An Analysis and Design of The Therapie Company Profile Website using User Experience Method (UX)

Abstrak THERAPIE adalah perusahaan yang bergerak dalam bidang konseling dan mempunyai program pelatihan. Dalam sebuah perusahaan harus memiliki kemampuan memublikasikan programnya kepada masyarakat. Penggunaan media cetak kurang efektif dalam publikasi suatu perusahaan, karena jangkauan publikasi terbatas dan membutuhkan biaya yang cukup besar.  Penelitian ini bertujuan untuk merancang website profil perusahaan yang dapat membantu publikasi informasi THERAPIE dengan berbagai content dan fungsi. Website ini dibuat dengan menggunakan metode user experience (the five planes) untuk memberikan kenyamanan untuk para pengunjung website. Dalam proses pengujian, dilakukan hosting kemudian uji coba secara langsung kepada beberapa customer dengan menggunakan kuisioner. Dari hasil kuisioner, responden merasakan website ini mudah digunakan dan memberikan informasi berbagai event THERAPIE. Kata kunci: web, user experience, information  Abstract THERAPIE is a company specializing in counseling, in which training is one of their events. A company must inform the public about its business. Using printed media can be ineffective for publication because the coverage is limited and it can be very costly. This research aims to create a company profile websites for the publication of Therapie including a variety of content and functions. This website is designed using user experience method (the five planes) to ease visitors accessing the website. The website test result is performed by by hosting and testing through questionnaire. The respondents feel the website is easy to access and offer information on various THERAPIE events. Key words: web, user experience, informatio

NetFlow Monitoring and Cyberattack Detection Using Deep Learning With Ceph

Figuring the network's hidden abnormal behavior can reduce network vulnerability. This paper presents a detailed architecture in which the collected log data of the network can be processed and analyzed. We process and integrate on-campus network information from every router and store the integrated NetFlow log data. Ceph is used as an open-source distributed storage platform that offers high efficiency, high reliability, scalability, and preliminary preprocessing of raw data with Python, removing redundant areas and unification. In the subanalysis, we discover the anomaly event and absolute flow by three times of standard deviation rule. Keras has been used to classify in-time data collected via a cyber-attack and to construct an automatic identifier template through the Recurring Neural Network (RNN) test. The identification accuracy of the optimization model is around 98% in attack detection. Finally, in the MySQL server, the results of the real-time evaluation can be obtained, and the results of the assessment can be displayed via ECharts

Indonesia's Role in Fulfilling the Right to Education Elementary and Intermediate in Border Areas

The role of the state in carrying out educational development and in order to fulfill the right to education, especially primary and secondary education in border areas must be further enhanced. The state must be present among school-age children in border areas by manifesting itself in the form of appropriate and representative school buildings. The state must exist in the form of adequate educational support facilities. The state must be present in the form of teachers and education personnel who are sufficient in number and have competence. The state must be present in the form of budget politics that supports education development in border areas. The state must also be present in a curriculum that suits the needs of school-age children in border areas as well as enhances their national insight

PEMANFAATAN TEKNOLOGI WEB SERVICES PADA PERTUKARAN DATA KATALOG ANTAR PERPUSTAKAAN

The role of university libraries in the era of information technology advances need to be developed towards the integration of data. Establishment of library networks can be an effective means of learning communities. Problems faced is the interoperability or the ability to integrate different applications in co-operation between libraries in the network. To overcome these problems required Web Service technology, ie technology that can integrate applications, programming languages, and different platforms via http, so that different applications can communicate and exchange data. In this paper, a simulation designed a catalog of data integration between the Library A and Library B. Web Services that bridges the library network is created using PHP using NuSOAP class, while the database used in this simulation is at the Library A MySql Database, and Visual Foxpro Database with ODBC connector on the Library B. Keyword: Web service, NuSOAP, integrated online catalogue, interoperabilit

Perancangan dan Simulasi Data Warehouse untuk Keputusan Promosi Musik

Abstrak Perkembangan teknologi yang demikian pesat saat ini membuat penyedia jasa penjualan rekaman musik mengubah cara penjualan dari unit fisik menjadi virtual. Penjualan virtual yang menerapkan dan mengutamakan perekaman data tersebut dapat dimanfaatkan secara efektif dan efsisien dalam mendukung keputusan strategis. Adapun pihak yang paling dapat memanfaatkan data penjualan tersebut adalah perusahaan rekaman dan promotor musik dalam melakukan berbagai macam promosi. Pada paper ini akan dibahas teknik perancangan Data Warehouse, dengan mensimulasikan database “chinookâ€, sebuah sample basis data yang tersedia untuk umum, yang dapat dipergunakan pada berbagai jenis pemroses basis data (Object Relational Mapping). Pembuatan Data Warehouse dimaksudkan untuk mensimulasikan pendukung dalam pengambilan keputusan untuk memudahkan penentuan subjek promosi atau strategi penjualan yang akan diambil oleh para pihak yang berkepentingan.Kata kunci: chinook, promosi musik, artist, iTunes, Data WarehouseAbstractRapid development in technology requires the music providers change their sales, from physical sales to virtual sales. The online system marketing that applies and prioritizes data recording could be used effectively and efficiently to support strategic decision. The party that can benefit the most from the sales data was recording companies and music promotors in promoting their services. This paper intends to design data warehouse, by simulating “chinookâ€, an open access database, which can be used in various database processor (Object Relational Mapping). The data warehouse design was intended to simulate supports in decision making, which further to determine the promotion subject or sales strategy decided by the stakeholders. Keywords: chinook, music promotion, artist, iTunes, Data Warehous

Fake News Classification Based on Content Level Features

Due to the openness and easy accessibility of online social media (OSM), anyone can easily contribute a simple paragraph of text to express their opinion on an article that they have seen. Without access control mechanisms, it has been reported that there are many suspicious messages and accounts spreading across multiple platforms. Accordingly, identifying and labeling fake news is a demanding problem due to the massive amount of heterogeneous content. In essence, the functions of machine learning (ML) and natural language processing (NLP) are to enhance, speed up, and automate the analytical process. Therefore, this unstructured text can be transformed into meaningful data and insights. In this paper, the combination of ML and NLP are implemented to classify fake news based on an open, large and labeled corpus on Twitter. In this case, we compare several state-of-the-art ML and neural network models based on content-only features. To enhance classification performance, before the training process, the term frequency-inverse document frequency (TF-IDF) features were applied in ML training, while word embedding was utilized in neural network training. By implementing ML and NLP methods, all the traditional models have greater than 85% accuracy. All the neural network models have greater than 90% accuracy. From the experiments, we found that the neural network models outperform the traditional ML models by, on average, approximately 6% precision, with all neural network models reaching up to 90% accuracy

In the Seeking of Association between Air Pollutant and COVID-19 Confirmed Cases Using Deep Learning

The COVID-19 pandemic raises awareness of how the fatal spreading of infectious disease impacts economic, political, and cultural sectors, which causes social implications. Across the world, strategies aimed at quickly recognizing risk factors have also helped shape public health guidelines and direct resources; however, they are challenging to analyze and predict since those events still happen. This paper intends to invesitgate the association between air pollutants and COVID-19 confirmed cases using Deep Learning. We used Delhi, India, for daily confirmed cases and air pollutant data for the dataset. We used LSTM deep learning for training the combination of COVID-19 Confirmed Case and AQI parameters over the four different lag times of 1, 3, 7, and 14 days. The finding indicates that CO is the most excellent model compared with the others, having on average, 13 RMSE values. This was followed by pressure at 15, PM2.5 at 20, NO2 at 20, and O3 at 22 error rates