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Jurnal Gaussian

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Published by Universitas Diponegoro

ISSN : - EISSN : 23392541 DOI : -

Core Subject : Education,

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Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM UNDIP.

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Articles 26 Documents

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Search results for , issue "Vol 3, No 3 (2014): Jurnal Gaussian" : 26 Documents clear

PERBANDINGAN ANALISIS KLASIFIKASI MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN) DAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) PADA DATA AKREDITASI SEKOLAH DASAR NEGERI DI KOTA SEMARANG Bisri Merluarini; Diah Safitri; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Classification methods have been developed and two of the existing are K-Nearest Neighbor (K-NN) and Multivariate Adaptive Regression Spline (MARS). The purpose of this research is comparing the classification of public elementary school accreditation in Semarang city with K-NN and MARS methods. This research using accreditation data with the result of eight accreditation components in public elementary school that has A accreditation (group 1) and B accreditation (group 2) in Semarang city. To evaluate the classification method used test statistic Press’s Q, APER, specificity, and sensitivity. The best classification results of the K-NN method is when using K=5 because it produces the smallest error rate and obtained information that the correct classification data are 159 and the misclassification data are 9. The best classification result of the MARS method is when using combination BF=32, MI=2, MO=1 because it produces the smallest Generalized Cross Validation (GCV) and obtained information that the correct classification data are 164 and the misclassification data are 4. Based on analyze result, Press’s Q showed that both methods are good as classification or statistically significant to classify the public elementary school in Semarang city based of the accreditation. APER, specificity, and sensitivity showed that classify of public elementary school accreditation in Semarang city using MARS method is better than K-NN method.

ANALISIS PENGENDALIAN KUALITAS MENGGUNAKAN DIAGRAM KENDALI DEMERIT (Studi Kasus Produksi Air Minum Dalam Kemasan 240 ml di PT TIW) Gita Suci Ramadhani; Yuciana Wilandari; Suparti Suparti
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The efforts to maintain and improve the quality of the resulting product with statistical process control. Demerit control chart is a control chart in which the defect type is categorized into several classes according to the level of disability interests. Types of defects in the production processes of bottled water 240 ml in PT TIW divided into critical defects, major defects and minor defects. Based on the results of the analysis that has been done shows that the production process has been controlled statistically using demerit control charts on the third iteration for each line 1 and line 2. Capability of production processes in line 1 and line 2 shows that although the production process has been controlled statistics, but the process still produces a product that is not in accordance with specifications. But in the end all defective products are produced, will be immediately discarded and will not be marketed or sold to the consumer. This is done for the commitment PT TIW who always maintain the best quality products. Based on pareto chart for this type of defect on line 1 and line 2, it is known that 20% of the total types of defects, obtained two types of defects which constitute 80% of disability of the entire production process. The defect type is slanted lid and reject filler. The factors that cause this type of defect are slanted lid and reject filler among others, there is a worn machine components and uncorrect machine settings, the operator has not been retrained and lack of focus so not accordance with the procedure in the work, the composition of the materials is uncorrect, and methods or procedures are less well executed.

PERBANDINGAN MODEL PERTUMBUHAN EKONOMI DI JAWA TENGAH DENGAN METODE REGRESI LINIER BERGANDA DAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION Kelik Isbiyantoro; Yuciana Wilandari; Sugito Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the equipments to see the success of the Government in economics field is the economic growth. To see the economic growth of a region, can be seen from the growth of region Gross Domestic Product (GDP). All this time, the economic growth is often modeled by multiple linear regression, whereas the model describes the general conditions. In fact, there are differences such as geographical factor, socio-cultural circumstance, and the other matters. This allows the appearance of spatial heterogenity in the regression parameters, to overcomes it, the OLS (Ordinary Least Square) regression is developed into Georaphically Weighted Regression (GWR). This model is a local linear regression model that generates local estimator model parameters for each point or location where the data is collected. This research discusses the factors that effect the economic growth in Central Java. The model suitability testing result shows that there is no differences in multiple linear regression model and GWR model toward the economic growth in Central Java. Results of the research shows there are three variables that have effect, they are: Total Labor Force, Major MSEs, and the number of markets. The three variables have the same effect in each county / city.

PENINGKATAN PRODUKTIVITAS BENANG POLYESTER COTTON 45 MELALUI ANALISIS TOTAL QUALITY CONTROL (Studi kasus di PT Panca Bintang Tunggal Sejahtera) Afifah Alrizqi; Yuciana Wilandari; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

PT Panca Bintang Tunggal Sejahtera is a company which operate in textill and garment. The main product is polyester cotton 45 yarn. In the production activity, still failed product. To determine what factors caused the failure of polyester cotton 45 yarn, used the analysis of Total Quality Control to control devices such as check sheet, stratification, bar chart, control chart, cause and effect diagrams, Pareto charts, and scatter plot. From the results of the check sheet, stratification and histogram obtained the highest type of failure is uneven sliver, which is as much as 1871 kg for a month. From the individual unit control chart, indicated that the activities of the production process there are deviations which are beyond the limits of product controllers that need improvement. A cause and effect diagram result show that the biggest factor causing the failure of the product due to labor factor due to lack of training and supervision. Therefore, the company can make improvements with priority on the labor factor.

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.

PENENTUAN BOBOT PORTOFOLIO OPTIMAL DENGAN METODE RESAMPLED EFFICIENT FRONTIER UNTUK PERHITUNGAN VALUE AT RISK PADA DATA BERDISTRIBUSI NORMAL Esti Pratiwi; Abdul Hoyyi; Sugito Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The investors have a goal of getting return when they invest their wealth, but on the other hand they should bear the risk that might arise from their investment. There are three categories of investors based on their preferences toward risk that is risk averter, moderate risk and risk taker. To establish a portfolio that is able to incorporate investor preferences is used Resampled Efficient Frontier Method. Resampled Efficient Frontier Method is a development of the Mean Variance Efficient Portfolios Method, which used Monte Carlo simulation to obtain more estimated of parameter inputs. Based on the efficient portfolios of Resampled Efficient Frontier along the efficient frontier with 51 efficient points, taken optimal portfolio for each investor type. Optimal portfolio for risk averter, moderate risk and risk taker respectively is an efficient portfolio on the first point, 26th point, and 51st point. To describe the loss of the optimal portfolio is used Value at Risk. VaR is calculated based on monthly return from BBCA, LPKR, PGAS and SMGR during January 2008 until December 2013. Estimated VaR on 95% confidence level during 20 days holding period and the amount of investment allocation Rp 100,000,000.00 from the optimal portfolio for risk averter, moderate risk and risk taker respectively is Rp 50,706,000.00, Rp 54,618,000.00 and Rp 64,522,000.00

PREDIKSI DATA HARGA SAHAM HARIAN MENGGUNAKAN FEED FORWARD NEURAL NETWORKS (FFNN) DENGAN PELATIHAN ALGORITMA GENETIKA (Studi Kasus pada Harga Saham Harian PT. XL Axiata Tbk) Ira Puspita Sari; Triastuti Wuryandari; Hasbi Yasin
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Artificial neural network (ANN) or Neural Network (NN) is an information processing system that has characteristics similar to biological neural networks. One of the ANN models have network is quite simple and can be applied to time series data prediction is Feed Forward Neural Networks (FFNN). In general, FFNN trained using Backpropagation algorithm to obtain weights, but performance will decrease and trapped in a local minimum when applied to data that have great complexity like financial data. The solution to this problem is to train FFNN using Genetic Algorithm (GA). GA is a search algorithm that is based on the mechanism of natural selection and genetics to determine the global optimum. Training FFNN using GA is a good solution but the problem is how to understand the workings of FFNN training using the GA, the determination of the combination of the probability of crossover (), number of populations, number of generations, and the size of the tournament (k) on the AG to produce predictive value approaching actual value. One possible option is to use the technique of trial-end-error by experimenting for some combination of these four parameters. Of the 64 times the application of the AG test results to train FFNN models on daily stock price data PT. XL Axiata Tbk obtained results are sufficiently accurate predictions indicated by the proximity of the target to the output of the crossover probability () 0.8, a population of 50, the number of generations 20000 and tournament size of 4 produces the testing RMSE 107.4769.

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.

OPTIMALISASI PROSES PRODUKSI YANG MELIBATKAN BEBERAPA FAKTOR DENGAN LEVEL YANG BERBEDA MENGGUNAKAN METODE TAGUCHI Annisa Intan Mayasari; Triastuti Wuryandari; Abdul Hoyyi
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Taguchi method is a method that purposes to improve the quality of products and processes at the same time with the purpose of reducing costs and resources to a minimum. Taguchi method is one example of a fractional factorial design that uses orthogonal arrays to reduce the number of experiments. The analytical tool used was ANOVA and Signal to Noise Ratio. ANOVA was used to determine the factors that affect the response and Signal to Noise Ratio are used to determine the combination of factors that affect the performance of the product so that the resulting optimal response. Based on the results of tests performed to determine the factors that influence the design of electronic circuits that will produce the center frequency of 35.75 megahertz at a temperature of -10 ℃, the significant factor is the factor A, B, C, D, F, and H. The best combination is obtained A2, B2, C2, D3, F2, dan H3. Factor F has the greatest percent contribution is 42.57%, the next factor D, H, C, A, and B, respectively 8.83%, 7.37%, 5.93%, 3.90% and 3.84%.

ANALISIS CONJOINT PAIRWISE-COMPARISON UNTUK MENGETAHUI TINGKAT KEPENTINGAN ATRIBUT JASA BIRO PERJALANAN WISATA (Studi Kasus Beberapa SMA Negeri di Kabupaten Klaten) Galih Maraseta W H Prasaja; Yuciana Wilandari; Sudarno Sudarno
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Competition in the business world travel agency today's increasingly stringent. Travel agency is a business that organizes tourist activities and other services related to the operation of the tour both domestically and abroad in a foreign country. To help business people of the travel agency in knowing and understanding consumer preferences on a combination of attributes of a travel agency conjoint analysis can be used. In this study conjoint analysis is used by using presentation method of pairwise-comparison. There are four attributes used in this analysis, they are bus facilities, agency facilities, hotel, and dining facilities. From the results of the analysis that obtained by the respondents, the most important attribute in selecting a travel agency is the dining attribute with a relative importance value of 38,02%. The next most important attribute according to the respondents is the attribute of the bus facility with a relative importance value of 28,46%, attributes agency facilities with a relative importance value of 19,58%, attributes the hotel facilities with a relative importance value of 13,94%. The combination of desired respondents in choosing or use the services of a travel agency is a travel agency with wifi bus facilities, hotel facilities with the large bed, an agency facility of video documentation and a buffet meal.

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Jawa tengah

INDONESIA