Jurnal Varian

Application of Mamdani’s Fuzzy Inference System in the Diagnosis of Pre-eclampsia

Tue, 31 Oct 2023 00:00:00 +0800

Pre-eclampsia is the second of the top three causes of death in pregnant women after bleeding and followed by infection. By knowing the risk factors, early detection of pre-eclampsia in pregnant women
needs to be done so that later it can be treated more quickly to prevent further complications. This study
aims to design a practical application of a decision-making system for the diagnosis of pre-eclampsia in
pregnant women using the Fuzzy Inference System (FIS) method so it can be used efficiently and effectively for the early diagnosis of pre-eclampsia. The method used in data analysis is the FIS Mamdani
method with defuzzification using the centroid method. The designed system considers blood pressure
and proteinuria as input variables and pre-eclampsia status as output variables. The research results
show that the system has 7.27% of Mean Absolute Percentage Error (MAPE) value and when comparing the final diagnosis of the system and expert diagnoses (doctors) from 20 patients at two hospitals, it
was found that the system diagnosis was 100% in accordance with the expert diagnoses.

Improved Chi Square Automatic Interaction Detection on Students Discontinuation to Secondary School

Fadhil Al Anshory, Siswanto Siswanto, Sri Astuti Thamrin, Ika Inayah — Tue, 31 Oct 2023 00:00:00 +0800

Improved Chi Square Automatic Interaction Detection (CHAID) with bias correction is the development
of the CHAID method by relying on Tschuprow’s T test calculations with bias correction in the process
of forming a classification tree. This study aims to obtain a classification of factors which influence
students for not continuing their education from junior high school or equivalent to high school or
equivalent. The results obtained in the classification tree produce nine classifications. Based on the
results of the classification tree, the classification of students who do not continue their education to
high school or equivalent is: students with disabilities who do not have access to Information and
Communication Technology (ICTs) (0.89); students who work without disability but do not have access
to ICTs (0.73); and students who do not work without disability but do not have access to in ICTs
(0.60). Based on the classification obtained the factors which influence students for not continuing
their education to high school or equivalent are access to ICTs, employment status, and persons with
disabilities. The classification accuracy of the results uses the Improved-CHAID method with bias
correction with a proportion of 80% training data and 20% testing data, namely 72.3033% on training
data and an increase of 73.3300% on testing data.

Modeling The Influenced Factors of Remaining Operation Results Using Multiple Linear Regression

Widiya Astuti Alam Sur, Ines Saraswati Machfiroh, Ricky Iskandar — Tue, 31 Oct 2023 00:00:00 +0800

The amount of Remaining Operation Results (ROR) obtained by Koperasi can reflect the health of
its financial management. Many economic factors can affect the ROR of Koperasi itself. This study
aims to determine the economic factors that significantly influence ROR based on a statistical model of
multiple linear regression. The novelty of this research provides new analytical results that compare the
most three influential factors based on previous research to show the factors significantly influencing
the ROR. The quantitative data used the five years financial statements of Koperasi Sawit Makmur in
2017-2021 consists of 20 data on liabilities, net worth, assets, and ROR of Koperasi Sawit Makmur. The
results show that asset variable as an excluded variable that does not affect the ROR of Koperasi with
R
2 = 0, 961. Liabilities and net worth variables can explain 96.1% of ROR, with 3.9% can be explained
by assets and other variables not included in the study. Liabilities have a negative and tangible effect,
and net worth has a positive and partially real influence on ROR. The factor with the most dominant
influence on ROR is net worth, with an influence percentage of 63,80%. The future research is expected
to provide an overview of net worth and asset determinants using related statistical methods.

Application of Artificial Neural Network in Predicting Direct Economic Losses Due to Earthquake

Ulil Azmi, Soehardjoepri Soehardjoepri, Rudi Prihandoko, Iqra Asif — Tue, 31 Oct 2023 00:00:00 +0800

Accurately predicting the direct economic losses caused by earthquakes is important for policy makers for disaster budgets. Before a disaster strikes, it is important to consider the public policy costs
associated with disaster relief and recovery. The aim of this study is to provide a risk assessment approach, which can benefit all parties involved. Artificial neural networks are widely used for time series
forecasting, especially financial forecasting. Therefore, this study proposes a cutting-edge forecasting
method such as backpropagation neural network (BPNN) and other prediction methods: neural network
autoregressive (NNAR) and ARIMA-GARCH to obtain the best prediction results. This paper applies
interpolation data to increase the amount of data used. Two interpolations were applied to amplify the
original small sample with virtual points, namely cubic splines and further piecewise interpolation using. The results of this study are the cubic spline interpolation is the most effective way to solve the
small sampling problem to predict direct economic losses due to the Indonesian earthquake and the
BPNN method outperforms other traditional methods with an RMSE of 0.024 in the training period and
0.174 in the testing period, significantly lower than other methods. The results of this research can be
used as reference material for the government in estimating the level of earthquake losses and can be
used to develop risk reduction strategies

The Role of Time Management on Behavior and Perception with Qualitative Descriptive

Suci Pertiwi, Sophya Hadini Marpaung, Joosten Joosten — Tue, 31 Oct 2023 00:00:00 +0800

Problems that occur at Mikroskil University student organizations include obstacles from the administrative side, such as delays in submitting proposals and reporting activities which result in delays/especially delays in the funding process, to issues of morality and management of each student
organization as well as time management itself. This research aims to determine and analyze the condition of Mikroskil University student organizations in running student organizations so that student
perceptions and behavior can be known, and this is the novelty of this research. This research used a
qualitative descriptive survey method with a purposive sampling technique involving core administrators and active members of divisions within Mikroskil University as samples. The results of the partial
test (t-test) show that the time management variable has a positive effect on student behavior and perceptions at the Mikroskil University Student Organization. The Adjusted R
2
value of the time management
variable on student behavior was obtained at 44.8%, while the time management variable on behavior
towards student perceptions was 32.8% and the remaining 55.2% and 67.2% were influenced by other
variables not examined in this research. The research results show that time management partially has
a positive and significant effect on behavior and perceptions

Determinants of Under-five Mortality Due to Pneumonia: A Negative Binomial Regression Analysis

Dhea Prawidia, Lidya Zhafirah, Nurzikri Saputra, Fitri Kartiasih, Uma Sahu — Tue, 31 Oct 2023 00:00:00 +0800

Pneumonia is one of the main causes of under-five mortality in Indonesia. In under-fives, pneumonia
is the number one killer in the world. Meanwhile, in Indonesia, it ranks second after diarrhea. On
average, the disease affects half a million children a year. This study aims to identify and analyze the
risk of variables that affect the number of under-five mortality due to pneumonia in Indonesia in 2021.
The novelty of this research focuses on the macro variables used, making it easier for policy makers to
make decisions. The research method used is negative binomial regression. The results showed that the
highest number of under-five mortality due to pneumonia was in Central Java Province. Meanwhile, the
lowest was in Jambi Province, South Sumatra, Riau Islands, DKI Jakarta, North Kalimantan, Southeast
Sulawesi, and Papua. The per capita income significantly reduces the number of under-five mortality
due to pneumonia, while the number of under-fives with severe pneumonia significantly reduces the
number of under-five mortality due to pneumonia in Indonesia. The government needs attention to
reduce the death rate of children under five due to pneumonia by providing social protection in the
fields of health and education for underprivileged communities.

Finding the Best Model in Nonlinear Regression: Using the Coefficient of Determination

Vitri Aprilla Handayani, Widya Reza, Saba Mehmood — Tue, 31 Oct 2023 00:00:00 +0800

In Indonesia, inflation plays a significant role in shaping economic growth. Therefore, it is essential to
examine the impact of inflation on economic growth through a comprehensive analysis. This analysis
aims to identify the factors influencing economic growth in Indonesia by utilizing nonlinear regression
analysis. The study focuses specifically on modeling economic growth in Batam City and its correlation with inflation. The primary goal is to identify the most effective nonlinear regression model that
accurately represents the relationship between economic growth and inflation, as determined by the coefficient of determination. The method used in this research is nonlinear regression methods provide
a more accurate and comprehensive analysis when dealing with complex relationships and can help
uncover valuable insights that may be missed by simpler linear models. The results of the analysis
finding the model that is suitable for modeling inflation on economic growth is a quadratic model with
a coefficient of determination of 73.4%. The research has found that the best model for explaining the
impact of inflation on economic growth is the Quadratic model with an R-value of 0.734 or 75%. These
results indicate that the Quadratic model can account for 75% of the influence of inflation on economic
growth.

Survival Analysis with Cox Proportional Hazard Model for Tuberculosis (TBC) Patients

Zahratun Nisa, Bobby Poerwanto, Muhammad Fahmuddin S — Tue, 31 Oct 2023 00:00:00 +0800

Survival analysis is a method in statistics which aims to analyze the relationship between time from the
beginning of observation until the occurrence of an event (response variable) with factors that have an
influence on the event (predictor variables). To determine the relationship between the response variable
and the predictor variable, where the response variable is the time until the event occurs, one method that
can be used is the cox proportional hazard regression method. The data used in this research is data on
hospitalizations of tuberculosis sufferers at Haji Makassar Hospital in 2022 because it has characteristics
that are in accordance with the aim of survival analysis, namely to determine the relationship between
the life span of TBC patients and the factors that influence TBC disease. The results of the analysis
obtained factors that significantly influence the recovery rate of patients with TBC are shortness of
breath and smoking habits. The shortness of breath variable has an influence on the recovery rate
of TBC patients, namely 0,3506, which means that TBC patients who do not experiencing shortness
of breath has a recovery rate of 0.3506 times the likelihood of recovery compared to patients who
experience shortness of breath. Variable smoking habit was 0.7367, which means that patients with
TBC did not smoking habit has a recovery rate of 0.7367 times recovered compared to patients who had
a smoking habit

Gold Price Fluctuation Forecasting Based on Newton and Lagrange Polynomial Interpolation

Andika Ellena Saufika Hakim Maharani, Dea Alvionita Azka, Darlena Darlena — Tue, 31 Oct 2023 00:00:00 +0800

Gold is a highly valuable commodity and an investment opportunity for many people. However, there
are often significant fluctuations in gold prices that affect investment decisions. Various mathematical
forecasting methods have been developed to anticipate gold price fluctuations. This study uses historical
daily data of gold prices during January-May 2023. The method used in this study is the Newton and
Lagrange polynomial interpolation method with several orders to analyze data and forecast gold price
fluctuations. The purpose of this study is to compare the performance and accuracy of the order levels of
the Newton and Lagrange polynomial interpolation forecasting models. In this study, the test data points
and orders are selected so that a range is formed that matches the amount of data available. The test
orders used in this study include orders 2, 3, 5, 6, and 10. This study found that the 2
nd order polynomial
interpolation method is more effective and accurate in forecasting gold price fluctuations compared to
the higher orders tested. This is indicated by the results of the calculation of MAE, RMSE, and MAPE
values in 2
nd order polynomial interpolation which are smaller than in 3
rd
, 5
th
, 6
th, and 10th order
polynomial interpolation. This suggests that a polynomial of 2
nd order has been able to model and
forecast gold price fluctuations well. However, it is important to remember that these conclusions are
based on the data and methods used in this study. Variability in forecasting results can occur depending
on the quality of the data, the time period used, and the interpolation method applied, among others.
Therefore, further research and wider testing needs to be conducted to validate these conclusions.

Comparison K-Means and Fuzzy C-Means In Regencies/Cities Grouping Based on Educational Indicators

Gerald Claudio Messakh, Memi Nor Hayati, Sifriyani Sifriyani — Tue, 31 Oct 2023 00:00:00 +0800

Cluster analysis is an analysis that aims to classify data based on the similarity of specific characteristics.
The methods used in this research are K-Means and Fuzzy C-Means (FCM). K-Means is a partitionbased non-hierarchical data grouping method. FCM is a clustering technique in which the existence
of each data is determined by the degree of membership. The purpose of this study is to classify
regencies/cities in Kalimantan based on education indicators in 2021 using K-Means and FCM and find
out which method is better to use between K-Means and FCM based on the standard deviation ratio so
it can be used efficiently and effectively for decision making by the government to advance the level
of education on the island of Kalimantan. Based on the results of the analysis, it’s concluded that KMeans is the better method with the ratio of the standard deviation within a cluster against the standard
deviation between clusters of 0.6052 which produces optimal clusters of 2 clusters, namely the first
cluster consisting of 14 Regencies/Cities, while the second cluster consists of 42 Regencies/Cities in
Kalimantan.