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All Journal Jurnal Varian ARRUS Journal of Mathematics and Applied Science VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Research Applications in Community Services Eksponensial IJASDS: Indonesian Journal of Applied Statistics and Data Science

Siringoringo, Meiliyani

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Author-ID : 1153728

Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Aplikasi Metode Double Exponential Smoothing Holt Dengan Optimasi Golden Section Untuk Peramalan Nilai Ekspor Provinsi Kalimantan Timur Andini, Putri Dwiayu Aulia; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 15 No. 1 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i1.1278

Exponential smoothing is a method of time series analysis used to forecast the future. The choice of forecasting method takes into account data patterns, such as Double Exponential Smoothing (DES) Holt is used on data that has a trend pattern, and Triple Exponential Smoothing (TES) Holt-Winters is used on trend and seasonal data. The aim of this research is to obtain the best forecasting method by optimizing the golden section on the export value of East Kalimantan Province from 2015 to 2022 and to obtain the results of forecasting the export value of East Kalimantan Province for the next 3 months using the best method by optimizing the golden section. The research results show that the parameter value using golden section optimization is for and for with a MAPE value of . Successive forecasting results in January 2023 are January 2023 is 3.503,201 million USD, February 2023 is 3.577,731 million USD, and March 2023 is 3.612,201 million USD.

Optimasi Parameter Pemulusan Pada Metode Peramalan Double Exponential Smoothing Holt Menggunakan Golden Section: Studi Kasus : NTPT Provinsi Kalimantan Timur Tahun 2014-2019 Yani, Tika Anggre Ria; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Double Exponential Smoothing Holt (DES Holt) is a method that can be used when the data pattern shows a trend pattern. Determination of smoothing parameters usually uses trial and error, but this method still has inefficient results to get the best accuracy. One method that can be used to determine the smoothing parameters value is the golden section method. The application of the DES Holt and golden section methods will be carried out to predict the Exchange Rate of Farmers Subsector Livestock (ERFSL) of East Kalimantan Province. The purpose of this study was to obtain forecasting results and the level of accuracy of the ERFSL of East Kalimantan Province for the period January, February, and March 2020 using the DES Holt methods with the golden section smoothing parameter optimization method. The Forecasting results of DES Holt method have increased in the next three periods with an accuracy rate of 0.8856663%. The level of accuracy of forecasting results using the DES Holt methods has a MAPE value of less than 10%, which means the methods very good for predicting the ERFSL of East Kalimantan Province.

Penerapan Model Geographically Weighted Logistic Regression Pada Data Status Kesejahteraan Masyarakat di Kalimantan Tahun 2017 Pratiwi, Nadya; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Logistic Regression (GWLR) model is a regression model developed from logistic regression which is applied to spatial data. The aims of research is a GWLR model determination on dichotomous data of community welfare status based on the Human Development Index (HDI) and to find the factors influencing the probability of high welfare status of each Regency/City on Kalimantan Island in 2017. Parameters estimation of the GWLR model was done at each observation location using a weighted Maximum Likelihood Estimation (MLE) method and maximum likelihood estimator was obtained by Newton Raphson iterative method. Spatial weighting on parameter estimation was determined using Adaptive Gaussian weighting function and optimum bandwidth was determined using Generalized Cross-Validation (GCV) criterion. Based on the result of GWLR parameter testing, it was concluded that the factors influencing the probability of high welfare status of Regency/City on Kalimantan Island in 2017 were school enrollment rates (senior high school), the number of health workers, real per capita income and the open unemployment rate.

Analisis Faktor-Faktor Yang Berpengaruh Terhadap Pencemaran Air Sungai Mahakam Menggunakan Pemodelan Geographically Weighted Logistic Regression Pada Data Dissolved Oxygen Lestari, Vivi Dwi; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Logistic Regression (GWLR) model is a local model of the logistic regression model applied to spatial data. Parameter estimation is performed at each observation location using spatial weighting. The spatial weighting is calculated by using an adaptive tricube function and bandwidth optimum was obtained based on Generalized Cross Validation (GCV) criteria. The purpose of this study was to obtain a GWLR model on the water pollution indicator Dissolve Oxygen (DO) in Mahakam River in East Kalimantan Province and to find factors affecting the probability of the Mahakam River water was not polluted based on DO indicator. The research data is secondary obtained from Environmental Department of East Kalimantan. The parameter estimation method was Maximum Likelihood Estimation (MLE). The research result showed that the closed form of ML estimator could not be found analytically and it can be approximed by using Newton-Raphson iterative methods. Based on the result of partial hypothesis test, the factors influencing the probability of the Mahakam River water was not polluted is different for every observation location. They were phosphate consentration, total dissolved solid and nitrite consentration. The factor influencing globally was total dissolved solid.

Peramalan Inflasi Kota Balikpapan Menggunakan Metode Singular Spectrum Analysis Sergio, Andrean; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 14 No. 1 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Singular Spectrum Analysis (SSA) is a nonparametric forecasting method capable of separating time series data into interpretable trend, seasonal, cycle, and noise. Methods with component separation are suitable for characterizing economic and business data trends that tend to contain stationary, trend, cycle, and seasonal factors. One of the economic data that can be used in research is inflation. The purpose of this study is to obtain the results of inflation forecast in Balikpapan City from November 2022 to October 2023. Based on the forecasting results of the SSA method on inflation in Balikpapan City, the MAAPE value was 23.53% which showed that the forecasting results were quite accurate. Based on the results of inflation forecast from November 2022 to October 2023, there was a decrease in inflation in November 2022 by -0.64% or it could be said that there would be deflation by 0.64%. Over the next period, inflation tends to increase where the highest inflation will occur in June 2023, which is 1.96%.

Penentuan Jalur Terpendek dengan Metode Heuristik Menggunakan Algoritma Sarang Semut (Ant Colony): Studi Kasus: Jalan Arteri Sekunder Kota Samarinda Hidayat, Alfian; Purnamasari, Ika; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Ant Colony algorithm was adopted from the behavior of ant colonies, known as the system of ants, ant colonies are naturally able to find the shortest route on their way from nest to food source places. Colony of ants can find shortest route between the nest and food sources based on the trajectory of footprints that have been passed. The density of ant footprints on the path is always updating because of the evaporation of the footprints and the determination of ant pathways using probability calculations. This study aims to determine the results of determining the shortest path using the ant colony algorithm as the best route from the Samarinda City secondary arterial road with the route starts from Slamet Riyadi road to DI Panjaitan road. Based on the results of the study using the ant colony algorithm obtained the shortest path of 8.307 kilometers with footprint density of 1.005.

Peramalan Harga Minyak Goreng di Kalimantan Timur Menggunakan Model Hybrid Time Series Regression Quadratic – Neural Network Wahyuni, Risa Kristia; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 14 No. 2 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i2.1123

A hybrid model is a combination of two or more forecasting methods. One of hybrid model that can be used in forecasting is Time Series Regression (TSR) Quadratic – Neural Network (NN). TSR Quadratic can be used in time series data that contains quadratic trend patterns, namely an increase or decrease that forms a curved or parabolic line NN is a method that has characteristics similar to biological neural networks in conducting data pattern recognition. This study was aimed to obtain a hybrid model of TSR quadratic-NN to forecast cooking oil prices in East Kalimantan and obtain forecasting results based on the best model. The results showed that the TSR Quadratic-NN hybrid model with 3 neurons in the hidden layer was the best model with a MAPE of 2.51368%. The forecasting results based on this model showed that cooking oil prices in East Kalimantan from January to December 2023 showed an increase

Peramalan Kredit Modal Kerja di Indonesia Menggunakan Brown's Double Exponential Smoothing dengan Optimasi Pencarian Dikotomis Yustiani, Iis; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Brown's Double Exponential Smoothing (DES) method is a forecasting method with the smoothing process carried out twice. DES Brown has one parameter to define, and it is usually done in a trial and error manner. Another way to determine value parameters more quickly and precisely is to use optimization methods. In this study, forecasting of working capital credit in Indonesia using DES Brown for the period May to July 2022 was carried out with dichotomous search optimization. The results showed that the results of forecasting for working capital loans showed a decrease in May then increased in June and July with a very good forecasting accuracy, namely the MAPE value of 1.480768%.

Model Geographically Weighted Weibull Regression pada Indikator Pencemaran Air Biochemical Oxygen Demand di Daerah Aliran Sungai Mahakam Rahmah, Siti Mahmudatur; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Weibull Regression (GWWR) Model is a Weibull regression model applied to spatial data. Estimation of the GWWR model is performed at every observation location using spatial weighting. The purpose of this study was to determine the GWWR model of water pollution indicator Biochemical Oxygen Demand (BOD) data and the factors that influence BOD in the Mahakam River. The estimating parameters method of the GWWR model was the Maximum Likelihood Estimation (MLE) and it’s estimator was obtained by Newton-Raphson Iterative method. Spatial weighting in parameter estimation was determined using the Adaptive Bisquare weighting function and bandwidth optimum was determined by using Generalized Cross-Validation (GCV) criteria. Based on the GWWR model parameters testing, the factors that influence BOD locally was nitrate concentrations, while the factors influence globally were temperature and nitrate concentration.

Indonesia Gold Price Forecasting Using ARIMA Model (0,1,1) - GARCH (1,0) Sari, Hafivah Rosvita; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 15 No. 1 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i1.1265

A frequently employed time series model is the Autoregressive Integrated Moving Average (ARIMA) model. In highly volatile data, ARIMA models sometimes produce residual variances that are heteroscedasticity. One method that can overcome the problem of residual variance heteroscedasticity is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) method. The purpose of this study is to obtain the ARIMA-GARCH model for daily gold price data in Indonesia for the period 1 January 2022 to 31 December 2022, and to obtain daily gold price forecasting results in Indonesia. The daily gold price forecasting model obtained for Indonesia is ARIMA (0,1,1) - GARCH (1,0) with a MAPE value of 0.5745% which shows that the model is very good because the MAPE value is less than 10%. The results of Indonesia's daily gold price forecast from January 1st, 2023 to January 3rd, 2023 remain stable.

Co-Authors Alfian Hidayat Andini, Putri Dwiayu Aulia Arumsari, Melisa Astafira, Ilyas Cahyani, Era Tri Chairina, Puspa Dani, Andrea Tri Rian Darnah Fauziyah, Meirinda Goenjatoro, Rito Ika Purnamasari Inayah, Ulfah Resti Kesuma, Ahmad Rizky Krisna Rendi Awalludin Lestari, Vivi Dwi M. Fathurahman Mahmuda, Siti Memi Nor Hayati Messakh, Gerald Claudio Mochammad Imron Awalludin Nida, Khairun Octavianto, Thifan Oroh, Chiko Zet Pradipa, Zalva Pratiwi, Nadya Primadigna, Ullimaz Sam Rahmah, Siti Mahmudatur Ramadhani, Adelia Rito Goejantoro, Rito Saputra, Ahmad Ronaldy Sari, Hafivah Rosvita Sergio, Andrean Sinaga, Yetty Veronica Lestari Sri Wahyuningsih Sudarman, Alfiannur Rizki Surya Prangga Suyitno Suyitno Suyono, Ari Krisna Syawal, Al Fitri Wahyuni, Risa Kristia Yani, Tika Anggre Ria Yuniarti, Desi Yustiani, Iis

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