In the year 2018, 18.9% of the population in Indonesia mentioned that the main reason for their use of the Internet is social media. One of the social media with an active user of 6.43 million users is Twitter. Based on the surge of information published via Twitter, it is possible that such information may contain the user's opinions on an object, such objects may be events around the community such as a product or service. This makes the company use Twitter as a medium to disseminate information. An example is an Internet Service Provider (ISP) such as Indihome. Through Twitter, users can discuss each other's complaints or satisfaction with Indihome's services. It takes a method of sentiment analysis to understand whether the textual data includes negative opinions or positive opinions. Thus, the authors use the Support Vector Machine (SVM) method in sentiment analysis on the opinions of the Indihome service user on Twitter, with the aim of obtaining a sentiment classification model using SVM, and to know how much accuracy the SVM method generates, which is applied to sentiment analysis, and to see how satisfied the Indihome service users are based on Twitter. After testing with SVM method The result is accuracy 87%, precision 86%, recall 95%, error rate 13%, and F1-score 90%

Armada kendaraan truk merupakan salah satu aset utama dalam bisnis di bidang jasa transportasi. Evaluasi kinerja amada secara cepat dan akurat diperlukan untuk mendukung tercapainya produktivitas armada secara maksimal sehingga target perusahaan dapat mudah tercapai. Proses evaluasi kinerja armada yang masih dilakukan secara manual menyebabkan rumitnya proses pengolahan dan kurang akurat nya hasil evaluasi yang diperoleh, sehingga diperlukan suatu teknik pengolahan data secara cepat dan lebih akurat salah satunya dengan namun menerapkan teknik data mining menggunakan metode clustering. Metode Clustering akan digunakan untuk mengelompokkan setiap armada kendaraan berdasarkan produktivitas kinerjanya. Penelitian ini membandingkan penerapan Algoritma K-Means dan K-Medoids, yang kemudian dilakukan uji validitas terhadap hasil cluster yang terbentuk. Davies Bouldin Index sebagai metode dalam analisis klaster menghasilkan nilai validitas sebesar 0,67 untuk K-Means clustering dan 1,78 untuk K-Medoids. Berdasarkan nilai validitas yang dihasilkan Algoritma K-Means dipilih untuk diimplementasikan pada pembuatan aplikasi clustering armada kendaraan berbasis web karena paling relevan dengan nilai validitas DBI yang lebih rendah dari pada K-Medoids. Pengujian yang telah dilakukan terhadap hasil clustering pada aplikasi web didapatkan persentase kesesuaian sebesar 97 % baik dengan tool Rapidminer maupun dengan perhitungan secara manual

Human-Centered Design Method is a method of approach in the development and design of a system that focuses on the user according to aspects of the needs and habits of the user. Difficulty in accessing information on the website becomes a problem faced by the user and in terms of visual website can not be responsive when accessed via mobile. The initial stage carried out in this method is observation which aims to find and to better understand the problems faced by users to conduct testing to find out whether the solutions provided can be understood and easily used by the user. Website testing is done by giving tasks to the user to interact on the website prototype, as the final result of success in the aspect of ease and comfort of the user using the website. After testing the user directly the test results are obtained, ie the user already feels quite understanding and easy when using the website that was created. The responsive mobile feature created also makes users feel helped when using a website on a smartphone.

Along with the times, the learning media also continues to grow. In solar system subjects usually, the media is used is books, where students can only see 2D forms. The purpose of this research is to build an application that can create a 3D object accompanied by an explanation, so as to make learning more interactive and easily understood using Augmented Reality (AR) technology. In previous journals, a solar system learning application has been made using AR technology, and this research will be developed by creating a quiz menu and true or false to find out how far students understand the material being taught. To ensure the application runs well, testing images, distance and angle markers, application features, and questionnaires using a black box. Marker test results can be distinguished well, markers can be detected well at a distance of 30-90 cm with an angle of 45ᴼ-90ᴼ, then questionnaires to 10 elementary school students related to this application 100% like the solar system AR application as a learning medium.

The Covid-19 pandemic in Indonesia has an impact on every sector of life, including the economy. The government implements social activities that make people have to carry out activities at home. Because of this, humans choose to do everything digitally, including ordering food. With the application of public interest in ordering food online, the income of one of the food orders, namely Gojek (Gofood) has increased. However, Gofood has many pros and cons in the community. In this case, many people give their opinion about the use of social media, especially twitter. The purpose of this study was to analyze public opinion on the performance of Gojek (Gofood) in Indonesia. The grouping into three classes, namely positive, negative and neutral classes were tested using the Naïve Bayes and SVM methods and compared the two methods. The analysis of public sentiment regarding Gofood on Twitter resulted in 92.8% worthy neutral, 5.2% worthy positive and 2.0% worthy negative. Comparing the accuracy results, the Support Vector Machine method has greater accuracy than the Naïve Bayes method, with the Support Vector Machine accuracy values of 83% and 98.5%, while the Nave Bayes accuracy values are 74.6% and 91.5% respectively.