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Tanti Octavia
Program Studi Industri, Universitas Kristen Petra Surabaya
Computer Science & IT

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Penerapan Artificial Neural Network dan Rule Based Classifier untuk Mengklasifikasikan Pendonor Darah Potensial pada Sistem Broadcast Pendonor Widya Arditanti; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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One of UTD PMI Surabaya’s task is to provide safe and quality blood when blood is needed in an emergency. The availability of blood at UTD PMI Surabaya can be erratic, because it depends on the number of donors that fluctuates and the storage time of blood is not long. Therefore, UTD PMI Surabaya needs a system to invite potential donors to meet blood needs when needed in an emergency, by minimizing blood wasted. The classification model and the creation of a recommendation system will produce a list containing donors who have been sorted by priority. Testing was carried out by dividing the data according to the conditions of the data collection environment (before the pandemic, during the pandemic and a combination of before and during the COVID-19 pandemic). The highest MRR value was obtained from the ANN model made from a combined data of 90% classification results using RBC and fake data. The accuracy value obtained from the model is 91.13% for training and 91.83% for testing. The resulting MRR value is 8.07 x 10-4 .
Sistem Otomasi Rute Order Picking Pada Gudang dengan Metode Simulated Annealing Stienley Nagata Cahyady; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Order Picking is a process to make a selection from products and picking them up from the place that products are stored and then sort the products out to fulfill the customer orders. Order picking process is the most expensive activity in the warehouse. The reason is order picking needs a lot of workforce and if order picking done manually it will cost as much as 55 % of the total cost of the warehouse. That’s why order picking is the correct part to be optimize to make warehouse become more effective and efficient. In this thesis, a web based application designed to solve all the problems above, which includes showing the shortest route to be pick for orders picking with simulated annealing method. Other than that, the application will be included with a hardware named RFID reader which can detect product placement and pickup from the shelf. The result of this thesis showed that simulated annealing algorithm able to reduce the range that are needed to order picking as much as 51.57058354 % for 100 data, 35.56569879 % for 500 data and 28.18222784% for 1000 data with fixed parameters. For the RFID reader it have the accuracy of 40% for reading products on the shelf. This is because the signals from tags clashing with each other which make the reader unable to read all of them.
Co-Authors Andreas Handojo Stienley Nagata Cahyady Widya Arditanti