Pearson Correlation Method and Web Scraping for Analysis of Islamic Content on Instagram Videos

Uriawan, Wisnu; Wahana, Agung; Wulandari, Diah Ayu Retnani; Darmalaksana, Wahyudin; Anwar, Rosihon

doi:10.1109/icwt50448.2020.9243626

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…Dalam prosesnya, penelitian ini dapat memanfaatkan sumber daya digital yang website yang didalamnya terkandung submber daya aksara bali yang dapat diekstraksi sesuai dengan kebutuhan, yang memberikan aksesibilitas yang lebih tinggi terhadap sumber data. Dengan menggunakan web scraping, penelitian ini memungkinkan pengumpulan data secara cepat, efisien, dan skalabilitas yang besar [29], sehingga memungkinkan analisis yang lebih mendalam tentang aksara Bali dalam berbagai konteks, termasuk pengenalan karakter, analisis linguistik, pengembangan aplikasi berbasis aksara Bali, dan penelitian budaya Bali [30].…”

Section: Dalamunclassified

Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition

Nugraha,

Asroni,

Dewi

et al. 2023

jurnalresistor

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Dataset gambar aksara Bali yang besar dan komprehensif adalah sumber daya penting dalam upaya pemeliharaan warisan budaya Bali serta pengembangan aplikasi terkait. Dataset ini memungkinkan analisis mendalam, pengenalan karakter, pemrosesan bahasa, dan pengujian aplikasi seperti pengenalan tulisan otomatis, pengajaran otomatis, dan pemahaman bahasa, yang semuanya mendukung kemajuan dalam pelestarian warisan budaya Bali. Metode penelitian untuk menghasilkan dataset aksara Bali melibatkan akses ke sumber data, analisis struktur web, dan penerapan teknik web scraping dengan JavaScript untuk pengambilan gambar secara otomatis. Dua tahap utama, yaitu inisiasi dan pengumpulan data, memungkinkan pengumpulan dataset dalam jumlah besar dengan efisiensi tinggi, mempercepat proses pengumpulan data dan meningkatkan akurasi dalam penelitian aksara Bali. Data yang digunakan berasal dari kamus bahasa Bali, bahasa Indonesia, dan bahasa Inggris, dengan total 35.319 kata dalam bahasa Bali, yang kemudian dikonversi menjadi aksara Bali. Hasil dari pembuatan dataset ini mencakup 35.319 pasang data berupa gambar teks aksara Bali dan tesk transliterasinya, memiliki potensi besar untuk pelatihan model pengenalan aksara Bali dan penelitian bahasa Bali. Langkah ini menguatkan ketersediaan dataset yang relevan, berkualitas tinggi, dan memiliki nilai signifikan dalam pengembangan teknologi serta penelitian lebih lanjut di bidang bahasa Bali dan pengenalan aksara Bali.

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Section: Dalamunclassified

Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition

Nugraha,

Asroni,

Dewi

et al. 2023

jurnalresistor

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“…In a survey conducted by the Indonesian Internet Service User Association (APJII), active social media users were 196.71 million from 266.91 million users in 2020 [1]. The average time users spend surfing in cyberspace per day is more than 5 hours.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Classification Algorithms for Cyberbullying Crime Detection: An Experimental Study of Twitter Social Media in Indonesia

Muzakir

Syaputra

Panjaitan

2022

SJI

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Purpose: This research aims to identify content that contains cyberbullying on Twitter. We also conducted a comparative study of several classification algorithms, namely NB, DT, LR, and SVM. The dataset we use comes from Twitter data which is then manually labeled and validated by language experts. This study used 1065 data with a label distribution, namely 638 data with a non-bullying label and 427 with a bullying label.Methods: The weighting process for each word uses the bag of word (BOW) method, which uses three weighting features. The three-word vector weighting features used include unigram, bigram, and trigram. The experiment was conducted with two scenarios, namely testing to find the best accuracy value with the three features. The following scenario looks at the overall comparison of the algorithm's performance against all the features used.Result: The experimental results show that for the measurement of accuracy weighting based on features and algorithms, the SVM classification algorithm outperformed other algorithms with a percentage of 76%. Then for the weighting based on the average recall, the DT classification algorithm outperformed the other algorithms by an average of 76%. Another test for measuring overall performance (F-measure) based on accuracy and precision, the SVM classification algorithm, managed to outperform other algorithms with an F-measure of 82%.Value: Based on several experiments conducted, the SVM classification algorithm can detect words containing cyberbullying on social media.

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Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System

Shi-biao¹,

Yong

2021

Sensors

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6G vehicle-to-everything (V2X) communication will be combined with vehicle automatic driving technology and play an important role in automatic driving. However, in 6G V2X systems, vehicle users have the characteristics of high-speed movement. Therefore, how to provide stable and reliable wireless link quality and improve channel gain has become a problem that must be solved. To solve this problem, a new multi-user scheduling algorithm based on block diagonalization (BD) precoding for 6G ultra-massive multiple-input multiple-output (MIMO) systems is proposed in this paper. The algorithm takes advantage of the sensitive nature of BD precoding to channel correlation, uses the Pearson coefficient after matrix vectorization to measure the channel correlation between users, defines the scheduling factor to measure the channel quality according to the user noise enhancement factor, and jointly considers the influence of the correlation between user channels and channel quality, ensuring the selection of high-quality channels while minimizing channel correlation. Simulation results show that compared with the multi-user scheduling algorithm based on subspace correlation, condition number, and geometric angle, the proposed algorithm can obtain higher user channel gain, effectively reduce the system bit error rate, and can be applied to 6G V2X communication.

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Pearson Correlation Method and Web Scraping for Analysis of Islamic Content on Instagram Videos

Cited by 3 publications

References 27 publications

Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition

Pembangkitan Dataset Aksara Bali Menggunakan Web Scrapping untuk Pengenalan Aksara Bali Berbasis Optical Character Recognition

A Comparative Analysis of Classification Algorithms for Cyberbullying Crime Detection: An Experimental Study of Twitter Social Media in Indonesia

Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System

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