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Jurnal Gaussian

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Published by Universitas Diponegoro

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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 733 Documents

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PENGGUNAAN REGRESI LOGISTIK BINER DAN ITERATIVE DICHOTOMISER 3 (ID3) DALAM PEMBUATAN KLASIFIKASI STATUS KERJA (Studi Kasus Penduduk Kota Surakarta Tahun 2015) Winastiti, Lugas Putranti; Rusgiyono, Agus; Safitri, Diah
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Discussing about the macro economy usually discuss about unemployment. Unemployment basically can not be fully eliminated. Unemployment usually symbolized with an employment status of person. In this research, two methods were used in making the classification of employment status in the population of the city of Surakarta in February 2015, the methods are binary logistic regression and Iterative Dichotomiser 3 (ID3) Algorithm. Predictor variables used in determining employment status were age, gender, status in the household, marital status, education and work training. Comparison of the training data and testing data is 60:40. Based on calculations obtained binary logistic regression variables that significantly affect the employment status are age, gender and marital status and the accuracy using testing data is 75%, while the calculations of a decision tree using iterative dichotomiser 3 algorithm the accuracy using testing data is 75%. Keywords: Classification, Iterative Dichotomiser 3 Algorithm, Binary Logistic Regression

ANALISIS KEPUASAN PENGUNJUNG MENGGUNAKAN SECOND ORDER CONFIRMATORY FACTOR ANALYSIS PADA STRUCTURAL EQUATION MODELING (Studi Kasus: Pengunjung Pemandian Air Panas (PAP) Guci) Niken Anggraini Dewi; Rita Rahmawati; Moch. Abdul Mukid
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Pemandian Air Panas (PAP) Guci is one of the famous natural destinations in Tegal regency. The visitors are fluctuated. Therefore, the writer carried out an analysis of visitor satisfaction using Stuctural Equation Modeling (SEM). Confirmatory factor analysis using in the reseach is second order. The construct used are the service quality (tangibles, reliability, responsiveness, insurance, and empathy), product quality (facilities, accessibility, source human and hygiene), price (affordability, suitability, and price comparisons), visitor satisfaction (overall satisfaction, satisfaction as expected, and the employee), and the interest reset. Choosing variables based on justification theory. Significant parameters, namely the quality service to the quality products by 50,8%, the quality product to the prices by 89%, the price to the visitor satisfaction of 91,4%, visitor satisfaction to the interest reset of 55%. Parameters were not significant, envelop service quality to price, quality service to visitor satisfaction, and quality product to visitor satisfaction. Keywords: Second Order Factor Analysis, SEM, Product Quality, Service Quality, Price, Visitor Satisfaction, Interest Reset.

PENGHITUNGAN PREMI ASURANSI LONG TERM CARE UNTUK MODEL MULTI STATUS Gumauti, Chrysmandini Pulung; Wilandari, Yuciana; Rahmawati, Rita
Jurnal Gaussian Vol 5, No 2 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Health insurance is insurance that provides health benefit in the form of a cash compensation for the cost of treatment and care. One of the health insurance’s products is Long Term Care (LTC) insurance. LTC insurance guarantees nursing and medical expense, preferred for elderly people in the future. Proper calculation the cost of premiums is needed to maintain the reserve fund appropriate for insurance company to fulfill the policy agreement. In this final project will be discussed about calculation of premiums for LTC insurance products Annuity as A Rider Benefit as a multi-state models (three states), which is based on Markov transition probability matrix. Data used is the data prevalence rate of heart disease in the United Kingdom in 2014. By calculating premiums of multi-state models, insurance products are expected to be able to guarantee health care expense according insured’s needs. Result of this premiums calculation is the older someone takes insurance, greater the annual net premium to be paid. Keywords: health insurance, Long Term Care insurance, multiple state models, Annuity as A Rider Benefit product, Markov transition.

PERBANDINGAN ARIMA DENGAN FUZZY AUTOREGRESSIVE (FAR) DALAM PERAMALAN INTERVAL HARGA PENUTUPAN SAHAM (Studi Kasus pada Jakarta Composite Index) Muhammad Fitri Lutfi Anshari; Dwi Ispriyanti; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The capital market is one of the most popular investment option today. In capital market, stock price prediction is an important issue for investors, so needed a good forecasting method as a basic for decision-making for the transaction. One of the most popular forecasting method is ARIMA, but this method still uses the concept that measurement error which is obtained from the difference between the observed values with estimated values. To resolve the error in modeling, Fuzzy Autoregressive was developed, it is a model combination of Fuzzy Regression and Autoregressive (AR). This method gives results in interval forecasting, thus providing information to decision makers regarding the best and worst situation that may occur. This paper discusses the application of Fuzzy Autoregressive forecasting interval for the Jakarta Composite Index and compare it with the ARIMA prediction interval. The result of this study is Fuzzy Autoregressive interval is narrower than the ARIMA 95% significance rate

METODE k-MEDOIDS CLUSTERING DENGAN VALIDASI SILHOUETTE INDEX DAN C-INDEX (Studi Kasus Jumlah Kriminalitas Kabupaten/Kota di Jawa Tengah Tahun 2018) Nahdliyah, Milla Alifatun; Widiharih, Tatik; Prahutama, Alan
Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The k-medoids method is a non-hierarchical clustering to classify n object into k clusters that have the same characteristics. This clustering algorithm uses the medoid as its cluster center. Medoid is the most centrally located object in a cluster, so it’s robust to outliers. In cluster analysis the objects are grouped by the similarity. To measure the similarity, it can be used distance measures, euclidean distance and cityblock distance. The distance that is used in cluster analysis can affect the clustering results. Then, to determine the quality of the clustering results can be used the internal criteria with silhouette width and C-index. In this research the k-medoids method to classify of regencies/cities in Central Java based on type and number of crimes. The optimal cluster at k= 4 use euclidean distance, where the silhouette index= 0,3862593 and C-index= 0,043893. Keywords: Clustering, k-Medoids, Euclidean distance, Cityblock distance, Silhouette index, C-index, Crime

PERHITUNGAN SUKU BUNGA EFEKTIF UNTUK PENENTUAN ALTERNATIF PEMBIAYAAN KENDARAAN MOTOR PADA LEASING DAN BANK DENGAN METODE INTERPOLASI LINIER (Studi Kasus Harga Sepeda Motor Honda Beat Injeksi Terdaftar Bulan September 2014) Swasnita Swasnita; Suparti Suparti; Sugito Sugito
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Imposition of interest rates by the bank and leasing in providing credit is different. The interest rate usually not included in the brochure loan installments. The calculation of the interest rate can be calculated using the flat rate and the effective interest rate. In the calculation of the effective interest rate can be performed using linear interpolation. Determination of the motorcycle financing alternative most favorable to the customer, can be seen from the lowest interest rates charged. The results of the case study Honda Beat injection prices listed September 2014 on credit motorcycle through leasing Central Sentosa Finance (CSF), leasing Adira Multifinance (Adira) and credit through Bank Rakyat Indonesia showed the lowest interest rate on the lease Central Sentosa Finance (CSF). In addition to low interest rates charged are other benefits that the filing procedures quickly and without collateral (guarantee). Keywords : Flat Interest Rate, Effective Interest Rate, Linear Interpolation, Leasing, Bank

PEMBENTUKAN POHON KLASIFIKASI BINER DENGAN ALGORITMA CART (CLASSIFICATION AND REGRESSION TREES) (Studi Kasus: Kredit Macet di PD. BPR-BKK Purwokerto Utara) Mardika, Zulfa Wahyu; Mukid, Moch. Abdul; Yasin, Hasbi
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Modernization and globalization of the world today has entered into various lines of Indonesian society. One consequence is people's lifestyles are more consumptive. This lifestyle causes people take out a loan at a bank or other financial institution to fulfill his wish. Some people pay the loan on credit. But in implementation, there is a variety of things causes the credit not running properly or called with problem loan. As a service provider of credit institutions, PD. BPR-BKK Purwokerto Utara is also not free from this problem. Therefore, it is necessary to classify customers based on demographic variables using Classification and Regression Trees (CART) to minimize the chances of problem loans. Based on analysis of customer credit status data PD. BPR-BKK Purwokerto Utara, optimal classification tree formed by the number of terminal nodes as much as 6 nodes. This means there are 6 characteristics of customers PD. BPR-BKK Purwokerto Utara. And level of accuracy of the classification tree in classifying credit status of customers is 81.0 % . Keywords: Modernization, Globalization, Credit, Problem Loan, Customer, CART, Classification Tree.

ANALISIS BIPLOT KOMPONEN UTAMA PADA BANK UMUM (COMMERCIAL BANK) YANG BEROPERASI DI JAWA TENGAH Ely Fitria Rifkhatussa'diyah; Hasbi Yasin; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Competition among banks in Indonesia nowadays are getting higher due to the good economic growth and increasing of middle social class in Indonesia. The number of banks cause high competition among banks and internal bank itselves. This high competition makes the management of the bank should think seriously to maintain its existence. In this case the assessment of the bank become very important in the banking business to survive in today's banking industry. This study was conducted to determine how competitive the Commercial Bank are operating in Central Java by a method of Principal Component Biplots. This analysis can be applied to find out information about the relative position, the similarity between objects and characteristic of variables in the three categories of commercial banks operating in Central Java based on their health aspects. The results of this study are the banks from each category have a distinct predominance in every aspect of health assessment variable. In addition, the biplots can give information on the variability more than 70% which means that principal component biplot explains the overall data well.

PERAMALAN JUMLAH WISATAWAN YANG BERKUNJUNG KE OBJEK WISATA DI JAWA TENGAH MENGGUNAKAN VARIASI KALENDER ISLAM REGARIMA Jesica, Haniela Puja; Ispriyanti, Dwi; Tarno, Tarno
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Tourism is one of the most strategically controlled areas that have been developed.The number of tourists in Central Java is constantly rising in the month of Eid Al-Fitr caused by holiday and mudik to hometown. The shift of the Eid Al-Fitr month on the data will form a seasonal pattern with an unequal period, then called moving holiday effect.One of the calendar variationsare often used to remove the moving holiday effect is RegARIMA model. RegARIMA is a combination of the linier regression and ARIMA, which a weight was used as a regression variable and error of regression model was used a variable in the ARIMA process. Based on the analysis carried out on the monthly number of tourists visiting tourist attractions in Central Java data for the period January 2011 to December 2017, the RegARIMA (1,1,1) (0,0,1)12model as the best model because it have the lowest AIC value than other model. The forecasting results in 2018 shows an increase on number of tourists data on June 2018 which coincided with the Eid Al-Fitr holiday on 15 June 2018. sMAPE value is 23,298%.Keyowrds:Time Series, Tourists, RegARIMA, Moving Holiday Effect

MODEL REGRESI MENGGUNAKAN LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) PADA DATA BANYAKNYA GIZI BURUK KABUPATEN/KOTA DI JAWA TENGAH Aulia Putri Andana; Diah Safitri; Agus Rusgiyono
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Gizi buruk adalah bentuk terparah dari proses terjadinya kekurangan gizi yang menahun. Gizi buruk dipengaruhi oleh banyak faktor yang saling terkait. Dalam penelitian ini, dilakukan pemodelan dari faktor-faktor yang mempengaruhi gizi buruk menggunakan metode Least Absolute Shrinkage Selection and Operator (LASSO) dengan algoritma Least Angle Regression (LARS) karena pada faktor-faktor yang mempengaruhi gizi buruk terdeteksi multikolinearitas. LASSO menyusutkan koefisien regresi dari variabel bebas yang memiliki korelasi tinggi menjadi tepat pada nol atau mendekati nol. Koefisien LASSO dicari dengan menggunakan pemrograman kuadratik sehingga digunakan algoritma LARS yang lebih efisien dalam komputasi LASSO. Berdasarkan analisis yang telah dilakukan, model LASSO pada data gizi buruk Kabupaten/Kota di Jawa Tengah tahun 2014 diperoleh pada tahap kedua saat nilai s=0.02 dengan nilai MSE sebesar 0,82977. Disimpulkan bahwa variabel bayi (0-6 Bulan) yang diberi ASI Eksklusif, rumah tangga berperilaku hidup bersih dan sehat, bayi yang mendapat imunisasi Hepatitis B, bayi yang mendapat imunisasi DPT-HB3, rumah dengan sanitasi yang layak, dan rumah dengan air minum sesuai dengan syarat kesehatan berpengaruh terhadap bayi gizi buruk di Jawa Tengah tahun 2014. Kata Kunci: gizi buruk, multikolinearitas, LASSO, LARS

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