Ekstraksi Informasi Destinasi Wisata Populer Jawa Timur Menggunakan Depth-First Crawling

Kristanto, Sepyan Purnama; Hakim, Lutfi

doi:10.30812/matrik.v21i1.1081

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Terdapat banyak tempat wisata alam dan buatan yang tersebar dibeberapa Kabupaten, membuat Jawa Timur berkembang dari aspek pariwisata. (Kristanto, Sepyan Purnama et al, 2020). Provinsi Jawa Timur memiliki 29 Kabupaten dan 9 Kota.…”

Section: Research Article E-issn: 2541-6130 P-issn: 2541-2523unclassified

Tourism Marketing: Banyuwangi Regency Government Partnership with Local Mass Media in Banyuwangi

Niko Pahlevi Hentika,

Erna Agustina

2024

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Banyuwangi Regency is one of the districts that is currently aggressively developing tourism potential. This development has been carried out since Regent Abdullah Azwar Anas. This is because the natural and cultural potential that Banyuwangi has is very good for tourism. One way to develop this is through partnerships in various fields. One of the most important areas in tourism development is partnerships in the field of tourism marketing. The partnership carried out so far is between the Banyuwangi Regency government and local mass media. Because of the above phenomenon, this qualitative-descriptive research is deemed necessary. The main aim of this research is to describe, analyze and interpret the partnership between the Banyuwangi Regency Government and local mass media in tourism marketing governance in Banyuwangi. Data collection methods were carried out by interviews, documentation and observation. The research results show that the two partnering parties, namely the Banyuwangi Regency Government and the local mass media play a mutual role. In addition, the model partnership between governments Banyuwangi and local mass madia is mutualism partnership

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Section: Research Article E-issn: 2541-6130 P-issn: 2541-2523unclassified

Tourism Marketing: Banyuwangi Regency Government Partnership with Local Mass Media in Banyuwangi

Niko Pahlevi Hentika,

Erna Agustina

2024

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“…Pada penelitian ini dikembangkan aplikasi berbasis web yang digunakan untuk mengelola model deteksi, kelola dataset dan kelola data artikel dan informasi obat yang didapatkan dari proses web crawling. Untuk teknik web crawling ini sendiri sudah diimplementasikan di beberapa penelitian terdahulu seperti crawling informasi destinasi wisata populer Jawa Timur di aplikasi Trip Advisor [10], crawling untuk pengambilan berita [11] dan spesifik konten berdasarkan konten dan structure mining [12], serta juga digunakan untuk melakukan crawling lokasi berbasis semantic information [13]. Sedangkan aplikasi android didesain untuk memudahkan pengguna khsususnya para petani dalam melakukan deteksi atau identifikasi penyakit pada batang buah naga melalui input gambar yang diambil melalui kamera maupun galeri handphone, menampilkan hasil deteksi dan yang dilengkapi dengan solusi atau langkah yang harus dilakukan oleh petani atau pengguna untuk menangani penyakit yang menyerang tanaman buah naganya.…”

Section: Pendahuluanunclassified

Sistem Deteksi Penyakit Dan Crawling Informasi Pada Tanaman Buah Naga Berbasis Web Dan Android

Hakim

Kristanto²,

Yusuf

et al. 2023

JTI

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Dragon fruit is a type of horticultural plant that has many benefits for human health. However, behind the many benefits, it does not necessarily make farmers always succeed in improving the quality and quantity of their crops. Disease attacks often disturb dragon fruit farmers, especially in Banyuwangi Regency. Therefore, in this research, web and android application was developed. In this study, the extreme programming method is proposed for system development. This application can be used by farmers to detect through their android devices based on image data. This application was developed by running the *h5 and tflite feature to run the detection model that has been created. Detection application can be accessed through web and android. In addition, this system also implements a web crawling technique to extract information related to disease on dragon fruit stems and how to handle them. The web crawling technique use the selenium and beautifulSoup libraries. Based on the tests carried out using the scenario test, it was found that the system can be used as expected, which is shown at 86,67% for web application showing the valid results and also 90,5% of valid result for android applications.

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“…Support Vector Machine (SVM) the method used for learning is like a machine according to statistical science theory. Support SVM is the analysis stage in machine learning techniques by analyzing the sentiments that arise through system learning by utilizing the hypothetical space of the linear function of the feature space that has high dimensions of the application of learning sourced from the theory of learning knowledge of statistics [11,12].…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis of Food Order Tweets to Find Out Demographic Customer Profile Using SVM

Efendi

Sihombing²

2022

matrik

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The use of online food ordering through food systems or applications continues to increase, requiring vendors to implement marketing and sales strategies through surveys, feedback. The problems that arise are building a system analysis model from a collection of tweets with hashtags or usernames for ordering food online . The Support Vector Machine (SVM) algorithm is used for text classification. Tweets are collected into data sets, training data, and testing data, then a classification model of the SVM Algorithm is built. Preprocessing data, tweets are cleansing, tokenized, and stopword remove. From the collected tweets, they are grouped into 10 variables to identify demographic profiles. The results of the analysis are classified as positive sentiments, namely residence, price range, using promos, paid types, halal food while negative sentiments are ethnicity, culture, vegetarianism, place. Classification accuracy is important to validate the results of the SVM model. From 500 train data tweet, the resulting classification is 66% positive sentiment and 34% negative sentiment. Overall accuracy model Linier SVM result 83.2% with accuracy 92.55%.

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Ekstraksi Informasi Destinasi Wisata Populer Jawa Timur Menggunakan Depth-First Crawling

Cited by 4 publications

References 9 publications

Tourism Marketing: Banyuwangi Regency Government Partnership with Local Mass Media in Banyuwangi

Tourism Marketing: Banyuwangi Regency Government Partnership with Local Mass Media in Banyuwangi

Sistem Deteksi Penyakit Dan Crawling Informasi Pada Tanaman Buah Naga Berbasis Web Dan Android

Sentiment Analysis of Food Order Tweets to Find Out Demographic Customer Profile Using SVM

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