Weight control system on the feeder conveyor determines the factor of the quality of products within an industry. The dynamics of the flow rate of material through the feeder conveyor weigh requires a good level of performance controllers. The base of current controllers such as FLC (Fuzzy Logic Controller) requires a certain amount of knowledge and expertise in its design that will make it difficult to achieve good system performance. These difficulties can be overcome by using systems based on ANFIS (Adaptive Neuro-Fuzzy Inference System). By doing the learning offline, using ANFIS can be obtained by fuzzy inference systems to create a controller FLC. Microcontroller have FLC controller program, its integrated with notebook can monitor and control the notebook weigh feeder conveyor system. Designing a system that has been created will give good results with an average error value of 3.86% at the set-point of 1000 grams / minute, and the average error of 5.03% on set-point 2000 grams / minute in ten times testing.
PT FGS Infotama merupakan perusahaan penyedia jasa Aplikasi Online Trading yang tidak hanya fokus pada implementasi tahap awal, melainkan beberapa hal penting lainnya, seperti pelatihan, pengembangan, perawatan dan sosialisasi terkait dengan software yang diterapkan. Saat ini keluhan diterima melalui email, telepon maupun whatsapp sehingga relatif sulit dalam mengelola keluhan yang masuk. Tujuan dari penelitian ini adalah membuat helpdesk ticketing system yang dilengkapi dengan klasifikasi tingkat urgensi keluhan, dan beberapa fitur lain seperti Frequently Asked Question, News yang berisi infomasi ke klien dari Perusahaan, dan Notifikasi tiket masuk dan ketika tiket telah diselesaikan. Metode yang digunakan untuk mengembangkan aplikasi ini adalah metode Waterfall, sementara algoritma yang digunakan untuk mengklasifikasi keluhan adalah Multinomial Naive Bayes Classifier. Algoritma ini diimplementasikan pada form create ticket. Aplikasi dikembangkan berbasis web. Setelah dilakukan pengujian, didapatkan hasil akurasi data yang berasal dari email sebesar 61.90% dan hasil akurasi dari data yang berasal dari whatsapp sebesar 73.6%.
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