cover
Contact Name
Meiliyani Siringoringo
Contact Email
meiliyanisiringoringo@fmipa.unmul.ac.id
Phone
+6285250326564
Journal Mail Official
eksponensial@fmipa.unmul.ac.id
Editorial Address
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
Location
Kota samarinda,
Kalimantan timur
INDONESIA
Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Articles 11 Documents
Search results for , issue "Vol 9 No 1 (2018)" : 11 Documents clear
Analisis Survival Data Kejadian Bersama dengan Pendekatan Efron Partial Likelihood Santi Prabawati; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (751.87 KB)

Abstract

Survival analysis is a statistical procedure used to analyze data related to survival time, from the defined time origin until the occurrence of certain events. In the survival analysis, sometimes ties are found, in which two or more individuals experience the same event at the same time. There are three widely used methods to treat ties in survival analysis, that is Exact method, Breslow approach, and Efron approach. Efron's approach has a simple, fast, and accurate calculation especially when the data contains many ties. The purpose of this study is to find out the Cox proportional hazard data ties model using Efron partial likelihood approach and to know the variables that affect the graduation time of student of Faculty of Mathematics and Natural Sciences of Mulawarman University class of 2011 that graduated until February 28, 2017. The variables are Gender, home area, funding sources, and GPA. Based on the results of the analysis that has been done with the help of software R, it is obtained that the variables that have significant effect are gender and GPA. For the gender variables it was concluded that female students had a chance of 1,362 times to graduate faster than male students. While for the GPA variable it is concluded that each addition of GPA of 0.1, then the student's chance to graduate faster will increase by 1,225 times.
Penerapan Metode Complete Linkage dan Metode Hierarchical Clustering Multiscale Bootstrap Lisda Ramadhani; Ika Purnamasari; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (566.958 KB)

Abstract

Cluster analysis is an analysis that has a purpose to grouping the data (object). The multiscale bootstrap method in cluster analysis is used as a manner for looking at the validity from the result of cluster analysis. The working process of multiscale bootstrap in cluster analysis is taking a sample that has been bootstrapped and then take the one of bootstrap resampling result that has been reputed to represent the distribution in East Kalimantan 2016. The purpose of this research is looking at the result of data agglomeration in poverty indicator in East Kalimantan 2016 in using a multiscale bootstrap method that produces four cluster types. The first cluster consists of two regencies/cities who has the low percentage of poverty indicator 49,32%. Additionally, the second cluster contains of five regencies/cities with the high percentage of poverty indicator 53,39%. In addition, the third cluster involves of two regencies/cities with the percentage of poverty indicator in high sufficient 51,46%. Finally, the fourth cluster consists of a regency/city which has a percentage of poverty indicator low adequate 51,02%.
Multi-Attribute Decision Making dengan Metode Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) Oktri Mayasari; Yuki Novia Nasution; Rito Goejantoro
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.686 KB)

Abstract

Fuzzy TOPSIS is a method that is used for identifying solution from one limited alternative set. The basic principle is that the chosen alternative must have the shortest distance from the positive ideal solution and the furthest distance from the negative ideal solution to determine relative proximity from an alternative with optimal solution. Fuzzy numbers in this method give effectiveness to determine the value of decision matrix. The purpose of this research is to find out the recommendation of investment in ADHI, PTPP, WIKA, and WSKT stocks by using fuzzy TOPSIS method. The alternatives that is used in this research are four stocks in the building construction sector on LQ45, from February to July 2017 namely Adhi Karya (Persero) Tbk. (ADHI), PP (Persero) Tbk. (PTPP), Wijaya Karya (Persero) Tbk. (WIKA), and Waskita Karya (Persero) Tbk. (WSKT) with the attributes that consist of nine financial ratios, namely Earnings Per Share (EPS), Book Value Per Share (BV), Debt to Assets Ratio (DAR), Debt to Equity Ratio (DER), Return on Assets (ROA), Return to Equity (ROE), Gross Profit Margin (GPM), Operating Profit Margin (OPM) and Net Profit Margin (NPM) on June 2016. The result of the research with fuzzy TOPSIS analysis generates preference value from stocks of ADHI amount 0,1711, stocks of PTPP amount 0,6169, stocks of WIKA amount 0,6310, and stocks of WSKT amount 0,7488. The result of preference value shows that stocks of WSKT with the highest preference value become the best recommendation option to invest rather than the stocks of ADHI, PTPP, or WIKA.
Analisis Positioning dengan Menggunakan Multidimensional Scaling Nonmetrik Devy Sintya Putri; Sri Wahyuningsih; Rito Goejantoro
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (674.431 KB)

Abstract

As the era progresses, more and more smartphone brands are present in the market in which it is difficult for consumers to decide which smart phone brands are good among others. The aims of this research are to know the position of five brands of the smart phone based on the consumer perception by using multidimensional scaling analysis (MDS) and also to know the superiority for each of these smartphone brands based also on the consumer perception focused on the product attribute and consumer perception about smartphone brands which they mostly prefered. So the result indicates that the coordinate points got based on the consumer perception by using MDS analysis are as follows; Asus is (10,494,2525), Oppo is (-4,154; 3,591), Samsung is (-4,216; (- 3,979)), Sony is (4,188 ; (- 3,985)), and Xiaomi is (-6,312; 1,848). Among the five smart phone brands above, Xiaomi has an advantage on the most affordable price attribute. Samsung has an advantage on the attributes of good screen display results, better known brands, more beautiful designs, complete features, ease for use, and large memory capacity. The smart phone brands of Asus, Oppo and Sony have the advantage on the results of a good camera and good processor performance. It is the fact that the most superior smart phone brands based on the consumer’s perception data are the brand of Oppo and Samsung smart phones.
Pemodelan Geographically Weighted Regression (GWR) Dengan Fungsi Pembobot Tricube Terhadap Angka Kematian Ibu (AKI) Di Kabupaten Kutai Kartanegara Tahun 2015 Muhammad Rahmad Fadli; Rito Goejantoro; Wasono Wasono
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (702.1 KB)

Abstract

Maternal Mortality in Kutai Kartanegara is a geographical problem that suspected affected by geographical factor which the global regression cannot model the relation well between the main problem and its independent variable. Therefore, Geographically Weighted Regression (GWR) is used to solve it. Spatial statistics is a method for analyzing data that has spatial correlation. GWR Model is the locally of global regression which considering the geographical or location as the weighted function for estimating the parameters of models. The tricube weighted function is used for the weighting. From this study, the models are different from location to others with also has the independent variables. For Samboja, Muara Jawa, Sanga-Sanga, Anggana, Muara Badak, Marang Kayu, and Tabang which are not affected by the indicators. Loa Janan, Loa Kulu, Muara Muntai, Kota Bangun, Tenggarong, Sebulu, Tenggarong Seberang, Muara Kaman, and Kenohan have the Maternal Mortality affected by Hospital Ratio per 1.000 Pregnant Mothers (x1). Muara Wis, Kenohan, dan Kembang Janggut have the Maternal Mortality affected by Childbirth with Medical Help (x2). Muara Muntai, Muara Wis, Kota Bangun, Sebulu, Tenggarong, Muara Kaman, Kenohan, and Kembang Janggut have the Maternal Mortality affected by Health Care of Childbed (x4).
Peramalan Dengan Metode Fuzzy Time Series Markov Chain Yenni Safitri; Sri Wahyuningsih; Rito Goejantoro
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.6 KB)

Abstract

Forecasting is an activity to predict what will happen in the future with certain methods. Fuzzy time series is a method known as artificial intelligence used to predict the problem which the actual data is formed in linguistic values using fuzzy principles as its basis. This study discusses the method of fuzzy time series developed by Ruey Chyn Tsaur to predict the closing price of the shares of PT. Radiant Utama Interinso Tbk April 2017. Markov Chain fuzzy time series method is used to analyze a time series data which is a combination of fuzzy time series model with Markov Chain. Forecasting of closing stock price based on data from January 2011 to March 2017 for April 2017 is Rp 224,29,00. Markov Chain's fuzzy time series method to forecast the closing stock prices data from January 2011 to March 2017 has a 3,48% of MAPE value or has a 96,52% of precision forecast. The results show that the Markov Chain fuzzy time series has an excellent level of accuracy for forecasting the closing stock prices.
Model Cox Proportional Hazard Pada Kejadian Bersama (Ties) dengan Metode Breslow Nazmi Soraya; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (770.285 KB)

Abstract

Cox proportional hazard model at the tied incident is a modification from Cox model while there are two or more individual that experienced tied. Parameter estimation in procedure formation of cox generally uses maximum partial likelihood estimation (MPLE) that maximised the function of partial likelihood. In incident with ties case, the modification at partial likelihood is done with breslow approach. The data used in this research were Dengue Hemorrhagic Fever patients (DHF) who were hospitalized at Dirgahayu Hospital Samarinda from July 2016 until June 2017. There are 100 patients with 5 independent variables that are suspected to affect the healing of Dengue Hemorrhagic Fever (DHF) patients, namely sex, age, platelet count, hematocrit count, and duration of fever before hospitalized. From the calculation of data used R 2.11.1 software, Cox proportional hazard model using Breslow method, it is obtained that significant variable, are the count of platelets and hematocrit, and the duration of fever before hospitalized, patient who had normal platelet count had a chance of healing 2.359 times faster than patients had a thrombocytopenia (low platelet). For the amount of heamatocrit each patient who had a normal hematocrit had a chance of healing 2.364 times faster than patients who had under-normal hematocrit, and each one day addition to duration of patient's long history fever before hospitalized, decreased the chance of healing by 0.849 times.
Penentuan Besaran Premi Asuransi Jiwa Berjangka dengan Model True Fractional Premiums Muhammad Al-Firdaus Erdian; Ika Purnamasari; Wenny Kristina
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (451.092 KB) | DOI: 10.30872/eksponensial.v9i1.271

Abstract

The model of the payment of life insurance premium that can be paid more than once a year is called fractional premiums. This model consists of two types, namely true fractional premiums and apportionable premium. The true fractional premiums is divided into two models of payment of compensation, namely discrete payment model and continuous payment model. This study aims to find out the comparison of 20 years life insurance premium with true fractional premiums model based on gender and number of payments made in a year from both payment models. The data used in this research is the simulation data. Based on the research result, it is found that the amount of life insurance premium using discrete compensation payment model is cheaper than the one using the continuous payment model. While based on gender, the premium of male is more expensive than female. Based on the amount of payments made in one year, payments made each month are more expensive than the payments made each quarter and semester.
Pemodelan Mixed Geographically Weighted Regression (MGWR) Nur Fajar Apriyani; Desi Yuniarti; Memi Nor Hayati
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (543.76 KB)

Abstract

Diarrhea disease is one of the conditions which a person has soft or liquid defecate consistency, even can be water and frequency more often in one day. The province of East Kalimantan includes areas where the percentage of diarrhea tends to increase annually. Therefore, as one of the efforts to handle cases of diarrhea in East Kalimantan Province, so that the research using Mixed Geographically Weighted Regression (MGWR) model which is a modeling method that combines global regression model and Geographically Weighted Regression (GWR) model. Modeling MGWR aim to find out the factors that affect the number of diarrhea sufferers, where factors are differentiated into factors that affect locally in each District/City and factors that affect globally throughout the District/City. The result of the research using the MGWR method, the variable of the number of households that live clean and healthy and the number of food management places do not meet the criteria affect globally. The number of communal latrine facilities affect locally.
Penentuan Besaran Premi Asuransi Jiwa dengan Model Apportionable Fractional Premiums Berdasarkan Tabel Mortalita dengan Metode Interpolasi Kostaki Muhammad Nor Abdul Rajak; Yuki Novia Nasution; Nanda Arista Rizki
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (595.108 KB) | DOI: 10.30872/eksponensial.v9i1.272

Abstract

Insurance is an agreement between the customer and insurance company, at which the insurance company bears some loss in the future and the customer pays the premium according to the agreement. Insurance company determines the amount of premiums based on mortality tables. The purpose of the research is to determine the characteristics of Indonesia mortaliy table with Kostaki interpolation method, to determine whole life insurance premium with apportionable fractional premiums model, and to determine the amount of the premium return. The results of the research indicate that in the mortality table of Indonesia in 2014, the number of female deaths tend to be lower than male at 1-74 years, but the number of deaths increased over the age of 75 years. The premiums paid by a 30 year-old male with a semester payment is Rp 2.358.988, quarterly payment is Rp 1.186.823, and monthly payment is Rp 397.253. The premiums paid by a 30 year-old female with a semester payment is Rp 2.044.666, quarterly payment is Rp 1.028.669, and monthly payment is Rp 344.242. Premium return of 30 years-old male is Rp 84.204.338 and of 30 years-old female is Rp 72.968.560.

Page 1 of 2 | Total Record : 11