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.

Noniterative Estimation for the Multiple Battery Factor Analysis Model

1997 ◽  
Vol 24 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Michael W. Browne ◽  
Krishna Tateneni
Keyword(s):  
Factor Analysis ◽  
Analysis Model ◽  
Factor Analysis Model

A Factor Analysis model of the instrumented Timed Up and Go test for physical capability assessment

2018 ◽  
Vol 66 ◽  
pp. S11-S12 ◽  
Author(s):  
A. Coni ◽  
S. Mellone ◽  
M. Colpo ◽  
S. Bandinelli ◽  
L. Chiari
Keyword(s):  
Factor Analysis ◽  
Analysis Model ◽  
Timed Up And Go ◽  
Factor Analysis Model ◽  
Physical Capability

scholarly journals Non-negative Independent Factor Analysis for single cell RNA-seq

2020 ◽  
Author(s):  
Weiguang Mao ◽  
Maziyar Baran Pouyan ◽  
Dennis Kostka ◽  
Maria Chikina
Keyword(s):  
Factor Analysis ◽  
Single Cell ◽  
Matrix Factorization ◽  
Component Analysis ◽  
Computational Techniques ◽  
Cell Type ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
Type Identity ◽  
Wide Range

AbstractMotivationSingle cell RNA sequencing (scRNA-seq) enables transcriptional profiling at the level of individual cells. With the emergence of high-throughput platforms datasets comprising tens of thousands or more cells have become routine, and the technology is having an impact across a wide range of biomedical subject areas. However, scRNA-seq data are high-dimensional and affected by noise, so that scalable and robust computational techniques are needed for meaningful analysis, visualization and interpretation. Specifically, a range of matrix factorization techniques have been employed to aid scRNA-seq data analysis. In this context we note that sources contributing to biological variability between cells can be discrete (or multi-modal, for instance cell-types), or continuous (e.g. pathway activity). However, no current matrix factorization approach is set up to jointly infer such mixed sources of variability.ResultsTo address this shortcoming, we present a new probabilistic single-cell factor analysis model, Non-negative Independent Factor Analysis (NIFA), that combines features of complementary approaches like Independent Component Analysis (ICA), Principal Component Analysis (PCA), and Non-negative Matrix Factorization (NMF). NIFA simultaneously models uni- and multi-modal latent factors and can so isolate discrete cell-type identity and continuous pathway-level variations into separate components. Similar to NMF, NIFA constrains factor loadings to be non-negative in order to increase biological interpretability. We apply our approach to a range of data sets where cell-type identity is known, and we show that NIFA-derived factors outperform results from ICA, PCA and NMF in terms of cell-type identification and biological interpretability. Studying an immunotherapy dataset in detail, we show that NIFA identifies biomedically meaningful sources of variation, derive an improved expression signature for regulatory T-cells, and identify a novel myeloid cell subtype associated with treatment response. Overall, NIFA is a general approach advancing scRNA-seq analysis capabilities and it allows researchers to better take advantage of their data. NIFA is available at https://github.com/wgmao/[email protected]

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI EFEKTIVITAS KEMITRAAN DALAM PENGEMBANGAN KAWASAN AGROWISATA CIHIDEUNG BANDUNG BARAT – JAWA BARAT

AdBispreneur ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 67
Author(s):  
Candradewini Candradewini
Keyword(s):  
Random Sampling ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Target Population ◽  
Field Studies ◽  
Exploratory Analysis ◽  
Dominant Factor ◽  
Average Score ◽  
Joint Ownership ◽  
Partnership Effectiveness

The tourism business is one of the mainstays of West Bandung Regency. One of them is the Cihideung agro-tourism area. This potential agro-tourism area requires cooperation from various related parties in order to develop better. This study aims to determine and analyze the factors that affect the partnership effectiveness in developing the Cihideung agro-tourism area. This research method uses a quantitative approach to the type of survey research. The target population in this study are the parties who partner in the development of the Cihideung agro-tourism area, West Bandung Regency. The sample size in this study was 45 people obtained by the simple random sampling technique. Data collection techniques by means of field studies, interviews and literature studies. The data were processed using Exploratory Analysis Factor (EFA). The results showed that the factors that affect the partnership effectiveness in developing the agro-tourism area of Cihideung, West Bandung Regency are Vision and Communication, Commitment and Partners, Vision of Partnership, Data Integration, Incentives and Information, Results and Progress, Joint Ownership and Outcome Accountability. A total of 2 factor points from which must be reduced from 26 factor points so as to produce 24 factor points that are truly dominant and form the effectiveness of the partnership. Overall, the partnership effectiveness was in the high category with an average score of 3.95. Vision and Communication factor is the most dominant factor, which is equal to 40.142%. Bisnis pariwisata merupakan salah satu andalan Kabupaten Bandung Barat. Salah satunya adalah kawasan agrowisata Cihideung. Kawasan agrowisata potensial ini memerlukan kerjasama dari berbagai pihak terkait agar berkembang lebih baik. Penelitian ini bertujuanuntuk mengetahui dan menganalisis faktor-faktor yang mempengaruhi efektivitas kemitraan pengembangan kawasan agrowisata Cihideung. Metode penelitian ini menggunakan pendekatan kuantitatif dengan jenis penelitian survei. Target populasi dalam penelitian ini ialah para pihak yang bermitra dalam pengembangan kawasan agrowisata Cihideung Kabupaten Bandung Barat. Ukuran sampel pada penelitian ini adalah 45 orang yang didapatkan dengan teknik Simple Random Sampling. Teknik pengumpulan data dengan cara studi lapangan, wawancara dan studi literatur. Data diolah menggunakan Exploratory Analysis Factor (EFA). Hasil penelitian menunjukkan bahwa faktor-faktor yang mempengaruhi efektivitas kemitraan pengembangan kawasan agrowisata Cihideung Kabupaten Bandung Barat adalah Visi dan Komunikasi, Komitmen dan Mitra, Visi Kemitraan, Integrasi Data, Insentif dan Informasi, Hasil dan Kemajuan, Kepemilikan Bersama dan Akuntabilitas Hasil. Sebanyak 2 butir faktor dari yang harus direduksi dari 26 butir faktor sehingga menghasilkan 24 butir faktor yang benar-benar dominan dan mempengaruhi efektivitas kemitraan. Secara keseluruhan, efektivitas kemitraan berada dalam kategori tinggi dengan nilai rata-rata sebesar 3,95. Faktor Visi dan Komunikasi merupakan faktor yang paling dominan yaitu sebesar 40,142%.

scholarly journals The Application of Value Clarification Technique (VCT) Learning Model on Students’ Characters of Adiwiyata Program

2018 ◽  
Vol 7 (3) ◽  
pp. 265-272
Author(s):  
Kumala Hidayatiningtyas ◽  
Retno Sri Iswari ◽  
Sri Sukaesih
Keyword(s):  
Sampling Technique ◽  
Simple Random Sampling ◽  
Learning Model ◽  
Shared Responsibility ◽  
Coefficient Of Determination ◽  
Dominant Factor ◽  
Control Group ◽  
Strong Positive Correlation ◽  
Control Group Design ◽  
Environmental Care

The concrete success of Adiwiyata program is a self-awareness of the surrounding environment in controlling undisciplined habit and taking action as a shared responsibility. The character building using Value Clarification Technique (VCT) learning model becomes a teacher’ alternative in emphasizing students’ activity. This study aimed at analyzing the effect of VCT learning on students’ characters through population density material and humans’ role in the environmental management. The research used quasi-experimental design with nonequivalent posttest only control group design. The population of this study was a total of 293 students of class VII in SMPN 2 Jati Kudus in the academic year of 2016/2017. The sampling used simple random sampling technique. The data of this research were characters of discipline, responsibility, and environmental care obtained from psychological scales instrument and observation sheets, implementation sheets of VCT models, and responses questionnaires of students and teacher. The data analysis techniques used t-test, simple regression, correlation test, and coefficient of determination. The results showed that the VCT learning model had a strong positive correlation to the responsibility character and a moderate correlation to the discipline and environmental care character that could be generalized. Moreover, the results of the correlation analysis and coefficient of determination of VCT learning on students’ characters of discipline, responsibility, and environmental care were 33.2%, 38.3%, and 22.7% respectively. These results indicated that there was another dominant factor on students’ characters.

scholarly journals The influence application of Information Technology and Competence on Employee Productivity through Job Satisfaction in the Civil Apparatus at Hasanuddin University

2020 ◽  
Vol 2 (3) ◽  
pp. 92-99
Author(s):  
Muhammad Erfan ◽  
Mahlia Muis ◽  
Andi Ratna Sari Dewi
Keyword(s):  
Job Satisfaction ◽  
Information Technology ◽  
Sampling Method ◽  
Work Productivity ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Measurement Scale ◽  
Employee Productivity ◽  
The Status ◽  
Minimum Number

This study aims to analyze (i) the effect of information technology variables on job satisfaction; (ii) the effect of competency variables on job satisfaction; (iii) the effect of information technology variables on work productivity; (iv) the effect of competency variables on work productivity; (v) the effect of job satisfaction variables on work productivity; (vi) the influence of information technology variables on work productivity through job satisfaction variables; and (vii) the effect of competency variables on work productivity through job satisfaction variables. The quantitative approach is used to test and analyze the factors that influence job satisfaction and work productivity. Research location at Hasanuddin University, Makassar City. The population in this study were Unhas employees with the status of ASN (State Civil Apparatus) as many as 935 people. The sampling method uses probability sampling with a simple random sampling technique. Withdrawing the number of samples using the Slovin formula, which produces 90 people as a minimum number. Data collection techniques using a questionnaire with a measurement scale used is a Likert scale with five components. Data analysis techniques in this study used path analysis. The results showed that information technology and competency variables significantly influence job satisfaction and work productivity. Information technology and competence have a significant effect on work productivity through job satisfaction variables. All hypotheses are accepted and supported by previous research.

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