Go-Pay is part of the Gojek application and one of the most popular finteches in Indonesia. Although the most popular, not all users have positive or even negative comments. Now users can submit various media opinions, one of which is Twitter. Twitter media has the advantage of a simple display, updated topics, open access to tweets and express opinions quickly. From a variety of comments on Twitter it takes a technique to divide into classes positive or negative opinions. This study uses prepocessing and labeling opinions into positive and negative classes with the lexicon Based method. As for the classification using the Support Vector Machine (SVM) method. The data used in the form of opinions about Go- Pay reviews from social media Twitter, amounting to 1210. The results of labeling with Lexicon Based amounted to 923 for positive and 287 for negative. While the classification of the SVM method using the Linear kernel produces 89.17% and 84.38% for the Polynomial kernel.
AbstrakPakan merupakan faktor utama dalam melakukan budidaya ikan, permasalahan utama yang dihadapai oleh pembudidaya ikan lele yaitu sistem pemberian ikan yang masih berorientasi pada sumberdaya manusia yang sifatnya masih manual. Kelemahan dari sistem ini yaitu pemberian pakan tidak dilakukan secara teratur karena pembudidaya ikan tidak selalu berada di lokasi kolam atau tambak secara langsung. Pemberian pakan ikan yang tidak teratur akan berdampak pada pertumbuhan dan produksi ikan yang dihasilkan, selain itu keterlambatan pemberian pakan dapat memicu sifat kanibalisme pada ikan lele. Tindakan preventif untuk mengatasi permasalahan tersebut salah satunya adalah pemberian pakan ikan secara terjadwal. Pada penelitian ini, merancang sebuah alat pemberian pakan ikan otomatis dengan kendali Raspberry Pi dan webcam. Prototype ini menggunakan teknologi IoT dengan Raspberry Pi dan webcam sebagai pengendali utamanya, kemudian menggunakan Telegram untuk mengontrol pemberian pakan ikan otomatis yang dikirim berupa pesan. Bahasa yang digunakan dalam program Raspberry Pi menggunakan bahasa Python. Dari data yang diperoleh akan dianalisa seberapa baik jaringan ketika mengirimkan data dari Raspberry Pi ke Telegram. Berdasarkan hasil pengujian Rasberry Pi dapat menerima perintah dari Telegram dan meneruskannya ke webcam, sensor LDR Infrared, dan motor stepper. Webcam berfungsi sebagai monitoring keadaan kolam, sensor LDR Infrared untuk mengecek keadaan isi tampungan, dan motor stepper untuk melakukan pengisian dan penyebaran pakan.
Universitas Muhammadiyah Ponorogo is a well-known campus in the district of Ponorogo. From various regions in the Madiun residency many people are familiar with the Muhammadyah Ponorogo University campus. There are also many other campuses that are socialized to schools in various ways to promote their campuses. This research resulted in an Augmented Reality application as an introduction to the Android-based Campus Building Muhammadiyah Ponorogo. The purpose of this application is to support the development of technology and also facilitate campus PMB in socializing Ponorogo Muhammadiyah University Campus to prospective new students and can be operated anywhere by the user. Users of this system can see images of campus buildings in 3D virtuosity and building information. This application was successfully run on an android smartphone and successfully presented campus information.
Storing student grades in universities is a sensitive issue when it comes to the security of campus computer networks. In this paper, we propose a blockchain model to ensure the secure storage of student grade data. Each record of recording student grades by a lecturer can be seen as a record in a journal or ledger. All records in one of the departments in a faculty can be seen as a student grade journal. Modeling this data by viewing data records as a journal allows us to model a database for all records in an encrypted and distributed manner. Namely, a model that resembles the blockchain model. In this perspective, a blockchain network can be made in which each node is stored in a different direction. So if there are three departments within the faculty, a blockchain with three vertices can be made. Each node keeps a copy of the overall student grade journal data. So that each node can mutually verify the validity of transaction records in each department. Student value journals are structured in such a way that they form a blockchain that builds hashes that lock together. This modeling of student value records answers the problem of being vulnerable to student scores hacked by irresponsible parties both from within the campus and from outside the campus. Security follows the protocols in the blockchain architecture.
The ideal conditions for the oyster mushrooms growth are at a humidity of 65-75% and 29-31C during incubation, while the growth of stems should be at a humidity of 70-90% 29-32C. This ideal ecosystem is maintained by aeration and manual watering. Still, the results are not optimal in preventing damage to the mycelium during the incubation period, resulting in a decrease in crop yields. Automatic control has not created ideal conditions because air temperature and humidity regulation are only based on fans and sprayers that do not directly affect air conditions. Therefore, we need a method to manipulate the mushroom greenhouse space ecosystem, namely fuzzy logic, the application of fuzzy logic integrated with sensors, actuators, and microcontrollers with the Internet of Things to solve this problem. The results of the installation of fuzzy logic in the mushroom's greenhouse in this system can be seen from the fan's modulation response and the pump's duration. The test results of this control feature can manipulate temperature and humidity. Therefore, the oyster mushroom greenhouse produces an ideal state of 29.8C, the humidity of 68.97% RH, and the production has been proven to be optimal with an average daily harvest of 3.8kg.
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