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All Journal Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang

Triastuti Wuryandari

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Author-ID : 452063

Decision Sciences, Operations Research & Management Other

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PENENTUAN MODEL KEMISKINAN DI JAWA TENGAH DENGAN MULTIVARIATE GEOGRAPHICALLY WEIGHTED REGRESSION (MGWR) Sindy Saputri; Dwi Ispriyanti; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The problem of poverty is a fundamental problem faced in a number of regions in Indonesia, to determine significant indicators on poverty by taking into account the spatial variation in the province of Central Java can use multivariate models Geographically Weighted Regression (MGWR). In the model MGWR model parameter estimation is obtained by using Weighted Least Square (WLS). Selection of the optimum bandwidth using Cross Validation (CV). The study looked for the best model among MGWR with multivariate regression and create distribution maps counties and cities in the province of Central Java based variables significantly to poverty. The results of testing the suitability of the model shows that there is no influence of spatial factors on the percentage of poor and non-poor in the province of Central Java. Variables expected to affect the percentage of poor people is a variable percentage of expenditures for food, while the percentage of the non-poor is a variable percentage of expenditure on food and the percentage of heads of household education level less than SD. Based on the AIC and the MSE obtained the best model is the model MGWR with AIC value of 44.4603 and MSE 0.454.Keywords: Cross Validation, MGWR, Poverty, Weighted Least Square

PERBANDINGAN ANALISIS KLASIFIKASI ANTARA DECISION TREE DAN SUPPORT VECTOR MACHINE MULTICLASS UNTUK PENENTUAN JURUSAN PADA SISWA SMA Rizky Ade Putranto; Triastuti Wuryandari; Sudarno Sudarno
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Data mining is a process that employs one or more of Machine Learning techniques to analyze and extract knowledge automatically. Analysis of data mining is to determine the classification of a new data record into one of several categories that have been defined previously, also known as Supervised Learning. Classification Decision Tree is one of the well-known technique in data mining and is one of the popular methods in the decision making process of a case in which the method is obtained entropy criteria, information gain and gain ratio. Classification Support Vector Machine Multiclass (SVMM) is known as the most advanced machine learning techniques to handle multi-class case where the output of the data set has more than two classes or categories. This final project aims to compare the level of accuracy and error rate of Decision Tree classification and prediction majors SVMM for high school students at SMAN 1 Jepara. The total accuracy of 88,57% and 11,43% error rate for the classification decision tree and the total accuracy of 87,14% and the error rate for the classification SVMM 12,86%. Keywords : Data Mining, Machine Learning, Supervised Learning, Decision Tree, Support Vector Machine Multiclass

ANALISIS BIPLOT ROW METRIC PRESERVING UNTUK MENGETAHUI KARAKTERISTIK PROVIDER TELEPON SELULER PADA MAHASISWA S1 FSM UNIVERSITAS DIPONEGORO Artha Ida Sri Anggriyani; Diah Safitri; Triastuti Wuryandari
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Communication is the basis of human interaction. One of the progression in telecommunications is telecommunication tools, e.g. a mobile phone. Usually on every communication tools such as mobile phones are equipped with a provider. The methods used to analyze mobile phone provider is the biplot analysis. Biplot analysis is an analysis which gives a demonstration of the matrix data graphically X into a plot with vector in row matrix X as describing an object, with a vector in column matrix X describing variables. If α = 1 then it is called analysis biplot Row Metric Preserving (RMP). The predictor variable used in this final project is the product, price, promotion and distribution. After analysis biplot, can be known that a two-dimensional graph biplot was able to explain 97,7% of actual data. The nearest competitor for Indosat provider is XL Axiata provider. Indosat provider winning in terms of promotions and distribution, Telkomsel provider winning in terms of products and Hutchison provider winning in terms of price. Keywords: telephone provider, Row Metric Preserving biplot, marketing mix

PREDIKSI NILAI KURS DOLLAR AMERIKA MENGGUNAKAN EXPONENTIAL SMOOTHING DENGAN KAJIAN GRAFIK MOVING AVERAGE (MA) DAN EXPONENTIALLY WEIGHTED MOVING AVERAGE (EWMA) (Studi Kasus: Kurs Jual dan Kurs Beli Dollar Amerika) Nova Yanti Gultom; Sudarno Sudarno; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The exchange rate is an exchange between two different currencies, it will receive the value or price comparisons between two currencies. It is to determine the predictive value of the exchange rate in the next period is done by using Exponential Smoothing. The quality control can be done by forming graphics controllers. The exchange rate can be done in small shifts, so the exchange rate can use graphics controller Moving Average and Exponentially Weighted Moving Average (EWMA). At the selling rate is found value trial and error alpha is 0,9 and gamma is 0,01 with value of MAPE is 0,37; MAD is 46,94 and value of MSD is 4515,27. At the buying rate is found value trial and error alpha is 0,84 and gamma is 0,01 with value of MAPE is 0,37; MAD is 46,57 and value of MSD is 4524,48. In the graph MA and EWMA most sensitive is the MA control chart so in the weekly chart MA selling rate with w is 5 and L is 2,8 obtainable UCL is 13132,52; CL is 12654, LCL is 12175,47. On the weekly chart MA buying rate with w is 5 and L is 2,8 obtainable UCL is 13002,08; CL is 12528, LCL is 12053,91. Then the possibility of the exchange rate for the next period will be increased or decreased to the rupiah.Keywords: Exchange Rate, Exponential Smoothing, Graphic control, Moving Average (MA), Exponentially Weighted Moving Average (EWMA).

IDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI TERJADINYA PREEKLAMPSIA DENGAN METODE CHAID (Studi Kasus pada Ibu Hamil Kategori Jampersal di RSUD Dr.Moewardi Surakarta) Restu Sri Rahayu; Moch. Abdul Mukid; Triastuti Wuryandari
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Pre-eclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy . This sickness is caused by many factors. To identify the factors, We lowercase a statistical analysis that can explain the characteristics of pregnant women who has pre-eclampsia. One analysis used for segmentation is CHAID (Chi-Squared Automatic Interaction Detection). This analysis classify and view the segmentation on nominal scale dependent variable (patient’s status). CHAID analysis result indicates that the history of hypertension is the most influential independent variable. The tree diagram shows that there are seven segments of pregnant women, this study reveals that, there are three segments that need to be concerned because these segments show a high number and high index value exceeds 100% of pregnant women with pre-eclampsia. These segments need an effort to support the reduction of MMR. The three segment are segment pregnant women who has the history of hypertension; segment pregnant women of primary school degree and who are jobless, overweight, with no history of hypertension; and segment pregnant women with elementary and junior high school degree, who has jobs, and no hypertension history. Accuration of the CHAID algorithm in classifying is 78,2%. Keywords: Pre-eclampsia, Classify, CHAID, Maternal Mortality Ratio, Accuration

ANALISIS PASIEN RAWAT INAP BERDASARKAN KELAS PERAWATAN DI RSUP Dr. KARIADI SEMARANG DENGAN METODE ANTRIAN Friska Irnas Adiyani; Sugito Sugito; Triastuti Wuryandari
Jurnal Gaussian Vol 2, No 4 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Health is the right of everyone. RSUP Dr. Kariadi as one of the health service facilities has an obligation to provide service optimally to overcome the necessities and complaints of the patients. Nevertheless, the high number of patients that are not in balance with the amount of service facilities be constraints in achieving this purpose, so the patient must be entered the waiting-list or having a queuing situation. This situation happens in queuing system of the hospitalization patients at the place for registration of hospitalization patients (TPPRI) and at the care room installation of hospitalization A and B RSUP Dr. Kariadi Semarang. Therefore, it is necessary to determine the queuing system models that is appropriately with the conditions and characteristics of the queuing at TPPRI and care room that classified based on care class. So it can help in determining the decision to achieve the effective and efficient service. From the analysis result, the best queuing model for TPPRI is and for the care room that is classified based on care class are for the main class, for the first class, for second class, dan the last for third class.

MODEL REGRESI COX STRATIFIED PADA DATA KETAHANAN Mohamad Reza Pahlevi; Mustafid Mustafid; Triastuti Wuryandari
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Stratified Cox model on the events are not identical is a modification of the Cox Proportional Hazard models when there are individuals who experienced more than one incident. This study aims to form a stratified Cox regression models for repeated occurrences of data are not identical and their application to cases of hemorrhagic stroke disease recurrence and to determine the factors that affect the case. Parameter Estimation in Stratified Cox models using Partial Maximum Likelihood Estimation (MPLE). Stratified Cox model building procedure consists of six stages: (1) identification data, which specify the variables that will be used in the Cox models. (2) Estimated Cox Proportional Hazard model parameters. (3) The test parameters for each variable using the Wald test. (4) Testing Proportional Hazard assumptions. (5) stratification variables. (6) Interpretation Stratified Cox models. This study uses data of patients who experienced a hemorrhagic stroke unspecified with 7 independent variables such as age, sex, blood pressure, blood sugar, triglycerides, cholesterol and replications. Based on the testing parameters obtained three variables that influence such as age, cholesterol levels and repeat. Furthermore, in assuming Proportional Hazard showed that replicates variable Proportional Hazard did not meet the assumptions that need to be stratified. Unspecified hemorrhagic stroke patients aged over 50 years admitted to 3.230 times longer than the patients were under 50 years old. Unspecified hemorrhagic stroke patients with high cholesterol levels are treated 0.182 times faster than patients with normal cholesterol levels. Keywords: Stratified Cox, Cox Proportional Hazard, MPLE, Haemorrhagic Stroke, Recurrent Events

PENGGUNAAN METODE PROJECTED UNIT CREDIT DAN ENTRY AGE NORMAL DALAM PEMBIAYAAN PENSIUN Ayu Hapsari Budi Utami; Yuciana Wilandari; Triastuti Wuryandari
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One effort to anticipate the risk of old age is to include every worker in a pension plan. From that pension plan, workers will get a pension benefit at retirement. Before reaching retirement age, there should be an actuarial cost, which includes the normal cost and actuarial liabilities. Both are calculated using actuarial cost methods. Actuarial cost methods are divided into two major categories, are Accrued Benefit Cost Method and Projected Benefit Cost Method. One example of the methods included in Accrued Benefit Cost Method is Projected Unit Credit Method, and one of the methods included in Projected Benefit Cost Method is Entry Age Normal Method. The data used in this thesis are secondary data from PT Taspen (Persero) KCU Semarang. The results of the calculation shows normal cost using Projected Unit Credit method continues to increase with increased salary. Whereas if using Entry Age Normal Method the same amount for each year on an employee. Besides, actuarial liability using Projected Unit Credit Method is smaller than using Entry Age Normal for each employee in each year.

RANCANGAN D-OPTIMAL UNTUK REGRESI POLINOMIAL DUA FAKTOR DERAJAT DUA Rosmalia Safitri; Tatik Widiharih; Triastuti Wuryandari
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Suatu penelitian dalam bidang kimia seringkali memerlukan suatu rancangan optimal untuk menentukan titik mana dari variabel prediktor yang akan dicobakan dengan tujuan memaksimalkan sejumlah informasi yang relevan sehingga terpenuhi kriteria yang diinginkan. Kriteria pemenuhan optimal didasarkan pada matriks rancangan dari model yang dipilih. Kriteria D-optimal digunakan untuk meminimalkan variansi dari estimasi parameter dengan cara memaksimalkan determinan matriks informasinya atau meminimalkan determinan matriks dispersinya. Pemilihan titik-titik dari variabel prediktor selain tergantung dari model yang dipilih juga tergantung dari banyaknya pengamatan yang diinginkan.Kriteria D-optimal diaplikasikan pada data simulasi untuk kasus pengukuran nilai persentase kelarutan enam reaksi kimia berdasarkan nilai suhu dan lama reaksinya. Diperoleh kesimpulan bahwa determinan matriks informasi maksimal terjadi pada saat iterasi keempat dengan nilainya sebesar 2.2070 x 109.

PENERAPAN METODE TAGUCHI UNTUK KASUS MULTIRESPON MENGGUNAKAN PENDEKATAN GREY RELATIONAL ANALYSIS DAN PRINCIPAL COMPONENT ANALYSIS (Studi Kasus Proses Freis Komposit GFRP) Annisa Ayu Wulandari; Triastuti Wuryandari; Dwi Ispriyanti
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Taguchi method is a method for quality control of product by off line. Taguchi method usually used to solve optimization problem with single respon. Multirespon case was done by using Grey Relational Analyisis (GRA) and Principal Component Analysis (PCA). With GRA method is obtained many Grey Relational Grade value. For weight is estimated using PCA. The case study use freis process GFRP composite with characteristic smaller is better. From the research is obtained combination in optimal canditions for factor fiber orientation angle at 150, helix angle at 250, and feed rate at 0,04 mm/rev. While the respon that observed are surface roughness, machine force, and delamination factor. The value of contribution percentage for each factor is 69,596% for fiber orientation angle, 9,768% for helix angle and 11,9841% for feed rate..Keywords : Multirespon Optimization, Taguchi Method, Grey Relational Analysis, Principal Component Analysis, Freis Process GFRP Composite

Co-Authors Abdul Hoyyi Agus Rusgiyono Akhmad Zaki Alif Hartati Angga Saputra Desti Annisa Ayu Wulandari Annisa Intan Mayasari ANNISA RAHMAWATI Artha Ida Sri Anggriyani Arya Fendha Ibnu Shina Avida Nugraheni C. Ayu Hapsari Budi Utami Bellina Ayu Rinni Danardono Danardono Desriwendi Desriwendi Desy Rahmawati Ningrat Di Asih I Maruddani Diah Safitri Dian Ika Pratiwi Dwi Ispriyanti Fitriani Fitriani Friska Irnas Adiyani Galuh Riani Putri Gian Kusuma Diah Tantri Gunardi Gunardi Haryanti Novitasari Hasbi Yasin Ibnu Athoillah Ira Puspita Sari Ishlahul Kamal Landong Panahatan Hutahaean Lintang Ratri Wardhani Maralika Yundya Sari Moch. Abdul Mukid Mohamad Reza Pahlevi Mustafid Mustafid Nova Yanti Gultom Novia Dian Ariyani Oka Afranda Puti Cresti Ekacitta Rahma Kurnia Widyawati Restu Sri Rahayu Rita Rahmawati Rizky Ade Putranto Rosmalia Safitri Sarita Budiyani Purnamasari Sindy Saputri Solly Aryza Sudarno Sudarno Sugito Sugito Suparti Suparti Susi Ekawati Syarah Widyaningtyas Tarno Tarno Tatik Widiharih Tri Murda Agus Raditya Tyas Ayu Prasanti Vina Riyana Fitri Wulan Safitri Yuciana Wilandari Yuyun Naifular

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