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JUTI: Jurnal Ilmiah Teknologi Informasi
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 24068535     EISSN : 14126389     DOI : http://dx.doi.org/10.12962/j24068535
Core Subject : Health, Science, Education,
Computer Science & IT Dentistry Education Library & Information Science
JUTI (Jurnal Ilmiah Teknologi Informasi) is a scientific journal managed by Department of Informatics, ITS.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 7, No 4, Juli 2009" : 5 Documents clear
RANCANG BANGUN OPTIMASI KEBUTUHAN BAHAN BAKU MENGGUNAKAN ALGORITMA WAGNER-WHITIN Saikhu, Ahmad; Sarwosri, Sarwosri; Laila, Nur
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 4, Juli 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (239.01 KB) | DOI: 10.12962/j24068535.v7i4.a87

Abstract

Lotting or purchasing raw materials is one step in Material Requirement Planning. Lotting technique that already known is the Wagner-Within algorithm. This algorithm is widely used because it provides optimal solutions for problem sizedeterministic dynamic reservation at a particular time period in which the needs of the entire period must be completed. It takes a application system of optimization planning raw material requirements using the Wagner-Whitin algorithm. The development of this process begins with building a power module of demand data using Arima method (1,1,1), then followed by forecasting modules of consumer demand for end product by using the multiplicative decomposition forecasting methods, and ends with the development of Materials Requirement Planning module (MRP I) using the Wagner-Whitin algorithm. The results of the test system with test data is the generation of data will form the same pattern that is likely up from week to week. Forecasting results have high accuracy registration of 99.48%, 99.64% and 99.68%. Wagner-Whitin algorithm always produces the combination of weeks. Result of the combination in the first week will produces the minimum cost for the entire week of production.
PERAMALAN KONSUMSI LISTRIK JANGKA PENDEK DENGAN ARIMA MUSIMAN GANDA DAN ELMAN-RECURRENT NEURAL NETWORK Suhartono, Suhartono; Endharta, A J
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 4, Juli 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (239.731 KB) | DOI: 10.12962/j24068535.v7i4.a88

Abstract

Neural network (NN) is one of many method used to predict the electricity consumption per hour in many countries. NN method which is used in many previous studies is Feed-Forward Neural Network (FFNN) or Autoregressive Neural Network(AR-NN). AR-NN model is not able to capture and explain the effect of moving average (MA) order on a time series of data. This research was conducted with the purpose of reviewing the application of other types of NN, that is Elman-Recurrent Neural Network (Elman-RNN) which could explain MA order effect and compare the result of prediction accuracy with multiple seasonal ARIMA (Autoregressive Integrated Moving Average) models. As a case study, we used data electricity consumption per hour in Mengare Gresik. Result of analysis showed that the best of double seasonal Arima models suited to short-term forecasting in the case study data is ARIMA([1,2,3,4,6,7,9,10,14,21,33],1,8)(0,1,1)24 (1,1,0)168. This model produces a white noise residuals, but it does not have a normal distribution due to suspected outlier. Outlier detection in iterative produce 14 innovation outliers. There are 4 inputs of Elman-RNN network that were examined and tested for forecasting the data, the input according to lag Arima, input such as lag Arima plus 14 dummy outlier, inputs are the lag-multiples of 24 up to lag 480, and the inputs are lag 1 and lag multiples of 24+1. All of four network uses one hidden layer with tangent sigmoid activation function and one output with a linear function. The result of comparative forecast accuracy through value of MAPE out-sample showed that the fourth networks, namely Elman-RNN (22, 3, 1), is the best model for forecasting electricity consumption per hour in short term in Mengare Gresik.
IDENTIFIKASI SINYAL ECG IRAMA MYOCARDIAL ISCHEMIA DENGAN PENDEKATAN FUZZY LOGIC N, Azhar A; Suyanto, Suyanto
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 4, Juli 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1060.926 KB) | DOI: 10.12962/j24068535.v7i4.a89

Abstract

The heart is one of vital organs in human body. Incidence of heart disease can be fatal for the patient. Myocardial ischemia, the disease that is often suffered by the human, is a disease due to clogged heart arteries blood vessels. One of the ways to detect this disease is by reading the graph output of electrocardiogram (ECG) signal. ECG signal represents the condition and activity of the heart. Specialized knowledge, accuration and expertise are required to read ECG graph. To help expert or doctor, expert system based on artificial intelligent, such as Fuzzy Logic approach, can be applied to improve diagnostic accuracy and thoroughness. Fuzzy logic can be applied because of it flexibility to understand the linguistic variables used in identifying myocardial ischemia disease.
RPLUGIN.ECONOMETRICS: PAKET GRAPHICAL USER INTERFACE OPEN SOURCE UNTUK ANALISIS RUNTUN WAKTU MENGGUNAKAN PERANGKAT LUNAK R Rosadi, Dedi; Marhadi, Adi
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 4, Juli 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (279.502 KB) | DOI: 10.12962/j24068535.v7i4.a85

Abstract

R (R Development Core Team, 2009) is one of the open source software that is popular and has become "lingua franca" or standard language for the purposes of computing the current statistics. In this paper, will be introduced and discussed RcmdrPlugin.Econometrics package (Rosadi, Marhadi and Rahmatullah, 2009), which is a GUI version (Graphical User Interface) of R for the purposes of econometric analysis or time series. RcmdrPlugin.Econometrics package is an additional menu (plug-in) which provided for the R Commander, which is the most popular GUI of R. To illustrate the design philosophy of this package, provided also illustrate the usage of the RcmdrPlugin.Econometrics package for the exponential smoothing.
PEMBENTUKAN SET JALUR ALIRAN PROGRAM MENGGUNAKAN TEKNIK JUMLAH JALUR MINIMUM DAN TEKNIK JUMLAH PREDIKAT MINIMUM Padmowati, Rosa de Lima Endang
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 4, Juli 2009
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.04 KB) | DOI: 10.12962/j24068535.v7i4.a86

Abstract

Structured testing is based on the control flow of programs. The analysis of the control flow of program is conducted on a reduced flowgraph, called a decision-to-decision graph (DDGraph). The relations of dominance and implication between arcs enable to immediate identification of a subset of DDGraph arcs. These arcs are called unconstrained arcs, which have a property that, when the unconstrained arcs are exercised, the traversal of all the other arcs are guaranteed. In order to find a path cover for given program flowgraph, there are two methods: minimum number of paths technique and less pred technique.

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