Triastuti Wuryandari
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PENENTUAN TREN ARAH PERGERAKAN HARGA SAHAM DENGAN MENGGUNAKAN MOVING AVERAGE CONVERGENCE DIVERGENCE (Studi Kasus Harga Saham pada 6 Anggota LQ 45) Tri Murda Agus Raditya; Tarno Tarno; Triastuti Wuryandari
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.898 KB) | DOI: 10.14710/j.gauss.v2i3.3670

Abstract

One of many examples of technical indicator that frequently used for stock price analysis is Moving Average Convergence Divergence (MACD). MACD generates two signal called goldencross and deathcross are used to find the reversal momentum of stock price trend movement. Goldencross as a oversold point marker serves to give a buying signal. While, deathcross as a overbought point marker serves to give a selling signal. Research on six stocks member of LQ45 (ANTM, BWPT, MNCN, TINS, BJBR, and LPKR) during the period January 1 until October 31, 2012 managed to prove the accuracy of the signal formed by MACD signal. By applying the MACD Indicator consistently, investors can get a percentage of profit above the actual inflation rate in 2012 by Indonesian Bank. On these  results, the goldencross and deathcross signal give a good performance as tool of technical analysis for determining the trend of the direction of stock price movements
ANALISIS INTERVENSI KENAIKAN HARGA BBM BERSUBSIDI PADA DATA INFLASI KOTA SEMARANG Novia Dian Ariyani; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.738 KB) | DOI: 10.14710/j.gauss.v4i3.9485

Abstract

Intervention model is a model of time series data analysis that originally used to explore impact of unexpectedly external events to the observation variable. In this study, an increases subsidized fuel price analysis has done  in June 2013 (first step function) and November 2014 (second step function) for Semarang inflation data at January 2007 until January 2015 and purposed to obtain the intervention model and forecast the Semarang inflation for some time later. Based on the result of inflated subsidized fuel price analysis for Semarang inflation data, the resulted model is ARIMA (1,0,0) with first intervention order   b = 1,  s = 2, r = 0 and second intervention order b = 1, s = 1, r = 0. Furthermore, the model is used to forecast inflation in Semarang for forward some periods.Keywords: ARIMA, intervention analysis, step function, inflation, subsidized fuel.
ANALISIS VARIAN PERCOBAAN FAKTORIAL DUA FAKTOR RAKL DENGAN METODE FIXED ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION Akhmad Zaki; Triastuti Wuryandari; Suparti Suparti
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.709 KB) | DOI: 10.14710/j.gauss.v3i4.7960

Abstract

Factorial experiment is an experiment where is in a condition (experiment unit) were attempted simultaneously from several single experiment. Two-factor factorial experiment with the basic design CRBD (Completely Randomized Block Design) is used to assess the interaction of genotype and environment on multi-location trials. The analysis can be applied in multi-location trials is AMMI analysis (additive main effects and multiplicative interaction). AMMI analysis in the calculations using analysis of variance in a factorial experiment to test the effect of the interaction and Principal Component Analysis (PCA)  to elucidate the effect of the interaction with the interpretation of the results using the biplot-AMMI. Based on research with seven genotypes of rice (S382b-2-2-3, 3-2-3-1 S2389d-, S24871-65-4, S2824-1d-6, S2945f-59, Poso, and C22) and four locations (Sukamandi 94, Batang 94, Taman Bogo 94, and Garut 94) there is the influence of genotype, location, and interaction with genotype and location on rice production. Obtained three Principal Component Interactions (KUI1, KUI2 and KUI3) with the contribution of diversity respectively 78.29%, 13.94% and 7.77%. Interpretation of the AMMI Biplot is obtained genotype 1 (S382b-2-2-3) very suitable to be planted in a location 4 (Garut 94), genotype 2 (S2389d-3-2-3-1) very suitable to be planted in a location 3 (Taman Bogo 94), genotype 3 (S24871-65-4) is more suitable to be planted in locations 2 (Batang 94), genotype 4 (S2824-1d-6) are very suitable to be planted in a location 4 (Garut 94), genotype 5 (S2945f-59) is more suitable to be planted in locations 2 (Batang 94), genotype 6 (Poso) very suitable to be planted in a location 1 (Sukamandi 94) and genotype 7 (C22) is very suitable to be planted in locations 2 (Batang 94). Keywords: Factorial Experiment, CRBD, AMMI, Analysis of Variance, PCA, Biplot
ANALISIS KORESPONDENSI UNTUK MENDAPATKAN PETA PERSEPSI DAN VARIABEL BAGI KEGIATAN USAHA (Studi Kasus Rumah Makan Spesial Sambal (SS) terhadap Pesaingnya) Susi Ekawati; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.862 KB) | DOI: 10.14710/j.gauss.v4i1.8153

Abstract

Correspondence analysis is a technique for displaying the rows and columns of a data matrix primarily, a two-way contingency table as points in dual low-dimensional vector spaces. This technique is used to reduce the dimension of variables and describe the profile vector of rows and columns of the contingency table. This research aims to determine the position of the rivalry between the restaurants in Tembalang region based on consumer’s perceptions and to identify variables that distinguish it. The variables which used are including the price, taste, cleanliness, service, variety of food, and parking lots. Correspondence analysis is used to determine the variables that distinguish the 5th of the restaurant. The correspondence analysis produces a combined perceptual map with the satisfaction variables restaurant. From the analysis, it can be concluded that the perceptual map in the correspondence analysis shows the proximity between restaurant and satisfaction variables. Keywords : correspondence analysis, perceptual map, restaurant, satisfaction.
ANALISIS KETAHANAN HIDUP PENDERITA TUBERKULOSIS DENGAN MENGGUNAKAN METODE REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus di Puskesmas Kecamatan Kembangan Jakarta Barat) Wulan Safitri; Triastuti Wuryandari; Suparti Suparti
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (881.966 KB) | DOI: 10.14710/j.gauss.v5i4.14735

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacteria of the Mycobacterium groups that is Mycobacterium Tuberculosis. Most of the TB germs attack the lungs, but can also on other organs. In Indonesia based on the Survei Kesehatan Rumah Tangga (SKRT) in 2001 showed TB is the first cause of death in the group of infectious diseases. To determine the factors that affect the rate of healing of patients with TB is using regression analysis, because the dependent variable is the time of failure that equipped with censorship then used cox proportional hazard regression. Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is the phrase used to describe the analysis of data in the form of times from a well-defined time origin until the occurrence of some particular event or end-point. The cases examined in this study are the factors that affect the rate of healing of patients with TB in Puskesmas Kecamatan Kembangan Jakarta Barat. The conclusion state that the factors affecting the rate of healing of patients with TB are a source of transmitting and medicine records. Keywords: Tuberculosis, Survival Analysis, Cox Proportional Hazard Regression
ANALISIS PEMILIHAN MEREK TELEPON SELULER PADA MAHASISWA UNIVERSITAS DIPONEGORO DENGAN METODE REGRESI LOGISTIK POLITOMUS Maralika Yundya Sari; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (660.93 KB) | DOI: 10.14710/j.gauss.v2i1.2743

Abstract

Telepon seluler (ponsel) merupakan alat telekomunikasi dua arah yang memiliki mobilitas sangat tinggi. Merek-merek ponsel yang beredar di Indonesia yaitu Nokia, Blackberry, Samsung, Sony Ericsson, merek China dan merek lain. Faktor-faktor yang diduga mempengaruhi mahasiswa Universitas Diponegoro dalam membeli sebuah merek ponsel adalah usia, jenis kelamin, nama merek, harga, fitur, desain dan gaya serta kinerja. Pengambilan sampel penelitian menggunakan salah satu teknik dari non probability sampling, yaitu teknik purposive sampling. Untuk menganalisis permasalahan ini digunakan analisis regresi logistik politomus. Berdasarkan uji signifikansi model dan parameter, diketahui usia, nama merek, harga, fitur, desain dan gaya serta kinerja berpengaruh terhadap pemilihan merek ponsel. Estimasi probabilitas terbesar untuk merek Nokia, Blackberry, Samsung, Sony Ericsson, merek China dan merek lain masing-masing adalah sebesar 96.83%, 94.26%, 86.98%, 93.45%, 86.07% dan 99.99%. Kata Kunci:    ponsel, purposive sampling, regresi logistik politomus
ANALISIS KEPUTUSAN KONSUMEN MEMILIH BAHAN BAKAR MINYAK (BBM) MENGGUNAKAN MODEL REGRESI LOGISTIK BINER DAN MODEL LOG LINIER (Studi Kasus SPBU 44.502.10 Ketileng Semarang) Lintang Ratri Wardhani; Yuciana Wilandari; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (363.172 KB) | DOI: 10.14710/j.gauss.v4i4.10228

Abstract

Fuel oil is a fuel derived and/or processed from petroleum. Fuel is often used for motor vehicles among others premium and pertamax. Some recent times has happened several times increase and decrease in fuel prices, even at the beginning of 2015 has happened  a new policy on the elimination of fuel subsidies. It affects on fuel consumption, especially consumption of premuim and pertamax. Many factors influence the consumer's decision in choosing a fuel, therefore needs to be analyzed to find out factors influencing consumer decision in choosing a fuel. This study was conducted to determine the factors that influence consumer decisions in choosing a fuel with a binary logistic regression model and the factors that influence the relationship with log linear models. Binary logistic regression is a method of data analysis used to find the relationship between the response variable (Y) that is binary or dichotomous with some predictor variables (X). Log linear models were used to analyze the relationship between categorical variables. Of a binary logistic regression model obtained influential variable is employment, vehicle age and income variable, with the biggest opportunity is 0,78862, is premium consumers with private employment, the age of the vehicle mote than 5 years and the income less than 1.500.000. for log linear models got the biggest opportunity is 0,91259, is premium consumers to the work of civil servant, the age of the vehicle mote than 5 years and the income less than 1.500.000. Keywords : fuel, binary logistic regression model, log linear models
ANALISIS LAMA KAMBUH PASIEN HIPERTENSI DENGAN SENSOR TIPE III MENGGUNAKAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus di RSUD Kartini Jepara) Ishlahul Kamal; Triastuti Wuryandari; Hasbi Yasin
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (480.438 KB) | DOI: 10.14710/j.gauss.v4i3.9475

Abstract

Hypertension is a disease that silently kills the patients because they do not realize that they get hypertension until they check their blood pressure. It is important for hypertensive patients to know the factors that lead to the relapse time. To determine the relationship between the relapse time on hypertensive patients with the influencing factors is using regression analysis, the dependent variable is the failure time so to determine the relationship is using regression Cox proportional hazard. This research uses the medical records of hypertensive patients in period January to December 2014 in RSUD Kartini Jepara. The results indicate that the factors which affect relapse time of hypertension are kidney disease and stroke. The hypertensive patients that also suffer from kidney disease have relapse time sooner than patients who do not suffer from kidney disease. The hypertensive patients that also suffer from stroke have relapse time sooner than patients who do not suffer from a stroke. Keywords: Hypertension, Survival Analysis, Regression Cox Proportional Hazards 
PENENTUAN KOMPOSISI WAKTU OPTIMAL PRODUKSI DENGAN METODE TAGUCHI (Studi Kasus: Penelitan di Pabrik Kerupuk Rambak Stik Cap Ikan Bawang, Semarang) Angga Saputra Desti; Triastuti Wuryandari; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.387 KB) | DOI: 10.14710/j.gauss.v3i1.4771

Abstract

Many businesses crackers facing obstacles in meeting the market demand. Business doers must minimize time in the process so that market demand can be fulfilled. This study aims to minimize the time making process as well as getting the right optimal composition without damaging the quality of the product. Settlement problems using the Taguchi method in experimental design . Factor used is steaming (22 and 19 minutes), the first drying (7 and 6 hours), the second drying (10 and 9 hours) and frying (2 minutes 45 seconds and 2 minutes 30 seconds), as well as variables assessed from the experimental results in terms of taste, color and crunchiness with using organoleptic assessment by a not trained panelists. From the experimental results best factor level selected by SNR and the mean value in terms of taste, color and crunchiness. The composition of the optimal cracker manufacture process to produce the most preferred crackers elected steaming (19 minutes), the first drying (7 hours) , the second drying (9 hours) and frying (2 minutes 30 seconds). Optimal composition of the comparison results with the standard factory based T – test independent sampel the response of taste, color and crunchiness produce the same average, with the time difference for once the process is 310 minutes or 5 hours 10 minutes.
MODEL REGRESI COX PROPORTIONAL HAZARDS PADA DATA LAMA STUDI MAHASISWA (Studi Kasus Di Fakultas Sains dan Matematika Universitas Diponegoro Semarang Mahasiswa Angkatan 2009) Landong Panahatan Hutahaean; Moch. Abdul Mukid; Triastuti Wuryandari
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.842 KB) | DOI: 10.14710/j.gauss.v3i2.5903

Abstract

High education has important role to increase the intellectual life of the nation and the development of natural sciences and technology by producing the quality graduates. The quality graduates just need 48 month to finish the study. There are many factors that will affect  time of study students as Grade Point Average(GPA), Bustle student level, etc. Hence, need to know what factors affecting time of study students. One method that can be used is Survival analysis. Survival Analysis is analysis of survival data from the beginning of time research until certain events occurred. One of the methods of survival analysis is Cox Proportional Hazards Regression. Cox Proportional Hazards Regression is a regression which used data of intervals of time an event. The case which is discussed in this research is factors that affect time of study students of Faculty of Science and Mathematics started 2009 Diponegoro of University with the second type of censoring. From the research give conclusion that factors affecting time of study  students is Department, GPA, and Organization