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PROCESS GENRE APPROACH IN TEACHING WRITING NARRATIVE TEXT: ITS IMPLEMENTATION, BENEFITS AND OBSTACLES (A Qualitative Research at a Senior High School in Cianjur) Elis Homsini Maolida; Pauziah Aisah Al Azhar
Jurnal JOEPALLT (Journal of English Pedagogy, Linguistics, Literature, and Teaching) Vol 7, No 2 (2019)
Publisher : Universitas Suryakancana

Nowadays, teachers should be more creative and innovative in teaching.In the real condition, students still have difficulties in writing class. To improve students’ writing ability in writing various genres of text, the teacher should choose an innovative strategy. Process genre is one of the approaches commonly used in teaching writing. This research aims to find outthe useof Process Genre Approach in teaching the narrative text as well asthe benefitsand obstacles of using Process Genre Approach in teaching narrative text. This research applied qualitative research. The data of this research were collected from three instruments:classroom observation, questionnaire, and interview. This research was carried out in a senior high school in Cianjurby involving twenty-three students of ten-grade and an English teacher.The first finding shows that in applying process genre approach in teaching writing of narrative text, there were six steps conducted by the teacher following Badger and White (2000) steps: preparation, modeling, planning, join constructing, independent constructing, and revising and editing. The second finding showsthat there were some benefits of using Process Genre Approach in teaching writing narrative text. Teacher’s interview reveals that the benefits of using process genre approach in teaching writing narrative text were the students can write a text step by step and the students not only can write a text but they can learn about a genre of text in detail. In addition, students questionnaire discloses several benefits of using process genre approach in teaching writing narrative text such as the students are easier to write a text and the students can make a text in detail. The last finding shows there were two obstacles, the first was students’low grammar mastery and the second was students low vocabulary mastery.

Developing Evaluative Descriptive Text with Rebecca M. Valetteâ€™s Taxonomy and CLIL Approach Khomsah, Arin Nur; Subyantoro, Subyantoro
Seloka: Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol 8 No 2 (2019): August 2019
Publisher : Pascasarjana Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (377.252 KB)

Learning evaluation  is an important factors of learning success. The results of monitoring and evaluating the implementation of the 2013 curriculum at the junior high school level in 2014 showed that one of the difficulties of educators in implementing the 2013 curriculum was assessment. The purpose of this study was to analyze the needs of teachers, produce characteristics, produce tools, find out the effectiveness of evaluation tools in composing description text with the taxonomy of Rebecca M. Valette and CLIL approach for grade VII junior high school students. The research method used in this study was the Research and Development research design (research and development) from Borg and Gall. The evaluation tools compiled description texts using Rebecca M. Valette's taxonomy and the CLIL approach were stated to be effective and feasible to assess aspects of the knowledge, attitudes, and skills of Indonesian language learning in seventh grade junior high schools, especially the basic competencies in composing description texts. This is because in this tool has been equipped with the aim of learning Indonesian language which includes aspects of language, culture, and communication in accordance with the 2013 curriculum. It was expected this evaluative instrument could  support  assessment of Indonesian language learning in 2013 curriculum  based on text.

The Effect Of Applying Somatic Auditory Visual (SAVI) Approach On Students’ Speaking Achievement In Oral Descriptive Text Of 2018/2019 Eleventh Year Students’ Of SMA Yayasan Pendidikan Harapan Bangsa Kabupaten Langkat Ummi Umara -
Jurnal Serunai Bahasa Inggris Vol 10, No 2 (2018): Jurnal Serunai Bahasa Inggris
Publisher : STKIP Budidaya Binjai

ABSTRACT This study is conducted as an attempt to find out the effect of applying SAVI approach on Students’ speaking Achievement in oral descriptive text. This study used the experimental design. The population of this study is the students of SMA Yayasan Pendidikan Harapan Bangsa . The sample of this study was the 2018/2019eleventh grade students of SMA Yayasan Pendidikan Harapan Bangsa . This study is conducted with two randomized groups namely experimental group and control group. The control group is taught by conventional method while experimental group is taught by applying SAVI Approach. The instrument used in this study was an oral test. To obtain the reliability of the test, the researcher used t-test formula.. The data were analyzed by using t-test. The calculation shows that t-observed (2.50) is higher than t-table (1.666) at the level of significance (α) 0.05 with the degree of freedom (df) 74. Therefore, null hypothesis (Ho) is rejected and alternative hypothesis (Ha) is accepted. It means that SAVI approach significantly affect the students’ speaking achievement in oral descriptive text.

A Novel Hybrid Classification Approach for Sentiment Analysis of Text Document Yassine Al Amrani; Mohamed Lazaar; Kamal Eddine El Kadiri
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Sentiment analysis is a more popular area of highly active research in Automatic Language Processing. She assigns a negative or positive polarity to one or more entities using different natural language processing tools and also predicted high and low performance of various sentiment classifiers. Our approach focuses on the analysis of feelings resulting from reviews of products using original text search techniques. These reviews can be classified as having a positive or negative feeling based on certain aspects in relation to a query based on terms. In this paper, we chose to use two automatic learning methods for classification: Support Vector Machines (SVM) and Random Forest, and we introduce a novel hybrid approach to identify product reviews offered by Amazon. This is useful for consumers who want to research the sentiment of products before purchase, or companies that want to monitor the public sentiment of their brands. The results summarize that the proposed method outperforms these individual classifiers in this amazon dataset.

Memetic algorithm for short messaging service spam filter using text normalization and semantic approach Arnold Adimabua Ojugo; Andrew Okonji Eboka
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Today’s popularity of the short messages services (SMS) has created a propitious environment for spamming to thrive. Spams are unsolicited advertising, adult-themed or inappropriate content, premium fraud, smishing and malware. They are a constant reminder of the need for an effective spam filter. However, SMS limitations of 160-charcaters and 140-bytes size as well as its being rippled with slangs, emoticons and abbreviations further inhibits effective training of models to aid accurate classification. The study proposes Genetic Algorithm Trained Bayesian Network solution that seeks to normalize noisy feats, expand text via use of lexicographic and semantic dictionaries that uses word sense disambiguation technique to train the underlying learning heuristics. And in turn, effectively help to classify SMS in spam and legitimate classes. Hybrid model comprises of text preprocessing, feature selection as well as training and classification section. Study uses a hybrid Genetic Algorithm trained Bayesian model for which the GA is used for feature selection; while, the Bayesian algorithm is used as classifier.

Text Wrapping Approach to natural Language Information retrieval using significant Indicator Toyin Enikuomehin; J S Sadiku
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 3: September 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (226.656 KB)

This paper continues the advancement of models proposed for Information Retrieval by understanding that, the Information Retrieval task continues to draw attention as the information repositories increase. Knowing that Natural Language presentation of user’s information need help to reduce the complexity of the search process, we propose the use of a well defined Significant Indicator, which uses the relevance index of terms derived from the position of the text, to perform retrieval. This is achieved by initiating a text wrapping process such that document representation in space could algebraically be measured and assigned appropriate function as similarity ratio for Query and Document. Benchmark tools for Information Retrieval were followed and experiment performed using TREC classified data implemented with TRECEVAL shows better performance against some baseline models. The paper suggests further research in the direction of the Significant Indicator as a method for large search space reductionDOI: http://dx.doi.org/10.11591/ij-ai.v2i3.2202

An Approach for Risk Estimation in Information Security Using Text Mining and Jaccard Method Prajna Deshanta Ibnugraha; Lukito Edi Nugroho; Paulus Insap Santosa
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Involvement of digital information in almost of enterprise sectors makes information having value that must be protected from information leakage. In order to obtain proper method for protecting sensitive information, enterprise must perform risk analysis of threat. However, enterprises often get limitation in measuring risk related information security threat. Therefore, this paper has goal to give approach for estimating risk by using information value. Techniques for measuring information value in this paper are text mining and Jaccard method. Text mining is used to recognize information pattern based on three classes namely high business impact, medium business impact and low business impact. Furthermore, information is given weight by Jaccard method. The weight represents risk levelof information leakage in enterprise quantitatively. Result of comparative analysis with existing method show that proposed method results more detailed output in estimating risk of information security threat.

Technical Approach in Text Mining for Stock Market Prediction: A Systematic Review Mohammad Rabiul Islam; Imad Fakhri Al-Shaikhli; Rizal Bin Mohd Nor; Vijayakumar Varadarajan
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 2: May 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i2.pp770-777

Text mining methods and techniques have disclosed the mining task throughout information retrieval discipline in the field of soft computing techniques. To find the meaningful information from the vast amount of electronic textual data become a humongous task for trading decision. This empirical research of text mining role on financial text analysing in where stock predictive model need to improve based on rank search method. The review of this paper basically focused on text mining techniques, methods and principle component analysis that help reduce the dimensionality within the characteristics and optimal features. Moreover, most sophisticated soft-computing methods and techniques are reviewed in terms of analysis, comparison and evaluation for its performance based on electronic textual data. Due to research significance, this empirical research also highlights the limitation of different strategies and methods on exact aspects of theoretical framework for enhancing of performance.

Liberal Thought in Qur’anic Studies: Tracing Humanistic Approach to Sacred Text in Islamic Scholarship M. Nur Kholis Setiawan
Al-Jami'ah: Journal of Islamic Studies Vol 45, No 1 (2007)
Publisher : Al-Jami'ah Research Centre

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ajis.2007.451.1-28

Literary approach to the Quran developed by al-Khuli created deep critiques from its opponents, in whose opinion, the usage of literary paradigm to the study of the Qur’an, according to them, implied a consequence of treating the Qur’an as a human text which clearly indicates a strong influence of a liberal mode of thinking that goes out of the line of the Qur’an’s spirit. This article shows a diametric fact compared to that they have claimed. The data proves that linguistic aspects of the Qur’an have succeeded in making an intellectual connection among progressive and liberal scholars in the classical and modern era. This supports the assumption that progressive and liberal thought whose one of its indicators is freedom of thought in accordance to Charles Kurzman term, is “children” of the Islamic civilization. Freedom of thought in the classical Islamic scholarship should be the élan of intellectualism including the field of Quranic studies.

INDONESIAN TEXT DATASET FOR DETERMINING SENTIMENT CLASSIFICATION USING MECHINE LEARNING APPROACH Syahputra, Indra Edy; Tulus, Tulus; Efendi, Syahril
JITE (JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING) Vol 3, No 2 (2020): EDISI JANUARI
Publisher : Universitas Medan Area

Advances in information technology encourage the emergence of unlimited textual information with the use of online media developing so rapidly that the emergence of the need for information presentation without reducing the value of the information presented. Basicaly the concept of the dataset is a general form of almost every discipline, where the dataset provides empirical basic information for research activities. Sentiment analysis is done to see opinions or feelings about a problem or identify and classify information trends from the problem. The dataset analysis in determining sentiment classification is a model of sentiment classification that has relevance to the dataset with the use of machine learning techniques with supervision that learns from experience to predict output from labeled input data and output from machine learning. The results of experiments and tests that have been carried out on machine learning techniques with supervision can classify sentiments in the tweet text properly and the level of accuracy can still be improved to a better direction with data namely baseline 100 (days) and 83 (weeks), naivebayes 100 (days) and 82 (weeks), maxent 100 (days) and 83 (weeks), and SVM 100 (days) and 83 (weeks).

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