In this digital age, where marketing strategies are continuously growing, many entrepreneurs start to utilize social media as one of tools to do marketing strategy. Twitter is one of their preference of social media as a medium to sell products. Unfortunately, Twitter does not provide feature to facilitate users in doing promotions, such as providing information about followers are more likely being active in Twitter and then categorizing the interest of followers accordingly. In order to overcome this problem, a Twitter client that can classify users' followers to be able to facilitate the promotion on Twitter. One way to categorize consumer interest on Twitter is by using text mining. The K-Nearest Neighbor algorithm is one of algorithms that can be used to perform classification task. Development of Twikipedia system with K-Nearest Neighbor algorithm is able to classify users' followers and facilitate the former in doing promotion on Twitter. Keywords: k-nearest neighbor, social media analytics, text mining, twitter AbstrakDi era digital ini, dimana strategi marketing terus berkembang, banyak pengusaha yang mulai memanfaatkan media sosial sebagai salah satu alat untuk melakukan strategi pemasaran. Twitter adalah salah satu media sosial yang digunakan sebagai media untuk memasarkan produk mereka. Sayangnya, Twitter tidak memberikan fitur untuk memudahkan penggunanya dalam melakukan promosi seperti memberikan informasi tentang waktu keaktifan follower serta mengkategorikan sesuai dengan ketertarikan dari follower. Untuk dapat mengatasi permasalahan tersebut, dibutuhkan sebuah Twitter client yang dapat melakukan klasifikasi terhadap follower dari pengguna dan memudahkan cara promosi di Twitter. Salah satu cara untuk mengkategorikan ketertarikan konsumen di Twitter adalah dengan menggunakan text mining. Algoritma K-Nearest Neighbor adalah salah satu algoritma yang bisa dimanfaatkan untuk implementasi pengklasifikasiannya. Pembangunan sistem Twikipedia dengan algoritma KNearest Neighbor mampu mengklasifikasikan follower dari pengguna dan memudahkan pengguna dalam melakukan promosi di Twitter. Kata Kunci: k-nearest neighbor, social media analytics, text mining, twitter PendahuluanDalam dunia bisnis, marketing merupakan hal yang paling crusial atau penting. Marketing atau pemasaran adalah aktivitas, serangkaian institusi dan proses menciptakan, mengkomunikasikan, menyampaikan dan mempertukarkan tawaran (offerings) yang bernilai bagi pelanggan, klien, mitra, dan masyarakat umum [1]. Di era digital ini, dimana strategi marketing terus berkembang, banyak pengusaha yang mulai memanfaatkan media sosial sebagai salah satu alat untuk melakukan strategi pemasaran. Dari fakta tersebut timbul sebuah fenomena baru, yaitu "Buzz Marketing" atau "Viral Marketing" yang merupakan teknik pemasaran produk atau jasa untuk menghasilkan bisnis melalui informasi dari akun sosial media yang satu ke akun sosial media lainnya [2]. Salah satu strategi pemasaran atau marketing (manual) yang biasa digunakan adalah dengan cara promosi. ...
The purpose of company management in general is to generate profit, but furthermore the management of the company is required to improve the welfare of the owners of the company or in this case the shareholders. To achieve these objectives, it is necessary to have ownership structures that can provide maximum supervision to managers in order to carry out their duties to improve the welfare of the owners of the company through increasing the value of the company. This is in accordance with the agency theory developed by Jensen Meckling stating that the manager as an agent delegated by the owner of the company to manage the company. In the process of managing the company, according to Jensen Meckling there is possible occurrence of agency problems, which arise because of the tendency of managers to not always make decisions that aim to meet the interests of principals or owners of the company to the fullest. To align the interests of managers and owners of the company so as to reduce agency problems, it is necessary to have a good ownership structure, capable of monitoring the performance of management in meeting the interests of the owner of the company. Therefore, this study would like to examine how ownership structures proxied with institutional ownership and managerial ownership can influence the value of firms that can ultimately have an impact on increasing shareholder wealth. This study tested 71 manufacturing companies listed on the Indonesian Stock Exchange in 2016 using multiple regression analysis techniques. The test results show the significant influence of variables with institutional ownership and managerial ownership of firm value, which shows that the ownership structure that allows the owner of the company to supervise the performance of the company's management can have an impact on the increase of company value.
Based on statistics from data.id, in the first quarter of 2016, there are 1,137 datasets distributed at 32 institutions and 18 groups in Indonesia. DKI Jakarta Province contributes to these data at the most, i.e. 714 datasets. A lot of accessible open datasets have an impact on the availability of valuable information that can be extracted to good use, for businesses, governments, and personal lives. To get the desired information, an exploratory data analysis is needed to make data more alive. The goal of this research is to provide a proper visualization of the given data. Data visualization is a way (perhaps a solution) to communicate abstract data, to aid in data understanding by leveraging human visual system. The result of this visualization is effective and engaging charts appropriates to the given data and can be run on mobile platforms.
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