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Meiliyani Siringoringo
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eksponensial@fmipa.unmul.ac.id
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Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
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INDONESIA
Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Core Subject : Economy, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 11 Documents
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Search results for , issue "Vol 9 No 2 (2018)" : 11 Documents clear
Pemodelan Generalized Space Time Autoregressive (GSTAR) Pada Data Inflasi di Kota Samarinda dan Kota Balikpapan Riska Handayani; Sri Wahyuningsih; Desi Yuniarti
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

One of the macroeconomic indicators used in the preparation of government’s economicpolicy is inflation. Inflation is a data time series monthly that also is influenced by location effects. Generalized Space Time Autoregressive (GSTAR) is a time series methode that combines time and location effects. The case study is applied of GSTAR for forecasting inflation in two cities in East Kalimantan namely Samarinda and Balikpapan. This research aims to implement GSTAR model to gain forecasting model for inflation data in Samarinda city and Balikpapan city by using method of cross-correlation normalization. The resulting model is GSTAR model GSTAR (2,1) and GSTAR (3,1). The model obtained is not feasible to be used for forecasting, because it does not meet the white noise assumption.
Penerapan Metode Fuzzy Subtractive Clustering Nur Azizah; Desi Yuniarti; Rito Goejantoro
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Cluster analysis is a statistical analysis to classify the objects to be some clusters based on checked variables and similarity of character between the objects. Quality of human living or society has been influenced by many things. In reality, population density is very influential to the quality of human living because high population density will cause many problems that impact on deterioration of quality of human living. Fuzzy Subtractive Cluster (FSC) methods using the data as a candidate of cluster center, so that duty of computation is hanging on the number of data and is not hang at dimension of data. This study aims is to determine the results of FSC at clustering the district in East Borneo based on wide of the district and total of population in 2015. The result shows there is 8 until 24 districts which have high population density. From validity of cluster, it isfounded that the best result for clustering the district in East Borneo based on wide of the district and sum of citizen in 2015 is 2 clusters, there are narrow district with many citizen and wide district with few citizen.
Analisis Value At Risk Portofolio Saham Menggunakan Metode Varian-Kovarian Nur Rizki Wahidah; Yuki Novia Nasution; Nanda Arista Rizki
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Investing is a human effort to save a certain amount of money in time, in the hope of gaining some profit in the future. Investment decisions are fundamentally related to the management of funds in a given period, in which investors have hope to earn income or profit from the funds invested. Almost all investors do not want losses when investing. Various ways are done to avoid loss, or at least maximize profits with minimal risk. The value of risk that is often used is Value At Risk (VaR). Values ​​At Risk (VaR) is one of the statistical tools used to measure the maximum loss of an asset or investment over a certain period with a certain degree of confidence to reduce the occurrence of the risk. This study aims to determine how the risk of stock portfolio of PT. Astra Agro Lestari Tbk (AALI) and PT.PP London Sumatra Indonesia Tbk (LSIP) use Value at Risk analysis using Varian-Covariance method at closing price of shares incorporated in Jakarta Islamic Index (JII) and Asset Value at Risk PT. Astra Agro Lestari Tbk (AALI) and PT.PP London Sumatra Indonesia Tbk (LSIP) to Value at Risk Portfolio. The results showed that if the initial fund invested to PT. Astra Agro Lestari Tbk. and PT.PP London Sumatra Indah Tbk. Rp. 10.000.000, - with a 95% confidence level obtained Value at Risk (VaR) of Rp. 369.682. this can be interpreted there is a 95% confidence that the losses received by investors will not exceed from Rp. 369.682..The result of PT. Astra Agro Lestari tbk. against portfolio risk at 6% and PT. PP London Sumatra Indonesia Tbk. of portfolio risk is 46%.
Penerapan Diagram Kontrol Multivariate Exponentially Weighted Moving Variance (MEWMV) Agustina Feni Baransano; Sri Wahyuningsih; Yuki Novia Nasution
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Statistical Process Control based on the quality characteristics can be divided into two kinds, namely univariate control chart and multivariate control charts.This study usedMultivariate Exponentially Weighted MovingVariance Control Chart (MEWMV).PDAM Tirta Mahakam in the districts of Kutai Kartanegara is one of the regional companies engaged in the production of drinking water, which is located in Tenggarong, East Kalimantan.In the production process, PDAM Tirta Mahakam always refers to the standard which is set by the government in producing drinking water.The purpose of this study was to determine whetherwater quality characteristics of PDAM Tirta Mahakam in a controlledstate or not by using control charts MEWMV,and to know the the water process capability. From the result of research it can be concluded that by using MEWMV control chart with weight , , and , show that the condition has been statistically in control. Process capability index MCpin multivariateexplains that the process has not been capable in precision with a value of 0,896 or not meet the specifications of the company.
Analisis Model Threshold Generalized Autoregressive Conditional Heteroskedasticity (TGARCH) dan Model Exponential Generalized AutoregressiveConditional Heteroskedasticity (EGARCH) Julia Julia; Sri Wahyuningsih; Memi Nor Hayati
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

In the field of finance, Autoregressive Integrated Moving Average (ARIMA) is one of the models that can be used. Financial data usually have a non constant variance error. Thus, Autoregressive Conditional Heterokedasticity (ARCH )model can be used to solve the problem. In addition, it also can be used the development of ARCH model that is Generalized Autoregressive Conditional Heterkadasticity (GARCH) model. The symmetry of residual data can be determined by using the model of Threshold Generalized Autoregressive Conditional Heterkadasticity (TGARCH) and the model of Exponential Generalized Autoregressive Conditional Heterkadasticity (EGARCH). The purpose of this research is to know the best model among the model of TGARCH and the model of EGARCH in predicting Indonesia Composite Index (ICI) and the results of ICI forecasting by using the best model for the period of July 2017 until December 2017. The best model in the ICI case study from January 2011 to June 2017 is the model of ARIMA (1,1,1) -GARCH (1,2) -EGARCH (1). The results of ICI forecasting by using the model of ARIMA (1,1,1) -GARCH (1,2) -EGARCH (1) obtained an upward trend in the period of July 2017 to December 2017.
Penerapan Metode Full-Profile Dalam Pengumpulan Data Untuk Analisis Konjoin Roy Tridoni Situmorang; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Conjoint analysis is an analytical technique that is used to examine the impact of attributes of goods or service. Conjoint analysis can be applied to know the attribute that become the main choice of student of Mulawarman University in choosing GSM prepaid card product. Where the attribute used are SMS tariff, phone tariff, internet package, signal and bonuses. The purpose of this study is to know the combination of attribute level which is most interested by student and relative importance value from each attribute. The result of this study is the combination of attributes of the GSM prepaid card that the student are interest in are the SMS package tarif with the utility value is 1,445, the phone tarif per minute with the utility value is 0,525, full 4G internet package with the utility value is 2,51, strong signal with the utility value is 1,895, SMS bonus with the utility value is 1,42. The attribute that become the student’s preferred choice in choosing GSM prepaid card is internet package with the relative importance value is 0,352.
Pengklasifikasian Item Persediaan Menggunakan Metode Always Better Control-Fuzzy Retno Octaviyani; Desi Yuniarti; Yuki Novia Nasution
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

ABC Classification is a method of controlling inventory to control a small quantity of goods but has a high usage value. Inventories are categorized into three classes, namely A, B, and C. Fuzzy classification is a classification used to classify training data sets (data sets used to generate membership functions) and to predict data testing. The purpose of this study was to control inventory using the ABC classification method, Fuzzy Classification, and ABC-fuzzy classification. The results of ABC classification showed that from 182 items of drug, class A is consisted of 15 items of drug with a value of 69,276% usage, class B is consisted of 34 items of drug with a value of use of 20.723%, and class C is consisted of 133 items of drug with value use of 10.010%. The results of the fuzzy classification showed that of the 182 drug items, fuzzy 3 consisted of 9 medicinal items which meant that, there were 9 very important drugs, fuzzy 2 consisted of 171 drug items which meant that there were 171 important medicines, and fuzzy 1 consisted of 2 items of medicine which means that, there are 2 less important drugs. The results of the ABC-fuzzy classification showed that of 182 drug items, there were 17 items of drugs in the first priority which means that the 17 items of this drug are most preferred, then there are 41 items of drug on the 2nd priority which means the stock of 41 items of this drug is preferred, 124 items of drug on priority 3 which means that 124 items of this drug is not preferred.
Prediksi Data Curah Hujan Dengan Menggunakan Statistika Non Parametrik Gracia Indah Fajarini; Ika Purnamasari; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Rainfall data analysis is the first stage of a water resource planning. One of rainfall data analysis method is using rain frequency analysis. In this research, rainfall frequency analysis is used to prediction the probability of occurrence from hydrological event. The maximum monthly rainfall frequency distribution is affects to rainfall during high repeat periods. Rainfall is the amount of water that falls on a flat surface during certain repetitive periods. Secondary data is got from Temindung Station of Samarinda City on 2007 to 2016. The type of distribution are used Normal, Gumbel, Log Pearson Type III, and Log Normal. Compatibility test of Non Parametric Statistics using Chi Square method. The results showed if the estimated rainfall at the highest repeating period of 2, 5, 10, 25, 50, and 100 years is Log Normal distribution. The distribution that requirement of qualify criteria is Log Normal and Gumbel distribution. The distribution that fit from Chi Square test is Gumbel distribution is 3,5177 and Log Normal distribution is 6,8945. From Kolmogorov Smirnov test the value of Gumbel distribution is 0, and Log Normal distribution is 0,0805. Rainfall patterns for Normal distribution, Gumbel distribution, Pearson Log distribution Type III and Log Normal distribution are horizontal patterns.
Penjadwalan Proyek Dengan Metode Program Evaluation and Review Technique (PERT) Nur Annisa Roziya; Ika Purnamasari; Wasono Wasono
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (541.805 KB) | DOI: 10.30872/eksponensial.v9i2.305

Abstract

Project scheduling is one of the techniques developed in operations research to solve management problems to obtain optimal solutions. One of the methods used for project scheduling is the method of Program Evaluation and Review Technique (PERT). In PERT method, three time estimates are used, that is optimistic time (a), pessimistic (b), and realistic (m). In this study, PERT method is used to determine the optimal duration and probability value of the completion of the Grand Sangatta housing project on house type 36 which is sourced from CV Miftah Collection. The data obtained are primary data and interview. Based on the results of the analysis, it can be know the activities that are on the critical path are the activities of making the foundation (B), concrete (D), wall (E), roof (H), ceiling (I), and painting (L). The minimum time duration of completion of type 36 homes is 34 days with a 50% confidence level which was originally scheduled for 60 days.
Analisis Survival pada Data Kejadian Bersama Menggunakan Metode Exact Partial Likelihood Rahmawati Isnaeni; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Survival data is the data of survival time until the appearance of certain events. In the survival analysis, ties are sometimes found, that is the situation where there are two or more individuals who experience the same event at the same time. There are several methods in estimating the parameters in the case of a ties, one of which is by applying the exact partial likelihood method. The exact method is the most accurate method, which can be applied in estimating Cox regression parameters from traffic accident data of Samarinda City in 2016. Traffic accidents are one of the most deadly events. The four main factors that cause traffic accidents are human factors, vehicles, roads, and weather or environmental factors. The variables used in this study are age, gender, role of victim, driver’s license, vehicle type, time of incident, line of the road, and weather. The results of analysis with the help of Rstudio software showed that the factors whose affect the fatality rate of traffic accident victims of Samarinda City are age and gender. For the age variables concluded that each addition of one year of age of the accident victim, the risk of dying from a traffic accident will also increase 1,0258 times. As for the gender variables concluded that the victim of male sex has a risk of 0.4180 times greater to die due to traffic accidents compared with female victims.

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