Aplikasi antrian ini dapat mengatur antrian pelanggan atau pasien yang mendapat pelayanan terhadap suatu instansi. Aplikasi mesin antrian ini terdiri dari Main Display LCD TV yang berfungsi untuk menampilkan aplikasi antrian, menampilkan nomor antrian yang dipanggil ketiap loket, menampilkan text untuk informasi, dan menampilkan siaran TV. Download aplikasi antrian paspor banyak dilakukan oleh sebagian besar warga masyarakat yang ingin mengurus paspor. Adanya layanan aplikasi antrean paspor yang semakin banyak digunakan kantor imigrasi banyak memberikan keuntungan.

Penelitian ini membahas mengenai perancangan program aplikasi antrian multiserver pada Bank dengan melibatkan waktu vacation. Program aplikasi ini dirancang dengan tujuan untuk memberikan informasi kepada nasabah/ customer tentang rata-rata waktu lama customer menunggu dalam antrian. Program aplikasi ini dikembangkan berdasarkan teori-teori antrian multiserver dengan melibatkan prosedur vacation. Notasi M yang pertama menunjukkan nilai rata-rata jumlah kedatangan customer per jam ( ), di mana berdistribusi poisson. Notasi M yang kedua menunjukkan nilai rata-rata jumlah customer yang dilayani per jam ( ), di mana berdistribusi eksponensial.

Notasi C menunjukkan jumlah server yang diteliti. Pada penelitian ini, jumlah server yang diteliti sebanyak 5 buah. Vacation adalah rata-rata waktu lama server berhenti per kejadian dalam melayani untuk sementara waktu. Dikarenakan studi kasus penelitian ini adalah sistem antrian Bank, maka sistem antrian yang digunakan adalah FIFO ( First In First Out). Keluaran dari program aplikasi ini berupa nilai rata-rata atau nilai ekspektasi, di mana nilainya tidak akan selalu tepat dengan realitanya. Akan tetapi dengan menggunakan prosedur vacation, maka keakuratan hasilnya dapat terjamin.

Kata kunci:, aplikasi antrian, antrian vacation, antrian multiserver. In this paper we create the application program of Bank multisever queueing system with vacation. This application program is designed with the purpose of providing information to customer. The information is average of customer’s waiting length time in queue. So, customers can find out how long they will be in queue and they can schedule their next activities. This application program is developed based on theories of multiserver queue involves vacation procedure.

First M notation shows average of customers’ arrival number per hour value ( ), where is distributed by poisson distribution. Second M notation shows average of customer’s served number per hour value ( ), where is distributed by exponential distribution.

C notation shows number of searched servers, which number of searched servers are 5. Multiserver shows that number of searched servers more than one. Vacation is average length of servers stop time per incident for awhile. Because of this essay case study is Bank system queuing, the queue discipline used is FIFO (First In First Out). Keep in mind that the output of this application program is average value or expected value, so that the results will not always be appropriate to the reality. However, because this application program using procedure vacation, then the result can be guaranteed for accuracy. Keywords:, queue application, vacation queue, multiserver queue.

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Abstract Waiting is a boring thing for most people. Moreover, if a person waiting in a very long queue. It provides a deterrent effect because they do not know how much longer they must to wait to get a service.Therefore, they invented a queueing system Android-based application that can provide information on the estimated waiting time for the Customer who is in a queue, so that they can know time estimation when they will be served. Android app on this thesis has a feature displays the current queue information required by the Customer and the current estimation waiting time, the queue number being served now, as well as the number of people waiting before the Customer. Customer ticket information delivered to the Android application with a feature of Google Cloud Messaging (push notification). From the test results, the system can generate the estimated waiting time of about 65.51% without tolerance over time and reached 67.95% with a tolerance of +/- 2 minutes.