E-learning is electronic-based learning using computers or computer-based. One e-learning application that is widely known today is Ruang Guru. One way to find out the success of an application is to do a sentiment analysis of the application. In this study, sentiment analysis was taken from Twitter social media user comments on Ruang Guru of 513 tweets, after data cleaning, with 338 tweets of positive sentiment and 175 tweets of negative sentiment. The data was extracted using the Naive Bayes (NB) algorithm, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), and feature selection with the Particle Swarm Optimization (PSO) algorithm. This study compares the NB, SVM, K-NN methods without using feature selection with the NB, SVM, K-NN methods that use feature selection and compares the Area Under Curve (AUC) values of these methods to find the most optimal algorithm. The test results get the results that the best optimization application in this model is the SVO-based PSO algorithm with an accuracy value of 78.55% and AUC of 0.853. This research succeeded in getting the most effective and best algorithm in classifying positive and negative comments related to Ruang Guru.

Menyelesaikan Pendidikan Magister Ilmu Komputer pada STMIK Nusa Mandiri dalam waktu 4 semester merupakan harapan setiap mahasiswa. Untuk dapat lulus tepat waktu setiap mahasiswa wajib memenuhi semua persyaratan yang telah ditentukan oleh pihak kampus. Dalam tiap semester terdapat berbagai kegiatan diluar kegiatan belajar mengajar yang wajib diikuti oleh mahasiswa. Kegiatan tersebut meliputi Seminar, Workshop, dan Tes TOEFL. Hal-hal tersebut seringkali tidak diketahui mahasiswa sehingga tidak lulus mata kuliah tertentu. Apabila seorang mahasiswa dinyatakan tidak lulus mata kuliah tertentu maka diwajibkan untuk mengulang di semester berikutnya. Mengulang mata kuliah akan menambah pengeluaran dan tentunya menambah waktu belajar sehingga tidak dapat lulus tepat waktu sesuai yang diharapkan. Pada paper ini akan membahas tentang bagaimana Finite State Automata (FSA) jenis Nondeterministic Finite Automata (NFA) dapat diimplementasikan dalam siklus pembelajaran Magister Ilmu Komputer pada STMIK Nusa Mandiri. Dengan diterapkan metode ini  diharapkan dapat membantu mahasiswa dalam pemenuhan persyaratan untuk mencapai kelulusan

Peningkatan jumlah siswa yang mendaftar disuatu sekolah membuat pihak sekolah perlu mengadakan penyeleksian siswa berdasarkan kriteria yang telah ditentukan sekolah. Sistem penerimaan siswa yang masih manual sering terjadi kesalahan baik dalam penginputan data maupun pembuatan keputusan menjadi permasalahan dalam penerimaan siswa. Dari permasalahan tersebut dibutuhkan sebuah metode yang dapat digunakan dalam proses perhitungan nilai kriteria kemudian diterapkan kedalam sistem pendukung keputusan untuk mempermudah dalam mengolah data. Tujuan penelitian ini untuk membantu proses penyeleksian siswa baru pada SMP Islam Al-Azhar 6 Jakapermai yang saat ini masih manual dengan menggunakan metode Simple Additive Weighting dengan kriteria dan  bobot kriteria yang telah ditetapkan kemudian diimplementasikan pada sistem menggunakan Visual Basic .Net dan SQL Server 2008. Kriteria dalam penerimaan siswa baru yaitu nilai bahasa indonesia, matematika, bahasa inggris dan ilmu pengetahuan alam. Metode SAW dimulai dengan pemberian nilai pada setiap kriteria, pembobotan, normalisasi dan perangkingan dari nilai tertinggi ke terendah. Dengan perangkingan tersebut dapat ditentukan siswa yang diterima dan tidak diterima. Penerapan sistem terkomputerisasi dapat mempermudah dalam penentuan penerimaan siswa baru sesuai kriteria, mengurangi human error dan keamanan data lebih terjamin karena disimpan dalam database.  Dimana sistem ini nantinya akan digunakan oleh staff tata usaha dalam pengolahan data dan penyajian laporan penerimaan siswa baru

The application of artificial intelligence (Artificial Intelligence) for problem-solving in the field of computer science has experienced rapid development from year to year as the development of artificial intelligence itself. Problems involving searching (searching) is one example of the use of artificial intelligence that is quite popular to solve various kinds of problems. In daily activities, the use of roads is always an unavoidable activity, so determining the shortest path from one point to another becomes a problem that is often encountered. This is also felt by residents who live in a large enough housing. Sometimes to be able to reach the destination they are often confused in deciding which way to go to get the shortest distance to the destination. Citra Indah City Housing is a residential area in the Jonggol District area, Bogor Regency, developed by the Ciputra group. Within the Vignolia Hill Cluster, there is a mosque located on the northwest corner of the Vignolia Hill cluster or at the western end of the AH.17 block. A large number of blocks raise problems regarding the shortest route that can be taken by residents to get to the mosque. So, the purpose of this research is to determine the shortest path taken by citizens to get to the mosque. The method used is to apply the Djikstra algorithm which is able to produce the shortest route for residents to get to the mosque.

The heart is an organ of the human body that has an important role in human life and is certainly very dangerous if our heart has problems remembering that many deaths are caused by heart disease. But with minimal knowledge and information, it is impossible to be able to maintain heart health. Therefore we need an expert who is an expert on the heart and various diseases. Based on the facts above, this research can help us to diagnose heart health and anticipate if there is a risk of heart disease by designing and implementing. This application was created using the web-based Finite State Automata algorithm which is still in the form of pseudocode. In this system several questions will be asked. After all the questions are answered, the results of the diagnosis will appear along with suggestions that can help anticipate the heart disease.