scholarly journals Structural model of sandalwood (Santalum album) regeneration in the forest and community plantation in Timor Island, Indonesia

2018 ◽  
Vol 2 (2) ◽  
pp. 41-47
Author(s):  
YOSEPH NAHAK SERAN ◽  
SUDARTO SUDARTO ◽  
LUCHMAN HAKIM ◽  
ENDANG ARISOESILANINGSIH
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Model ◽  
Diversity Index ◽  
Abiotic Factors ◽  
Partial Least Square ◽  
Index Number ◽  
Santalum Album ◽  
Climate Data ◽  
Host Diversity

Seran YN, Sudarto, Hakim L, Arisoesilaningsih E. 2018. Structural model of sandalwood (Santalum album) regeneration in the forest and community plantation in Timor Island, Indonesia. Trop Drylands 2: 41-47. Sandalwood (Santalum album L.) is a very important forest product in NTT, an endemic species in the world with a high economic value.. This study aimed to identify and produce a structural model of sandalwood regeneration in both the forests and the community plantation in the Regency of Timor Tengah Selatan (TTS) and Timor Tengah Utara (TTU). The method used in this research was vegetation analysis by purposive sampling method on 8 observation stations with 87 plots. The plot size was 20x20 m2 (trees), 10x10 m2 (poles), 5x5 m2 (saplings), and 2x2 m2 (seedlings). Data observed in the field included the mean sandalwood population size in the forms of trees, poles, saplings and seedlings phase, vegetation data in sandalwood habitat which included tree wealth index, diversity index, number of individuals and sandalwood host diversity index data. Geographical factors such as altitude and slope, and abiotic factors such as soil organic matter, soil pH and soil conductivity were also recorded. Climate data included the number of dry months and rainfall. Sandalwood regeneration data included sandalwood vitality, pests and diseases and the number of seeds. Secondary data included climate data (ten years time) obtained from BMKG of NTT Province in Kupang. These data were used as the indicators of the latent variables (six variables) which consisted of geography, soil, climate, population, vegetation, and regeneration. Obtained data were subjected to both descriptive analysis and multivariate statistics with structural modeling of Warp Partial Least Square (WarpPLS 6.0). The results showed that most of the proposed indicators significantly influenced the compiled six latent variables except the host diversity. Some indicators significantly or highly significantly affected the latent variable with 15 indicators that significantly composed the latent variable. The resulting structural model is very relevant and has a relevance value of Q2 prediction of 96,65% so that the structural model proposed in this study has very relevant and high predictive value on factors that influence sandalwood regeneration. Therefore, this model is feasible or appropriate to be used as recommendations in the framework of sandalwood development in the forest and the community plantation in the West part of Timor Island, Nusa Tenggara Timur.

MODELING OF SEA SURFACE TEMPERATURE BASED ON PARTIAL LEAST SQUARE - STRUCTURAL EQUATION

2021 ◽  
Vol 14 (2) ◽  
pp. 170-182
Author(s):  
Miftahuddin Miftahuddin ◽  
Retno Wahyuni Putri ◽  
Ichsan Setiawan ◽  
Rina Suryani Oktari
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Model ◽  
Partial Least Square ◽  
Least Square ◽  
Sea Surface ◽  
Equation Modeling

Variability of Sea Surface Temperature (SST) is one of the climatic features that influence global and regional climate dynamics. Missing data (gaps) in the SST dataset are worth investigating since they may statistically alter the value of the SST change. The partial least square-structural equation modeling (PLS-SEM) approach is used in this work to estimate the causality relationships between exogenous and endogenous latent variables. The findings of this study, which are significant indicators that have a loading factor value > 0.7 are as follows: i) sea surface temperature (oC) as a measure of the latent variable changes in SST, ii) wind speed (m/s) and relative humidity (%) as a measure of the latent variable of weather, and iii) air temperature (oC), long-wave solar radiation (w/m2) as a measure of climate latent variables. The size of the Rsquare value is influenced by the number of gaps. The results of the boostrapping show that the latent variables of weather and climate have a significant effect on changes in SST which are indicated by the value of tstatistics > ttabel. The structural model obtained Changes in SST (η) = -0.330 weather + 0.793 climate + ζ. The model shows that the weather has a negative coefficient, which means that the better the weather conditions, the lower the SST changes. Climate has a positive coefficient, which means that the better the climate, the SST changes will also increase. Rising sea surface temperatures caused by an increase in climate can lead to global warming, impacting El-Nino and La-Nina events.

scholarly journals ANALISIS KEKAMBUHAN ORANG DENGAN SKIZOFRENIA MENGGUNAKAN METODE PARTIAL LEAST SQUARE STRUCTURAL EQUATION MODEL

2019 ◽  
Vol 8 (3) ◽  
pp. 222
Author(s):  
IRA INDRIYANTI ◽  
G.K. GANDHIADI ◽  
MADE SUSILAWATI
Keyword(s):  
Family Support ◽  
Structural Equation Model ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Model ◽  
Medication Compliance ◽  
Equation Model ◽  
Partial Least Square ◽  
Least Square

Schizophrenia is a psychotic disorder characterized by major disorders in the mind and emotions. People with schizophrenia (ODS) can experience recurrence if they do not receive proper care. The latent variable used in this study was ODS reccurence. One method that can determine the relationship between latent variables and latent variables with the indicator is the partial least square structural equation model (PLS-SEM). This study was conducted to see how the structural model of ODS recurrence data and to know the factors that most influence ODS recurrence. The results of this study concluded that the resulting model was good enough with a large R-square value of 0.8577, but not all variables used in this study had a significant effect on ODS recurrence. ODS recurrence is significantly influenced by family support and community social support variables. While medication compliance and physician control regularity will not have a significant effect without family support. The worse treatment of families and communities around ODS recurrence will occur more often.

scholarly journals FAKTOR-FAKTOR PENENTU PERILAKU GURU SMP MENGGUNAKAN TEKNOLOGI DALAM PEMBELAJARAN ONLINE: STUDI KASUS DI PROVINSI RIAU

2021 ◽  
Vol 22 (2) ◽  
pp. 123-133
Author(s):  
Defrizal Hamka ◽  
Neng Sholihat
Keyword(s):  
Online Learning ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Partial Least Square ◽  
Least Square ◽  
Influential Factor ◽  
Equation Modeling ◽  
Purposive Sampling ◽  
Facility Conditions

The purpose of this research is to investigate factors that influence the intent of behavior using technology in online learning. The study uses structural equation modeling using a partial least square approach to test the hypotheses. Respondents selected using purposive sampling, and the questionnaires were distributed through online surveys and received a response of 96 respondents. Results show that latent variables, performance expectations, business expectations, and facility conditions have a positive and significant relationship with the intent of individual behaviour in the use of technology in online learning. The latent variable "condition facility" is the most influential factor. This research provides an important overview and understanding for policymakers in designing frameworks to pay attention to facility conditions. Further research is suggested in the future covering samples from various provinces in Indonesia. This study adds to the literature primarily on factors affecting behavioral intent to use technology in online learning. Tujuan dari penelitian ini adalah untuk menganalisis faktor-faktor yang mempengaruhi niat perilaku guru menggunakan teknologi dalam pembelajaran online. Penelitian ini menggunakan pemodelan persamaan struktural dengan menggunakan pendekatan partial least square untuk menguji hipotesis. Berdasarkan purposive sampling, kuesioner disebarkan melalui survei online dan mendapat tanggapan dari 96 responden. Hasil penelitian menunjukkan bahwa variabel laten, ekspektasi kinerja, ekspektasi usaha, dan kondisi fasilitas memiliki hubungan positif dan signifikan dengan niat perilaku individu dalam penggunaan teknologi dalam pembelajaran online. Variabel laten “fasilitas kondisi” merupakan faktor yang paling berpengaruh. Penelitian ini memberikan gambaran dan pemahaman penting bagi pembuat kebijakan dalam merancang kerangka kerja untuk memperhatikan kondisi fasilitas. Penelitian lebih lanjut disarankan di masa depan mencakup sampel dari berbagai provinsi di Indonesia. Studi ini menambah literatur terutama pada faktor-faktor yang mempengaruhi niat perilaku untuk menggunakan teknologi dalam pembelajaran online.

Logistics performance collaboration strategy and information sharing with logistics capability as mediator variable (study in Gafeksi East Java Indonesia)

2019 ◽  
Vol 36 (8) ◽  
pp. 1301-1317
Author(s):  
Indro Kirono ◽  
Armanu Armanu ◽  
Djumilah Hadiwidjojo ◽  
Solimun Solimun
Keyword(s):  
Information Sharing ◽  
Latent Variables ◽  
Latent Variable ◽  
Business Performance ◽  
Positive Impact ◽  
Partial Least Square ◽  
Least Square ◽  
Content Type ◽  
Strategic Role ◽  
Research Populations

Purpose The purpose of this paper is to analyze the effect of collaboration, capability and information sharing (IS) on logistic performance, the effect of collaboration and IS on capabilities, the effect of collaboration on logistic performance through capabilities, the influence of IS on logistic performance through capabilities and the effect of logistics capabilities on logistics performance. Design/methodology/approach This study uses a quantitative approach and is included in explanatory research. This research uses cross section research design. The research populations are all companies incorporated in GAFEKSI (Joint Forwarder and Expedition Indonesia) of East Java. Sampling in this research is by using a purposive sample. The sample of this study amounted to 47 forwarder and expedition companies. Data analysis method used is partial least square. Findings Collaboration has a positive impact on capabilities (CAP); capability (LOC) positive impact on logistic performance; collaboration does not directly affect the logistics performance; and construct capabilities (LOC) is the mediation of IS in building business logistics performance. Increasing the intensity of IS has no direct contribution to increased flexibility, and collaboration is driven by partnership and network, whereas CT (trust) can be ignored, as it is not proven to make a dominant contribution to collaboration. Originality/value The novelty of this research is found in the strategic role of capabilities as the dominant latent variable in building business performance of logistic companies. This study finds dual mediation, where both mediations are expressed as full mediation, because the direct effect of mediator latent variables is significant (Little et al., 2010; Hair et al., 1995).

scholarly journals Modeling Academic Performance of the Students by using Partial Least Square

2020 ◽  
Vol 8 (5) ◽  
pp. 5438-5443
Keyword(s):  
Academic Achievement ◽  
Socioeconomic Status ◽  
School Environment ◽  
Latent Variables ◽  
Latent Variable ◽  
Partial Least Square ◽  
Least Square ◽  
Learning Motivation ◽  
Inner Model ◽  
Almost All

This study aims to model the relationship between predictor variables consisting of learning motivation (LM), parents' socioeconomic status (SS), and school environment (SE) which are all latent variables to academic achievement (AC) which are not latent variables. Modeling is done by the method of partial least square (PLS) which is expected to explore the various effects found in the inner model and also confirm the questionnaire items forming the latent variables. With a real level of 5%, almost all loading values on each latent variable are significant. Likewise, a simple linear relationship consisting of 5 models has a coefficient that has a significant effect. The influence of learning motivation (LM), parents' socioeconomic status (SS), school environment (SE) on academic achievement are 0.270, 0.249, and 0.320, respectively. while learning motivation (LM), socioeconomic status of parents (SS) contributing to academic achievement (AC) were 17.7% and 3.13%, respectively..

scholarly journals ANALISIS KEPUASAN DAN LOYALITAS PELANGGAN DALAM PEMESANAN TIKET PESAWAT SECARA ONLINE MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (PLS)

2018 ◽  
Vol 7 (4) ◽  
pp. 361-372
Author(s):  
Trisnawati Gusnawita Berutu ◽  
Abdul Hoyyi ◽  
Sugito Sugito
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Service Providers ◽  
Web Design ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Internet Service ◽  
Access Security

Technology advances are bring rapid changes, thus bringing the world to the information society. From this technological progress thus e-commerce emerged, as a means to meet the needs of goods and services through internet access (online). This is what the airlines utilized by cooperating with various internet service providers (online), to provide convenience and comfort of airplane passengers in buying tickets without having to come directly to the place and through intermediaries. To provide the best service, need to know what factors that influence customer satisfaction in ordering airline tickets online. Appropriate modeling for this problem using structural equation modeling, with Partial Least Square (PLS) approach. The PLS approach is chosen because it is not based on several assumptions, one of these is the normal multivariate assumption. In this research, the exogenous latent variables used are performance, access, security, sensation, information, and web design, while the endogenous latent variables are satisfaction and loyalty. Based on the results of the analysis it can be concluded that the latent variables of access, security, sensation, information, and web design are able to explain the latent satisfaction variable of 70.32% while the satisfaction latent variable is able to explain the latent variable of loyalty by 36.02%. 

scholarly journals Effect of Hybrid Resources on Management Outcomes Micro-Hydro Power Plants in Remote Areas

2020 ◽  
Vol 15 (6) ◽  
pp. 855-864
Author(s):  
Muhammad Yusan Naim ◽  
Henny Pramoedyo ◽  
Nuddin Harahab ◽  
Syarifuddin Nodjeng ◽  
Sudirman Syam
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Power Plants ◽  
Structural Model ◽  
Electrical Power ◽  
Hydro Power ◽  
Remote Areas ◽  
Manifest Variable ◽  
Hydropower Plants ◽  
Hydro Power Plants

The effect of developing hybrid resources on the management outcomes of micro-hydropower plants in remote areas has been studied and analyzed. The hybrid resource is a combination of two energy sources, such as water and solar energy, that operate together in meeting the needs of electrical power in Ambava Village, Tinondo Sub-district, East-Kolaka Regency, Southeast Sulawesi Province. This study has used a management model describing the relationship and influence of latent variables and their manifestation variables. Here, Confirmatory Factor Analysis (CFA) based Common-Pool-Resources (CPR) is the proper method of testing the structural model used. The results show that the Critics-Ratio (CR) and Standard Loading Factor (SLF) have fulfilled the expected value. The direct influence of the variable exogenous hybrid resources to the endogenous variable outcome of 0.213 has fulfilled the Gold of Fit criteria. Then, the direct impact of the most dominant latent variable is the operating dimension of the resource. At the same time, the indirect effect on the manifest variable is the increase in electricity reserve. Furthermore, the most dominant indirect impact of the hybrid resources latent variable is the benefit and cost dimensions, while the most dominant manifest variable is people's welfare savings.

Influence of justice, culture and love of money towards ethical perception on tax evasion with gender as moderating variable

2020 ◽  
Vol 23 (1) ◽  
pp. 245-266
Author(s):  
Dodik Ariyanto ◽  
Gusti Ayu Putu Weni Andayani ◽  
I. Gusti Ayu Made Asri Dwija Putri
Keyword(s):  
Tax Evasion ◽  
Latent Variables ◽  
Structural Model ◽  
Tax Compliance ◽  
Measurement Model ◽  
Partial Least Square ◽  
Ethical Perception ◽  
Ethical Perceptions ◽  
Content Type ◽  
Love Of Money

Purpose The purpose of this study is to evaluate the influence of justice, culture and love of money on ethical perceptions about tax evasion. As well as gender will strengthen the influence of justice, culture and love of money on ethical perceptions about tax evasion. Design/methodology/approach The primary data were collected and analyzed using a popular component-based model called partial least square (PLS). PLS consists of two sub-models, measurement model or outer model and structural model or inner model. The measurement model shows how real or observable variables are latent variables to be measured. While the structural model shows the level of estimation between latent or construct variables. Findings The statistical analysis showed that neither the coefficient of gender (moderating variable) nor the interaction between gender and the exogenous variable are significant. Solimun (2010) explained that such moderating variable is called homologizer moderation (potential moderation). Homologizer moderation refers to variable that may potentially become a moderating variable influencing relationship between predictor (exogenous) and dependant variable (endogenous). This variable has no interaction with predictors or can be said to be insignificant on the dependent variable. In this study, gender is a potential moderating variable (homologizer moderation). Gender can potentially become a moderating variable influencing relationship between justice, culture and love of money and ethical perception on tax evasion. Gender does not have interaction with justice, culture and love of money or significant influence toward ethical perception on tax evasion. Originality/value There are very few studies on tax evasion from an ethical point of view so this study is not only important but also interesting because it shows that tax evasion is a classic problem taking place in nearly all countries that apply taxation system; cultural difference results in different views on ethical perceptions on tax evasion (Basri, 2015); this study uses the local wisdom of Balinese people, namely, Tri Hita Karana and thus, this study becomes relatively new; justice is one of the non-economic variables of tax compliance behavior (Darmawan, 2012), so that the researcher is interested in conducting further research on the effect of justice toward ethical perception on tax evasion; there are very few studies discussing love of money (Hnisz et al., 2013); therefore, research on the effect of love of money toward ethical perception on tax evasion is of necessity and the findings of previous studies that are inconsistent. The researcher predicted that there are contingency factors that influence the relationship between justice, culture and love of money toward ethical perceptions on tax evasion. As suggested by Baridwan (2012), gender, the moderating variable in this study, refers to masculine and feminine character as a dimension of social culture; this study is carried out in the Tax Service Office (KPP Pratama) of Badung Utara because during the 2015 tax year, KPP Pratama Badung Utara was one of the KPPs in Bali DGT Regional Office which experienced a decline in realization of revenues and a sharp decline in growth.

Comparison of partial least square algorithms in hierarchical latent variable model with missing data

SIMULATION ◽  
2020 ◽  
Vol 96 (10) ◽  
pp. 825-839
Author(s):  
Hao Cheng
Keyword(s):  
Missing Data ◽  
Quantile Regression ◽  
Latent Variables ◽  
Latent Variable ◽  
Partial Least Square ◽  
Least Square ◽  
Latent Variable Model ◽  
Data Handling ◽  
Variable Model ◽  
Handling Methods

Missing data is almost inevitable for various reasons in many applications. For hierarchical latent variable models, there usually exist two kinds of missing data problems. One is manifest variables with incomplete observations, the other is latent variables which cannot be observed directly. Missing data in manifest variables can be handled by different methods. For latent variables, there exist several kinds of partial least square (PLS) algorithms which have been widely used to estimate the value of latent variables. In this paper, we not only combine traditional linear regression type PLS algorithms with missing data handling methods, but also introduce quantile regression to improve the performances of PLS algorithms when the relationships among manifest and latent variables are not fixed according to the explored quantile of interest. Thus, we can get the overall view of variables’ relationships at different levels. The main challenges lie in how to introduce quantile regression in PLS algorithms correctly and how well the PLS algorithms perform when missing manifest variables occur. By simulation studies, we compare all the PLS algorithms with missing data handling methods in different settings, and finally build a business sophistication hierarchical latent variable model based on real data.

scholarly journals ANALISIS TECHNOLOGY ACCEPTANCE MODEL PADA APLIKASI PLATFORM SHOPEE DENGAN PENDEKATAN PARTIAL LEAST SQUARE (STUDI KASUS PADA MAHASISWA UNIVERSITAS DIPONEGORO)

2021 ◽  
Vol 10 (3) ◽  
pp. 423-434
Author(s):  
Ovie Auliya’atul Faizah ◽  
Suparti Suparti ◽  
Abdul Hoyyi
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Equation Modeling ◽  
Acceptance Model

E-commerce refers to business transactions using digital networks such as the internet. Based on the rank on the Appstore and Playstore, Shopee places the first rank. In 2019, Shopee had 56 million visitors. Meanwhile, in the same year, it had 3,225 workers. The imbalance between the number of Shopee visitors and Shopee employees allows users to be disappointed with Shopee's services, but on the other hand, there are also many users who are happy with its services. With both positive and negative responses to the services provided by Shopee, this study analyzes the factors affecting the acceptance of Shopee Apps on students of Universitas Diponegoro Semarang. The analysis was based on the Technology Acceptance Model (TAM). It used the Structural Equation Modeling with the Partial Least Square (SEM-PLS) approach. The study used primary data obtained by distributing questionnaires to students of Universitas Diponegoro. The result showed 28 valid indicators, 5 deal inner models, and 8 significant pathways. All the causality between latent variables contained in the Technology Acceptance Model (TAM) have a positive and significant effect, it's just that the results of integrating trust variables on TAM, namely the latent variable between trust and interest in usage behavior, have no significant effect. 

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