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All Journal Jurnal Informatika Jurnal Teknik Elektro Jurnal Teknik Industri Jurnal Titra Record and Library Journal Journal of Documentation and Information Science International Journal of Industrial Optimization (IJIO)

Siana Halim

Fakulty of Industrial Technology,Industrial Engineering Department, Petra Christian University, Jl. Siwalankerto 121-131, Surabaya 60236

Author-ID : 273217

Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 33 Documents Claim Missing Document

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Articles

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PENDEKATAN MODEL MATEMATIS UNTUK MENENTUKAN PERSENTASE MARKUP HARGA JUAL PRODUK Yuliana, Oviliani Yenty; Wahyudi, Yohan; Halim, Siana
Jurnal Teknik Industri Vol 4, No 2 (2002): DECEMBER 2002
Publisher : Institute of Research and Community Outreach - Petra Christian University

The purpose of this research is to design Mathematical models that can determine the selling volume as an alternative to improve the markup percentage. Mathematical models was designed with double regression statistic. Selling volume is a function of markup, market condition, and substitute condition variables. The designed Mathematical model has fulfilled by the test of: error upon assumption, accurate model, validation model, and multi collinear problem. The Mathematical model has applied in application program with expectation that the application program can give: (1) alternative to decide percentage markup for user, (2) Illustration of gross profit estimation that will be achieve for selected percentage markup, (3) Illustration of estimation percentage of the units sold that will be achieve for selected percentage markup, and (4) Illustration of total net income before tax will get for specific period. Abstract in Bahasa Indonesia : Penelitian ini bertujuan untuk merancang model Matematis guna menetapkan volume penjualan, sebagai alternatif untuk menentukan persentase markup harga jual produk. Model Matematis dirancang menggunakan Statistik Regresi Berganda. Volume penjualan merupakan fungsi dari variabel markup, kondisi pasar, dan kondisi pengganti. Model Matematis yang dirancang sudah memenuhi uji: asumsi atas error, akurasi model, validasi model, dan masalah multikolinearitas. Rancangan model Matematis tersebut diterapkan dalam program aplikasi dengan harapan dapat memberi: (1) alternatif bagi pengguna mengenai berapa besar markup yang sebaiknya ditetapkan, (2) gambaran perkiraan laba kotor yang akan diperoleh setiap pemilihan markup, (3) gambaran perkiraan persentase unit yang terjual setiap pemilihan markup, dan (4) gambaran total laba kotor sebelum pajak yang dapat diperoleh pada periode yang bersangkutan. Kata kunci: model Matematis, aplikasi program, volume penjualan, markup, laba kotor.

Credit Scoring Modeling Halim, Siana; Humira, Yuliana Vina
Jurnal Teknik Industri Vol 16, No 1 (2014): JUNE 2014
Publisher : Institute of Research and Community Outreach - Petra Christian University

It is generally easier to predict defaults accurately if a large data set (including defaults) is available for estimating the prediction model. This puts not only small banks, which tend to have smaller data sets, at disadvantage. It can also pose a problem for large banks that began to collect their own historical data only recently, or banks that recently introduced a new rating system. We used a Bayesian methodology that enables banks with small data sets to improve their default probability. Another advantage of the Bayesian method is that it provides a natural way for dealing with structural differences between a bankâ€™s internal data and additional, external data. In practice, the true scoring function may differ across the data sets, the small internal data set may contain information that is missing in the larger external data set, or the variables in the two data sets are not exactly the same but related. Bayesian method can handle such kind of problem.

Defect Detection on Texture using Statistical Approach Halim, Siana
Jurnal Teknik Industri Vol 17, No 2 (2015): DECEMBER 2015
Publisher : Institute of Research and Community Outreach - Petra Christian University

In this paper we present several techniques for detecting simple defect on the texture. The simple defect means, that the defect can be detected via image histogram or via wavelet of the image histogram. Hill estimator is one of the techniques that we suggest to use to solve this problem, since it does not need estimate parameters for estimating the image density

PENGGUNAAN BOOTSTRAP DATA DEPENDEN UNTUK MEMBANGUN SELANG KEPERCAYAAN PADA PARAMETER MODEL PERAMALAN DATA STASIONER Halim, Siana; Mallian, Herman
Jurnal Teknik Industri Vol 8, No 1 (2006): JUNE 2006
Publisher : Institute of Research and Community Outreach - Petra Christian University

The Bootstrap is a lively research area. A lot Of ideas are around and have let to quiet different proposals. In this paper we sketch briefly some Bootstrap methods for independent and dependent data. Finally we give an Bootstrap example for constructing confidence interval in the forecasting for stationer data. Abstract in Bahasa Indonesia : Bootstrap merupakan area penelitian yang terus berkembang. Ada banyak ide dan proposal-proposal yang berbeda telah diberikan oleh para peneliti. Namun demikian, dalam makalah ini hanya akan diulas secara singkat beberapa metode Bootstrap untuk data independen maupun data dependen. Akhirnya akan diberikan sebuah contoh kasus penggunaan Bootstrap untuk membangun selang kepercayaan pada peramalan data stasioner. Kata kunci: Bootstrap, resampling, peramalan

MODEL MATEMATIK UNTUK MENENTUKAN NILAI TUKAR MATA UANG RUPIAH TERHADAP DOLLAR AMERIKA Halim, Siana; Adelia, Shirley; Rahardjo, Jani
Jurnal Teknik Industri Vol 1, No 1 (1999): JUNE 1999
Publisher : Institute of Research and Community Outreach - Petra Christian University

The main objective of this paper is to estimate parameters in the heteroskedasticity models, particularly in Auto Regressive Conditional Heteroskedasticity - ARCH(1) and Generalized Autoregressive Conditional Heteroskedasticity- GARCH(1,1). These models will be used to fit, to forecast and to update the volatility of Rupiah Vs US.Dollar rate. In order to get the estimation of fitting and updating parameters of ARCH(1) and GARCH(1,1), here will be used iterative method which is derived from the standard maximum likelihood estimation and the initial values are taken from the result of Yule Walker Estimation. The updating parameters will be estimated by using the approach of ARIMA(p,d,q) updating parameters models. The heteroskedasticity models will give a good fitting even a good forecast in near stasioner condition, however this models can not detect the jump that can be happend due to the changes of political situation that happend in Indonesia. Abstract in Bahasa Indonesia : Tujuan utama dari penelitian ini adalah untuk menentukan nilai estimasi pada parameter-parameter yang terdapat pada model-model heteroskedastik, khususnya dalam Auto Regressive Conditional Heteroskedasticity - ARCH(1) dan Generalized Autoregressive Conditional Heteroskedasticity- GARCH(1,1). Model-model ini akan digunakan untuk menentukan, meramalkan dan memperbaharui nilai parameter dari nilai tukar mata uang Rupiah terhadap Dollar Amerika. Nilai estimasi pada model ARCH(1) dan GARCH(1,1) diperoleh dengan metode iteratif yang diturunkan dari estimasi maksimum likelihood baku dan nilai awalnya didapat dari pendekatan Yule Walker. Penentuan nilai parameter yang diperbaharui akan diestimasi dengan menggunakan pendekatan model ARIMA(p,d,q). Model-model heteroskedastik memberikan nilai pendekatan nilai tukar yang baik bahkan memberikan nilai peramalan yang baik pula, namun demikian model ini belum dapat mendeteksi terjadinya loncatan yang terjadi yang diakibatkan oleh perubahan situasi politik di Indonesia. Kata kunci: ARCH, GARCH, YWE, MLE, Heteroskedasticity

PERAMALAN MULTIVARIATE UNTUK MENENTUKAN HARGA EMAS GLOBAL Christian, David; Halim, Siana
Jurnal Teknik Industri Vol 18, No 2 (2016): DECEMBER 2016
Publisher : Institute of Research and Community Outreach - Petra Christian University

Gold is one of the most enticing commodities and a very popular way of investing. Gold?s price is allegedly influenced by another factors such as US Dollar, oil?s price, inflation rate, and stock exchange so that its model is not only affected by its value. The aim of this research is to determine the best forecasting model and influencing factors to gold?s price. This research is modeling gold using multivariate analysis and reviews the univariate modeling as a benchmark and comparison to the multivariate one. Univariate time series is modeled using the ARIMA model which indicates that the fluctuation of the gold prices are following the white noise. Gold?s multivariate modeling is built using the Vector Error Correction Model with oil?s price, US Dollar and Dow Jones indices, and inflation rate as its predictors. Research?s result shows that the VECM model has been able to model the gold?s price well and all factors investigated are influencing gold?s price. US Dollar and oil?s price are negatively correlated with gold?s price as the inflation rate is positively correlated. Dow Jones Index is positively correlated with gold?s price only at its first two periods.

Deteksi Keausan Alat pada Proses Pengeboran Sumber Alam Halim, Siana; ., Felecia
Jurnal Teknik Industri Vol 14, No 2 (2012): DECEMBER 2012
Publisher : Institute of Research and Community Outreach - Petra Christian University

In this paper we applied change point detection methods for failures detection in the drilling process. We calculated the change points on three drilling parameters, i.e., the weight on bit, top drive torque and rate of penetration. Using the concept of reliability, we measured the time between change points as the time between failures. The minimum of mean time between change points from those three parameters is suggested to be the time for monitoring the drilling process.

Pemodelan Time Series Multivariat secara Automatis Halim, Siana; Chandra, Arif
Jurnal Teknik Industri Vol 13, No 1 (2011): JUNE 2011
Publisher : Institute of Research and Community Outreach - Petra Christian University

This research aims at establishing model of multivariate time series by means of econometric instruments. Four instruments in use are vector auto regressive (VAR), structural vector auto regressive (SVAR), vector error correction model (VECM), and structural vector error correction (SVEC). VAR and VECM are employed to estimate and construct models and, subsequently, predict the future values of an object. SVAR and SVEC serve to analyze innovative structures of a model. VAR and SVAR can be implemented only to stationary data whilst VECM and SVEC can be applied to non-stationary inputs. The identification and estimation of the model in this research are specifically designed by R software. Based on this software, all the aforestated models are conclusively able to identify dynamic relationship of endogenous variabel in a model well.

PENERAPAN JARINGAN SARAF TIRUAN UNTUK PERAMALAN Halim, Siana; Wibisono, Adrian Michael
Jurnal Teknik Industri Vol 2, No 2 (2000): DESEMBER 2000
Publisher : Institute of Research and Community Outreach - Petra Christian University

Many methods have been developed to get the optimal result in forecasting. One of them that will be used in this paper is using Neural Network for forecasting. The result will be compared with GARCH(1,1) in the terms of Means Absolute Deviation (MAD) and Means Square Error (MSE). Besides that the accuracy and the power to damp the jump will be observed. The data is currency rate from 4 countries in Asia taken during the Asian Monetary Crisis from 1997 up to 1999 since the jump was happened in that series. Abstract in Bahasa Indonesia : Ada banyak metode yang telah dikembangkan untuk mencapai hasil yang optimal dari suatu peramalan. Salah satu yang akan diulas pada makalah ini adalah penggunaan Neural Network atau jaringan saraf untuk mendapatkan hasil peramalan yang diharapkan dapat meningkatkan optimasi dan akurasinya. Hasil dari metode ini akan dibandingkan dengan metode GARCH(1,1) dalam bentuk Means Absolute Deviation (MAD) dan Means Square Error (MSE). Selain itu dilakukan pula pengamatan terhadap peredaman jump (perubahan mendadak). Data yang digunakan adalah nilai tukar mata uang dari empat negara di Asia yang diambil selama krisis moneter di Asia. Kata Kunci: Backpropagation, MAD, MSE, GARCH(1,1), jump.

Pemetaan Penderita Pneumonia di Surabaya dengan Menggunakan Geostatistik Hartanto, Stefanie; Halim, Siana; Yuliana, Oviliani Yenty
Jurnal Teknik Industri Vol 12, No 1 (2010): JUNE 2010
Publisher : Institute of Research and Community Outreach - Petra Christian University

In this paper we mapped the location of Pneumonia disease in Surabaya. We also analyse the survival of the afflicted and predict the spread of the disease using Kriging. The study reveals that after 45 days in the hospital, the survival of the Pneumoniaâ€™s patients decrease to 46.8%. Moreover, the centers of this disease are in Tubanan and Sukomanunggal Both of these regions are in West Surabaya which also is an industrial part of the city.

Co-Authors Adrian Michael Wibisono Agnes Eval Aida Fitriani Tobing Amelia Agnes Sunjono, Amelia Agnes Arif Chandra Cicely Elviani David Christian, David David Soebiantoro Demmy Kasih, Demmy Dian Wulandari Felecia - Felecia . Felecia Felecia Felicia Tedja Widjaja, Felicia Tedja Genesius Chandra Hendrik Sumawi Herman Mallian Indriati Bisono Indriati N Bisono Inggrid -, Inggrid Inggrid Inggrid Jani Rahardjo Johan Widjaja Njo Anastasia Olivia Sigit, Olivia Oviliani Yenty Yuliana Pauline Astari Singgih Putri, Kristina Sanjaya Shirley Adelia Stefanie Hartanto Tan Didik Wardoyo Tanusi Tanti Octavia Valencia Suseno veronica - Yohan Wahyudi Yuliana Vina Humira

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