Winita Sulandari
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ESTIMASI PARAMETER MODEL MIXTURE AUTOREGRESSIVE (MAR) MENGGUNAKAN ALGORITMA EKSPEKTASI MAKSIMISASI (EM) Asrini, Mika; Sulandari, Winita; Wiyono, Santoso Budi
MEDIA STATISTIKA Vol 6, No 1 (2013): Media Statistika
Publisher : Jurusan Statistika FSM Undip

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Abstract

Mixture autoregressive (MAR) Model is a mixture of Gaussian autoregressive (AR) components. The mixture model is capable for modelling of nonlinear time series with multimodal conditional distributions. This paper discusses about the parameters estimation using EM algorithm. All possible models are then applied to national maize production data. In this case, the BIC is used for the MAR model selection. Keywords : Mixture Autoregressive, EM Algorithm, BIC, Maize Production
PENERAPAN MODEL HYBRID ARIMA BACKPROPAGATION UNTUK PERAMALAN HARGA GABAH INDONESIA Janah, Sufia Nur; Sulandari, Winita; Wiyono, Santoso Budi
MEDIA STATISTIKA Vol 7, No 2 (2014): Media Statistika
Publisher : Jurusan Statistika FSM Undip

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Abstract

Hybrid model discussed in this paper combining ARIMA and backpropagation is applied to grain price forecasting in Indonesia for period January 2008 until April 2013. The grain price time series consists of linear and nonlinear patterns. Backpropagations can recognize non linear patterns that can not be done by ARIMA. In order to find the best model, some combinations of prepocessing transformations, the number of input and hidden units, and the activation function were applied in the contruction of the network structure. Based on the experiments, it can be showed that ARIMA backpropagation hybrid model provides more accurate results than ARIMA model.  The hybrid model would rather be used in the short-term forecasting, no more than three periods.   Keywords: ARIMA, Backpropagation, Hybrid, Grain Price
Forecasting electricity load demand using hybrid exponential smoothing-artificial neural network model Sulandari, Winita; Subanar, Subanar; Suhartono, Suhartono; Utami, Herni
International Journal of Advances in Intelligent Informatics Vol 2, No 3 (2016): November 2016
Publisher : Universitas Ahmad Dahlan

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Abstract

Short-term electricity load demand forecast is a vital requirements for power systems. This research considers the combination of exponential smoothing for double seasonal patterns and neural network model. The linear version of Holt-Winter method is extended to accommodate a second seasonal component. In this work, the Fourier with time varying coefficient is presented as a means of seasonal extraction. The methodological contribution of this paper is to demonstrate how these methods can be adapted to model the time series data with multiple seasonal pattern, correlated non stationary error and nonlinearity components together. The proposed hybrid model is started by implementing exponential smoothing state space model to obtain the level, trend, seasonal and irregular components and then use them as inputs of neural network. Forecasts of future values are then can be obtained by using the hybrid model. The forecast performance was characterized by root mean square error and mean absolute percentage error. The proposed hybrid model is applied to two real load series that are energy consumption in Bawen substation and in Java-Bali area. Comparing with other existing models, results show that the proposed hybrid model generate the most accurate forecast
PERAMALAN PENGGUNAAN BEBAN LISTRIK JANGKA PENDEK GARDU INDUK BAWEN DENGAN DSARIMA Saptyani, Marita; Sulandari, Winita; Pangadi, Pangadi
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Jurusan Statistika FSM Undip

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Abstract

Bawen substation is a part of electrical distribution system. Forecasting load demand is required for power planning. Data used in this research are an hourly load demand of Bawen, Salatiga for 3 months, from February 2, 2013 to April 29, 2013, measured in Megawatt (MW).A half hourly load demand forecasting is needed for real time controlling and short-term maintenance schedulling. Since the data have two seasonal periods, i.e. daily and weekly seasonality with length 48 and 336 respectively, the model of double seasonal ARIMA (DSARIMA) is proposed as the most appropriate model for the case. Initial model is determined by the pattern of the data, based on the autocorrelation function plot. Some experiments was done by choosing several periods data. The most suitable model is chosen based on the outsample mean absolute percentage error (MAPE). The current study shows that the DSARIMA (0, 1, [1, 20, 47])(0, 1, 1)48(0, 1, 0)336 is the best model to forecast  336 next period.   Keywords: DSARIMA, MAPE, Electricity, Bawen
PERANCANGAN DAN PEMBUATAN APLIKASI D3 TEKNIK INFORMATIKA UNS BERBASIS WEB DAN ANDROID Yudhanto, Yudho; Nova, Dimas Sadewo Jumpa; Sulandari, Winita
Indonesian Journal of Applied Informatics Vol 1, No 1 (2016)
Publisher : Universitas Sebelas Maret

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Abstract

Field of information technology is one of the major role holder still lives today. With the technology more easily obtain the information society.System and Application D3TIUNS created using waterfall method, D3TIUNS web based applications created using programming language PHP with CodeIgniter Framework. And Android-based applications D3TI created using the Java programming language with Android Studio tool with the programming language php, java and using CodeIgniter Framework.The design used in the making of this application include: table of functional requirements, use case diagram, ERD, activity diagrams, Sequence diagrams and interface design. For application testing using methods blackbox. The results of this thesis is the creation of information system D3 Informatics Engineering UNS web-based and application-based android D3TI
PERANCANGAN DAN PEMBUATAN APLIKASI SISTEM GUDANG SENJATA (SGS) DI BATALYON XYZ Yudhanto, Yudho; Darmawan, Setiadi; Sulandari, Winita
Indonesian Journal of Applied Informatics Vol 1, No 1 (2016)
Publisher : Universitas Sebelas Maret

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Abstract

The armory is an important place in a battalion. The function of armoury is weapon place when the weapon is not used by members. Members acquire weapons of the lending process in the armory by armory staff. The process of borrowing in an armory still use manual recording so it takes time. So the armory need a system to speed up the transaction process of borrowing and the returning weapons to the armory.The implementation of application is using codeigniter framework, PHP, Javascript and barcode. Results of the application armory system that can handle the transaction process of borrowing and returning weapons using barcode. The application also able weapons data management as well as members involved in it.
PERANCANGAN DAN PEMBUATAN APLIKASI CARIKOST DENGAN METODA SIMPLE ADDITIVE WEIGHTING BERBASIS WEB DAN ANDROID Yudhanto, Yudho; Khairun, Fadlul Ilmi; Sulandari, Winita
Indonesian Journal of Applied Informatics Vol 1, No 1 (2016)
Publisher : Universitas Sebelas Maret

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Abstract

Boarding house is a residence for rent for certain immigrants who settled diarea within a certain period . There have been many technologies that offer information about the boarding house but is still considered to be less efficient due to search for boarding in accordance with the desired criteria , boarding seekers still have to compare one by one facility as well as the criteria that owned the boarding house . Use of Simple Additive weighting method ( SAW ) on a decision support system is one of the solutions to deal with such matters , where the boarding seekers will find it helpful because it can give recommendations boarding places corresponding to the desired criteria .Research methodology to design and create this application is to use research methods waterfall that is by collecting data, analyzing system (define functional requirements and non functional), do the design (ERD, use case diagrams, use case text, sequence diagrams, and class diagram), and implementation (coding and testing). Marketplace information system is created using the programming language PHP CodeIgniter-based framework 2 and the MySQL database.Applications are focused in finding a boarding recommendation in accordance with the criteria corresponding to the booking to boarding room can be done with this application . With the app is expected to help seekers boarding house to get the best boarding recommendation and can assist in the boarding room reservations and provide benefits to the owner of the boarding house to be able to market his boarding house .
Estimating the function of oscillatory components in SSA-based forecasting model Sulandari, Winita; Subanar, Subanar; Suhartono, Suhartono; Utami, Herni; Lee, Muhammad Hisyam
International Journal of Advances in Intelligent Informatics Vol 5, No 1 (2019): March 2019
Publisher : Universitas Ahmad Dahlan

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Abstract

The study of SSA-based forecasting model is always interesting due to its capability in modeling trend and multiple seasonal time series. The aim of this study is to propose an iterative ordinary least square (OLS) for estimating the oscillatory with time-varying amplitude model that usually found in SSA decomposition. We compare the results with those obtained by nonlinear least square based on Levenberg Marquardt (NLM) method. A simulation study based on the time series data which has a linear amplitude modulated sinusoid component is conducted to investigate the error of estimated parameters of the model obtained by the proposed method. A real data series was also considered for the application example. The results show that in terms of forecasting accuracy, the SSA-based model where the oscillatory components are obtained by iterative OLS is nearly the same with that is obtained by the NLM method.