The key to the success of an educational organization in achieving its goals of course cannot be separated from the quality of service both in academic and non-academic forms. Where in achieving these goals of course by giving satisfaction to the academics. The case study was carried out to predict service satisfaction at the Open University by using comments on social media Youtube as data processing. The text mining approach is a good alternative in terms of interpreting the meaning in the comments given. This study aims to analyze the predictions of service satisfaction from several categories as a benchmark. The categories are: Module, Tutorial, Scholarship, Lecturer, Exam, Application, Non-Academic and Others. The research method used is comparative, by applying 4 algorithms, namely Decision Tree (DT), Support Vector Machine (SVM), Naïve Bayes (NB) and Random Forest (RF) for Prediction Accuracy. The total initial dataset is 7776 data and after cleansing and preprocessing is 6920 data. And then evaluated for the 7 categories after being accured to produce: Module category with the highest accuracy of 99.37% using the DT algorithm, Application Category with the highest accuracy of 100% using the DT algorithm, Teaching Category the highest accuracy of 99.42% using the algorithm DT. The tutorial category has the highest accuracy 92.4% using the SVM algorithm, the exam category has the highest accuracy 99.7% using the RF algorithm, the non-academic category has the highest accuracy 99.90% using the DT algorithm. And for the Others category the highest accuracy is 96.58% using the DT algorithm

Vending machine merupakan salah satu bentuk perkembangan teknologi. Di Indonesia, jenis yang sering dijumpai adalah vending machine, sejenis minuman ringan dengan beberapa pilihan. Melihat peluang bisnis yang ada di sektor minuman kekinian, dalam penelitian ini Finite State Automata (FSA) diterapkan pada mesin penjual otomatis pembuat teh. FSA adalah model matematika yang dapat menerima input dan output dari keadaan yang sama. Mesin penjual otomatis teh ini dapat menghasilkan 6 jenis teh dan 4 pilihan topping sebagai pelengkap. Vending machine ini dilengkapi dengan fasilitas kaca upsize dari ukuran sedang hingga besar. Untuk pembayaran, vending machine ini menyediakan opsi cash dan Cashless. Dalam penerapan konsep FSA, penelitian ini melakukan uji coba FSA dengan menggunakan JFLAP. Sehingga dengan penerapan konsep FSA menjadi salah satu alternatif dalam merancang mesin penjual otomatis pembuat teh.

Retired Dana Pensiun Perkebunan Defined Benefit Pension Plan (PPMP) participants are required to certify annually that they still meet the criteria for being a valid pensioner. The retiree uses the Dapenbun online application to take a photo of himself and her ID card and wait for the data to be processed by the administrator. Pensioners who do not report will have their pension entitlements suspended. The number of retirees managed by the Plantation Pension Fund is over 216,000, and managers are overwhelmed with approval at the start of the re-data period. For this reason, authors design systems that can run automated approval and classification systems to facilitate data approval. Applying the FSA concept to this system reduces the processing of participant data as automation is applied to the first process of automatic termination of pensions for children aged 21 and over, second data with criteria for automatic approval. It will be faster. Categorizing data reduces approval errors and makes it easier for users to approve data.