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Jurnal Varian
Published by Universitas Bumigora
ISSN : -     EISSN : 25812017     DOI : https://doi.org/10.30812/varian
Core Subject : Economy, Science, Education, Social,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Social Sciences Other
Jurnal Varian adalah salah satu Jurnal Ilmiah yang terdapat di Universitas Bumigora. Jurnal ini bertujuan untuk memberikan wadah atau sarana publikasi bagi para dosen, peneliti dan praktisi baik di lingkungan internal maupun eksternal Universitas Bumigora Mataram. Jurnal ini terbit 2 (dua) kali dalam 1 tahun pada periode Genap (April) dan Ganjil (Oktober). Jurnal Varian fokus memuat publikasi pada Bidang Matematika dan Statistika.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 168 Documents
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Modeling The Influenced Factors of Remaining Operation Results Using Multiple Linear Regression Widiya Astuti Alam Sur; Ines Saraswati Machfiroh; Ricky Iskandar
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2635

Abstract

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 R2 = 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 Mamdani’s Fuzzy Inference System in the Diagnosis of Pre-eclampsia Grandianus Seda Mada; Maria Julieta Esperanca Naibili; Siprianus Septian Manek; Estevania Daonce Mau; Wasim Raza
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2764

Abstract

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.
Determinants of Under-five Mortality Due to Pneumonia: A Negative Binomial Regression Analysis Dhea Prawidia; Lidya Zhafirah; Nurzikri Saputra; Fitri Kartiasih; Uma Sahu
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2768

Abstract

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.
The Role of Time Management on Behavior and Perception with Qualitative Descriptive Suci Pertiwi; Sophya Hadini Marpaung; Joosten Joosten
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2795

Abstract

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 R2 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
Comparison K-Means and Fuzzy C-Means In Regencies/Cities Grouping Based on Educational Indicators Gerald Claudio Messakh; Memi Nor Hayati; Sifriyani Sifriyani
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2879

Abstract

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 partition-based 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 K-Means 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.
Survival Analysis with Cox Proportional Hazard Model for Tuberculosis (TBC) Patients Zahratun Nisa; Bobby Poerwanto; Muhammad Fahmuddin Sudding
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2994

Abstract

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
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.3230

Abstract

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 2nd 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 2nd order polynomial interpolation which are smaller than in 3rd, 5th, 6th, and 10th order polynomial interpolation. This suggests that a polynomial of 2nd 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.
Estimating and Forecasting Jakarta Composite Index in Pandemic Era Using ARIMA-GARCH Model Agus Sofian Eka Hidayat; Gilang Primajati
Jurnal Varian Vol 7 No 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.2103

Abstract

Many industries have suffered financial losses as a result of the COVID-19 epidemic. The stock market's movement has been impacted by this circumstance. Due to the influence of some people, a large number of individuals with limited trading knowledge are attempting to participate in the stock market. Market volatility should be understandable in order to gain profit instead of having losses. Therefore, it's essential to comprehend the market of the future through analysis of the data. The purpose of this study is to use ARIMA-GARCH to predict the Indonesian stock market price during. The period covered by the dataset is January 2020–December 2022. The training data indicates that ARIMA (2,1,2) is the best model for ARIMA. The results showed that data residual fitted by ARIMA (2,1,2)-GARCH (1,2) exhibits heteroscedasticity, according to the residual analysis. The MAPE score is 2%, which is relatively small. It means that ARIMA (2,1,2)-GARCH (1,2) is good enough for forecasting the Jakarta Composite Index.
Naive Bayes Algorithm with Feature Selection Using Particle Swarm Optimization Siswanto Siswanto; Iwan Kurniawan; Sri Astuti Thamrin
Jurnal Varian Vol 7 No 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.2409

Abstract

The COVID-19 vaccine in Indonesia has led to the emergence of public opinion which is conveyed on social media such as Twitter. One of the analyses that can be done to produce various information from public opinion is sentiment analysis. Sentiment analysis is used to determine whether an opinion tends to be positive or negative. This study aims to classify the public opinion of the COVID-19 vaccine in Indonesia with sentiment analysis and to visualize the location of the sentiment of the COVID-19 vaccine tweet data in Indonesia. To achieve this aim, the Naïve Bayes algorithm with Particle Swarm Optimization (PSO) feature selection was used. This study uses opinions into positive and negative class sentiments towards 2,547 tweets related to the COVID-19 vaccine in Indonesia from January to June 2021. The results show that the distribution of positive and negative class sentiments is 2,328 and 219, respectively. In addition, the positive sentiment for the COVID-19 vaccine was dominated by people on the island of Java based on a random number matrix initialized by the PSO method. The classification of public opinion on Twitter media provides accurate and optimal performance results using a combination of the Naïve Bayes algorithm with PSO feature selection. The results of the combination of these methods have accuracy and F1 score values of 91.28% and 95.38%, respectively. The visualization of geo-spatial mapping showed that positive sentiments related to the COVID-19 vaccine exist in almost all regions in Indonesia but are dominated by the Jabodetabek area.
Natural Disaster Mapping on Java Island Using Biplot Analysis Pressylia Aluisina Putri Widyangga; M. Fariz Fadillah Mardianto; Firda Aulia Pratiwi; Andi Vania Ghalliyah Putrie; Putu Eka Andriani; Dita Amelia; Deshinta Arrova Dewi
Jurnal Varian Vol 7 No 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.2634

Abstract

Indonesia is located in the ring of fire region. This condition causes Indonesia to have the potential to experience various disasters, such as volcano eruptions. In addition, rapid population growth has led to rampant land conversions that cause floods, landslides, tornadoes, droughts, and forest fires. The research aims to map natural disasters in Indonesia, especially Java Island to find out the provinces and their natural disasters tendency using Biplot analysis. Based on the results, Central Java, East Java, and West Java have a tendency to have floods and landslides. East Java tends to undergo earthquakes and Central Java has the potential to experience volcano eruptions. Through the natural disasters mapping, the government, especially the BMKG, will be able to find various solutions to overcome the natural disasters that have great potential to occur in provinces in Indonesia, especially Java Island as the manifestation toward SDGs Target 2030.

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