scholarly journals The Development of a Psychodiagnostic Instrument Based on Ego state, Impasse and Drama Triangle Concepts (ZESUI)

2013 ◽  
Vol 4 (1) ◽  
pp. 39-48
Author(s):  
Kristina Brajovic Car ◽  
Marina Hadzi Pesic ◽  
Jasmina Nedeljkovic
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Statistical Method ◽  
Instrument Development ◽  
Principal Component ◽  
Type I ◽  
Transactional Analysis ◽  
Final Version ◽  
Analysis Theory ◽  
Ego States

The process of developing the final version of the Impasses, Ego state and Drama Triangle Role Inventory (in short - ZESUI) presented in this article involved repeated iterations over four years. The scale is based on the Transactional analysis theory of personality, interpersonal styles and pathology. The statistical method used in the process of the instrument development, with specific attempts to increase the factor saturation and items internal consistency is exploratory factor analysis, more specifically methods of principal component analysis. The questions within the inventory include the relevant aspects of the diagnosis (assessment) of the Ego state, Impasses and Roles profiles. It consists of 62 items which measure three types of Impasses: Type I, II and III, nine Functional Ego States and three Drama Triangle Roles: Rescuer, Persecutor and Victim.

scholarly journals Analisis Partial Least Square Menghasilkan Output Alternatif Antarmuka Tambahan Dari Kansei Engineering

2020 ◽  
Vol 17 (2) ◽  
pp. 67
Author(s):  
Arief Ginanjar ◽  
Awan Setiawan
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Correlation Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Kansei Engineering ◽  
Coefficient Corrélation

Ketika menggunakan Kansei Engineering dalam mencari kandidat terbaik untuk menentukan model perancangan antarmuka website, peneliti menggunakan metode analisis Partial Least Square (PLS) yang dilakukan secara berulang hingga ditemukan elemen terbaik yang dapat diimplementasikan. PLS sebagai alat bantu untuk menentukan nilai terbaik antara elemen website. Output perbandingan yang dihasilkan akan dikelompokkan berdasarkan Kansei Word sebagaimana yang telah ditentukan dalam rencana awal implementasi Kansei Engineering, output perbandingan PLS iterasi pertama mempunyai kemungkinan mendapatkan nilai usulan terbaik jika digabung dengan melakukan iterasi kedua terhadap asimilasi dua atau tiga elemen yang mempunyai nilai tertinggi. Metodologi yang digunakan mengacu kepada Kansei Engineering Type I dengan melalui pengolahan data menggunakan Cronbach’s Alpha untuk menguji kelayakan responden, kemudian untuk mengetahui hubungan Kansei Words dapat menggunakan Coefficient Correlation Analysis (CCA), sedangkan hubungan antara Kansei Words dengan spesimen dapat menggunakan Principal Component Analysis (PCA), sedangkan mencari pengaruh Kansei Words paling kuat dapat menggunakan Factor Analysis (FA) dan analisis Partial Least Square (PLS) namun harus dilakukan iterasi proses PLS hingga variabel rekomendasi model perancangan antarmuka yang dihasilkan menjadi lebih bervariatif.

scholarly journals Finding Structures of Interest in a Large Data Set Using Factor Analysis

2016 ◽  
Vol 26 (2) ◽  
Author(s):  
Peter Filzmoser
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Statistical Method ◽  
Principal Component ◽  
Large Data ◽  
Component Analysis ◽  
Factor Space ◽  
Data Set ◽  
Large Data Set

In this paper we introduce a statistical method which can be used in combination with principal component analysis or factor analysis. Certain variables of a large data set which are of interest can be selected in order to calculate loadings and scores of these variables. We describe how the remaining variables of the data set can be presented in the previously extracted factor space. Furthermore, a possibility for the representation of the results is shown which is helpful for the interpretation.

scholarly journals Implementasi Kansei Engineering Dalam Desain Tampilan Website Perguruan Tinggi

2018 ◽  
Vol 3 (1) ◽  
pp. 71
Author(s):  
Yudhi Raymond Ramadhan
Keyword(s):  
Higher Education ◽  
Principal Component Analysis ◽  
Factor Analysis ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Kansei Engineering ◽  
Alpha Coefficient ◽  
Coefficient Corrélation

Tampilan sebuah website awalnya dikembangkan dari sisi fungsi dan kegunaan website tersebut. Seiring dengan perkembangan zaman, dalam merancang tampilan sebuah website mulai melibatkan sisi perasaan atau emosi dari pengguna website. Penelitian ini mengimplementasikan metode Kansei Engineering dalam merancang tampilan sebuah website perguruan tinggi, dimana sisi perasaan atau emosi pengguna dapat dilibatkan dalam merancang tampilan sebuah website. Metodologi yang digunakan adalah metodologi Kansei Engineering Type I, yang memecah sebuah konsep desain menjadi sub konsep. Penelitian ini menggunakan 15 Kansei Word dan 16 spesimen website perguruan tinggi. Partisipan yang terlibat pada penelitian ini adalah 70 partisipan yang terdiri dari 10 orang dosen dan  60 orang mahasiswa STIEB Perdana Mandiri. Hasil kuesioner dari partisipan kemudian diolah dengan menggunakan analisis statistik multivariat yakni Cronbach’s Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) dan analisis Partial Least Square (PLS). Berdasarkan hasil pengolahan data dari seluruh partisipan diperoleh tiga rekomendasi elemen desain tampilan website Perguruan Tinggi yang mewakili perasaan atau emosi dari pengguna website perguruan tinggi.Kata kunci: Kansei Engineering, website, perasaan, emosi, perguruan tinggi The website interface was originally developed in terms of functionality and usability of the website. Along with the development of the era, in designing website interface began to involve the feelings or emotions of website users. This research implemented Kansei Engineering method of designing higher education website interface, which are the feelings or emotions of users can be involved in designing website interface. The methodology used was the Kansei Engineering Type I, which breaks down a design concept into sub concepts. This study used 15 Kansei Words and 16 specimens of higher education websites. Participants involved in this research were 70 participants consisted of 10 lecturers and 60 students of STIEB Perdana Mandiri. The results of questionnaires from the participants were processed using multivariate statistical analysis are Cronbach's Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) and Partial Least Square (PLS) analysis. Based on the results of data processing from all participants, there are obtained three recommendations of design elements of the higher education website that represents the feelings or emotions of higher education website users.Keywords: Kansei Engineering, website, feelings, emotions, higher education 

scholarly journals Harmful Chemicals in the Work Environment

2020 ◽  
Vol 18 (1-2) ◽  
Author(s):  
Predrag Ilić ◽  
Dragana Nešković Markić ◽  
Zia Ur Rahman Farooqi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Correlation Analysis ◽  
Work Environment ◽  
Statistical Method ◽  
Principal Component ◽  
Hospital Personnel ◽  
Multivariate Statistical ◽  
Multivariate Statistical Method ◽  
Method Factor

For hospital personnel, a number of harmful chemicals exist. The paper deal with very different harmful chemicals, but all chemicals are important and continuing problems where the risks to health, if uncontrolled, are serious. In the research was used descriptive statistical operations and multivariate statistical method, factor analysis (FA), i.e. principal component analysis (PCA). An analysis of 24 organic and inorganic parameters was performed. Results of the correlation analysis suggest that these pollutants pairs might have similar sources or have been affected by similar factors. PCA she confirmed that the mutually correlated elements constitute a group of elements with a similar origin.

scholarly journals Metacognitive Rating Scale: A Study Applying a Korean Translation to Individuals with Schizophrenia

2021 ◽  
Vol 18 (13) ◽  
pp. 6853
Author(s):  
Mihwa Han ◽  
Kyunghee Lee ◽  
Mijung Kim ◽  
Youngjin Heo ◽  
Hyunseok Choi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Mental Status ◽  
Rating Scale ◽  
Anger Expression ◽  
Principal Component ◽  
Negative Beliefs ◽  
Five Factors ◽  
Metacognitive Beliefs

Metacognition is a higher-level cognition of identifying one’s own mental status, beliefs, and intentions. This research comprised a survey of 184 people with schizophrenia to verify the reliability of the metacognitive rating scale (MCRS) with the revised and supplemented metacognitions questionnaire (MCQ) to measure the dysfunctional metacognitive beliefs of people with schizophrenia by adding the concepts of anger and anxiety. This study analyzed the data using principal component analysis and the varimax method for exploratory factor analysis. To examine the reliability of the extracted factors, Cronbach’s α was used. According to the results, reliability was ensured for five factors: positive beliefs about worry, negative beliefs about uncontrollability and danger of worry, cognitive confidence, need for control, and cognitive self-consciousness. The negative beliefs about uncontrollability and danger of worry and the need for control on anger expression, which were both added in this research, exhibited the highest correlation (r = 0.727). The results suggest that the MCRS is a reliable tool to measure the metacognition of people with schizophrenia.

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