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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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METODE DBSCAN UNTUK PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN PRODUKSI PADI SAWAH DAN PADI LADANG Diah Safitri; Triastuti Wuryandari; Rita Rahmawati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 5, No 1 (2017): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Padi merupakan tanaman yang penting di Jawa Tengah karena nasi merupakan makanan pokok sebagian besar masyarakat di Jawa Tengah. Provinsi Jawa Tengah terdiri dari 35 kabupaten/kota, dalam penelitian ini berdasarkan produksi padi sawah dan padi ladang, kabupaten/kota di Provinsi Jawa Tengah akan dikelompokkan menjadi beberapa kelompok menggunakan metode Density Based Spatial Clustering Algorithm With Noise (DBSCAN)berdasarkan produksi padi sawah dan padi ladang, dimana pada masing-masing kelompok dapat dilihat karakteristiknya mengenai potensi produksi padi sawah dan padi ladang. Metode DBSCAN adalah metode yang tangguh untuk mendeteksi noise. Kelompok 1 terdiri dari Kabupaten/Kota di Provinsi Jawa Tengah selain yang sudah masuk dalam kelompok 2 dan 3, kelompok 1 adalah kelompok yang mempunyai hasil produksi padi sawah terendah dibandingkan dengan kelompok yanglain. Kelompok 2 adalah kelompok yang mempunyai hasil produksi padi ladang tertinggi dibandingkan dengan kelompok yang lain. Kelompok 2 terdiri dari KabupatenKebumen dan Kabupaten Blora. Kelompok 3 terdiri dari Kabupaten Sragen, Kabupaten Grobogan, Kabupaten Pati, Kabupaten Demak, dan Kabupaten Brebes, adalahkelompok yang mempunyai hasil produksi padi sawah tertinggi dibandingkan dengan kelompok yang lain. Pada penelitian ini ditemukan 2 noise, yaitu Kabupaten Cilacapdan Kabupaten Wonogiri.Kata Kunci: DBSCAN, Padi Sawah, Padi Ladang

MODEL REGRESI COX PROPORSIONAL HAZARD PADA DATA DURASI PROSES KELAHIRAN DENGAN TIES Triastuti Wuryandari; Danardono Danardono; Gunardi Gunardi
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 1 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.1.2021.47-55

Survival data are usually found in the fields of health, insurance, epidemiology, demography, etc. Survival data is characterized by a response in the form of time, one example is the duration of the birth process. The duration of the birth process is thought to be influenced by several factors, including the baby's weight, baby's height, mother's age, gestational age, gender and the method used to birth process. One of the regression models for survival data is the Cox regression proportional hazard model. Parameter estimation in the Cox regression is based on partial likelihood. If two or more individuals have the same survival value, it is called ties. If there are ties, then the partial likelihood will have problems in determining the risk set, so it is necessary to modify the partial likelihood. Methods that can be used to overcome ties are the Breslow, Efron and Exact methods. This method is a modification of parameter estimation using maximum partial likelihood. Parameter estimation results are obtained by maximizing the partial likelihood function using Newton Raphson iteration. The case study in this paper is data on the duration of the birth process. The best model for the duration of the birth process with ties is the Exact method because it has the smallest AIC value

MODEL REGRESI DATA TAHAN HIDUP TERSENSOR TIPE III BERDISTRIBUSI LOG-LOGISTIK Ibnu Athoillah; Triastuti Wuryandari; Sudarno Sudarno
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Lifetime T is the time from initial treatment until the first response is to be observed which can be death due to a particular disease, illness that recur after treatment or the emergence of new diseases. In research of survival testing the data term are censored and not censored. Censored observation occur if the survival time of the observed individual is not known with certainty while the observation not censored if the survival time of observation is known with certainty. There are three different types of censoring observation that are type I,type II, and type III. Censoring type III is an observation made to several individuals at different time within a certain period, this is because an individual entry into the observations at different times. Influence of other factros on the response variable that is survival time relation should be considered. One way to know relationship is through a regression model. Regression model of survival data with censoring type III of log-logistic distribution is made following the curve of the response variable. Estimation of parameters using maximum likelihood methods. Regression model was apllied to estimate the survival time of patients with lung cancer for factors of the infected cell and type of treatment.

ANALISIS CLUSTER DENGAN ALGORITMA K-MEANS DAN FUZZY C-MEANS CLUSTERING UNTUK PENGELOMPOKAN DATA OBLIGASI KORPORASI Desy Rahmawati Ningrat; Di Asih I Maruddani; Triastuti Wuryandari
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a method of grouping data (object) that are based on information that found in the data which describes the object and relation within. Cluster analysis aims to make the joined objects in the cluster are identical (or related) with one another and different (not related) to objects in another cluster. In this study used two method of grouping; Fuzzy C-Means and K-Means Clustering. The data used in this research had been using 357 corporate bonds data on December 1st, 2015. The variables used in this study consist of coupon rate, time to maturity, yield and rating of each corporate. The determination of the number of optimum clusters performed by Xie Beni index of validity calculation at FCM method. Having obtained the optimum number of clusters, evaluation step was conducted by comparing FCM method to K-Means method with noticing the average of standard deviation in the clusters and the average of standard deviation inter-clusters (Sw/Sb) from each method. Method with the smallest Sw/Sb ratio value would get chosen as the best method. Based on the validity index Xie Beni, the most optimum number of cluster is 10 because it has the smallest Sw/Sb ratio value compared to FCM, the value is 0,6651. Afterwards, the result of K-Means clustering is analyzed to determined the interpretation and characteristics of each formed clusters.Keyword: Cluster Analysis, coupon rate, time to maturity, yield, rating, Fuzzy C-Means, K-Means, Xie Beni Index, Sw/Sb ratio.

PEMODELAN LAJU KESEMBUHAN PASIEN RAWAT INAP TYPHUS ABDOMINALIS (DEMAM TIFOID) MENGGUNAKAN MODEL REGRESI KEGAGALAN PROPORSIONAL DARI COX (Studi Kasus di RSUD Kota Semarang) Bellina Ayu Rinni; Triastuti Wuryandari; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Typhus Abdominalis (typhoid fever) is a systemic infectious disease caused by Salmonella typhi and ranked 3rd of 10 major inpatient diseases in the hospitals of Indonesia based on Indonesia’s health profile data in 2010. It's important to know the factors that can affect the rate of recovery of hospitalized patients suffering from typhoid fever. One way is to use survival analysis that is a statistical method to analyze survival data. Cox proportional hazards regression is a model in survival analysis used to determine the relationship between one or more independent variables and the dependent variable. This model does not require information about the underlying distribution, but the hazard functions of different individuals assumed to be proportional. The Data used are from 45 patients of thypoid fever on RSUD Kota Semarang who have been medically recorded from August 1st 2012 until November 30st 2012. Furthermore it is concluded that the factors that affect the rate of recovery of inpatients suffering from typhoid fever were age.

RANCANGAN D-OPTIMAL LOKAL UNTUK REGRESI POLINOMIAL ORDE 3 DENGAN HETEROSKEDASTISITAS Arya Fendha Ibnu Shina; Tatik Widiharih; Triastuti Wuryandari
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Kemajuan ilmu pengetahuan dan teknologi di berbagai bidang menuntut adanya rancangan percobaan yang efisien. Rancangan D-optimal merupakan rancangan yang efisien. Dalam suatu percobaan yang menggunakan model regresi polinomial orde dengan heteroskedastisitas dengan fungsi bobot , rancangan D-optimal dan polinomial Jacobi menghasilkan titik-titik rancangan yang akan dicobakan. Suatu rancangan yang terdiri dari titik-titik rancangan dengan proporsi pengamatan yang menghasilkan determinan matriks rancangan maksimal merupakan rancangan D-Optimal. Rancangan D-optimal yang memiliki nilai variansi terstandardisasi sama dengan jumlah parameter di setiap titiknya, merupakan rancangan D-optimal lokal.

PENDUGAAN DATA HILANG PADA RANCANGAN ACAK KELOMPOK LENGKAP DENGAN ANALISIS KOVARIAN Vina Riyana Fitri; Triastuti Wuryandari; Diah Safitri
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Analysis of Covariance (ANCOVA) is mostly used in the analysis of research or experimental design. ANCOVA is the combination between regression analysis and Analysis of Variance (ANOVA). ANCOVA were used because there are some concomitant variable, which is variable that difficult to control by the researchers but an impact on observed the response variable. The purpose from concomitant variable is reduces variability in the experiment. If there is missing data on Randomized Complete Block Design (RCBD) the first must be done estimating the missing data before ANCOVA done. ANCOVA on RCBD with complete data or missing data isn’t much different, if there are missing data, the degrees of freedom is reduced by the total amount of missing data and the sum of square treatment reduced by the value of the bias. Application of tensile strength of the glue experiment to the case ANCOVA on RCBD with one missing data show no effect of treatment and group by the tensile strength of the glue. For Fe toxicity experiment with two missing data are found only treatment effect to Fe texicity. Based on value from the coefficient of variance for one missing data and two missing data showed that ANCOVA is more appropriately used than ANOVA.

PERBANDINGAN ANALISIS KLASIFIKASI NASABAH KREDIT MENGGUNAKAN REGRESI LOGISTIK BINER DAN CART (CLASSIFICATION AND REGRESSION TREES) Agung Waluyo; 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

Credit is the greatest asset managed by the bank and also the most dominant contributor to the bank's revenue. Debtor to pay credit to the bank may smoothly or jammed. There is a relationship variables that affect a debtor smoothly or jammed in paying credit. This study aims to identify the variables that affect a debtor's credit status. The variables used in this study were gender, education level, occupation, marital status and income. Analytical methods used include Binary Logistic Regression analysis and CART (classification and regression trees). Classification accuracy of the two methods will be compared. Based on the research results of binary logistic regression showed that the variables that affect the debtor's credit status is revenue with 80% classification accuracy. While the results of CART (classification and regression trees) in the form of a decision tree shows the type of work chosen as the root node spliting, with a classification accuracy of 81%. Keywords: credit status, logistic regression, CART

PEMILIHAN CLUSTER OPTIMUM PADA FUZZY C-MEANS (STUDI KASUS: PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA) Sarita Budiyani Purnamasari; Hasbi Yasin; Triastuti Wuryandari
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Cluster analysis is a process of separating the objects into groups, so that the objects that belong to the same group are similar to each other and different from the other objects in another group. One method of clustering is Fuzzy C-Means (FCM). FCM is used because each data in a cluster determined by a degree of membership that have value between 0 and 1. This research use two kinds of distance, Manhattan and Euclidean. To determine the proper distance in clustering district / city in Central Java based on indicators of Human Development Index (HDI), we have to calculate the ratio of the standard deviation, where the smaller value indicates a better clustering. While the optimum number of groups obtained from the minimum value of Xie Beni. Variables that used in this research are the indicators of HDI in 2012 for district / city in Central Java, consists of: Life Expectancy Value (years), Literacy Rate (percent), Average Length of School (years), and Purchasing Power Parity (thousands rupiah). The results from this research are the distance that gives a better quality is Euclidean and the optimum cluster given when the number of cluster is five with the smallest value of Xie Beni is 0,50778.

ANALISIS RANCANGAN BUJUR SANGKAR GRAECO LATIN Yuyun Naifular; Triastuti Wuryandari; Yuciana Wilandari
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The design of the experiment is a test or series of tests, using both descriptive statistics and inferential statistics that aims to transform the input variables into an output which is the response of the experiment. The Graeco Latin Square Design was built to control the diversity of component units of local control experiment of three is a row, column, and Greek letters. Terms the Graeco Latin Square Design is if the rows, columns, Latin letters, and Greek letters have the same level and each Greek letter appears only once in each row, column, and Latin letter. The steps in the analysis of the test Graeco Latin Square Design to test the normality of the error, homogeneity of variance test, determine the degrees of freedom, calculating Sum of Squares and Mean Square every factor. Next calculate the value of F for test row, column, treatments Latin letter, and treatment of Greek letters, draw up a table of variance analysis, and conclude whether there is any effect on the response variance of each source. If there is impact, it is necessary to further test using the Duncan test

Co-Authors Abdul Hoyyi Agung Waluyo 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 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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