Developing Students? Writing Skill on Recount Text by Using Photograph and Group Grid Technique

Kemampuan menulis adalah kemampuan yang sangat sulit bagi para murid Sekolah Menengah Pertama. Mereka kesulitan untuk menuliskan ide-ide mereka karena mereka merasa tidak percaya diri dalam menulis kalimat berbahasa Inggris. Olehkarena itu, peneliti menggunakan teknik group grid dan media foto untuk merangsang para murid mendapatkan ide-ide mereka dalam menulis bahasa Inggris.Penelitian ini adalah untuk meningkatkan kemampuan menulis para murid dalam menulis teks recount dengan teknik group grid dan media foto. Penelitian ini merupakan penelitian tindakan kelas. Peneliti menggunakan dua siklus. Setiapsiklus terdiri dari empat tahap yaitu perencanaan (planning), tindakan (acting), observasi (observing), dan refleksi (reflecting). Metode yang digunakan dalam pengumpulan data adalah tes, observasi, wawancara, dan kuesioner. Penelitian inimenggunakan teknik group grid dengan menggunakan media foto untuk meningkatkan kemampuan menulis para murid dalam menulis teks recount serta untuk mengetahui pencapaian dan respon para murid selama proses pembelajaran.Temuan dalam penelitian ini menunjukkan bahwa ada peningkatan dalam penguasaan murid dalam menulis teks recount. Hal itu dapat dilihat dari nilai rata-rata murid dalam pre-test yaitu 40.56. Kemudian, nilai rata-rata di posttest 1 adalah 72.93, dan nilai rata-rata post-test 2 adalah 78.12. Persentase kelas untuk murid yang nilainya diatas KKM dari post-test 1 adalah 53% dan post-test 2 adalah 84%. Respon para murid dalam implementasi teknik group grid dan media foto sangat bagus. Hal tersebut juga dapat dilihat dari hasilkuesioner dengan persentase nilai total tertinggi 96% dan nilai terendah 70%. Ratarata persentase yang didapat adalah 84%Berdasarkan perhitungan dari hasil data, bisa disimpulkan bahwa implementasi teknik group grid dan media foto dapatmeningkatkan kemampuan para murid dalam menulis teks recount

Enumerating Subgraph Instances Using Map-Reduce

The theme of this paper is how to find all instances of a given "sample" graph in a larger "data graph," using a single round of map-reduce. For the simplest sample graph, the triangle, we improve upon the best known such algorithm. We then examine the general case, considering both the communication cost between mappers and reducers and the total computation cost at the reducers. To minimize communication cost, we exploit the techniques of (Afrati and Ullman, TKDE 2011)for computing multiway joins (evaluating conjunctive queries) in a single map-reduce round. Several methods are shown for translating sample graphs into a union of conjunctive queries with as few queries as possible. We also address the matter of optimizing computation cost. Many serial algorithms are shown to be "convertible," in the sense that it is possible to partition the data graph, explore each partition in a separate reducer, and have the total computation cost at the reducers be of the same order as the computation cost of the serial algorithm.Comment: 37 page

A New Framework for Join Product Skew

Different types of data skew can result in load imbalance in the context of parallel joins under the shared nothing architecture. We study one important type of skew, join product skew (JPS). A static approach based on frequency classes is proposed which takes for granted the data distribution of join attribute values. It comes from the observation that the join selectivity can be expressed as a sum of products of frequencies of the join attribute values. As a consequence, an appropriate assignment of join sub-tasks, that takes into consideration the magnitude of the frequency products can alleviate the join product skew. Motivated by the aforementioned remark, we propose an algorithm, called Handling Join Product Skew (HJPS), to handle join product skew

A measure of the investment climate in South Africa

Magister Scientiae - MScInvestor confidence is a concept many investors are constantly trying to gauge. In practice however these concepts are usually not easy to measure. This study attempts to capture the total sum of investor perception in South Africa by examining market behaviour. Data from the JSE/FTSE (1995-2009) will be used to determine an Equity Risk Premium. Bond Yield Spreads will also be calculated from data provided by I-NET BRIDGE. An amalgamation of these components will produce the proposed Investment Confidence Index. Similar indices currently on the South African Market are based on subjective surveys and might therefore be biased. The proposed index which is a first in SA will prove invaluable to practitioners in the financial sector.South Afric