KONTRIBUSI GURU GEOGRAFI DALAM MITIGASI BENCANA ERUPSI GUNUNG MERAPI

Gunung Merapi merupakan salah satu gunung aktif di Indonesia. Aktivitas vulkanik yang sangat aktif membutuhkan perhatian dari berbagai kalangan, salah satunya dalam dunia pendidikan. Penelitian ini bertujuan untuk mengetahui besar kontribusi guru Geografi dalam mitigasi bencana erupsi gunung Merapi pada siswa Sekolah Menengah Atas Negeri di Kabupaten Sleman Yogyakarta. Penelitian ini merupakan jenis penelitian deskriptif kuantitatif yang dilaksanakan di Kabupaten Sleman. Populasi dalam penelitian ini adalah seluruh guru Geografi pada SMA Negeri di Kabupaten Sleman sebanyak 24 responden. Teknik pengumpulan data dilakukan dengan wawancara terstruktur. Instrumen penelitian ini berupa pedoman wawancara. Hasil penelitian menunjukkan bahwa kontribusi guru Geografi dalam mitigasi bencana erupsi gunung Merapi pada siswa SMA Negeri di Kabupaten Sleman Sebagian besar berada pada kategori cukup yaitu 58 persen. Maka dapat disimpulkan bahwa kontribusi guru Geografi pada SMA Negeri di Kabupaten Sleman cenderung cukup. Hal ini disebabkan karena tidak semua guru Geografi mengajarkan secara mendalam mengenai bencana gunung Merapi pada siswa SMA Negeri, bahkan hanya sebagian saja yang secara produktif mengajarkan mengenai bencana gunung Merapi pada siswa, baik di dalam kelas maupun di luar kelas

ANALISIS PENGARUH HARGA DAN KUALITAS PRODUK TERHADAP KEPUTUSAN PEMBELIAN DAN MINAT BELI ULANG SMARTPHONE MEREK XIAOMI PADA MASA PEMBELAJARAN JARAK JAUH

The Covid-19 pandemic has made the world of education change the way in the learning process. The need for a communication device, in this case a smartphone, has become a necessity. This study aims to determine the effect of price and product quality on purchasing decisions and intention to repurchase Xiaomi brand smartphones during the distance learning period. The type of research used is quantitative research. The location of the research was carried out at the Mataram State Islamic University. The sample used in this study were students totaling 100 people. The analytical technique used in this research is descriptive analysis, data analysis, and statistical analysis with SEM (Structural Equation Modeling). The results of this study indicate that the price and quality of the product affect the purchasing decisions and interest in repurchasing Xiaomi brand smartphones in students

ANALISIS KEPUASAN MAHASISWA TERHADAP SISTEM PEMBELAJARAN ONLINE BERDASARKAN END USER COMPUTING SATISFACTION (EUCS) SELAMA PANDEMI COVID -19

The Covid-19 pandemic has forced educational institutions to change the way they carry out the teaching-learning process. The process of teaching-learning activities has changed from face to face directly to teaching-learning in a network (online). The need for a system that can support this process change is urgently needed. Responding to this need, Mataram State Islamic University as an educational institution, utilizes its system, namely the Learning Management System (LMS) application. This study aims to analyze student satisfaction with the LMS application system, which is based on the End User Computing Satisfaction (EUCS) model. The type of research used in this research is quantitative research. The location of the research was carried out at the Mataram State Islamic University. The sample used in this study were 90 students. The analytical technique used in this research is descriptive statistical analysis. The results of this study indicate that students are quite satisfied with the LMS application system used to support the teaching-learning process.Pandemi Covid-19 membuat lembaga-lembaga pendidikan mengubah cara mereka dalam melaksanakan proses kegiatan belajar-mengajar. Proses kegiatan belajar-mengajar berubah dari tatap muka secara langsung menjadi belajar-mengajar dalam jaringan (daring). Kebutuhan akan sistem yang dapat menunjang perubahan proses ini sangat dibutuhkan. Menanggapi kebutuhan itu, Universitas Islam Negeri Mataram sebagai salah satu lembaga pendidikan, memanfaatkan sistem yang dimiliki, yaitu aplikasi Learning Management System (LMS). Penelitian ini bertujuan untuk menganalisis kepuasan mahasiswa terhadap sistem aplikasi LMS itu, yang didasarkan pada model End User Computing Satisfaction (EUCS). Jenis penelitian yang digunakan dalam penelitian ini adalah penelitian kuantitatif. Lokasi penelitian dilakukan di Universitas Islam Negeri Mataram. Sampel yang digunakan dalam penelitian ini adalah mahasiswa yang berjumlah 90 orang. Teknik analisis yang digunakan dalam penelitian ini adalah analisis statistik deskriptif. Hasil penelitian ini menunjukkan bahwa mahasiswa merasa cukup puas dengan sistem aplikasi LMS yang digunakan dalam menunjang proses kegiatan proses belajar-mengajar

Concern with COVID-19 pandemic threat and attitudes towards immigrants: The mediating effect of the desire for tightness

Tightening social norms is thought to be adaptive for dealing with collective threat yet it may have negative consequences for increasing prejudice. The present research investigated the role of desire for cultural tightness, triggered by the COVID-19 pandemic, in increasing negative attitudes towards immigrants. We used participant-level data from 41 countries (N = 55,015) collected as part of the PsyCorona project, a crossnational longitudinal study on responses to COVID-19. Our predictions were tested through multilevel and SEM models, treating participants as nested within countries. Results showed that people’s concern with COVID19 threat was related to greater desire for tightness which, in turn, was linked to more negative attitudes towards immigrants. These findings were followed up with a longitudinal model (N = 2,349) which also showed that people’s heightened concern with COVID-19 in an earlier stage of the pandemic was associated with an increase in their desire for tightness and negative attitudes towards immigrants later in time. Our findings offer insight into the trade-offs that tightening social norms under collective threat has for human groups

Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study

Background. The effective implementation of government policies and measures for controlling the coronavirus disease 2019 (COVID-19) pandemic requires compliance from the public. This study aimed to examine cross-sectional and longitudinal associations of trust ingovernment regarding COVID-19 control with the adoption of recommended health behaviours and prosocial behaviours, and potential determinants of trust in government duringthe pandemic.Methods. This study analysed data from the PsyCorona Survey, an international project onCOVID-19 that included 23 733 participants from 23 countries (representative in age andgender distributions by country) at baseline survey and 7785 participants who also completedfollow-up surveys. Specification curve analysis was used to examine concurrent associationsbetween trust in government and self-reported behaviours. We further used structural equation model to explore potential determinants of trust in government. Multilevel linear regressions were used to examine associations between baseline trust and longitudinal behavioural changes.Results. Higher trust in government regarding COVID-19 control was significantly associatedwith higher adoption of health behaviours (handwashing, avoiding crowded space, self-quarantine) and prosocial behaviours in specification curve analyses (median standardised β =0.173 and 0.229, p < 0.001). Government perceived as well organised, disseminating clear messages and knowledge on COVID-19, and perceived fairness were positively associated withtrust in government (standardised β = 0.358, 0.230, 0.056, and 0.249, p < 0.01). Higher trustat baseline survey was significantly associated with lower rate of decline in health behavioursover time ( p for interaction = 0.001).Conclusions. These results highlighted the importance of trust in government in the control of Covid-19

.Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individuallevel injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant

‘We are all in the same boat’ : how societal discontent affects intention to help during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has caused a global health crisis. Consequently, many countries have adopted restrictive measures that caused a substantial change in society. Within this framework, it is reasonable to suppose that a sentiment of societal discontent, defined as generalized concern about the precarious state of society, has arisen. Literature shows that collectively experienced situations can motivate people to help each other. Since societal discontent is conceptualized as a collective phenomenon, we argue that it could influence intention to help others, particularly those who suffer from coronavirus. Thus, in the present study, we aimed (a) to explore the relationship between societal discontent and intention to help at the individual level and (b) to investigate a possible moderating effect of societal discontent at the country level on this relationship. To fulfil our purposes, we used data collected in 42 countries (N = 61,734) from the PsyCorona Survey, a cross-national longitudinal study. Results of multilevel analysis showed that, when societal discontent is experienced by the entire community, individuals dissatisfied with society are more prone to help others. Testing the model with longitudinal data (N = 3,817) confirmed our results. Implications for those findings are discussed in relation to crisis management. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement

Using Machine Learning to Identify Important Predictors of COVID-19 Infection Prevention Behaviors During the Early Phase of the Pandemic

Before vaccines for COVID-19 became available, a set of infection prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection prevention behavior in 56,072 participants across 28 countries, administered in March-May 2020. The machine- learning model predicted 52% of the variance in infection prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual- level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically-derived predictors were relatively unimportant

COVID-19 stressors and health behaviors. A multilevel longitudinal study across 86 countries

Anxiety associated with the COVID-19 pandemic and home confinement has been associated with adverse health behaviors, such as unhealthy eating, smoking, and drinking. However, most studies have been limited by regional sampling, which precludes the examination of behavioral consequences associated with the pandemic at a global level. Further, few studies operationalized pandemic-related stressors to enable the investigation of the impact of different types of stressors on health outcomes. This study examined the association between perceived risk of COVID-19 infection and economic burden of COVID-19 with health-promoting and health-damaging behaviors using data from the PsyCorona Study: an international, longitudinal online study of psychological and behavioral correlates of COVID-19. Analyses utilized data from 7,402 participants from 86 countries across three waves of assessment between May 16 and June 13, 2020. Participants completed self-report measures of COVID-19 infection risk, COVID-19-related economic burden, physical exercise, diet quality, cigarette smoking, sleep quality, and binge drinking. Multilevel structural equation modeling analyses showed that across three time points, perceived economic burden was associated with reduced diet quality and sleep quality, as well as increased smoking. Diet quality and sleep quality were lowest among respondents who perceived high COVID-19 infection risk combined with high economic burden. Neither binge drinking nor exercise were associated with perceived COVID-19 infection risk, economic burden, or their interaction. Findings point to the value of developing interventions to address COVID-related stressors, which have an impact on health behaviors that, in turn, may 111 influence vulnerability to COVID-19 and other health outcomes

Politicization of COVID-19 health-protective behaviors in the United States: Longitudinal and cross-national evidence

During the initial phase of the COVID-19 pandemic, U.S. conservative politicians and the media downplayed the risk of both contracting COVID-19 and the effectiveness of recommended health behaviors. Health behavior theories suggest perceived vulnerability to a health threat and perceived effectiveness of recommended health-protective behaviors determine motivation to follow recommendations. Accordingly, we predicted that—as a result of politicization of the pandemic—politically conservative Americans would be less likely to enact recommended health-protective behaviors. In two longitudinal studies of U.S. residents, political conservatism was inversely associated with perceived health risk and adoption of health-protective behaviors over time. The effects of political orientation on health-protective behaviors were mediated by perceived risk of infection, perceived severity of infection, and perceived effectiveness of the health-protective behaviors. In a global cross-national analysis, effects were stronger in the U.S. (N = 10,923) than in an international sample (total N = 51,986), highlighting the increased and overt politicization of health behaviors in the U.S