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All Journal Media Statistika Jurnal Gaussian TRANSIENT: Jurnal Ilmiah Teknik Elektro

Rita Rahmawati

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 3131505

Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Other

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PERBANDINGAN METODE ARIMA BOX-JENKINS DENGAN ARIMA ENSEMBLE PADA PERAMALAN NILAI IMPOR PROVINSI JAWA TENGAH Riski Arum Pitaloka; Sugito Sugito; Rita Rahmawati
Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Import is activities to enter goods into the territory of a country, both commercial and non-commercial include goods that will be processed domestically. Import is an important requirement for industry in Central Java. The increase in high import values can cause deficit in the trade balance. Appropriate information about the projected amount of imports is needed so that the government can anticipate a high increase in imports through several policies that can be done. The forecasting method that can be used is ARIMA Box-Jenkins. The development of modeling in the field of time series forecasting shows that forecasting accuracy increases if it results from the merging of several models called ensemble ARIMA. The ensemble method used is averaging and stacking. The data used are monthly import value data in Central Java from January 2010 to December 2018. Modeling time series with Box-Jenkins ARIMA produces two significant models, namely ARIMA (2,1,0) and ARIMA (0,1,1). Both models are combined using the ARIMA ensemble averaging and stacking method. The best model chosen from the ARIMA method and ensemble ARIMA based on the least RMSE value is the ARIMA model (2,1,0) with RMSE value of 185,8892 Keywords: Import, ARIMA, ARIMA Ensemble, Stacking, Averaging

ANALISIS VARIANSI PADA RANCANGAN BUJUR SANGKAR YOUDEN DENGAN DUA DATA HILANG Amalina Sari Dewi; Tatik Widiharih; Rita Rahmawati
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Youden Square Design (YSD) is an incomplete latin square design with at least one row/column which can’t run in an experiment. In this research we took 5x4 YSD (one column is not runned in an experiment). This design has a balance characteristic from a balanced incomplete block design where all treatments appears with the same number in each row. Missing data can occur in YSD. In this discussion, YSD with two missing data was used. Missing data is estimated by an iterative method then we arrange analysis of variance and LSD test. Analysis of variance with two missing data in YSD is calculated by adjusting the treatment sum of squares with it’s bias value and the total degrees of freedom and error degrees of freedom are substracted by two. LSD test is carried out if the treatment has a significant effect to the response. To clarify the discussion in YSD, example of application in the field of industry is given by observing the effect of the assembly method to the length of assembly time of X component. The assembly method has an effect to the length of assembly time of X component and if the missing data are and so the suggested assembly method is E method because it has the fastest average assembly time. Keywords: YSD, Missing Data, Analysis of Variance, LSD Test

SEGMENTASI PELANGGAN E-MONEY DENGAN MENGGUNAKAN ALGORITMA DBSCAN (DENSITY BASED SPATIAL CLUSTERING APPLICATIONS WITH NOISE) DI PROVINSI DKI JAKARTA Windy Rohalidyawati; Rita Rahmawati; Mustafid Mustafid
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Customer segmentation is one effective way of marketing to determine the most potential target market. Increasing of E-money usage in DKI Jakarta and more banks are providing E-money products. One way to be able to compete in the global market, banks can segment customers. Determining potential customers of E-money users in DKI Jakarta can form segments by applying the DBSCAN (Density Based Spatial Clustering Application with Noise) algorithm. The quality of segments was measured by using the Silhouette Coefficient. In this study, E-money customers were grouped by reason of using the bank used, transaction activities, number of transactions, nominal balance, and frequency of top-up. The results of this study were using the density radius of 2 and minimum 3 objects that enter the density radius forming 2 segments and 17 noises. The segment quality value of 0.26. The most potential segment was the segment that has an average greater than the average of all data.

ANALISIS KURVA SURVIVAL KAPLAN MEIER MENGGUNAKAN UJI LOG RANK (Studi Kasus :Pasien Penyakit Jantung Koroner di RSUD Undata Palu) Arianti Suhartini; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Coronary heart disease is one of the leading causes of death in the world, including Indonesia. Based on doctor-diagnosed interviews, coronary heart disease’s prevalence in Indonesia on 2013 is 0,5% and based on a doctor-diagnosed is 1,5%. Central Sulawesi is ranked first and second for prevalence based on doctor-diagnosed interviews and doctor-diagnosed. The high number of people with coronary heart disease caused by lack of self-awareness in lifestyle changes. One of the parameters used to assess the success of treatment is the probability of survival. Survival analysis is a data analysis where the outcome of the variables studied is the time until an event occurs. This study raised the problem of survival of coronary heart patients at Undata Palu Hospital which is the main referral hospital for Central Sulawesi region. This research uses nonparametric method that is Kaplan Meier and Log Rank Test based on six factors are age, gender, stadium, disease status, complication and status of anemia. Nonparametric methods do not follow a particular distribution for survival time. Kaplan Meier's survival curve will describe the patient's characteristics of survival probability and followed by a Log Rank test to see if there are differences between curves. The result of analysis and discussion based on Log Rank test result showed that the factors of age, sex and disease status differ significantly. Keywords: Coronary heart disease, RSUD Undata Palu, Kaplan Meier analysis, Log Rank test.

PEMODELAN PENGELUARAN PER KAPITA DAN PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH MENGGUNAKAN REGRESI BIRESPON SPLINE TRUNCATED Merinda Pangestikasari; Rita Rahmawati; Dwi Ispriyanti
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The Central Bureau of Statistics states that the average per capita spending (Y1) of Central Java Community in 2016 is around 27.808 rupiah per day. This value is still considered low, because it covers all the needs of an individual's life. The low expenditure per capita indicates the low level of welfare. Another indicator that can be used to measure community welfare is the percentage of poverty (Y2). Through this variable can be known how proportion of people who still difficult to meet their needs. Many factors are suspected to affect welfare, one of which is the average variable of school length (X). This study aims to get the best model and know the goodness of the model. Approach is done by nonparametric regression that is regres biresponse spline truncated. Nonparametric approach is done when data function does not show certain pattern. The best spline truncated biresponse model is highly dependent on determining the order and location of the optimal knot point that has a minimum Mean Square Error (MSE) value. In this study, the best model is obtained when order of Y1 is 2 and order of Y2 is 2 with five knots. The location of the knot point obtained is 7,05; 7,17; 7,32; 9,82 and 10,29 with MSE value of 662634,2. The goodness of the model is measured based on R-Square and MAPE, R-Square=43,21%, means the variance of response variables that can be explained by the predictor variable are 43,21% while the rest is influenced by other variables and MAPE=14,25%. Based on the value of MAPE can be said that the model had a good performance. Keywords: Welfare, Expenditure, Percentage of Povery, Birespon Spline, Truncated, MSE

PERAMALAN EKSPOR NONMIGAS DENGAN VARIASI KALENDER ISLAM MENGGUNAKAN X-13-ARIMA-SEATS (Studi Kasus: Ekspor Nonmigas Periode Januari 2013 sampai Desember 2017) Eka Lestari; Tatik Widiharih; Rita Rahmawati
Jurnal Gaussian Vol 7, No 3 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Non-oil and gas exports are one of the largest foreign exchange earners for Indonesia. Non-oil and gas exports always experience a decline in the month of Eid Al-Fitr due to delays in the delivery of export goods because the loading and unloading of goods at the port is reduced during Eid Al-Fitr. The shift of the Eid Al-Fitr month on the data will form a pattern or season with an unequal period called the moving holiday effect. The time series forecasting method that usually used the ARIMA method. Because the ARIMA method only suitable for time series data with the same seasonal period and can’t handle the moving holiday effect, the X-13-ARIMA-SEATS method used two steps. First, regARIMA modeling is a linear regression between time series data and the weight of Eid Al-Fitr and the residuals follow the ARIMA process. The weighting is based on three conditions, namely pre_holiday, post_holiday, and multiple. Second, X-12-ARIMA decomposition method for seasonal adjustments that produces trend-cycle components, seasonal, and irregular. Based on the analysis carried out on the monthly non-oil and gas export data for the period January 2013 to December 2017, the X-13-ARIMA-SEATS (1,1,0) model was obtained in the post_holiday condition as the best model. The forecasting results in 2018 show the largest decline in non-oil and gas exports in June 2018 which coincided with the Eid Al-Fitr holiday. MAPE value of 10.90% is obtained which shows that the forecasting ability is good.Keywords: time series, non-oil and gas, X-13-ARIMA-SEATS, moving holiday

PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017) Eka Destiyani; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords: Ordinary Least Squares (OLS), Multicollinearity, Outliers, RidgeRegression, Robust Regression, AKB.

GRAFIK PENGENDALI MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING COVARIANCE MATRIX (MEWMC) PADA DATA SAMPEL ZAT KANDUNGAN BATU BARA (Studi Kasus : PT Bukit Asam (Persero) Tbk. Tahun 2016) Sensiani Sensiani; Tatik Widiharih; Rita Rahmawati
Jurnal Gaussian Vol 9, No 1 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The progress of industrial business in the midst of global competition increased rapidly. A businessman should have special treatment for their products to compete of market quality. The quality of product is an important factor in choosing a product or service, particularly for the costumers. In technological development, the factors of failure in the product can be minimized by Statistical Quality Control. Besides to reducing diversity in product characteristics, statistical quality control can increase business income. The data source of this research is sekunder sample data of coal products of PT Bukit Asam (Persero) Tbk. with seven variables, the variables is Total Moisture (TM), Inherent Moisture (IM), Ash Content (ASH), Volatile Matter (VM), Fixed Carbon (FC), Total Sulfur (TS), and Calorific Value (CV). The analytical method is the controlling chart of Multivariate Exponentially Weighted Moving Covariance Matrix (MEWMC) which is one of the multivariate charts that serves to detect small shift in covariance matrix and the development of Multivariate Exponentially Weighted Moving Average (MEWMA) charts. Based on the results of the analysis, the MEWMA control chart is statistically controlled with a weighting value λ=0,2 while the MEWMC chart with λ=0,2 is not controlled statistically and detected small shift in covariance matrix . In a controlled process, the capability value of multivariate process is 0,83222 < 1 which means the process is not capable.Keywords: MEWMA control chart, MEWMC control chart, Process capability analysis.

PERBANDINGAN REGRESI KOMPONEN UTAMA DENGAN REGRESI KUADRAT TERKECIL PARSIAL PADA INDEKS PEMBANGUNAN MANUSIA PROVINSI JAWA TIMUR Vetranella .T.R.A. Sinaga; Diah Safitri; Rita Rahmawati
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v8i4.26749

The multiple regression classic assumptions are used to give linear unbiased and minimum variance estimator. In Human Development Index (HDI) and influencing factors in East Java, there are two variables with VIF more than 10 so the assumption of non-multicollinearity is not fulfilled. Principal component regression (PCR) and partial least squares regression (PLS-R) can solve this problem. By doing principal component analysis, there are two linear combinations to take as the new independent variables which are free from collinearity. In the PLS-R, NIPALS algorithm is used to calculate the components and other structures and to estimate the parameter. While in PCR all independent variables are significant, the percentage of households with drinking water is feasibles is not significant in the model. PLS-R’s is 95,85% is greater than PCR’s = 93,42%. PCR’s PRESS = 81,78 is greater than PLS-R’s PRESS = 61,0595.Keywords: Human Development Index (HDI), Multicollinearity, Principal Component Regression, Partial Least Squares Regression, , PRESS

ANALISIS KESEIMBANGAN BEBAN DI GEDUNG ICT UNIVERSITAS DIPONEGORO Rita Devi Rahmawati; Bambang Winardi; Ajub Ajulian Zahra
Transient: Jurnal Ilmiah Teknik Elektro TRANSIENT, VOL. 10, NO. 2, JUNI 2021
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/transient.v10i2.361-369

Gedung ICT Universitas Diponegoro merupakan gedung yang difungsikan sebagai gedung perkantoran bagi Lembaga Pengembangan & Penjaminan Mutu Pendidikan (LP2MP) dan Lembaga Penelitian dan Pengabdian Kepada Masyarakat(LPPM).Dengan data hasil pen gukuran yang dilakukan menggunakan Power Quality Analyzer dan tangampere, maka didapatkan adanya ketidakseimbangan beban. Salah satu tanda ketidakseimbangan beban adalah adanya arus netral. Pengukuran pada SDP lantai 1 diketahui arus netral sebesar 5,8 A. Oleh karena itu dilakukan analisis mengenai keseimbangan beban di Gedung ICT Universitas Diponegoro menggunakan software bantu ETAP 12.6 dan evaluasi Circuit Breaker sebagai perlatan proteksi demi terciptanya keamanan dan kenyamanan. Berdasarkan hasil perhitungan dan simulasi ETAP 12.6 maka didapatkan nilai arus netral pada SDP Lantai 1 sebesar 0,7 A, selain itu Circuit breaker yang terpasang masih berfungsi dengan baik.

Co-Authors Abdul Hoyyi Abdur Rofiq Agus Rusgiyono Ajub Ajulian Zahra Macrina Alika Ramadhani Amalina Sari Dewi Arianti Suhartini Bambang Winardi Budi Warsito Denny Jales Manalu Di Asih I Maruddani Diah Safitri Dina Rahma Prihatiningsih Dwi Ispriyanti Eka Destiyani Eka Lestari Ekky Rosita Singgih Wigati Enggartya Andini Ihdayani Banun Afa Ihdayani Banun Afa Jeffri Nelwin J. O. Siburian Merinda Pangestikasari Mustafid Mustafid Mutik Dian Prabaning Tyas Riski Arum Pitaloka Rukun Santoso Sensiani Sensiani Sudarno Sudarno Sugito Sugito Suparti Suparti Suparti Suparti Tatik Widiharih Triastuti Wuryandari Umiyatun Muthohiroh Vetranella .T.R.A. Sinaga Windy Rohalidyawati

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