This study aimed to explore of what factors that influencing gratitude of Muslim parents who having children with special needs. This study was a preliminary stage to develop an instrument of specific gratitude. The research methods used literature study and qualitative approach by in-depth interview. The subjects were six couple of parent from childrens with special needs. The result found that there were differences as well as similarities about concept of gratitude between Western perspective and Islam particularly in term of appreciation and expression. Gratitude emerged to respond something acquired covering things, happiness moments, ability to cope difficulties, and weaknesses. There was also having added value namely spiritual experience that pushed motive to getting closer toward Alloh SWT. Positive feeling and emotion emerged such as kindhearted, positive thinking, and optimistic in facing the life.
Indonesia is a big country with high pluralism. Country
AbstrakIndonesia adalah negara besar yang memiliki berbagai kemajemukan. Negara seperti Indonesia memerlukan sikap toleransi yang tinggi. Penelitian ini ingin memperoleh gambaran sikap toleransi pada mahasiswa berdasarkan tipe kepribadian. Penelitian mengambil subjek 350 mahasiswa UIN Sunan Gunung Djati Bandung dengan pendekatan kuantitatif. Variabel yang dilibatkan adalah tipe kepribadian dan sikap toleransi. Tipe kepribadian menggunakan skala yang disusun dari teori Big Five yang dirumuskan dari International Personality Item Pool (IPIP). Untuk sikap toleransi diukur dengan menggunakan skala yang dikembangkan oleh van der Waltz. Hasil yang diperoleh adalah tipe kepribadian Conscientious mendominasi subjek dan tidak ada satu subjekpun yang memiliki tipe kepribadian Agreeableness. Sedangkan untuk keempat tipe kepribadian yang ada, Analisis Variansi (Anava) tidak ditemukan perbedaan yang signifikan pada sikap toleransi mereka. Diduga mayoritas mahasiswa UIN Sunan Gunung Djati memiliki nilai moral yang baik sehingga bisa toleran dalam menerima perbedaan. Kata Kunci: big five factor, kepribadian, mahasiswa, nilai moral, toleransi
This study will determine the length of time for large-scale social restrictions, in Indonesia is known as the Large-Scale Social Distancing (LSSD), which requires in a region to reduce the number of different covid-19 cases. Associated with the implementation of the LSSD, it turns out that many things can influence the LSSD to be able to run effectively in the community, from internal and external factors. This research was conducted for 15 days from 1 June 2020 to 15 June 2020, to find out the factors that had a significant influence on the effectiveness of LSSD using Cox Proportional Hazard Regression. The dependent variable used in the study is the length of time the LSSD system (Y). From the results can concluded that the socialization variable (X1) has a significant effect to the effectiveness of LSSD.
A sudden jump in the value of the state variable in a certain dynamical system can be studied through a catastrophe model. This paper presents an application of catastrophe model to solve psychological problems. Since we will have three psychological aspects or parameters, intelligence (I), emotion (E), and adversity (A), a Swallowtail catastrophe model is considered to be an appropriate one. Our methodology consists of three steps: solving the Swallowtail potential function, finding the critical points up to and including threefold degenerates, and fitting the model into our measured data. Using a polynomial curve fitting derived from the potential function of Swallowtail catastrophe model, relations among three parameters combinations are analyzed. Results show that there are catastrophe phenomena for each relation, meaning that a small change in one psychological aspect may cause a dramatic change in another aspect.
In 2022, the COVID-19 virus is still making headlines in various mass media because it is a virus that is very dangerous to health. The world health organization, WHO, explained that the virus caused a global pandemic that infected the whole world. The condition of a pandemic has not yet turned into an endemic. Based on the total confirmed COVID-19 positive cases, Indonesia ranks 18th in the world out of 222 infected countries. To determine the influence factors on COVID-19 cases, survival analysis is one of the techniques that could be applied. One of the most commonly used models in survival analysis is Accelerated Failure Time (AFT) model. In the AFT model, it is required to check assumptions regarding the feasibility of the distribution form. In this study, the distributions used are Weibull, Exponential, Log-normal, and Log-logistics distributions. We compare each distribution to get the best model to analyze death cases due to COVID-19. Comparisons are made by comparing the AIC values of each distribution. The best model is selected based on the smallest AIC value. The AFT model with a log-normal distribution is selected as the best model with an AIC value of 142.763. The AIC value for this log-normal distribution is the smallest compared to the AIC value for other distributions.Keywords: accelerated failure time model; COVID-19; mortality analysis; survival analysis. AbstrakTahun 2022, virus COVID-19 masih menjadi berita utama di berbagai media massa karena merupakan salah satu virus yang sangat berbahaya bagi kesehatan. Badan organisasi kesehatan dunia, WHO menjelaskan bahwa virus menyebabkan terjadinya pandemi global yang menginfeksi seluruh dunia. Kondisi pandemi masih belum berubah menjadi endemi. Dari total yang terkonfirmasi positif COVID-19 Indonesia menduduki posisi ke-18 di dunia dari 222 negara yang terinfeksi. Untuk mengetahui faktor-faktor yang berpengaruh terhadap COVID-19 dan untuk menentukan model dari COVID-19 ini salah satunya dapat dilakukan dengan analisis survival. Salah satu model survival yang digunakan yaitu model Accelerated Failure Time (AFT). Dalam model AFT ini diharuskan melakukan pengecekan asumsi-asumsi mengenai kelayakan bentuk distribusi. Pada penelitian ini distribusi yang digunakan yaitu distribusi Weibull, Eksponensial, Log-normal, dan Log-logistik. Dilakukan perbandingan antar tiap distribusi untuk mendapatkan model terbaik yang dapat digunakan dalam menganalisis kasus kematian akibat COVID-19. Perbandingan dilakukan dengan membandingkan nilai AIC dari setiap distribusi. Hasil penelitian memilih model AFT dengan distribusi log-normal sebagai model terbaik dengan nilai AIC sebesar 142,763. Nilai AIC untuk distribusi log-normal ini paling kecil dibandingkan dengan nilai AIC untuk distribusi lainnya.Kata Kunci: analisis mortalitas; analisis survival; COVID-19; model accelerated failure time. 2020MSC: 62P10
The problem of the extraction of the relevant information for prediction purposes -in a Big Data time series context -is tackled. This issue is especially crucial when the forecasting activity involves macroeconomic time series, i.e. when one is mostly interested in finding leading variables and, at the same time, avoiding overfitted model structures. Unfortunately, the use of big data can cause dangerous overparametrization phenomena in the entertained models. In addition, two other drawbacks should be considered: firstly, human-driven handling of big data on a case-by-case basis is an impractical (and generally not viable) option and secondly, focusing solely on the raw time series might lead to suboptimal results. The presented approach deals with these problems using a twofold strategy: i) it expands the data in timescale domain, in the attempt to increase the likelihood of giving emphasis to possibly weak, relevant, signals and ii) carries out a multi-step dimension reduction procedure. The latter task is done by means of cross-correlation functions (whose employment will be theoretically justified) and a suitable objective function.
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