Dukungan Suami Meningkatkan Kunjungan Pemeriksaan K4 Ibu Hamil

Background: K4 is the fourth prenatal check-up visit for health workers to obtain antenatal care according to standards and to detect complications as early as possible during pregnancy. The K4 coverage in Batang-Batang Daya village, the working area of ​​the Batang-Batang Puskesmas is still below the target in 2018. The purpose of this study was to determine the relationship between husband's support and the decision of pregnant women in carrying out K4 examinations. Methods: The design of this study is analytic correlational with a cross-sectional study approach, the population of pregnant women in the third trimester of pregnancy in Batang-Batang Daya Village in 2019 was 27 respondents, using total sampling techniques, husband's support data was collected using a valid and reliable questionnaire. K4 examination data used a checklist in the KIA book, and the statistical test used was Chi-Square with an expected value of less than 5. Result: The results showed that most of the pregnant women received support from their husbands as many as 20 people (74.1). Most of the pregnant women underwent a K4 examination (4th pregnancy visit), as many as 20 people (74.1%). The analysis result from the Chi-Square test shows the value (ρ) = 0.000. Conclusion: It can be concluded that the husband's support is related to the decision by pregnant women to carry out K4 examinations. Husbands should always provide support to their wives to carry out routine checks so that pregnant women are motivated to carry out K4 examinations, and are more confident about carrying out their pregnancy

Penilaian Kinerja Guru Menggunakan Metode Topsis

Determining the level of individual contributions in completing the tasks for which they are responsible needs to be carried out objectively, transparently and through a specific method that can be trusted for accuracy. In addition to teaching in the classroom, a teacher is required to have the character as implied by Tut Wuri Handayani. The problem of the teacher performance appraisal process occurs because of unclear criteria and assessment weight. Decision Supprot System (DSS) can help the optimal decision-making process, namely TOPSIS (Technique For Order Preference by Similarity to Ideal Solution). In determining teacher performance appraisal agreed upon criteria for assessment of teacher performance assessment criteria: Pedagodic Competence (K1), Personality Competence (K2), Social Competence (K3), Proffesional Competence (K4). The acquisition of the final result of the TOPSIS calculation becomes the Teacher Performance Assessment Decision with the Status: Poor, Good, and Very Good. Very good teacher performance assessment, namel

K3K_3-WORM colorings of graphs: Lower chromatic number and gaps in the chromatic spectrum

A $K_3$-WORM coloring of a graph $G$ is an assignment of colors to the vertices in such a way that the vertices of each $K_3$-subgraph of $G$ get precisely two colors. We study graphs $G$ which admit at least one such coloring. We disprove a conjecture of Goddard et al. [Congr. Numer., 219 (2014) 161--173] who asked whether every such graph has a $K_3$-WORM coloring with two colors. In fact for every integer $k\ge 3$ there exists a $K_3$-WORM colorable graph in which the minimum number of colors is exactly $k$. There also exist $K_3$-WORM colorable graphs which have a $K_3$-WORM coloring with two colors and also with $k$ colors but no coloring with any of $3,\dots,k-1$ colors. We also prove that it is NP-hard to determine the minimum number of colors and NP-complete to decide $k$-colorability for every $k \ge 2$ (and remains intractable even for graphs of maximum degree 9 if $k=3$). On the other hand, we prove positive results for $d$-degenerate graphs with small $d$, also including planar graphs. Moreover we point out a fundamental connection with the theory of the colorings of mixed hypergraphs. We list many open problems at the end.Comment: 18 page

The decision problem of modal product logics with a diagonal, and faulty counter machines

In the propositional modal (and algebraic) treatment of two-variable first-order logic equality is modelled by a `diagonal' constant, interpreted in square products of universal frames as the identity (also known as the `diagonal') relation. Here we study the decision problem of products of two arbitrary modal logics equipped with such a diagonal. As the presence or absence of equality in two-variable first-order logic does not influence the complexity of its satisfiability problem, one might expect that adding a diagonal to product logics in general is similarly harmless. We show that this is far from being the case, and there can be quite a big jump in complexity, even from decidable to the highly undecidable. Our undecidable logics can also be viewed as new fragments of first- order logic where adding equality changes a decidable fragment to undecidable. We prove our results by a novel application of counter machine problems. While our formalism apparently cannot force reliable counter machine computations directly, the presence of a unique diagonal in the models makes it possible to encode both lossy and insertion-error computations, for the same sequence of instructions. We show that, given such a pair of faulty computations, it is then possible to reconstruct a reliable run from them

Constructing practical Fuzzy Extractors using QIM

Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers ( log2 6 / 2-1) approx. 3 extra bits per dimension of the space compared to the known square quantization based fuzzy extractor

Distributed Testing of Excluded Subgraphs

We study property testing in the context of distributed computing, under the classical CONGEST model. It is known that testing whether a graph is triangle-free can be done in a constant number of rounds, where the constant depends on how far the input graph is from being triangle-free. We show that, for every connected 4-node graph H, testing whether a graph is H-free can be done in a constant number of rounds too. The constant also depends on how far the input graph is from being H-free, and the dependence is identical to the one in the case of testing triangles. Hence, in particular, testing whether a graph is K_4-free, and testing whether a graph is C_4-free can be done in a constant number of rounds (where K_k denotes the k-node clique, and C_k denotes the k-node cycle). On the other hand, we show that testing K_k-freeness and C_k-freeness for k>4 appear to be much harder. Specifically, we investigate two natural types of generic algorithms for testing H-freeness, called DFS tester and BFS tester. The latter captures the previously known algorithm to test the presence of triangles, while the former captures our generic algorithm to test the presence of a 4-node graph pattern H. We prove that both DFS and BFS testers fail to test K_k-freeness and C_k-freeness in a constant number of rounds for k>4

Q-learning: flexible learning about useful utilities

Dynamic treatment regimes are fast becoming an important part of medicine, with the corresponding change in emphasis from treatment of the disease to treatment of the individual patient. Because of the limited number of trials to evaluate personally tailored treatment sequences, inferring optimal treatment regimes from observational data has increased importance. Q-learning is a popular method for estimating the optimal treatment regime, originally in randomized trials but more recently also in observational data. Previous applications of Q-learning have largely been restricted to continuous utility end-points with linear relationships. This paper is the first attempt at both extending the framework to discrete utilities and implementing the modelling of covariates from linear to more flexible modelling using the generalized additive model (GAM) framework. Simulated data results show that the GAM adapted Q-learning typically outperforms Q-learning with linear models and other frequently-used methods based on propensity scores in terms of coverage and bias/MSE. This represents a promising step toward a more fully general Q-learning approach to estimating optimal dynamic treatment regimes