PEMAHAMAN RELASIONAL SISWA DALAM MENYELESAIKAN SOAL PROGRAM LINEAR DI KELAS XI MAN 2 PONTIANAK

Abstract This study aims to find out students' relational understanding linear program materials in the class XI MAN 2 Pontianak . This form of quantitative descriptive research, for the data collection techniques used are test techniques and indirect communication techniques. For the data-mining techniques used is a matter of tests and interviews. Student relational understanding in this study is measured using linear program material consisting of 6 essay questions. The relational understanding referred to in this study is the students' ability to solve the linear program problem by using appropriate procedures and knowing why it is used. It is known that students who have the relational understanding ability to solve a problem is that students have the prerequisite ability to solve linear programs that fall into a very good category, to be able to do overall procedures in ending linear programs in excellent categories, and to get the right results and provide logical reasons for completing linear programs. Overall students have a high relational understanding with very good percentages. Keywords: Relational Understanding, Conceptual Understanding and Procedural Understanding, Linear Progra

Relational program synthesis with numerical reasoning

Program synthesis approaches struggle to learn programs with numerical values. An especially difficult problem is learning continuous values over multiple examples, such as intervals. To overcome this limitation, we introduce an inductive logic programming approach which combines relational learning with numerical reasoning. Our approach, which we call NUMSYNTH, uses satisfiability modulo theories solvers to efficiently learn programs with numerical values. Our approach can identify numerical values in linear arithmetic fragments, such as real difference logic, and from infinite domains, such as real numbers or integers. Our experiments on four diverse domains, including game playing and program synthesis, show that our approach can (i) learn programs with numerical values from linear arithmetical reasoning, and (ii) outperform existing approaches in terms of predictive accuracies and learning times

On Classical PCF, Linear Logic and the MIX Rule

We study a classical version of PCF from a semantical point of view. We define a general notion of model based on categorical models of Linear Logic, in the spirit of earlier work by Girard, Regnier and Laurent. We give a concrete example based on the relational model of Linear Logic, that we present as a non-idempotents intersection type system, and we prove an Adequacy Theorem using ideas introduced by Krivine. Following Danos and Krivine, we also consider an extension of this language with a MIX construction introducing a form of must non-determinism; in this language, a program of type integer can have more than one value (or no value at all, raising an error). We propose a refinement of the relational model of classical PCF in which programs of type integer are single valued; this model rejects the MIX syntactical constructs (and the MIX rule of Linear Logic)

The role of individual relationship marketing factors in influencing customer retention among microfinance institutions in Kenya

Organizations seeking a competitive advantage are increasingly embracing relationship marketing programs to manage customer relationships more efficiently. However, despite the deployment of such relationship management programs, customer retention continues to be the greatest challenge facing many organizations. This paper argues that relationship marketing factors - trust, commitment, strong bonds, communication, shared values and keeping promises - each plays a unique role in influencing customer retention, however, the nature of the influence of these individual factors on customer retention moreover in a developing market context has not been empirically investigated much. Relying on social exchange theory and relational market behavior theory, this study sought to determine the relationship between these relational factors and customer retention. Data were collected among 492 customers of Kenya's microfinance sector, using a structured self-administered questionnaire. The association between individual relationship marketing factors and customer retention was tested through simple linear regression analysis. Results showed that among the six relational factors, communication and shared values were the most significant. The study makes a theoretical contribution to the relationship marketing knowledge base by providing empirical evidence on the role of individual relationship marketing factors in predicting customer retention. Marketing practitioners should develop relationship management programs that promote communication effectiveness and shared values

Refinement Calculus of Reactive Systems

Refinement calculus is a powerful and expressive tool for reasoning about sequential programs in a compositional manner. In this paper we present an extension of refinement calculus for reactive systems. Refinement calculus is based on monotonic predicate transformers, which transform sets of post-states into sets of pre-states. To model reactive systems, we introduce monotonic property transformers, which transform sets of output traces into sets of input traces. We show how to model in this semantics refinement, sequential composition, demonic choice, and other semantic operations on reactive systems. We use primarily higher order logic to express our results, but we also show how property transformers can be defined using other formalisms more amenable to automation, such as linear temporal logic (suitable for specifications) and symbolic transition systems (suitable for implementations). Finally, we show how this framework generalizes previous work on relational interfaces so as to be able to express systems with infinite behaviors and liveness properties

Enhancing Predicate Pairing with Abstraction for Relational Verification

Relational verification is a technique that aims at proving properties that relate two different program fragments, or two different program runs. It has been shown that constrained Horn clauses (CHCs) can effectively be used for relational verification by applying a CHC transformation, called predicate pairing, which allows the CHC solver to infer relations among arguments of different predicates. In this paper we study how the effects of the predicate pairing transformation can be enhanced by using various abstract domains based on linear arithmetic (i.e., the domain of convex polyhedra and some of its subdomains) during the transformation. After presenting an algorithm for predicate pairing with abstraction, we report on the experiments we have performed on over a hundred relational verification problems by using various abstract domains. The experiments have been performed by using the VeriMAP transformation and verification system, together with the Parma Polyhedra Library (PPL) and the Z3 solver for CHCs.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854