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| Pengarang | : | Frans Maniagasi |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 73-80 |
| Abstrak | : | - |
DICARI: GENERASI MUDA KRISTEN DENGAN WAWASAN TEOLOGIS DAN WAWASAN KEBANGSAAN YANG TINGGI
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 69-72 |
| Abstrak | : | - |
DILEMA PEMBANGUNA INDONESIA TIMUR: SUATU TINDAKAN EKONOMI-POLITIK
| Pengarang | : | Marthen L. Ndoen |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 61-68 |
| Abstrak | : | - |
KEMISKINAN DAN KETIMPANGAN DISTRIBUSI PENDAPATAN DI INDONESIA: TANTANGAN UTAMA PEMBANGUNAN NASIONAL INDONESIA MENJELANG REPELITA VI
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 49-60 |
| Abstrak | : | - |
Model-Assisted Uniformly Honest Inference for Optimal Treatment Regimes in High Dimension
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 305-314 |
| Abstrak | : | This article develops new tools to quantify uncertainty in optimal decision making and to gain insight into which variables one should collect information about given the potential cost of measuring a large number of variables. We investigate simultaneous inference to determine if a group of variables is relevant for estimating an optimal decision rule in a high-dimensional semiparametric framework. The unknown link function permits flexible modeling of the interactions between the treatment and the covariates, but leads to nonconvex estimation in high dimension and imposes significant challenges for inference. We first establish that a local restricted strong convexity condition holds with high probability and that any feasible local sparse solution of the estimation problem can achieve the near-oracle estimation error bound. We further rigorously verify that a wild bootstrap procedure based on a debiased version of the local solution can provide asymptotically honest uniform inference for the effect of a group of variables on optimal decision making. The advantage of honest inference is that it does not require the initial estimator to achieve perfect model selection and does not require the zero and nonzero effects to be well-separated. We also propose an efficient algorithm for estimation. Our simulations suggest satisfactory performance. An example from a diabetes study illustrates the real application. Supplementary materials for this article are available online. |
HUTANG,HUTAN, HURU-HARA, DAN HURA-HURA: SUATU KRITIK TERHADAP STRATEGI ADVOKASI LINGKUNGAN YANG TERLALU BERTUMPU PADA DIPLOMASI HUTANG LUANG NEGERI
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 33-48 |
| Abstrak | : | - |
LAYING THE FOUNDATION OF CRITICAL THINKING SKILLS IN EFL PRIMARY SCHOOLS' LEARNERS THROUGH TEACHERS' QUESTIONS
| Pengarang | : | Hadisantosa, Nilawati |
| Nama Majalah/Jurnal | : | Indonesian JELT: Indonesian Journal of English Language Teaching |
| Volume / Edisi | : | 7 (No. 2) |
| Halaman | : | 152-167 |
| Abstrak | : | More parents and educators realize that our children need to be prepared to think critically as part of the life skills education. Thinking skills are becoming the necessary skills to acquire in order to be able to face the challenges of our rapidly changing global infonnation age. In 1956, Benjamin Bloomfield developed a strategy to categorize levels of reasoning skills. Bloom's six cognitive levels range from simple recall or recognition of facts through increasingly more complex and abstract intellectual tasks. In order, the levels are (1) knowledge, (2) comprehension, (3) application, ( 4) analysis, ( 5) synthesis, ( 6) evaluation. This research therefore attempts to explore the types of questions asked by six EFL teachers in primary schools according to Bloom's Taxonomy of cognitive domain and see whether they fit to the criteria of questions that trigger critical thinking skills. The results showed that the six teachers performed questions that covered all levels of Bloom's Taxonomy. However, knowledge and comprehension types of question which are regarded as lower cognitive levels dominated the other types of Bloom's cognitive level. The last four levels which are classified as higher cognitive levels actually are the ones that are considered as the foundation of critical thinking. |
ANXIETY IN ORAL PERFORMANCE TESTS: A CASE STUDY OF INDONESIAN LEARNERS
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Indonesian JELT: Indonesian Journal of English Language Teaching |
| Volume / Edisi | : | 7 (No. 2) |
| Halaman | : | 135-151 |
| Abstrak | : | This study examined anxiety experienced by students before an oral performance test, the relationship between the anxiety and their test performance, and strategies they applied to reduce the anxiety. The participants were 107 Indonesian students who enrolled the English speaking classes. This study revealed that the students did not experience a high level of anxiety before the oral performance test. There was not a very significant relationship between anxiety and their score in the performance test. Finally, some strategies to cope the anxiety were also discussed. |
Variable Selection Via Thompson Sampling
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 287-304 |
| Abstrak | : | Abstract–Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has a long tradition in machine learning. The algorithm has a Bayesian spirit in the sense that it selects arms based on posterior samples of reward probabilities of each arm. By forging a connection between combinatorial binary bandits and spike-and-slab variable selection, we propose a stochastic optimization approach to subset selection called Thompson variable selection (TVS). TVS is a framework for interpretable machine learning which does not rely on the underlying model to be linear. TVS brings together Bayesian reinforcement and machine learning in order to extend the reach of Bayesian subset selection to nonparametric models and large datasets with very many predictors and/or very many observations. Depending on the choice of a reward, TVS can be deployed in offline as well as online setups with streaming data batches. Tailoring multiplay bandits to variable selection, we provide regret bounds without necessarily assuming that the arm mean rewards be unrelated. We show a very strong empirical performance on both simulated and real data. Unlike deterministic optimization methods for spike-and-slab variable selection, the stochastic nature makes TVS less prone to local convergence and thereby more robust. |
ANATOMI HISTORIS DAN PROSPEK PENANAMAN MODAL ASING DI INDONESIA
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Bina Darma |
| Volume / Edisi | : | 11-40 (No. 40) |
| Halaman | : | 24-32 |
| Abstrak | : | - |