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Department of Statistic, Faculty of Science and Mathematics , Universitas Diponegoro Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro Gedung F lt.3 Tembalang Semarang 50275
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Jurnal Gaussian
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 7 Documents
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Search results for , issue "Vol 6, No 4 (2017): Jurnal Gaussian" : 7 Documents clear
PENERAPAN ANALISIS KLASTER METODE WARD TERHADAP KABUPATEN/KOTA DI JAWA TENGAH BERDASARKAN PENGGUNA ALAT KONTRASEPSI Yogi Isna Hartanto; Agus Rusgiyono; Triastuti Wuryandari
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30387

Abstract

The cluster analysis of the Ward method is a cluster forming method based on minimizing the loss of information due to the incorporation of objects into clusters. An Error Sum of Square (ESS) is used as an objective function. Two objects will be combined if they have the smallest objective function among possibilities. The similarity measure used is the Euclidean distance. In this experiment used data from the number of users of contraceptives in Central Java Province. Contraceptives that can be detected its use is IUD, MOW, MOP, condoms, implants, injections, and pills. The results of cluster analysis of Ward method were obtained as many as 3 clusters. First cluster consists of 9 districts/cities with the number of use of most contraceptives, namely Cilacap, Banyumas, Pati, Pemalang, Tegal, Jepara, Grobogan, Demak, and Semarang City. Second cluster consists of 21 districts/cities with the number of use of medium contraceptives, namely Purbalingga, Banjarnegara, Kendal, Wonogiri, Pekalongan, Blora, Brebes, Kebumen, Wonososbo, Boyolali, Karanganyar, Sragen, Magelang, Klaten, Semarang, Purworejo, Temanggung , Sukorejo, Rembang, Batang, and Kudus. Third cluster consists of 5 districts/cities with the number of use of contraceptives a little, namely Magelang City, Salatiga City, Surakarta City, Pekalongan City, and Tegal City. Keywords: Contraceptives, Cluster Analysis, Ward Methods, Euclidean Distance
PENERAPAN GRAFIK KENDALI JUMLAH KUMULATIF UNTUK MENDETEKSI PERGERAKAN KURS MATA UANG (Studi Kasus: Kurs Jual dan Kurs Beli Dollar Amerika) Silvia Julietty Sinaga; Mustafid Mustafid; Sugito Sugito
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30382

Abstract

The Average Control Chart (  can be used to see if there has been an average change in a process. But this graph has a weakness that is not sensitive to small average shifts. The Cumulative Sum Control Chart (CUSUM) is considered to be more effective in detecting small average process shifts, because it combines information taken from multiple samples by describing the cumulative number of sample deviations from the target value. Both of these graphs are used to detect currency exchange rate shifts with the conclusion that the exchange rate of US Dollar (USD) to Rupiah (IDR) are out of control. The Average Run Length (ARL) value of the CUSUM Chart tends to be smaller than ARL of the  chart. The ARL of CUSUM Control Chart for the selling rate and buying rate is 14,4269 and 19,3798. The ARL of  chart with the 3 sigma limit is 370,37. CUSUM control chart also gives the result that the average of selling rate has increased from 13,022 to 13,200 and the average of buying rate has decreased from 13,022 to 12,6027. This means that the Dollar selling price in the bank will increase/expensive while the Dollar purchase price will decrease/cheaper. Keywords: Exchange Rate, Average Control Chart, Cumulative Sum Control Chart (CUSUM), Average Run Length (ARL), US Dollar (USD), Rupiah (IDR)
KLASIFIKASI PERUSAHAAN DI INDONESIA DENGAN MENGGUNAKAN PROBABILISTIC NEURAL NETWORK (Studi Kasus: Perusahaan yang Terdaftar di Bursa Efek Indonesia Tahun 2016) Adi Waridi Basyirudin Arifin; Hasbi Yasin; Budi Warsito
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30383

Abstract

Classification of company performance can be judged by looking at it’s financial status, whether poor or good state. In order to classifying the financial status, annual financial report will be required. By learning financial status of company, it would be useful to evaluate the performance of the company itself from management cause, or as an investor, making strategy for investment to certain company would be easier. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric method. One of the models in Artificial Neural Network is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclid distance and each class share the same values as their weights. By using the holdout method as an evaluation in honesty, the results show that modeling the company performance with PNN model has a very high accuracy. This is confirmed by the level of accuracy of the data model built on the training data is 100%, while trial data also got 100% accuracy.            Keywords : Classification of Company Performance, PNN, Holdout.
PENGGUNAAN WEIGHTED PRODUCT (WP) DAN ELIMINATION ET CHOIX TRANDUSIANT LA REALITÉ (ELECTRE) DALAM MENENTUKAN TEMPAT BERBELANJA KEBUTUHAN RUMAH TANGGA TERFAVORIT BERBASIS GUI MATLAB (Studi Kasus : Ritel Modern di Kota Surakarta) Syavhana Yusricha Zuhri Putri; Sudarno Sudarno; Tatik Widiharih
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30384

Abstract

Surakarta is one of the fastest growing cities. One of them is marked by many shopping places to fulfill household needs. This causes competition between shopping places. Based on these conditions, a method is needed to assess the customer's favorite shopping place to create a shopping place that matches the customer's expectations. Methods that can be applied to choose the most favorite shopping place are WP and ELECTRE. These two methods can make a decision to get a favorite alternative based on certain criteria in solving Multi Attribute Decision Making (MADM) problems. There are eight alternatives and thirteen criterias. The alternatives are Indomaret Point, Alfamidi, Superindo, Lotte Mart, Hypermart, Carrefour, Luwes Group and Goro Assalam. While the criterias are price of goods, service, stock of goods, arrangement of goods, hygiene, location, ease of transaction, facility, employee appearance, place comfort, employee friendliness, security, and courtesy of employee. The result of this study shows that the favorite type of shopping place for household needs according to WP and ELECTRE method is Carrefour. This study also produces a GUI Matlab  programming application that can help users in performing data processing.Keyword : MADM, WP, ELECTRE, Shopping place, GUI Matlab
IMPLEMENTASI SUBSET AUTOREGRESSIVE MENGGUNAKAN PAKET FITAR Tomi Ardi; Rukun Santoso; Alan Prahutama
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30385

Abstract

Time series data analysis is one of the important points in statistics that is a time-dependent analysis. The commonly used model for time series data is ARIMA (Autoregressive Integrated Moving Average) or often also called the Box-Jenkins time series method. A model of ARIMA used in time clock data forecasting is the AR subset (autoregressive). The AR subset model is suitable for a long time series with a more than 5th order lag. The statistical software used is the R. time series AR subset approach on R using the FitAR package. The main function of the FitAR package is SelectModel and FitAR. SelectModel function to get the model automatically while FitAR is used to determine the temporary suspect model. Data used in the form of dataset contained in package FitAR that is SeriesA. The SeriesA data is data about the chemical concentration process observed every 2 hours for 17 days. SeriesA is processed using FitAR package so that the best model is AR [1,2,7].Keywords : Time Series, Time Series Non-stasioner, Subset AR, FitAR Package
PENGENDALIAN KUALITAS PRODUK MINO DI HOME INDUSTRY “SARANG SARI” BANYUMAS Winahyu Handayani; Tatik Widiharih; Budi Warsito
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30386

Abstract

Mino is Banyumas’s signature souvenir that is fancied by the public. High competitiveness makes mino manufacturers are prosecuted to improve the quality of their products. One of the ways to ascertain whether a product has a good quality is by looking at the number of defective products, the less the number of defective products the better the quality. The objective of the study is to minimize broken and burnt products and also size faultiness of the mino. Control Charts   and R are used to view defectiveness data from mino’s diameter and mino’s weight respectively, where as Control Chart p is used to see the data of burnt and broken mino. Furthermore, the value of process capability (Cpk) used to review whether the process is considered capable or not capable. The result and analysis at “Sarang Sari” Nopia and Mino’s Home Industry Banyumas show attribute data in the form of broken and burned defects is restrained after eliminating seven observations data. Thereupon, the variable data in the form of mino’s weight data is restrained after omitting the three observations data with Cpk value is 1.1180, and for mino’s diameter data process has been restrained with Cpk value of 0.9559. Factors that are affecting mino’s defectiveness are equipment, method and measurement. Meanwhile, the profit value of this mino home industry business is Rp 9.276.110 per month. Keywords: Mino, Chart Control, Process Capability, Economic Analysis
PENERAPAN METODE WAVELET NEURO-FUZZY SYSTEM (WNFS) DALAM MEMPREDIKSI HARGA BERAS DUNIA (Studi Kasus: Harga Beras Thailand sebagai Harga Acuan Dunia) Sri Endah Moelya Artha; Hasbi Yasin; Budi Warsito
Jurnal Gaussian Vol 6, No 4 (2017): 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.v6i4.30381

Abstract

Rice trade is one of the food resistance components in terms of its availability. The comprehensive integration between international commodity rice prices and domestic prices encourage the prediction of world rice prices, using the Thai rice price as the world's reference price. In this study, the wavelet neuro-fuzzy system which combines the wavelet transform and the neuro-fuzzy technique has been applied to monthly predict the world rice price. The observed monthly rice price data are decomposed into some sub-series components by maximal overlap discrete wavelet transform (MODWT), and then the appropriate sub-series that have higher correlation to the real data are used as inputs of the neuro-fuzzy model for monthly predicting world rice prices for six months in advance. The neuro-fuzzy model is begun with determining the membership value of each data using Fuzzy C-Means, followed by fuzzy inference procedure of the Sugeno zero-order model. Obtained results showed that the WNFS method can be used to predict the world rice price, with the error value resulted from learning process of MSE 20,69097 and MAPE 0,65584%. While the error measurement results for the six months in advance prediction shows the acquisition of MSE 3610,14847 and MAPE 13,62334%. Keywords : Prediction of Monthly World Rice Price, Maximal Overlap Discrete Wavelet Transform, Neuro-fuzzy System.

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