Journals of Universitas Sangga Buana
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Machine Learning Approaches for Meta-Analytic Estimates of Important Predictors in Behavioral Science Studies: An Analysis of Cooperation in Social Dilemmas
No full textResearch in the social and behavioral sciences is accumulating at an exponential rate. One of the challenges facing scientists is how to quantitatively determine, in an unbiased manner, which predictors contribute the most to explaining variation in a specific phenomenon. To address these issues and improve the predictor importance estimation, we propose an enhanced grouped permutation feature importance (GPFI) method using a state-of-the-art ensemble machine learning regression model. A simulation study utilizing four artificial datasets demonstrated that the mean absolute percentage error of importance estimation was reduced to 5.0% with the proposed method compared to 30.0% with the conventional GPFI method. As an applied example, we utilized the Cooperation Databank to assess the relative importance of 106 predictors of cooperation, including parameters of the study’s experimental paradigm (e.g., group size, incentive structure, and repeated interaction) and sample characteristics (e.g., gender, age, and ethnicity), and found that the proposed technique was able to identify the top predictors of cooperation. These results clarify the implications of such information for understanding and promoting cooperation. The analytical methods developed in this study can be applied across the social and behavioral sciences, especially in well-developed topics that involve accumulated empirical studies
Artificial Intelligence Technology Adoption Decision-Making Process in MSMEs Marketing Practices
Get PDFArtificial intelligence (AI) is a technology that transforms various aspects of life, including business marketing practices. This study aims to describe the decision-making process in adopting AI among MSMEs in DKI Jakarta and Greater Bandung. A descriptive quantitative method was used with descriptive analysis and cross-tabulation. A total of 119 MSME respondents who are digitalized and familiar with AI were analyzed to map the AI adoption process. The results show that most respondents have adopted AI, especially micro-businesses in the culinary sector. Respondents demonstrated basic knowledge of AI, along with personal characteristics and communication habits that support adoption. AI is perceived to offer relative advantages, compatibility with values and needs, ease of trial, and observable results. However, some respondents still find AI difficult to use. Improving AI training, digitalization efforts, and supportive policy-making are needed to strengthen the digital ecosystem for MSMEs
Fringe Benefits Provision, Payroll Policy, and Its Influence on Tax Planning at RSU Bungsu Bandung
Get PDFBungsu General Hospital in Bandung City has implemented several tax planning strategies. These strategies include optimizing tax benefits by providing fringe benefits to employees, such as health benefits and health insurance. In addition, the hospital also uses an efficient payroll policy by considering the difference in payroll between Indefinite Term Employment Agreements (PKWTT) and Certain Term Employment Agreements (PKWT). This is expected to help reduce the tax burden and optimize the available tax benefits. The presentation of this analysis uses a descriptive verification method. The purpose of this study is specifically to find out the relationship between fringe benefits, payroll policies and tax planning. This study used a total sampling technique that resulted in 120 respondents. Primary data were obtained through questionnaires. Data analysis used multiple linear regression and hypothesis testing. The results showed that the provision of Fringe benefits and payroll policies of Indefinite-Term Employment Agreements (PKWTT) and Certain-Term Employment Agreements (PKWT) had an influence on tax planning at Bungsu General Hospital, Bandung City, both partially and simultaneously
Predictive Processing in Autistic and Schizotypal traits: A Neurophysiological study
No full textPredictive Processing (PP) has been suggested as a valuable model for understanding the pathophysiological mechanisms underlying Schizophrenia Spectrum Disorder (SSD) and Autism Spectrum Disorder (ASD). According to this model, both disorders' core deficits and symptomatic heterogeneity may be due to an imbalance in prediction error mechanisms and perceptual processing. These mechanisms are expected to be disrupted in both disorders but in opposite directions, such that autism and schizotypy (specifically, positive symptoms) could represent opposite psychological dimensions in the PP framework. High scores of autistic and schizotypal in the general population that do not reach the clinical diagnosis criteria are considered subclinical samples. We will test this innovative hypothesis by examining predictive processing in a subclinical sample from the community. Two tasks of a 2-stimuli visual and auditory oddball paradigm will be performed to elicit brain Event-related Potentials (ERPs) to examine the Mismatch Negativity (MMN) and P300, which are suggested to represent error detection and mental model updating. We expect opposite patterns of error sensitivity and prediction updating in MMN and P300, as reflected by: a) a positive correlation of these ERPs with autistic traits, b) a negative correlation with schizotypy traits scores on the positive dimension
Social justice beliefs and information in China: Second experiment
No full textThis experiment aims to understand how information about inequality affects the cultural logics of justice in China. Individuals are randomly assigned to an informational treatment about wealth inequality in China or to a control group. Then, we examine the effect of information on a factorial survey or traditional measurements of fairness principles. The former is a measurement of non-declarative culture while the later measures declarative culture
Scoping Review Protocol for the Risk Factors Contributing to Perinatal Psychological Distress among First-time Fathers
No full textThe study completed and published. The study can be accessed via the following link:
https://doi.org/10.1177/15579883251320035
Historically, researchers, policymakers, and healthcare professionals have centered maternal mental health during the perinatal period. International studies establish that fathers also experience psychological distress during the perinatal period of their partners, but understanding and addressing paternal perinatal mental health seems to be taken for granted. There is a knowledge gap about the experiences of Pakistani first-time fathers who may face mental health challenges during their wives’ perinatal period. To date, these fathers’ experiences have neither been explored nor reported