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"Indonesia telah mengembangkan program perlindungan sosial untuk meningkatkan angka partisipasi sekolah, di antaranya ialah Program Indonesia Pintar (PIP). Akan tetapi, semakin berkembang rekognisi bahwa program perlindungan sosial yang diimplementasikan negara berkembang memiliki akurasi sasaran yang relatif buruk walaupun hal tersebut erat kaitannya dengan efisiensi serta efektivitas pelaksanaan program. Penelitian ini bertujuan untuk menganalisis mengenai akurasi sasaran Program Indonesia Pintar serta korelasinya dengan salah satu tujuan program, yakni keputusan kembali bersekolah. Dengan metode analisis secara deskriptif menggunakan data SUSENAS, diketahui bahwa targeting error masih signifikan terjadi pada PIP walau ada indikasi perbaikan pada 2018 dibandingkan dengan 2017. Di samping itu, metode regresi logit dengan data SUSENAS tahun 2018 digunakan untuk melihat korelasi PIP dengan keputusan kembali bersekolah dan ditemukan korelasi secara positif serta signifikan. Hal ini membuktikan bagaimana penerimaan PIP mampu berkontribusi untuk meningkatkan angka partisipasi sekolah dengan menarik kembali individu yang sempat berhenti sekolah. Namun, signifikannya permasalahan pada akurasi sasaran tetap menjadi perhatian.

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Indonesia has been developing social assistance program to increase school participation rate, one of which is Program Indonesia Pintar (Educational Cash Transfer for the Poor/PIP). However, there is a growing recognition that many existing social assistance programs in developing countries are badly targeted although it is highly correlated with the efficiency and effectiveness of the program execution. This study aims to analyze the targeting performance of Program Indonesia Pintar and its correlation with one of the program’s objective, re-enrolment decision. By utilizing descriptive analysis with SUSENAS data, it is found that targeting error is still significantly found in the implementation of PIP although it’s relatively lower in 2018 compared to 2017. Furthermore, logistic regression method with 2018 SUSENAS data is used to analyzed the correlation of PIP reception with re-enrolment decision, which is proven to be positive and significant. It verifies how PIP reception can contribute to increase school participation rate by encouraging individuals who have dropped out of school to go back to school. Nonetheless, the issue of targeting error still needs to be figured."

"Penelitian ini menganalisis korelasi bantuan pendidikan dengan basis syarat need dan merit di Universitas Indonesia terhadap pendapatan individu dan ketimpangan pada tingkat program studi. Studi ini menggunakan metode pooled cross section regression dengan data Tracer Study Universitas Indonesia. Hasil menunjukkan penerima bantuan berbasis need memiliki pendapatan yang lebih rendah sedangkan penerima bantuan merit memiliki pendapatan lebih tinggi dibandingkan non-penerima bantuan. Pada penelitian ini juga ditemukan korelasi positif antara proporsi bantuan pendidikan need terhadap ketimpangan prodi. Namun tidak ditemukan korelasi antara proporsi bantuan merit dengan ketimpangan pendapatan pada tingkat program studi. Studi ini memberikan pemahaman yang lebih mendalam tentang dampak dari dua jenis bantuan pendidikan di tingkat perguruan tinggi, khususnya di Universitas Indonesia.

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This research analyzes the correlation of educational aid based on need and merit at the University of Indonesia with individual income and inequality at the study program level. This research uses pooled cross-section regression method with data from the Tracer Study at the University of Indonesia. The results show that need-based aid recipients have lower incomes, while merit-based aid recipients have higher incomes compared to non-recipients. The study also found a positive correlation between the proportion of need-based educational aid and income inequality at the study program level. However, no correlation was found between the proportion of merit-based aid and income inequality at the study program level. The study provides a deeper understanding of the impact of these two types of education assistance at the university level, especially at the University of Indonesia."

"This volume makes it very clear, however, that there is no one approach to standards-based reform and countries change, there is a danger in paying attention to its evolution and impact in only one context. Louis Volante has drawn together descriptions from a wide range of countries, all involved in large-scale reform and using standards and assessments as part of their process. What becomes very obvious is that the language may be the same but the words reflect different contexts and can represent very different ideals, values, and processes. "

"Boys are falling behind in school. The world has become more verbal; boys haven't. Even in their traditionally strong subjects of science and math, boys are hit at a young age with new educational approaches, stressing high-level reading and writing goals that they are developmentally unable to achieve. The gap between male and female achievement has reached the college level, where only 40 per cent of graduates next year will be male. This doesn't just mean fewer male doctors and lawyers, it also means fewer men in the careers that previously did not require post-high school degrees but do now. "Why Boys Fail" examines the roots and repercussions of this problem and spells out the educational, political, social and economic challenges we face as we work to end it."

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Universitas Sriwijaya merupakan satuan pendidikan yang menyelenggarakan pendidikan tinggi di kota Palembang. Berdasarkan Undang-Undang Republik Indonesia No. 12 Tahun 2012, penyelenggara perguruan tinggi wajib menyampaikan data dan informasi penyelenggaraan perguruan tinggi kepada PDDikti dengan memastikan kelengkapan, kebenaran ketepatan dan kemutakhirannya. Namun, hingga saat ini Universitas Sriwijaya masih belum sepenuhnya dapat memenuhi tuntutan peraturan tersebut. Permasalahan tersebut menjadi perhatian manajemen, karena pelaporan data kepada PDDikti merupakan standar nasional pendidikan tinggi yang harus dipenuhi dan informasi yang telah terkumpulkan di PDDikti  akan menjadi sumber informasi bagi lembaga akreditasi untuk melakukan akreditasi program studi dan perguruan tinggi sedangkan bagi masyarakat untuk mengetahui kinerja program studi dan perguruan tinggi. Berdasarkan kondisi tersebut, maka penelitian ini ditujukan untuk dapat membantu mengatasi permasalahan terkait kualitas data pada Universitas Sriwijaya dengan menyusun rekomendasi peningkatan kualitas data. Untuk menyusun rekomendasi tersebut dilakukan penilaian manajemen kualitas data saat ini, yaitu melalui penilaian terhadap dimensi kualitas data dan penilaian terhadap maturitas manajemen kualitas data. Rekomendasi yang diberikan meliputi delapan komponen dalam Data Quality Framework dari David Loshin dengan menerapkan praktik terbaik manajemen kualitas data dari Data Management Book of Knowledge dari DAMA Institute. Rekomendasi tersebut diharapkan dapat digunakan sebagai acuan dalam melaksanakan program peningkatan kualitas data pokok pendidikan di Universitas Sriwijaya.

 

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Sriwijaya University is an education unit that organizes higher education in the city of Palembang. Based on the Law of the Republic of Indonesia No. 12 of 2012, higher education institutions are required to submit data and information on the organization of higher education to PDDikti by ensuring completeness, accuracy and accuracy. However, until now Sriwijaya University still cannot fully fulfill the demands of the regulation. These problems are of concern to management, because reporting data to PDDikti is a national standard of higher education that must be fulfilled and information that has been collected in PDDikti will be a source of information for accreditation institutions to accredit study programs and universities while for the public to know the performance of study programs College. Based on these conditions, this research is intended to be able to help overcome problems related to data quality at Sriwijaya University by compiling recommendations for improving data quality. To compile these recommendations, an assessment of the current data quality management is carried out, namely through an assessment of the dimensions of data quality and an assessment of data quality management maturity. The recommendations given include eight components in the David Quality Quality Framework by implementing data quality management best practices from the Data Management Book of Knowledge from DAMA Institute. The recommendation is expected to be used as a reference in implementing the basic data quality improvement program at Sriwijaya University.

 

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