Implementasi Web Crawling untuk Mengumpulkan Informasi Wisata Kuliner di Bandar Lampung

Hanifah, Raidah; Nurhasanah, Isye Susana

doi:10.25126/jtiik.201855842

Cited by 4 publications

(3 citation statements)

References 0 publications

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“…The review dataset in this study was taken from the DXOMARK website for reviews made by those who have done the research, and this site focuses on providing reviews of cameras and displays. Retrieval of review data using manual methods, not automatic data retrieval methods from other websites or a web crawling system [19]. The review data taken were 223 smartphone review data and five different review content.…”

Section: Dataset Review (Origin Of the Dataset)mentioning

confidence: 99%

Smartphone Purchase Recommendation System Using the K-Nearest Neighbor (KNN) Algorithm

Setiaji

Utama²,

Adiwijaya³

2022

mib

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Indonesia is in the fourth position of the countries with the most smartphone users worldwide. Smartphones are needed in today's modern times. Smartphones are also used not only for long-distance communication but also for carrying out daily work. Smartphones are currently used for study and work and also become entertainment to play. Therefore, smartphones are very much sought after for the suitability of users who carry out their daily activities. So this research is very helpful for users to find smartphones that support their daily activities such as studying, working, and playing. This research is based on a website that can make it easier for users to see their smartphone recommendations directly. The analysis uses the K-Nearest Neighbor (KKN) method to see the ratings reviewed by other users who have tried using their smartphones with different phone brands. The calculation method in the current study uses 3 KNN calculations and uses the concept of combining calculations to find the maximum recommendation results. The result of the recommendation system using the K-Nearest Neighbor method is in the form of a review stating whether the user agrees or disagrees. In the current study, there have been 100 reviews from users, and it has a percentage of 78% for success and 22% for failure.

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Section: Dataset Review (Origin Of the Dataset)mentioning

confidence: 99%

Smartphone Purchase Recommendation System Using the K-Nearest Neighbor (KNN) Algorithm

Setiaji

Utama²,

Adiwijaya³

2022

mib

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“…Crawling data merupakan proses pengumpulan data yang akan digunakan untuk menjelajahi web dan mengunduh halaman web secara otomatis untuk mengumpulkan informasi [11].…”

Section: Crawling Dataunclassified

Penerapan Algoritma Katz Pada Struktur Komunitas Jejaring Sosial Twitter

Sari,

Kurniati

2022

JBKom

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Social Network Analysis (SNA) merupakan sebuah studi yang mempelajari tentang hubungan manusia dengan memanfaatkan teori graf. SNA dapat menemukan beberapa komunitas dan besar pengaruh sentralitas pada komunitas dalam jejaring sosial. Namun seberapa besar ukuran dari jaringan komunitas, kepadatan jaringan, dan resiprositas dari jaringan komunitas serta berapa banyak jumlah akun sebagai important user pada suatu komunitas dalam jaringan sosial sampai saat ini belum pernah dilakukan. Penelitian ini bertujuan untuk mengidentifikasi ukuran dari dari jaringan komunitas, kepadatan jaringan, dan resiprositas dari jaringan komunitas dan mengidentifikasi jumlah akun sebagai important user pada suatu komunitas dalam jaringan sosial. Sampel yang digunakan adalah pengguna twitter yang melakukan posting atau melakukan mention dengan kata kunci “Jokowi”. Penarikan data sampel menggunakan teknik systematic random sampling. Analisis yang dilakukan menggunakan metode algoritma Katz. Berdasarkan hasil penelitian, bahasa pemprograman phyton dan algoritma katz berhasil menemukan ukuran dari jaringan komunitas dengan kata kunci “jokowi” sejumlah 4052 nodes. Kepadatan jaringan rendah yaitu 0,0002 jika dibulatkan menjadi 0 (nol). Resiprositas pada penelitian ini yaitu berlangsung dua arah. Diameter jaringan pada penelitian ini adalah 6 dan jarak / Average Path length yaitu 2.23 dan terdapat 12 akun sebagai important users.

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“…Penelitian lainnya adalah melakukan akuisisi data untuk mengumpulkan informasi wisata kuliner [10]. Hal ini berguna untuk menangkap peluang bisnis wisata kuliner dengan cara pemetaan lokasi wisata kuliner strategis.…”

Section: Penelitian Terdahuluunclassified

Analisa Jenis Interaksi Masyarakat dengan Akuisisi Data Sosial Media Pemerintah KAB/Kota Provinsi Riau

Najwa

Yuliska

Syaliman

2020

JKT

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This study aims to analyze the type of interaction which is done by acquiring City/District Government’s Facebook Fan page. The acquisition of Facebook Fan page is performed by identifying the number of followers, the number of likes of the page, the number of postings, the number of comments, the number of shared postings and the number of likes of postings. We perform the acquisition in 90 days. Based on the result of data acquisition on 13 Cities/Districts in Riau Province, it indicates that 100% City/District Governments have performed One-Way Push Interaction and 70% of them classified as Two-Way Pool interaction. As for network co-designer of service Interaction, we found that Bengkalis District is the most active in implementing this type of interaction. Based on the results of analyzing the type of interaction between citizens and local governments in Riau Province, most of the Social media Fan Page of local governments are passive. The Collaboration of governments and citizens, which is based on the number of shared postings is classified as low. The next study may discuss the strategy that can be implemented by the governments to maximize the use of social media as media to interact and communicate with the citizens.

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Implementasi Web Crawling untuk Mengumpulkan Informasi Wisata Kuliner di Bandar Lampung

Cited by 4 publications

References 0 publications

Smartphone Purchase Recommendation System Using the K-Nearest Neighbor (KNN) Algorithm

Smartphone Purchase Recommendation System Using the K-Nearest Neighbor (KNN) Algorithm

Penerapan Algoritma Katz Pada Struktur Komunitas Jejaring Sosial Twitter

Analisa Jenis Interaksi Masyarakat dengan Akuisisi Data Sosial Media Pemerintah KAB/Kota Provinsi Riau

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