In December 2016, Bank Indonesia (BI) officially launched the 2016 Year Emission Rupiah. With the development of technology, the process of buying and selling are not only possible between humans and humans, but humans with a machine. In addition, the machine must also be able to read and recognize the nominal banknotes in various variations of face and rotation. This is because humans can put money in machines with various variations of face and rotation. This study aims to apply and analyze the level of accuracy of nominal rupiah banknotes identification with the SURF and FLANN methods for rotation variation. Testing for identification of nominal rupiah banknotes is carried out with different rotation variations, namely 0o, 90o, 180o, and 270o. The proposed identification method provides 100% of accuracy.
Instagram is a social media that allows us to easily promote products where one of them is done by publishing promotional content. However, posting promotional material at the right time to get an optimal response from the audience is a complex problem. This study aims to analyze the best publishing time to publish promotional content from 10 open trip service provider accounts on the Instagram platform. Researchers use the web scraping method to extract data from Instagram accounts and the aggregation, ordering, and selecting methods to analyze the best time. The basis used to determine the best time is the number of likes and comments on all posts. This research has succeeded in extracting Instagram's web data and analyzing post data from several Instagram accounts of open trip service providers. The results of this study indicate that each account has a different best time to publish content. For example, the best time to post content from an Instagram @hvtrip account is Friday between 20:00 and 20.59. The study can be used as a recommendation for Instagram account holders of open trip service providers regarding the best time to publish promotional content on Instagram to reach an optimal audience. Of course, this is not limited to Instagram accounts open service providers only. Keywords: social media analytics, Instagram data, marketing, open trip services, the best time ABSTRAK Instagram merupakan salah satu media sosial yang memungkinkan kita untuk mempromosikan produk dengan mudah dimana salah satunya dilakukan dengan cara menerbitkan konten promosi. Akan tetapi, penerbitan konten prosmosi pada waktu yang tepat untuk mendapatkan tanggapan dari audiens secara optimal merupakan masalah yang kompleks. Penelitian ini bertujuan menganalisis waktu penerbitan terbaik untuk menerbitkan konten promosi dari 10 akun penyedia jasa open trip pada platform Instagram. Peneliti menggunakan metode web scraping untuk mengekstrak data dari akun Instagram dan metode aggregation, ordering, dan selecting untuk menganalisis waktu terbaik. Dasar yang digunakan untuk menentukan waktu terbaik adalah jumlah suka dan komentar pada semua post. Penelitian ini telah berhasil mengekstraksi data web Instagram dan melakukan analisis data post dari beberapa akun Instagram penyedia jasa open trip. Hasil penelitian ini menunjukkan bahwa setiap akun memiliki waktu terbaik yang berbeda-beda untuk menerbitkan konten. Sebagai contoh, waktu terbaik untuk menerbitkan konten dari akun Instagram @hvtrip adalah hari Jumat antara jam 20.00 sampai jam 20.59. Hasil dari penelitian ini dapat dijadikan sebagai sebuah rekomendasi bagi pemilik akun Instagram penyedia jasa open trip mengenai waktu terbaik untuk menerbitkan konten promosi pada Instagram untuk menjangkau audiens secara optimal. Tentunya, hal ini tidak terbatas pada akun Instagram penyedia jasa open trip saja. Kata kunci: analisis media sosial, data Instagram, pemasaran, jasa open trip, waktu terbaik
Instagram has been used by many groups, such as business people, academics, to politicians, to take advantage of the insights gained by processing and analyzing Instagram data for various purposes. However, before processing and analyzing data, users must first pass data collection or downloading from Instagram. The problem faced is that most data collection methods are still done manually as for many parties that offer Instagram account data download services with various price options. This research applied a web scraping method to automatically build a web-based Instagram account data download application so that several parties can use it. The web scraping method was chosen because by using this method, researchers do not need to use Instagram's Application Programming Interface (API), which has access restrictions in retrieving data on Instagram. In this study, application testing was conducted on 15 Instagram accounts with various publications, namely between 100 and 11000. Based on the download data analysis results, the application of the web scraping method to download Instagram account data can successfully download a maximum of 2412 account data. In this application, users can download Instagram account data to Data Collection and then manage it like deleting and exporting data collection in the form of CSV, Excel, or JSON.
The volume of digital documents available online is growing exponentially due to the increasing use of the internet. Categorization of information obtained online is needed to make it easier for recipients of information to determine and filter which information is needed. Classification of web pages can be based on titles and descriptions, which are text data that can be done by utilizing deep learning technology for text classification. This study aimed to conduct data training and analysis experiments to determine the accuracy of the proposed deep learning architecture in classifying web page titles and descriptions. In this research, we proposed a Convolution Neural Network (CNN) architecture that generates few parameters. The training and evaluation set was conducted on the web page dataset provided by DMOZ. As a result, the proposed CNN architecture with the number of N (Dropout + 1D Convolution + ReLU activation) equal to 1 achieves the best validation accuracy. It achieves 79.51% with only generates 825,061 parameters. The proposed CNN architecture achieved outperformed performance on the accuracy of the five other technologies in the state-of-the-art.
Abstrak -Pada beberapa tahun terakhir, Instagram telah menjadi salah satu platform media sosial yang mengalami pertumbuhan paling cepat. Pencarian gambar di Instagram dapat dilakukan dengan menggunakan sebuah kata kunci tertentu atau sering disebut sebagai hashtag. Hashtag merupakan salah satu parameter yang digunakan untuk mengetahui topik yang sedang hangat dibicarakan pada media sosial. Terdapat banyak keuntungan dari mengetahui topik yang sedang hangat pada media sosial untuk mendukung pengambilan keputusan. Penelitian ini bertujuan untuk memantau tren hashtag pada platform Instagram menggunakan teknik web scraping. Penelitian ini telah berhasil mengekstraksi dan melakukan analisis data post pada Instagram untuk memberikan informasi tren dari sebuah hashtag #MerryChrismas. Hasil dari penelitian ini adalah terlihatnya tren pada hashtag #MerryChrismas mengalami kenaikan pada dua hari terakhir yaitu pada tanggal 24 dan 25 Desember 2019. Selain itu, penelitian ini juga berhasil menampilkan post dengan jumlah like dan jumlah comment terbanyak dari sebuah hashtag pada periode waktu tertentu.
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