Poverty reduction has become a priority for government of the Republic of Indonesia in the last decade. One among poverty reduction programs based on family called Program Keluarga Harapan (PKH). PKH is a conditional cash transfer (CCT) program for poor families. PKH has addressed to cut off poverty chain through the accessibility of education, health, and social welfare services. PKH beneficiaries, besides getting social assistance in the form of cash transfer, also received capacity building in the form of Family Development Sessions (FDS). FDS has formed as behavioral change intervention that carried out by PKH Facilitator. This study has aimed to describe and analyze the implementation of FDS and changes in poor family behavior. Qualitative approach has been used for this research with an open-ended interview as a collective data technique. The FDS meeting was held at beneficiaries' household, and public facilities. The findings of this study indicate that the implementation of FDS is highly dependent on the competency of PKH Facilitator, frequency has done once a month, each for two hours. Teaching aids in the form of modules and flipcharts. The FDS material consists of education and parenting, economics, health, and child protection. Changes in Poor Family Behavior include being able to regulate household financial planning, healthier lifestyles, childcare and care for the elderly and disability. This study recommends the need for material adaptation according to regional conditions. The economic module needs to be added to the session on social entrepreneurship, especially for PKH beneficiaries who will graduate.

tenggara Timur, menggunakan pendekatan kualitatif. Teknik pengumpulan data dilakukan dengan observasi, wawancara, dan Focus Group Discussion. Data yang terkumpul dianalisis secara deskriptif. Hasil penelitian menyimpulkan bahwa untuk mempercepat penanggulangan kemiskinan melalui PKH perlu dilakukan redesign berupa inovasi program dalam rangka pengembangan program secara fundamental. Inovasi ini difokuskan pada 2 hal, yaitu: (1) merespon upaya yang sudah dilakukan tetapi belum optimal; dan (2) melakukan reorientasi program secara mendasar dengan menjadikan PKH sebagai pintu masuk menuju integrasi program perlindungan sosial sekaligus integrasi program penanggulangan kemiskinan di Indonesia, dengan fokus memperkuat keberfungsian keluarga miskin secara utuh. Upaya ini diharapkan akan "memaksa" anggota keluarga berperilaku produktif, bukan kontraproduktif. Sejalan dengan kesimpulan di atas, penelitian ini merekomendasikan agar penyelenggara segera mengambil inisiatif untuk menjadikan PKH sebagai pintu masuk menuju integrasi program perlindungan sosial sekaligus integrasi program penanggulangan kemiskinan di Indonesia. Langkah ini hendaknya diikuti denggan kajian khusus terhadap berbagai produk kebijakan terkait.

No abstract

Background: While deepfake technology is still relatively new, concerns are increasing as they are getting harder to spot. The first question we need to ask is how good humans are at recognizing deepfakes - realistic-looking videos or images that show people doing or saying things that they never actually did or said generated by an artificial intelligence-based technology. Research has shown that an individual’s self-efficacy correlates with their ability to detect deepfakes. Previous studies suggest that one of the most fundamental predictors of self-efficacy are personality traits. In this study, we ask the question: how can people’s personality traits influence their efficacy in recognizing deepfakes?  Methods: Predictive correlational design with a multiple linear regression data analysis technique was used in this study. The participants of this study were 200 Indonesian young adults. Results: The results showed that only traits of Honesty-humility and Agreeableness were able to predict the efficacy, in the negative and positive directions, respectively. Meanwhile, traits of Emotionality, Extraversion, Conscientiousness, and Openness cannot predict it. Conclusion: Self-efficacy in spotting deepfakes can be predicted by certain personality traits.

No abstract