Ekstraksi Data pada Tabel dari Halaman Web Menggunakan Pohon Document Object Model

Akbar, Memen; Patmala, Cici; Nurmalasari, Dini

doi:10.22146/jnteti.v5i4.273

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…Penelitian dilakukan dengan cara melakukan studi literatur terlebih dahulu diantaranya pada penelitian Irawan menjelaskan tentang penggunaan web crawler untuk mengambil data -data Google Playstore yang nantinya data tersebut dibuatkan web service agar dapat diakses dengan cara cross platform [6]. Penelitian Akbar dkk menjelaskan tentang penggunaan Document Object Model (DOM) untuk dilakukan ekstraksi halaman web dengan metode penelurusan Dept Fist Search (DFS) dan hasilnya aplikasi yang dibuat dapat melakukan ekstraksi data [7]. Penelitian Negara dkk menjelaskan tentang data ekstraksi twitter untuk mengambil data lokasi awal kemunculan terhadap sebuah isu di media sosial proses yang dilakukan pertama dengan melakukan penarikan data (crawling) , penyimpanan, analisis dan visualisai, dan hasil penelitian bersifat exploratory sebagai upaya sumbangsih pengembangan teknologi ekstraksi data twitter geospasial [8].…”

Section: Penelitian Terdahuluunclassified

Ekstraksi Data Produk E-Marketplace Sebagai Strategi Pengolahan Segmentasi Pasar Menggunakan Web Crawler

Surahman¹,

Octaviansyah²,

Darwis³

2020

SISTEMASI

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ABSTRCT Market Situation is something that will provide valuable benefits to increase the productivity of selling a product both conventionally and online, Indonesian e-commerce map data in the second quarter shows that the increase in sales of goods and services online is increasing, it was seen from 3 (three) major e-marketplaces namely Tokopedia, Shopee, and Bukalapak, then e-commerce activities in Indonesia in January 2019 for purchasing products or service online by 86%, it means that 86% of activities will buy products and services which located in Indonesian e-commerce. This situation creates fierce competition for sellers or business people or entrepreneurs who are just starting their business. One way for sellers to get a primacy in this competition is to apply segmentation to the products that they will sell in the online shop, but the data from a study by the association revealed that if a product stays online for a long time (more than 550 days) then 78% is very likely not to be purchased, the product placement activity in the online shop must be segmented appropriately, this research provided an effort to apply data extraction technology with web crawlers to present the segmentation, and the results of prototype testing to 9 entrepreneurs, 210 students who will start an online business, and 19 private employees which produce web crawler technology testing to help product segmentation with the result of successful was 79% with the Good category in laying online product was segmented.

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Section: Penelitian Terdahuluunclassified

Ekstraksi Data Produk E-Marketplace Sebagai Strategi Pengolahan Segmentasi Pasar Menggunakan Web Crawler

Surahman¹,

Octaviansyah²,

Darwis³

2020

SISTEMASI

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“…Data awal yang ditarik dari database mencapai 4.790 data namun setelah dilakukan pemilihan tahap pertama data yang terpilih sebanyak 1.017 data. Data SQL diproses convert terlebih dahulu dan dapat diambil file dengan format Comma Separated Values (CSV) sehingga bisa dibuka dengan aplikasi Notepad, Wordpad, ataupun MS Excel[20].…”

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Analisis Trend Berita Media Online di Masa Pandemi Covid-19 dengan Metode Monte Carlo

Lima

Hustinawati

2023

Jur. Ris. Kom.

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The News reports for online media always follows the trending issues that are actually predictable. In general, online media news apart from presenting various events that have occurred, also focuses on reporting issues which is of concern to the public. During the Covid-19 pandemic, almost all mass media, including online media, continued to report various news about the Covid-19 case and its impact on society. The problem is how to understand the news accumulation in a certain period of time to find out the trend in reporting on Covid-19. Because the news has resulted in a huge accumulation of data related to Covid-19 news which can be used to build data mining. The purpose of this study is to analyze online media coverage during the Covid-19 pandemic using the Monte Carlo method to find out news trends. The process uses a data mining approach by collecting a lot of data from existing reports and processing the data to find important information from the data set. The data used to analyze news trends were taken from the main news on the online media Suarapembaruan.com for seven (7) months and processed using knowledge discovery in database (KDD) techniques. The Monte Carlo method is applied to data mining to calculate probability values or possible values that will occur in the future. The results of this study indicate that the trend of news related to Covid-19 in the future will be dominated by News on the Handling of Covid-19 with a trend percentage rate of 23.12 percent. Meanwhile, the news about the Covid-19 Case and the Impact of Covid-19 was getting lower with a trend rate of 21.82 percent and 19.22 percent. Meanwhile, The Other News with related to Covid-19 has a higher trend percentage of 35.84 percent

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“…Penelitian mengenai ekstraksi bagian tabel dari sebuah halaman web telah banyak dilakukan. Namun, sedikit sekali yang membahas mengenai ekstraksi tabel yang berbentuk column-row wise, di antaranya adalah (Akbar, et al, 2015) dan (Akbar, et al, 2016). Tabel yang berbentuk column-row wise diekstrak menjadi sebuah tabel baru dengan mengasumsikan bagian atribut yang terdapat pada baris pertama sebagai atribut dan menambahkan satu nama atribut untuk bagian ini.…”

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Ekstraksi Tabel HTML Bentuk Column-Row Wise ke dalam Basis Data

Akbar

Wibowo

2018

JTIIK

Self Cite

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Pada halaman web, tabel adalah bagian penting dari masalah yang dijelaskan dalam sebuah artikel. Tabel yang terdapat pada halaman web berbeda dari tabel dalam basis data. Tabel di halaman web cenderung tidak memiliki aturan atau bentuk standar. Salah satu bentuk tabel yang tidak standar pada halaman web adalah column-row wise. Penelitian ini menawarkan pendekatan untuk mengekstraksi isi tabel sedemikian sehingga arti dari keterkaitan antara dua atribut dan data dalam tabel column-row wise tidak hilang. Data yang diekstrak disimpan ke dalam basis data yang membentuk tiga tabel, yaitu tabel yang menyimpan atribut pertama, tabel yang menyimpan atribut kedua, dan tabel yang menyimpan atribut pertama, kedua, dan data dari atribut pertama dan kedua. Penelitian ini menghasilkan sebuah algoritma untuk mengekstrak data dari tabel yang berbentuk column-row wise pada sebuah halaman web. Algoritma yang dihasilkan dari penelitian ini diharapkan dapat diimplementasikan dalam berbagai bahasa pemrograman. Untuk pengujian, algoritma telah diimplementasikan dengan Bahasa pemrograman Python dan berhasil melakukan ekstraksi tabel dan menyimpannya dalam basis data. Abstract Tables are an important part of a web page. The table contains tabulations of data or information that you want to convey from the web page. This data tabulation can be used for comparisons with similar tables or as a trigger for action. However, tables on web pages are independent of webpage makers. There is no standard form or layout for a table on a web page. One of the table layouts on a web page is column-row wise. This study offers an approach for extracting table contents such that the meaning of the linkage between two attributes and a data in the column-row wise table is not disappeared. The extracted data is stored into a database that forms three tables, ie the table that stores the first attribute, the table that stores the second attribute, and the table that stores the first, second, and second attributes of the two attributes. Output of this research is an algorithm to extract data of column-row wise table in a web page. The algorithm generated from this research is expected to be implemented in various programming languages. For testing, the algorithm is implemented in Python and success to extract table and save the data into database. Cyclomatic complexity number of the proposed algorithm is 12. This means that the complexity of the proposed algorithm is still high.

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Ekstraksi Data pada Tabel dari Halaman Web Menggunakan Pohon Document Object Model

Cited by 4 publications

References 4 publications

Ekstraksi Data Produk E-Marketplace Sebagai Strategi Pengolahan Segmentasi Pasar Menggunakan Web Crawler

Ekstraksi Data Produk E-Marketplace Sebagai Strategi Pengolahan Segmentasi Pasar Menggunakan Web Crawler

Analisis Trend Berita Media Online di Masa Pandemi Covid-19 dengan Metode Monte Carlo

Ekstraksi Tabel HTML Bentuk Column-Row Wise ke dalam Basis Data

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