scholarly journals ANALISIS STRUKTUR GAJI TERHADAP KEPUASAN KERJA, KOMITMEN ORGANISASIONAL DAN TURNOVER INTENTION (STUDI KASUS PADA RUMAH SAKIT UMUM DAERAH AL-MULK KOTA SUKABUMI)

2020 ◽  
Vol 11 (1) ◽  
pp. 75
Author(s):  
Yathestha Yoga Dwi Rahestha ◽  
Budi Hartono ◽  
Gofur Ahmad
Keyword(s):  
Path Analysis ◽  
Turnover Intention ◽  
Structural Equation ◽  
Structural Equation Models

Dampak dari struktur gaji merupakan fenomena yang sering terjadi pada sebuah perusahaan dimana karyawan memiliki keinginan keluar dari perusahaan karena rendahmya kegairahan kerja karyawan serta ketidakpuasan karyawan saat bekerja yang dapat mengakibatkan kondisi pekerjaan yang tidak nyaman sehingga akan terjadi turnover intention yang tinggi. Penelitian ini bertujuan untuk menganalisis pengaruh stuktur gaji teradap kepuasan kerja, komitmen organisasional dan turnover intention. Metode penelitian ini adalah penelitian kuantitatif dengan model SEM (Structural Equation Models) dengan tehnik analisis jalur (path analysis). Penelitian ini dilakukan pada Agustus-Oktober 2019 pada 118 sampel karyawan RSUD Al-Mulk Kota Sukabumi dengan teknik sampling jenuh. Hasil penelitian didapatkan bahwa struktur gaji berpengaruh sebesar 0,58 terhadap kepuasan kerja, sebesar 0,11 terhadap komitmen oganisasional dan sebesar 0,11 terhadap turnover intention. Kepuasan kerja berpengaruh sebesar 0,51 terhadap komitmen organisasional dan berpengaruh sebesar -0,34 terhadap turnover intention. Komitmen organisasional berpengaruh sebesar -0,23 terhadap turnover intention. Kepuasan kerja, komitmen organisasional, dan turnover intention secara simultan berpengaruh signifikan terhadap struktur gaji. Pihak rumah sakit agar memperhatikan permasalahan terkait struktur gaji yang ada untuk meminimalisir terjadinya turnover intention pada karyawan.

scholarly journals ShareSEM: Example and Template R Scripts for SEM, Bayesian, and More

2019 ◽  
Author(s):  
Daniel John Phipps
Keyword(s):  
Path Analysis ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Bayesian Modelling ◽  
Meta Analyses

The ShareSEM project is a simple depository of R scripts for running structural equation models and Bayesian modelling in R. The scripts are designed such that, if measurement items are named consistently, models can be ran with no extra scripting. If models or items differ from the template file, the scripts are designed to be easily adaptable. Bayesian path analysis scripts are also available, with pre-specified priors from meta-analyses of the models.

scholarly journals SELECTION OF VEGETATIVE AND GENERATIVE CHARACTERS OF ARABICA COFFEE BY USING SEQUENTIAL PATH ANALYSIS AND STRUCTURAL EQUATION MODELS

2020 ◽  
Vol 20 (2) ◽  
pp. 77 ◽  
Author(s):  
EDI WARDIANA ◽  
DIBYO PRANOWO
Keyword(s):  
Path Analysis ◽  
Positive Selection ◽  
Structural Equation ◽  
Selection Criteria ◽  
Structural Equation Models ◽  
Arabica Coffee ◽  
Coffee Plants ◽  
Generative Phase ◽  
Observation Method ◽  
Selection Of

<p>ABSTRACT<br />Interrelations among vegetative, generative and yield characters in<br />coffee plantation is important in breeding and selection programs.<br />Interrelationships among these characters are the causal model and it can<br />be analyzed by Sequential Path Analysis (SPA). This research was carried<br />out at Pakuwon Experimental Station located at 450 m above sea level, in<br />Latosol soil type with B type of climate, from December 2010 to April<br />2012. The objectives of this research is to analyze the direct or indirect<br />influence of several vegetative and generative characters on yield<br />characters of Arabica coffee through the application of SPA and Structural<br />Equation Models (SEM). The observation method with systematic<br />sampling on 40 Arabica coffee plants of Kartika 1 and Kartika 2 varieties<br />were used in this study. The results showed that the number of cherries of<br />Arabica coffee var. Kartika 1 and 2 population in Pakuwon Experimental<br />Station were affected directly by generative and indirectly by vegetative<br />characters. Plant height and stem girth can be used as positive selection<br />criteria for high yielding at vegetatite phase, while the character of width<br />canophy can be used as negative selection criteria. In generative phase, the<br />character of quantity of productive branches and the amount of berries and<br />flower cluster can be used as positive selection criteria.<br />Keywords: Coffea arabica, selection, vegetative, generative, yield,<br />sequential path analysis, structural equation models</p><p>ABSTRAK<br />Keterkaitan antara karakter vegetatif, generatif dan hasil pada<br />tanaman kopi merupakan hal penting dalam program pemuliaan dan<br />seleksi. Model saling keterkaitan antar karakter tersebut adalah model<br />sebab-akibat dan dapat dianalisis melalui Analisis Lintasan Bertahap<br />(ALB). Penelitian ini dilakukan di Kebun Percobaan Pakuwon, pada<br />ketinggian tempat 450 m dpl, jenis tanah Latosol, dan tipe iklim B, mulai<br />bulan Desember 2010 sampai April 2012. Tujuan penelitian adalah untuk<br />menganalisis beberapa karakter vegetatif dan generatif yang berpengaruh<br />terhadap karakter hasil tanaman kopi Arabika melalui penggunaan ALB<br />dan Model Persamaan Struktural (MPS). Metode yang digunakan adalah<br />metode observasi dengan teknik penentuan pohon contoh secara sistematis<br />sebanyak 40 tanaman kopi Arabika varietas Kartika 1 dan Kartika 2. Hasil<br />penelitian menunjukkan bahwa jumlah buah pada populasi kopi Arabika<br />varietas Kartika 1 dan 2 di KP Pakuwon dipengaruhi secara langsung oleh<br />karakter generatif dan secara tidak langsung oleh karakter vegetatif. Pada<br />fase vegetatif, karakter tinggi tanaman dan diameter batang dapat<br />digunakan sebagai kriteria seleksi positif untuk produksi tinggi,<br />sedangkan karakter lebar tajuk dapat digunakan sebagai kriteria seleksi<br />negatif. Pada fase generatif, karakter jumlah cabang produktif serta jumlah<br />klaster buah dan bunga dapat digunakan sebagai kriteria seleksi positif.<br />Kata kunci: Kopi arabika, seleksi, vegetatif, generatif, hasil, analisis<br />lintasan bertahap, model persamaan struktural</p>

Ammonia elimination processes in stabilisation and high-rate algal pond systems

1995 ◽  
Vol 31 (12) ◽  
pp. 303-312 ◽  
Author(s):  
E. Gómez ◽  
C. Casellas ◽  
B. Picot ◽  
J. Bontoux
Keyword(s):  
Path Analysis ◽  
Total Nitrogen ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Ammonia Concentration ◽  
High Rate ◽  
Coefficient Of Determination ◽  
Nitrogen Input ◽  
Analysis Technique ◽  
Methodological Considerations

Stabilisation pond (SP) and high-rate algal pond (HRAP) wastewater treatment systems are based on the same processes, but differ in their capacity to remove ammonia. This study analyzes the processes concerning ammonia elimination. The different factors studied are: (i) light irradiance and temperature, (ii) phytoplankton uptake, and (iii) chemical characteristics affecting ammonia concentration. The variables relevant to these processes have been used in path analysis studies. Different variables describing the studied processes have been used to quantify the different phenomena. A conceptual model has been developed, and applied to each pond. Path analysis technique has been applied. It is a causal modelling technique. The evaluation of causal models involves theoretical, methodological and statistical analysis. Theoretical considerations have been defined in the list of the processes studied. Methodological considerations involve the variable measurements on a defined time-scale. The statistical aspect consists of the evaluation of structural equation models. The results of these studies show that the principal phenomena affecting ammonia in SP systems are temperature, pH, and total nitrogen input. In HRAP systems ammonia variability is directly linked to pH, temperature, nitrite and total nitrogen input, and indirectly linked to chlorophyll a concentration and pH. The percentage of observed variability given by the models (R2 =coefficient of determination) ranges between 46% and 60.8%.

An Introduction to Path Analysis Modeling Using LISREL

2011 ◽  
pp. 57-81
Author(s):  
Sean B. Eom
Keyword(s):  
Path Analysis ◽  
Statistical Models ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Statistical Tools ◽  
Multivariate Statistical ◽  
Wide Range ◽  
Confirmatory Factor ◽  
E Learning ◽  
Research Stream

Over the past decades, there has been a wide range of empirical research in the e-learning literature. The use of multivariate statistical tools has been a staple of the research stream throughout the decade. Path analysis modeling is part of four related multivariate statistical models, including regression, path analysis, confirmatory factor analysis, and structural equation models. This chapter focuses on path analysis modeling for beginners using LISREL 8.70. Several topics covered in this chapter include foundational concepts, assumptions, and steps of path analysis modeling. The major steps in path analysis modeling explained in this chapter consist of specification, identification, estimation, testing, and modification of models.

scholarly journals Mediating effects of nurses ‘personal and organizational values between organizational commitment and turnover: Cross-sectional study

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258387
Author(s):  
Wentong Wei ◽  
Mengxin Gan ◽  
Yanhui Liu ◽  
Mengyu Yang ◽  
Jingying Liu
Keyword(s):  
Organizational Commitment ◽  
Turnover Intention ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Multivariate Regression Analysis ◽  
Organizational Values ◽  
Mediating Effect ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
The Impact

Background The values of individuals and organizations are the core factors driving and guiding nurses’ decision-making and actions. Previous studies mainly focused on the impact of organizational commitment and other influencing factors on turnover intention. Aim To explore the mediating effect of personal and organizational values matching the relationship between organizational commitment and turnover intention of nursing staff. Methods A cross-sectional survey of 490 subjects in four tertiary hospitals in Tianjin was conducted by convenient sampling. Multivariate regression analysis and structural equation models were used to test each hypothesis. Results The results showed that there is a negative correlation between personal and organizational values, organizational commitment and turnover intention, and personal and organizational values played an indirect intermediary role between organizational commitment and turnover intention. Conclusions Organizational commitment reduces nurses’ turnover intention indirect through personal and organizational values paths. Leaders can improve nurses’ values as members of the organization, so as to participate in their own work more actively. Implications for nursing management Managers should effectively reduce the turnover rate and stabilize the nursing team by improving the organizational commitment and personal and organizational values of clinical nurses.

Perceived Organizational Support, Organizational Identification, and Employee Outcomes

2010 ◽  
Vol 9 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Martin R. Edwards ◽  
Riccardo Peccei
Keyword(s):  
National Health Service ◽  
Organizational Support ◽  
Organizational Identification ◽  
Turnover Intention ◽  
Structural Equation ◽  
Perceived Organizational Support ◽  
Structural Equation Models ◽  
Uk National Health Service ◽  
Organizational Involvement ◽  
Positive Effect

This study involves a multifoci analysis of antecedents and outcomes of organizational identification (OID), within a dual-organizational identity context. We investigate links between perceived organizational support (POS), OID, organizational involvement, and turnover intention with 736 employees from a UK National Health Service (NHS) Trust. Using Structural Equation Models (SEM), we analyzed models using the Trust and the NHS as organizational foci. With both Trust and NHS foci, POS had a positive effect on identification which, in turn, predicted both outcomes. Organizational support showed a direct and an indirect effect on outcomes through OID. Generally the effects were foci specific, though limited downward crossfoci effects were found.

scholarly journals Analisis Jalur dan Aplikasinya dalam Menentukan Faktor yang Mempengaruhi Derajat Kesehatan Balita di Sulawesi Selatan

2020 ◽  
Vol 3 (1) ◽  
pp. 64
Author(s):  
Wahidah Sanusi ◽  
S. Sukarna ◽  
Elma Selviana Darwis
Keyword(s):  
Health Status ◽  
Path Analysis ◽  
Pregnant Women ◽  
Direct Effect ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Path Model ◽  
Children Under Five ◽  
Under Five ◽  
South Sulawesi

Penelitian ini bertujuan untuk mengaplikasikan analisis jalur dan untuk mengetahui seberapabesarfaktor-faktor yang berpengaruhterhadapderajat kesehatan balita Di Sulawesi Selatan baiksecara pengaruh langsung maupun secara pengaruh tidak langsung Menganalisis model dan menginterpretasikan hasil. Data yang digunakan adalah data jumlah rekapitulasi derajat kesehatan balita di Provinsi Sulawesi Selatan tahun 2019. Variabel yang digunakan adalah Jumlahibuhamil 20-30 tahun (X1), Jumlahbalita yang mendapatkan ASI full 6 bulandari ibu yang tidak bekerja (X2), Kelainandalamkandungan (X3),Bayi yang terdampakgiziburuk pada ibuhamil yang usia 30-35 tahun(Y1), dan Bayi yang meninggaldalamkandungan (Y2). Penelitian ini menggunakan model dua persamaan jalur (two equation paths). Penelitian ini dimulai dari merumuskan persamaan model struktural, menghitung koefisien jalur secara simultan dan secara parsial, melakukan simulasi model menggunakan softwere SPSS 22, memaknai dan menyimpulkan. Hasil penelitian diperoleh model dua persamaan struktural;taraf signifikan (α)untuk hasil simulasi sebesar 5% atau 0,05; menjelaskan bahwa setiap model sub-struktur yang diuji secara simultan dan secara parsial memiliki pengaruh yang positif dan signifikan terhadapderajat kesehatan balita Di Sulawesi Selatan.Kata kunci: Analisis Jalur, two equation paths, direct effect, inderect effectThis study aims to apply path analysis and to determine how much the factors that influence the health status of children under five in South Sulawesi, both directly (direct effect) and indirectly (inderect effect). Analyze models and interpret the results. The data used is the data on the recapitulation of the health status of children under five in South Sulawesi Province in 2019. The variables used are the number of pregnant women 20-30 years (X1), the number of children under five who received full 6 months of breastfeeding from mothers who do not work (X2), in the womb (X3), babies who are affected by malnutrition in pregnant women aged 30-35 years (Y1), and babies who die in the womb (Y2). This study uses a two equation path model. This research starts from formulating structural model equations, calculating path coefficients simultaneously and partially, performing model simulations using SPSS 22 software, interpreting and concluding. The results of the study obtained two structural equation models; the significant level (α) for the simulation results is 5% or 0.05; explained that each sub-structure model tested simultaneously and partially had a positive and significant effect on the health status of children under five in South Sulawesi.Keywords: Path Analysis, two equation paths, direct effect, indirect effect

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