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All Journal AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Eksponensial
Desi Yuniarti
Universitas Mulawarman
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other

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Perbandingan Pengelompokan K-Means dan K-Medoids Pada Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas Athifaturrofifah Athifaturrofifah; Rito Goejantoro; Desi Yuniarti
EKSPONENSIAL Vol 10 No 2 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

The cases of forest/land fires in Indonesia seem endless, almost every year in the dry season similar problems always occur. Some areas in Indonesia often occur in forest fires and result in losses of up to trillions of rupiah. Various ways have been made to help the government in minimizing the potential for forest or land fires, one of them is by monitoring hot spots. In this study using data hot spots with parameters of latitude, longitude, brightness, fire radiation power and confidence by using the method of grouping K-Means and K-Medoids. The difference between these two methods is that the K-means method uses the mean as the center of the cluster, while K-Medoids uses representative objects (medoids) as the center of the cluster. This study aims to compare the results of the grouping of K-Means method with K-Medoids by using 42 data. The results of this study indicate that the K-Means method produces Silhouette Coefficient scores greater than K-Medoids. So that, K-Means can provide more accurate grouping results with a greater Silhouette Coefficient value.
Analisis Pengendalian Kualitas Produk Amplang Menggunakan Peta Kendali Kernel Rahmad Fahreza Adiyasa; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 10 No 1 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Quality control is the use of techniques and activities to maintain and improve the quality of products or services. One of the quality control methods is epanevhnikov kernel control chart. The epanevhnikov kernel control chart is a control chart used to evaluate nonparametric product quality characteristic data because it does not require certain assumptions. The purpose of this research is to find out whether the 1 kg packaged Amplang product in UD. H. Icam Samarinda is within the control limit and what factors can cause the weight of the product becomes uncontrollable. The result shows that there is no sample point outside the control limits in the control chart with kernel density function estimation. So it can be concluded that the weight of the product is within a controlled condition. The factors that can cause the products uncontrolable are environmental factors, human factors, machine factors and material factors.
Penerapan Metode Full-Profile Dalam Pengumpulan Data Untuk Analisis Konjoin Roy Tridoni Situmorang; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Conjoint analysis is an analytical technique that is used to examine the impact of attributes of goods or service. Conjoint analysis can be applied to know the attribute that become the main choice of student of Mulawarman University in choosing GSM prepaid card product. Where the attribute used are SMS tariff, phone tariff, internet package, signal and bonuses. The purpose of this study is to know the combination of attribute level which is most interested by student and relative importance value from each attribute. The result of this study is the combination of attributes of the GSM prepaid card that the student are interest in are the SMS package tarif with the utility value is 1,445, the phone tarif per minute with the utility value is 0,525, full 4G internet package with the utility value is 2,51, strong signal with the utility value is 1,895, SMS bonus with the utility value is 1,42. The attribute that become the student’s preferred choice in choosing GSM prepaid card is internet package with the relative importance value is 0,352.
Peramalan Dengan Menggunakan Metode Double Exponential Smoothing Dari Brown Etri Pujiati; Desi Yuniarti; Rito Goejantoro
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Consumer Price Index (CPI) is one of the economic indicator that givethe information about the price of goods andservices which paid by consumer. CPI in Samarinda City increases so long which the pattern of the data is indicating a trend pattern. Time series forecasting designed to handle the trend of data which used a double exponential smoothing method. The purpose of this study is to determine the using of the parameters α and the forecasting amount of CPI in Samarinda City for three months that use double exponential smoothing method. The best parameter α which use to forecast CPI in Samarinda City is (0,61). To forecast CPI in Samarinda City is using double exponential smoothing method obtained F72+m=119,83+1,62 m. The forecasting result of CPI in Samarinda City from January to March 2015 are 121,44, 123,06, and 124,68.
Model Regresi Logistik Spasial Tiara Nurul Ma’ala; Desi Yuniarti; Memi Nor Hayati
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Logistic regression modeling procedure is applied to model the response variable (Y) which is based on one or more categorical explanatory variable (X) which is categorical or continuous. In the application of logistic regression is often found that there are spatial influences that affect the model. The existence of spatial relationships between regions that cause necessary to accommodate the spatial diversity into the model, so that the analysis used logistic regression spatial. First law of geography says that everything is related to everything else, but near things are more related than distant things. Then, when a region becomes a major cause of the spread of a disease is suspected, the region will provide the spread of a disease to the new area adjacent to it. The way to find out the adjacent area with the same characteristics can be done with spatial logistic regression method.The spread of TB disease in Samarinda City is quite high. TB is a chronical disease which has been known by the public and feared of its infection. This study’s aim is to determine the appropriate model to estimate the spread of TB disease. From this model it is known that the factors that influence the number of people with TB disease in every village in Samarinda City in the year 2013 are the number of primary school in every village and the spatial effect. This means that there is the influence of spatial factors to the spread of TB disease in every village in Samarinda City in the Year 2013.
Penerapan Metode Choice Based Conjoint Hidaya Annur; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 10 No 1 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Lecturer is an important factor in the process of teaching and learning process in universities. This study was conducted with the aim to know the characteristics of students of Statistics Program Department of Mathematics at FMIPA Mulawarman University on the characteristics of the expected lecturers. One method that can be used to know the options is the conjoint-based optional method. Choice Based Conjoint (CBC) is a conjoint analysis that measures preferences based on conceptual choices and is used to determine the concept of attributes of lecturer characteristics expected by students. Attributes used in this study are the background of lecturers, lecturer characters, learning methods and interaction in the class. The data analysis technique used in the conjoint-based optional method is the conditional logit model. The result of CBC analysis shows that the attribute that is considered most important by the respondents based on attribute importance value is classroom interaction with percentage of 48,41% and seen from the value of the utility of interaction in the class with a positive value is the interaction in the active class with a value of 1.331. The characteristics of lecturers that are expected to be possessed by lecturers are casual lecturer character, last doctoral education, creative teaching methods and active classroom interaction.
Perbandingan Metode Bootstrap Dan Jackknife Resampling Dalam Menentukan Nilai Estimasi Dan Interval Konfidensi Parameter Regresi Dessy Ariani; Yuki Novia Nasution; Desi Yuniarti
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Regression analysis is a study that describes and evaluates the relationship between an independent variable and the dependent variable for the purpose of estimating or predicting the value of the dependent variable based on the value of the independent variables. Resampling is used when samples obtained for analyzing is less. In this study, Bootstrap method and Jackknife method are using. Both methods are used to find the value of regression parameter estimates and confidence intervals of regression parameter values which applied to the data position of Public Deposits in four groups of banks : Persero Banks, Government Banks, National Private Banks and Foreign Banks to knowing the best resampling methods to find the value of regression parameter estimates and confidence intervals of regression parameter values. There are three independent variables which are used in this study, namely investments loans, working capital loans and consumer loans. From the research results, it is obtained that the Jackknife method is the most appropriate method because it has smaller standard error values so Jackknife methods have a narrow range confidence intervals.
Pengklasifikasian Item Persediaan Menggunakan Metode Always Better Control-Fuzzy Retno Octaviyani; Desi Yuniarti; Yuki Novia Nasution
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

ABC Classification is a method of controlling inventory to control a small quantity of goods but has a high usage value. Inventories are categorized into three classes, namely A, B, and C. Fuzzy classification is a classification used to classify training data sets (data sets used to generate membership functions) and to predict data testing. The purpose of this study was to control inventory using the ABC classification method, Fuzzy Classification, and ABC-fuzzy classification. The results of ABC classification showed that from 182 items of drug, class A is consisted of 15 items of drug with a value of 69,276% usage, class B is consisted of 34 items of drug with a value of use of 20.723%, and class C is consisted of 133 items of drug with value use of 10.010%. The results of the fuzzy classification showed that of the 182 drug items, fuzzy 3 consisted of 9 medicinal items which meant that, there were 9 very important drugs, fuzzy 2 consisted of 171 drug items which meant that there were 171 important medicines, and fuzzy 1 consisted of 2 items of medicine which means that, there are 2 less important drugs. The results of the ABC-fuzzy classification showed that of 182 drug items, there were 17 items of drugs in the first priority which means that the 17 items of this drug are most preferred, then there are 41 items of drug on the 2nd priority which means the stock of 41 items of this drug is preferred, 124 items of drug on priority 3 which means that 124 items of this drug is not preferred.
Penerapan Metode ARIMA Ensembel pada Peramalan Hasniah Hasniah; Sri Wahyuningsih; Desi Yuniarti
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

ARIMA ensemble is a method of combination forecast results from multiple ARIMA models. ARIMA method as individuals and ARIMA ensemble as a combination model to forecasting of national inflation in Indonesia. Ensemble method used to combine the forecast result in this study were averaging and stacking. The data used in this study is the nasional monthly inflation of Indonesian from January 2010 to December 2014. The results showed that for forecasting the next twelve months ensemble averaging method produces the smalles RMSE values ​​and obtained models equation where zt(1) is ARIMA models (2,0,2) and zt2 is ARIMA models (2,0,3). Based on ARIMA ensemble averaging model the monthly inflation forecasting national Indonesia next twelve months forwards experience of fluctuation where highest inflation in January 2015, that is 1,13% and smallest in March 2015, that is equal to -0,13%.
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

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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.
Co-Authors Andini Juita Sari Athifaturrofifah Athifaturrofifah Budi Nugroho Darnah Andi Nohe Dessy Ariani Etri Pujiati Hadi Dwi Darmawan Hasniah Hasniah Hidaya Annur Iim Masfian Nur Ika Purnamasari Lili Widyastuti Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Muhajir Choir Nurahman Nur Azizah Nur Fajar Apriyani Nurul Rahmahani Pratama Yuly Nugraha Rahmad Fahreza Adiyasa Rakhmanto Anugrah Darmawan Retno Octaviyani Reyham Nopriadi Gurianto Riska Handayani Rito Goejantoro, Rito Ronald Tediwibawa Roy Tridoni Situmorang Sri Wahyuningsih Sri Wahyuningsih Tiara Nurul Ma’ala Yuki Novia Nasution Yuki Novia Nasution Yuli Ratnasari