1,720,955 research outputs found
Implementasi algoritma CNN untuk mendeteksi pelafalan huruf hijaiyah berharakat kasrah
Full text linkINDONESIA:
Sebagai seorang muslim yang baik dianjurkan untuk senantiasa membaca al-Quran dengan benar setidaknya sepuluh ayat setiap hari. Al-Qur’an disusun dengan huruf hijaiyah dengan makhraj yang berbeda. Selain itu terdapat harakat yang digunakan untuk mempermudah membaca huruf arab. Namun tidak semua orang islam mampu melafalkan bacaan al-Qur’an dengan benar. Penelitian ini mengusulkan sebuah metode yang mampu mengenalkan dan mengajarkan lafal huruf hijaiyah menggunakan teknologi speech recognition yang dapat mengenali suara baik per kata maupun per kalimat. Suara kemudian diekstraksi menggunakan model Mel- frequency cepstral coefficients (MFCC) dan selanjutnya diklasifikasikan menggunakan model deep learning dengan algoritma CNN. Penelitian ini berhasil mengklasifikasikan harakat kasrah menggunakan CNN dengan metode MFCC dengan kinerja terbaik pada akurasi 62.45%, presisi 75%, recall 50% dan f1-score sebesar 58%.
ENGLISH:
As a good Muslim it is recommended to always read Al-Qur'an correctly at least ten verses every day. Al-Qur'an is arranged in hijaiyah letters with different makhraj. In addition there is a vowel that is used to make it easier to read Arabic letters. However, not all Muslims are able to pronounce the recitation of Al-Qur'an correctly. This study proposes a method that is able to introduce and teach hijaiyah pronunciation using speech recognition technology that can recognize sounds both words and sentences. The sound is then extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This study has succeeded in classifying the harakat kasrah using CNN with the MFCC method with the best performance at an accuracy of 62.45%, 75% precision, 50% recall and an f1-score of 58%
XGBoost and Convolutional Neural Network Classification Models on Pronunciation of Hijaiyah Letters According to Sanad
Full text linkAccording to Sanad, the pronunciation of Hijaiyah letters can serve as a benchmark for correct or valid reading based on the makhraj and properties of the letters. However, the limited number of Qur\u27anic Sanad teachers remains one of the obstacles to learning the Qur\u27an. This study aims to identify the most practical combination of classification models in constructing a voice recognition system that facilitates learning without requiring direct interaction with a teacher. The methods employed include the XGBoost algorithm and CNN. As a result, out of the 12 letter trait labels, the CNN model was utilized for 10 of them, specifically for traits S1, S2, S4, S5, T1, T2, T3, T4, T5, and T6, on trait labels S3 and T7 applying the XGBoost model. Furthermore, the inclusion of additional data yielded performance results for each property, with an average accuracy of 78.14% for property S (letters with opposing properties), 70.69% for property T (letters without opposing properties), and an overall average of 73.79% per letter.Huruf Hijaiyah adalah huruf yang terdapat dalam susunan Al-Qur\u27an. Karakter huruf hijaiyah adalah kenampakan karakter yang keluar dari makhrajnya, sedangkan huruf makharijul adalah tempat keluarnya huruf saat melafalkan huruf hijaiyah. Huruf Hijaiyah yang ada dalam Sanad dapat dijadikan sebagai patokan bacaan yang benar atau sahih karena sudah memenuhi ciri dan makna huruf tersebut. Terbatasnya jumlah pengajar Al-Qur\u27an masih menjadi salah satu kendala dalam mempelajari Al-Qur\u27an dengan baik. Hal ini ditunjukkan dengan sedikitnya pengajaran Al-Qur\u27an pada Sanad yang membuka pembelajaran tahsin, padahal pembelajaran tahsin pada Sanad merupakan salah satu pelajaran yang memiliki standar dalam pengucapan kaidah huruf sesuai dengan sifat hurufnya. Sistem pengenalan suara dapat mengenali suara sehingga dengan teknologi ini diharapkan dapat mendukung pembelajaran tanpa harus bertemu dengan guru. Pada penelitian ini dibangun model klasifikasi huruf hijaiyah berdasarkan karakteristik huruf menggunakan algoritma pembelajaran dangkal XGBoost dan algoritma pembelajaran mendalam CNN. CNN cenderung menghasilkan kinerja yang lebih baik daripada Extreme Gradient Boosting (XGBoost). Model algoritme XGBoost memiliki akurasi superior pada properti S2 dan T7. Namun, memorinya rendah. Penambahan data memberikan keseimbangan terhadap hasil kinerja sehingga nilai akurasi, presisi, memori, dan skor F-1 memiliki tingkat yang cukup. Akurasi untuk sifat S rata-rata 78,14%, properti T 70,69%, dan rata-rata per huruf 73,79%
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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