Ikhthison Mekongga
State Polytechnic of Sriwijaya

Published : 3 Documents
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The Application of Fuzzy Time Series Singh for Forecasting Bandwidth Network Demand Aryanti, Aryanti; Mekongga, Ikhthison
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.2.527

Abstract

Abstract- The purpose of this research is to develop information system which forecast bandwidth network demand by using Fuzzy time series Singh. Data were taken in State Polytechnic of Sriwijaya during learning hour starting from 07.00 am - 06.00 pm from Monday to Saturday in odd semester of Academic Year 2011/2012. Next, the data were processed by fuzzy time series Singh in order to get forecasted data. Then, the forecasted data were compared to the actual data in order to get validity of the data. The forecasted data using fuzzy time series Singh was nearly precise to the actual data with mean absolute percentage error of 8.523 %.
PERANCANGAN APLIKASI ANDROID SEBAGAI PENGENDALI APB (AUTOMATIC PATIENT BED) DENGAN METODE SEKUENSIAL (WATERFALL) Mekongga, Ikhthison; Aryanti, Aryanti; Hasan, Yordan
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 9, No 1 (2019): Volume 9 Nomor 1 Tahun 2019
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.595 KB) | DOI: 10.21456/vol9iss1pp103-111

Abstract

Patient beds in hospitals are beds designed for people who need health care. Complaints of hospital nurses are still severe when moving patients from the patient's bed to the operating bed. Therefore we need a tool that can make it easier for nurses to move the patient's body from a particular operating bed to an inpatient bed or vice versa called APB (Automatic Patients Beds). However, the performance of APB (Automatic Patient Beds) that designed is still manual. In this study, android applications developed as controllers of APB (Automatic Patient Beds) with a sequential (waterfall) method, where this application will control the bed so that it can move automatically via android via bluetooth communication. In system design with sequential method consists of several stages, starting from the needs analysis, system design, writing program code, testing, and implementing the program. The results showed that if the patient's bed button clicked, the system would move the mattress to the operating bed, and if the operating bed button were clicked, the mattress would move to the operating bed, the patient's bed would stop if one of the beds were active, This indicates that the mattress has moved to the right position. With this application, it is expected to facilitate patient care in the hospital.
THE PREDICTION OF BANDWIDTH ON NEED COMPUTER NETWORK THROUGH ARTIFICIAL NEURAL NETWORK METHOD OF BACKPROPAGATION Mekongga, Ikhthison; Gernowo, Rahmat; Sugiharto, Aris
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 2, No 2 (2012): Volume 2 Nomor 2 Tahun 2012
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (971.992 KB) | DOI: 10.21456/vol2iss2pp098-107

Abstract

The need for bandwidth has been increasing recently. This is because the development of internet infrastructure is also increasing so that we need an economic and efficient provider system. This can be achieved through good planning and a proper system. The prediction of the bandwidth consumption is one of the factors that support the planning for an efficient internet service provider system. Bandwidth consumption is predicted using ANN. ANN is an information processing system which has similar characteristics as the biologic al neural network.  ANN  is  chosen  to  predict  the  consumption  of  the  bandwidth  because  ANN  has  good  approachability  to  non-linearity.  The variable used in ANN is the historical load data. A bandwidth consumption information system was built using neural networks  with a backpropagation algorithm to make the use of bandwidth more efficient in the future both in the rental rate of the bandwidth and in the usage of the bandwidth.Keywords: Forecasting, Bandwidth, Backpropagation