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 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 ANALISIS USER EXPERIENCE UNTUK PERANCANGAN USER INTERFACE INDIGOES MENGGUNAKAN METODE KANSEI ENGINEERING

2017 ◽  
Author(s):  
Martanto
Keyword(s):  
User Interface ◽  
User Experience ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Kansei Engineering ◽  
Alpha Coefficient ◽  
Coefficient Corrélation ◽  
E Learning

Website E-Learning saat ini sudah banyak digunakan pada dunia pendidikan, baik sekolah tingkat atas hingga perguruan tinggi. STMIK IKMI Cirebon telah menggunakan website E-Learning yang diberi nama Indigoes namun pemanfaatannya masih belum maksimal karena tampilan Indigoes yang sangat sederhana. User experience pengguna Indigoes dapat digunakan untuk perancangan user interface Indigoes yang baru sesuai dengan keinginan pengguna. Kansei engineering adalah sebuah metode perancangan yang menggunakan perasaan pengguna dalam membuat desain produk baru dan penelitian ini menerapkan metode Kansei Engineering Type I untuk merancang user interface Indigoes yang baru.Penelitian ini menggunakan Kansei Word untuk mendeteksi emosi atau perasaan pengguna Indigoes. Jumlah Kansei word yang digunakan sebanyak 23 kata yang mewakili perasaan pengguna terkait dengan desain user interface Indigoes yang baru. Alternatif desain yang digunakan sebanyak 5 buah. Penelitian ini melibatkan 30 partisipan dengan perincian 15 orang adalah mahasiswa dan 15 orang mahasiswi dari jurusan Komputerisasi Akuntasi dan Manajemen Informatika. Hasil kuisioner dari partisipan kemudian diolah menggunakan analisis statistik multivarit yaitu Cronbach’s Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) dan analisis Partial Least Square (PLS).

scholarly journals Penerapan Kansei Engineering dalam Perbandingan Desain Aplikasi Mobile Marketplace di Indonesia

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Nucky Vilano ◽  
Setia Budi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Mobile Application ◽  
Principal Component ◽  
Kansei Engineering ◽  
Multivariate Statistical ◽  
Christian University ◽  
Emotional Factors ◽  
Coefficient Corrélation ◽  
Major Factors

The company's application design is very important because it displays the company's image and to attract more users to purchase/utilize the application. This research applies Kansei Engineering Method to analyze the emotion or feelings of the user towards the design of a mobile application interface. Six Kansei Words and three specimens are utilised in this research, where Kansei words are selected from words related to user experience. The participants of this research consist of 54 students from Maranatha Christian University. Participants’ responses are studied using multivariate statistical analysis (e.g., Coefficient Correlation Analysis, Principal Component Analysis, and Factor Analysis). This study explores the emotional factors that occur in designing an application. This analysis shows that there are some major factors that greatly influence the design of a mobile application interface.

scholarly journals Implementasi Kansei Engineering pada Aplikasi E-learning Untuk Sekolah Menengah Kejuruan

2019 ◽  
Vol 9 (2) ◽  
pp. 165
Author(s):  
Yoga Megasyah
Keyword(s):  
Teaching And Learning ◽  
Logical Consequence ◽  
Principal Component ◽  
Word List ◽  
Partial Least Square ◽  
Least Square ◽  
Kansei Engineering ◽  
Multivariate Statistical ◽  
Coefficient Corrélation ◽  
E Learning

E-learning is the basis and logical consequence of the development of information and communication technology. With E-learning, teaching and learning methods in schools that use technology through electronic media such as computers, laptops, netbooks, or smartphones with internet networks or others. This study uses Kansei Word to detect the feelings of users of E-learning applications. The Kansei Word list is used as many 15 words related to the appearance of the E-learning application. E-learning application specimens used 8 specimens. This study involved 80 participants consisting of 40 students from SMK PGRI 3 Cimahi, 40 students from SMK 4 Padalarang. The questionnaire results from participants were then processed using multivariate statistical analysis, namely Cronbach's Alpha, Coefficient Correlation Analysis (CCA), Principal Component Analysis (PCA), Factor Analysis (FA) and Partial Least Square (PLS) analysis. This study produced 3 recommendations for the design of E-learning application. This recommendation is the result of the Kansei Engineering process which comes from 3 groups of participant data, namely groups of data of all participants, participants of SMK PGRI 3 Cimahi students and participants of SMK 4 Padalarang students.

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 Analysis of pork adulteration in the corned products using FTIR associated with chemometrics analysis

10.5219/1412 ◽  
2020 ◽  
Vol 14 ◽  
pp. 1042-1046
Author(s):  
Any Guntarti ◽  
Mustofa Ahda ◽  
Aprilia Kusbandari ◽  
Faradita Natalie
Keyword(s):  
Principal Component Analysis ◽  
Fourier Transform ◽  
Quantitative Analysis ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Soxhlet Apparatus ◽  
Infrared Spectral ◽  
Ftir Spectrophotometry ◽  
Reference Samples

Meat-based foods such as beef corned became one of the targets of counterfeiting with pork because relatively cheaper. This becomes a serious problem for Muslims, especially in Indonesia. One method that can be used to detect fat was Fourier transform infrared (FTIR) spectrophotometry. The purpose of this study was to quantitatively analyze and a group of corned beef and corned pork using FTIR spectrophotometry combined with chemometrics. Reference samples corned pork-beef made of 7 various concentration (0%, 25%, 35%, 50%, 65%, 75%, 100%) and 6 product samples purchased in the Umbulharjo, Yogyakarta. Extraction was carried out by the soxhlet apparatus using n-hexane technical solvent for 4 – 5 hours at 69 – 70 °C. Fat analyzed using FTIR spectrophotometry for generating infrared spectral data then processed with Partial least square (PLS) chemometrics for quantitative analysis and Principal component analysis (PCA) for grouping. Results of quantitative analysis chemometrics PLS, selected areas fingerprints for analysis corned pork-beef was 1180 – 730 cm-1 with R2 0.9833; RMSEC 2.06%; RMSEP 1.65% and RMSECV 2.22%. The results of PCA showed groupings in different quadrants between corned pork 100% and corned beef 100%. Results showed that FTIR spectrophotometry combined with chemometrics can be used for quantitative analysis and grouping of pork corned and beef corned on the market but it can not identify pork in corned after choking process.

scholarly journals Fault identification for chiller sensor based on partial least square method

2021 ◽  
Vol 233 ◽  
pp. 03057
Author(s):  
Bang Wu ◽  
Yunpeng Hu ◽  
Chuanhui Zhou ◽  
Guaiguai Chen ◽  
Guannan Li
Keyword(s):  
Principal Component Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Principal Component ◽  
Component Analysis ◽  
Fault Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Fault Identification ◽  
Least Squares Regression

Sensor failures can lead to an imbalance in heating, ventilation and air conditioning (HVAC) control systems and increase energy consumption. The partial least squares algorithm is a multivariate statistical method, compared with the principal component analysis, its compression factor score contains more original data characteristic information, therefore, partial least squares have greater potential for fault diagnosis than the principal component analysis. However, there are few studies based on partial least squares in the field of HVAC. In order to introduce partial least squares into the field, based on the partial least squares fault detection theory, a fault analysis method suitable for this field is proposed, and the RP1403 data published by ASHARE was used to verify this method. The results show that on the basis of selecting the appropriate number of principal components, partial least squares have the ability to diagnose the fault of the chiller sensor. With the known fault source, partial least squares regression, a method with better data reconstruction accuracy than principal component analysis, is used to repair the fault. Finally, the purpose of fault identification can be achieved.

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