference Test, (3) forming a correlation matrix, (4) determining factor analysis methods, (5) extracting factors, (6) rotating factors, and (7) interpret factors. Based on the results of the study, the number of factors formed from the reduction process is 7 factors. Consisting of one factor (F1) with a correlation value of 0.608, factor two (F2) with a correlation value of -0.277, factor three (F3) with a correlation value of -0.246, factor four (F4) with a correlation value of 0.419, factor five (F5) with the correlation value is 0.716, factor six (F6) with a correlation value of -0.392, factor seven (F7) with a correlation value of 0.570. The most dominant factor affecting consumer interest in using KRL Commuter Line transportation services is factor five (F5) with a correlation value of 0.716 or 71.6%.

scholarly journals Data-driven integration evaluation from the perspective of Adaboost and its application in WeChat public number ranking

2020 ◽  
Vol 309 ◽  
pp. 02017
Author(s):  
Yicheng Gong ◽  
Juan Zhao ◽  
Dongyang Zhang
Keyword(s):  
Factor Analysis ◽  
Adaptive Learning ◽  
Evaluation Model ◽  
Complex Structure ◽  
Principal Component ◽  
Data Driven ◽  
Analysis Method ◽  
Topsis Method ◽  
Evaluation Models ◽  
Weak Evaluation

The traditional comprehensive evaluation is difficult to model when dealing with large data with large parameters and complex structure, and it cannot adapt to the update of data. In order to improve this situation, this paper draws on the Adaptive Learning Adaboost perspective in statistical learning to develop a data-driven integrated evaluation model that updates the weight of sample weights and weak evaluation models with data. Three specific weak evaluation models were selected: data-driven Topsis method, principal component analysis method and factor analysis method. Taking the ranking of WeChat public account as an example, the results show that the accuracy of the integrated evaluation model is 88.57%, which is 17.14%, 31.43% and 28.57% higher than the data-driven Topsis method, principal component method and factor analysis method.

scholarly journals Personal Cyber Security Provision Scale development studyKişisel Siber Güvenliği Sağlama Ölçeği geliştirme çalışması

2015 ◽  
Vol 12 (2) ◽  
pp. 75 ◽  
Author(s):  
Osman Erol ◽  
Yusuf Levent Şahin ◽  
Eray Yılmaz ◽  
Halil İbrahim Haseski
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Cyber Security ◽  
Structural Equation ◽  
Principal Component ◽  
Equation Modeling ◽  
Item Pool ◽  
Analysis Method ◽  
Internet Users ◽  
Rotation Method

<p>The aim of this study is to develop a scale to determine internet users behavior related to cyber security. In this context created an item pool in accordance with expert opinion. This item pool was administered to 810 people for exploratory factor analysis. In exploratory factor analysis; principal component analysis method which is commonly used and Varimax vertical rotation method to determine the factor structure was used. Scale was administered to 292 people and structural equation modeling approach was applied to confirmation study.As a result of factor analysis,“Personal Cyber Security Provision Scale" which consists of 5 factors and 25 items and has a good compatibility was occurred.</p><p> </p><p><strong>Özet</strong></p><p>Bu araştırmanın amacı internet kullanıcılarının siber güvenlik ile ilgili davranışlarını belirlemeye yönelik bir ölçek geliştirmektir. Bu bağlamda öncelikle uzman görüşü doğrultusunda 26 maddelik bir madde havuzu oluşturulmuştur. Bu madde havuzu yapı geçerliliğinin test edilmesi için Facebook sosyal paylaşımda bir uygulamayı kullanan 810 kişiye uygulanarak açımlayıcı faktör analizi yapılmıştır. Açımlayıcı faktör analizinde en sık kullanılan yöntem olan temel bileşenler analizi yöntemi kullanılmış, ölçekteki faktör yapısını belirlemek için ise Varimax - dikey döndürme yöntemi kullanılmıştır. Ölçeğin doğrulama çalışması için ise aynı sosyal ağ uygulamasını kullanan ve daha önce ölçeğin uygulandığı kişilerin elendiği292 kişinin verisi kullanılarak yapısal eşitlik modeli yaklaşımı uygulanmıştır. Açımlayıcı faktör analizi sonucunda 5 faktörlü ve 25 maddeden oluşan; doğrulayıcı faktör analizi sonucunda ise elde edilen uyum indekslerine göre iyi bir uyuma sahip "Kişisel Siber Güvenliği Sağlama Ölçeği" ortaya çıkmıştır.</p>

scholarly journals Using Principal Component Analysis for Factor Analysis in Indonesian Automotive Industries

2020 ◽  
Vol 8 (2) ◽  
pp. 62
Author(s):  
Ulil Hamida
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Automotive Industry ◽  
Principal Component ◽  
Component Analysis ◽  
Influential Factors ◽  
Analysis Method ◽  
Vehicle Ownership ◽  
Principal Component Analysis Algorithm

Policies related to the automotive industry have become significant for the Ministry of Industry. The problem in determining these policies is the determination of important factors for the automotive industry so that the policies formulated are right on target. The search for these important factors can be done by using the factor analysis method. So far, no studies have been conducted to examine the factors that influence the growth of the automotive industry. In this study, factor analysis is performed on factors in the automotive industry using the principal component analysis algorithm. The algorithm seeks to describe independently the aspects that become the main factors in determining the automotive industry. Based on an analysis of factors in the automotive industry production, the most influential factors are foreign investment, vehicle ownership ratios, and at last the change in GDP.

scholarly journals Driving Factors of Consumer to Purchase Furniture Online on IKEA Indonesia Website

2018 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Trisha Gilang Saraswati
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Perceived Risk ◽  
Online Shopping ◽  
Principal Component ◽  
Influential Factors ◽  
Driving Factors ◽  
Analysis Method ◽  
Long Time

The tendency of consumers in shopping for furniture is very different from shopping for other goods or services, because furniture is expected to be stored and used in a long time. Considering that, consumers tend to want to shop directly to offline stores in order to see, feel and check quality directly because of many aspects that are assessed such as the quality of materials, models, colors and more. Behind the trend to shop furniture offline, IKEA continues to innovate to improve the performance of its website so that consumers can shop online. Therefore, this study intends to analyze what factors are driving consumers in shopping for furniture online especially on the website of IKEA Indonesia. From two grounded theory employed on this research, there are 14 factors that can influence consumers to buy online. This data analysis uses Principal Component Analysis (PCA), a factor analysis method that extracts factors by using total variance in the analysis. From data calculation, it is known that there are 8 driving factors of consumer to purchase furniture online on IKEA Indonesia’s website: Enjoyment, Perceived Risk, Efficiency, Service & Merchandise Quality, Ease of Navigation, Price Attractiveness, Flexibility and Reliability. By knowing what factors can affect consumers in doing online shopping for furniture, companies in this case IKEA Indonesia can optimize the use of its website in accordance with influential factors.

scholarly journals Dietary patterns are associated with insulin resistance in Chinese adults without known diabetes

2012 ◽  
Vol 109 (9) ◽  
pp. 1662-1669 ◽  
Author(s):  
Hui Zuo ◽  
Zumin Shi ◽  
Baojun Yuan ◽  
Yue Dai ◽  
Xiaoqun Pan ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Factor Analysis ◽  
Dietary Patterns ◽  
Principal Component ◽  
Continuous Variable ◽  
Model Assessment ◽  
Analysis Method ◽  
Chinese Adults ◽  
Nutrition Survey ◽  
Health And Nutrition

The aim of the present study was to examine the association between dietary patterns and insulin resistance in Chinese adults without known diabetes. Study subjects were 1070 Chinese adults aged 18 years and above in Jiangsu Province who participated in the 2006 wave of the China Health and Nutrition Survey. Usual dietary intake was assessed by using a validated FFQ. Dietary patterns were identified by factor analysis using a principal component analysis method. Insulin resistance was defined as the highest quartile of the homeostasis model assessment of insulin resistance (HOMA-IR) scores. We derived four dietary patterns in our population by factor analysis: the Western, High-wheat, Traditional and Hedonic pattern. After adjusted for potential confounders, the Western pattern was significantly associated with greater odds for insulin resistance (P for trend = 0·009), while a significant negative association was found between the Hedonic pattern and insulin resistance (P for trend = 0·035). Compared with the lowest quartile of the Western pattern, the highest quartile had higher odds of insulin resistance (adjusted OR 1·89, 95 % CI 1·12, 3·19). There was a 42 % decrease in the odds after adjustment for all covariates in the highest quartile of the Hedonic pattern, compared with the lowest quartile (adjusted OR 0·58, 95 % CI 0·34, 0·99). HOMA-IR levels as a continuous variable also increased across the quartiles of the Western pattern and decreased across the quartiles of the Hedonic pattern. In conclusion, dietary patterns were significantly associated with insulin resistance in Chinese adults without known diabetes.

scholarly journals Analisis Faktor Dalam Meningkatkan Prestasi Belajar Siswa Kelas X IPS SMA Negeri 1 Adonara Timur, Provinsi

2018 ◽  
Vol 11 (2) ◽  
pp. 29-36
Author(s):  
Maria Prisca
Keyword(s):  
Factor Analysis ◽  
Curriculum Change ◽  
Principal Component ◽  
Primary Data ◽  
Quality Of Education ◽  
Analysis Method ◽  
Simple Description ◽  
Improving Student Achievement ◽  
Internal And External Factors

Education is very important in achieving the ideals of the nation to improve the quality of human resources as well. Curriculum change in 2013 is one of the government's efforts in improving the quality of education in Indonesia. To improve students' learning achievement, internal and external factors are needed to encourage students to keep their spirit in learning. In this study, the researcher took a case about factor analysis in improving the achievement of the students of class X IPS of SMA Negeri 1 Adonara Timur. Achievement of study in SMA Negeri 1 Adonara East class X particularly good, although there are achievement of learning in class X IPS is often low. This study aims to determine what factors are formed in improving student achievement class X IPS in SMA Negeri 1 Adonara Timur. The data used in this study is the primary data obtained through the distribution of questionnaires, with a sample of 47 students. The analysis method used in this research is factor analysis. Factor analysis is one of the statistical techniques that can be used to provide a relatively simple description through the reduction of the number of variables called factors. Since the purpose of factor. Pendidikan merupakan hal yang sangat penting dalam mencapai cita-cita bangsa sehingga  meningkatkan Sumber Daya Manusia yang berkualitas. Perubahan Kurikulum pada tahun 2013 merupakan upaya pemerintah dalam meningkatkatkan kualitas pendidikan di Indonesia yang diketahui berdasarkan prestasi belajar siswa. Untuk meningkatkan prestasi belajar siswa, diperlukan faktor intern dan faktor ekstern yang mendorong siswa untuk tetap semangat dalam belajar. Prestasi belajar di SMA Negeri 1 Adonara Timur khususnya kelas X tergolong baik, Namun, prestasi belajar pada kelas X IPS seringkali rendah. Penelitian ini bertujuan untuk mengetahui faktor-faktor apa saja yang terbentuk dalam meningkatkan prestasi belajar siswa kelas X IPS di SMA Negeri 1 Adonara Timur. Data yang digunakan dalam penelitian ini adalah data primer yang diperoleh melalui penyebaran kuesioner, dengan sampel sebanyak 47 siswa. Metode analisis yag digunakan dalam penelitian ini adalah analisis faktor. Tujuan dari analisis faktor pada penelitian ini adalah untuk mereduksi data maka metode analisis faktor yang digunakan adalah Principal Component Analysis   (PCA). Hasil dari penelitian ini diperoleh 5 faktor yang diduga dapat meningkatkan prestasi belajar siswa kelas X IPS di SMA Negeri 1 Adonara Timur. Faktor-faktor tersebut adalah Lingkungan Sekolah, Peranan Orang Tua, Peranan Guru, Disilpin Belajar, dan Motivasi Belajar.

scholarly journals ANALISIS RESISTANCE FACTOR DALAM PENERAPAN PEMBELAJARAN BERBASIS ELEKTRONIK MENGGUNAKAN PENDEKATAN HUMAN-CENTERED-APPROACH

2020 ◽  
Vol 22 (3) ◽  
pp. 278-285
Author(s):  
Viska Armalina ◽  
Wisnu Hera Pamungkas
Keyword(s):  
Information Technology ◽  
Factor Analysis ◽  
Resistance To Change ◽  
Principal Component ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Dominant Factor ◽  
Personality Factors ◽  
Analysis Model ◽  
Factor Analysis Model

E-learning becomes an alternative way to transfer information effectively and efficiently in adopting information technology as a means of teaching and learning. Information technology applied must be Acceptable, if it’s not, it will display the behavior of resistance to change. This study uses the Human-Centered Approach-related resistance to change in preparation of the questionnaire instrument and using factor analysis in data processing and analysis. The process of taking samples using simple random sampling technique in which the taking of samples of the population that was randomly without regard to strata that exist in the population. Factor analysis model used is Principal Component Analysis (PCA). Phases of analysis of factors such as the correlation matrix, factor extraction, factor rotation, and interpretation of factors. Results from this research can be concluded that these factors play a role in the emergence of resistance to change in sequence from the most dominant factor Competence Factor, Motivation and Planning Implementation Factors, Communications in Leadership Factors, Culture Factor, Situations and Conditions Factors, Personality Factors, and Security Factor. It would be better if the sampling is not only for teachers but also involves students and mapped based on certain criteria which are equipped with the characteristics of each sample.

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