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INDONESIA
Enthusiastic : International Journal of Applied Statistics and Data Science
Published by Universitas Islam Indonesia
ISSN : 2798253X     EISSN : 27983153     DOI : 10.20885
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics
ENTHUSIASTIC is an international journal published by the Statistics Department, Faculty of Mathematics and Natural Sciences, Universitas Islam Indonesia. ENTHUSIASTIC publishes original research articles or review articles on all aspects of the statistics and data science field which should be written in English. ENTHUSIASTIC has the vision to become a reputable journal and publish good quality papers. We aim to provide lecturers, researchers both academic and industry, and students worldwide with unlimited access to be published in our journal. Specifically, these scopes of the ENTHUSIASTIC journal are: 1. Statistical Disaster Management 2. Actuarial Science 3. Data Science 4. Statistics of Social and Business 5. Statistics of Industry
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 73 Documents
 1   2   3   4   5 
Multiple Correspondence Analysis towards the Change of Income and Sociodemographic of Citizens due to COVID-19 Pandemic in Malaysia Ong Wen Xuan; Lim Chui Ting; Nurulain Nabilah Binti Muhammad Aris Fadzilah; Nora Binti Muda
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 2, October 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss2.art5

Abstract

This paper intends to observe the economic impact and spending patterns of citizens when the spread of coronavirus occurred uncontrollably in Malaysia. The data used in this paper is the result of a first-round Special Survey ‘Effect of COVID-19 on Economy and Individual’ conducted by the Department of Statistics Malaysia. Based on the paired-t test, all the aspects tested are found to have significant differences before and during the pandemic. This is likely because citizens comply with the rules set during Movement Control Order. Next, the Chi-square test between the changes in citizens’ monthly income and sociodemographic factors are significantly associated. Therefore, factors state, gender, ethnicity, and age group of citizens are used in further analysis of multiple correspondence (MCA) to study the relationship between several categorical variables. Hence, citizens of age group 35­–44 years old from Central region and Chinese citizens have no changes in their income before and during the pandemic. Citizens of age group 15–34 years old and Northern region have both increment or reduction income whereas men citizens received lower-income payments. Indian women and citizens from Eastern region tend to not work during the pandemic. This study can be a guide to the government in overcoming social problems. 
Portfolio Analysis Using Malaysia Stock Market Data: Before and During COVID-19 Pandemic Khah May, She; Wei Yeing, Pan
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 2, October 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss2.art4

Abstract

This study attempts to evaluate Malaysia’s stock performance before and during COVID-19 across all sectors by using the Sharpe ratio and Sortino ratio with risk measured by standard deviation. We develop an algorithm for stock selection to construct the portfolio investment. In our study, we apply the Sharpe ratio, Treynor ratio and Jensen’s alpha to identify the optimal portfolio. The result shows that the portfolio with stock selection based on the Top 20 Sortino ratio from all stocks is superior to stock selection based on the Top 3 Sortino ratio for each sector. The daily adjusted closing stock prices are collected from March 1, 2019 to December 31, 2021. The result of this study indicates that several sectors are not affected during the COVID-19 pandemic, which are Technology, Industrial, Consumer Products and Services and Property. Hence, investors are suggested to form an optimal portfolio investment based on these sectors. Stock analysts are recommended to imply various risk-adjusted measures to evaluate the portfolio performance with a comprehensive perspective to support the outcome analysis.
AI-Based Personalized Virtual Therapist for Alcohol Relapse Win, Myat Noe; Han, Lim Whei; Samson Chandresh Kumar, Eric Kamalesh Kumar; Keat, Tan Yong; Ravana, Sri Devi
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 2, October 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss2.art3

Abstract

Binge drinking is one type of harmful alcohol use that has a variety of negative health impacts in both the drinker and others, either globally or in Malaysia. According to previous research, one in two current drinkers in Malaysia who are 13 years and older reported having engaged in binge drinking. Therefore, increased attention should be given to understand the drinking pattern of an individual and propose a solution that can help with addiction relapse. Thus, this study identified interventions that could assist alcohol relapse recovery and proposed a new generation of relapse prevention solution based on artificial intelligence (AI). By using a deep learning approach and machine learning based recommendation technique, it predicts the relapse rate of users, providing recovery consultation based on the user’s data and clinical data through a chatbot. This study involved helpful data collection, advanced data modeling, prediction analysis to support the alcohol relapse recovery journey. Hence, the proposed AI solution acted as a personalized virtual therapist to help the addicts stay sober. The objective is to present the design and realization of the AI based solution for sober journey. The proposed solution was tested with pilot study and significant benefits of virtual therapists for alcohol addiction relapse is reported in this paper.
Modeling the Rural Banks’ Survival in Semarang City and Regency during the COVID-19 Pandemic Naufal, Cesario Hanif; Putri, Santi Maudila; Ekaria
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 2, October 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss2.art7

Abstract

The COVID-19 pandemic has a significant impact on all sectors including the financial sector. Rural banks are one of the financial institutions that has been affected by the pandemic. The pandemic makes debtors unable to repay the loans that can lead to the increase of non-performing loans. This increase will affect the performance of the rural banks which can lead to the liquidation of rural banks. This is reflected by the decrease in the number of rural banks in Indonesia in 2018–2020 periods. On the other hand, it turns out that rural banks in Semarang City and Regency were not affected by the pandemic. Those rural banks are relatively able to survive, which is reflected by the stable level of the bank’s health. Therefore, this study aims to determine factors that affect the survival status of rural banks in Semarang whether they survive or not during the COVID-19 pandemic. To achieve this goal, binary logistic regression was used in this study. The results show that firm size, income growth, and debtors’ quality have a significant effect on the survival status of rural banks in Semarang City and Regency during the COVID-19 pandemic.
Optimal Classification of Emotions from Electroencephalography (EEG) Signals M.P., Mahima; Reddy, Meghana; C., Rachita; Hegde, Rajeshwari
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 2 Issue 2, October 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol2.iss2.art6

Abstract

It is incredibly challenging to build an intelligent algorithm for emotion recognition that can deliver high accuracy because electroencephalography (EEG) signals are not stationary, nonlinear, and noisy. First, decomposing the preprocessed EEG signals of the SEED dataset into five frequency bands: delta, theta, alpha, beta, and gamma, and then calculated their energy and entropy from the extracted features. Then Principal Component Analysis (PCA) method for feature reduction was performed.  It is important to note that different types of wavelets transform (db6, db5, etc.) were tested, and hyperparameter tuning of classification models was done to obtain optimal accuracy. The next step is classifying the emotions into three states:  -1(negative), 0(neutral), and +1(positive), and tested the dataset on two types of classification models, namely Random Forest and Support vector machine (SVM). SVM gives better performance compared to Random Forest with an accuracy of 80.74%.
Research on Decision-Making Strategies of Regional Geography Teaching in High School Based on Data-Driven Yuan, Rui; Gao, Yaqi; Li, Jiansheng
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art4

Abstract

With the development of big data technology, it has become a trend to analyze students’ behavioral data to promote teachers’ precision teaching. In this context, this study cooperates with a senior high school geography teacher in Changsha City, Hunan Province, collects the students’ examination data from 2020 to 2021 academic year with the help of Zhixue.com, divides the students into four groups according to the examination results, and takes regional geography knowledge as an example to analyze the weak knowledge points, discipline core literacy and practical application ability of students at all levels. Based on the analysis results, the improvement strategies of teachers’ subsequent precision teaching were proposed, including students’ stratification should be carried out according to daily performance and examination results; The weak knowledge points of students of different grades overlap and differ, so teachers should carry out targeted teaching for students of different grades. At the same time, the multi-level teaching method should be improved to enhance students’ discipline core literacy. Pay attention to contact life reality, enhance students’ practical application ability.
Prediction of PM2.5 in DKI Jakarta Using Ordinary Kriging Method Salsabilla, Shafira; Fitri Syaharani, Amadea; Chamidah, Nur
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art5

Abstract

Air pollution is a serious matter that must be addressed promptly and quickly. One of the most dangerous pollutants in the air is PM2.5. This pollutant is particulates dust measuring 2.5 micrometers. PM2.5 can cause environmental and health problems such as acute respiratory infections, lung cancer, cardiovascular cancer, and premature death. Air pollution occurs in big cities such as the capital city of Indonesia, DKI Jakarta, which is the city with the highest PM2.5 levels in Indonesia. There are 6 six stations in DKI Jakarta that measure PM.2.5 level at 6 areas. The ordinary kriging is one of spatial methods  that can be used to predict PM2.5 level in outside the existing stations, for example in the Pulogadung industrial area. This area was selected because there are many factories in this area that can increase levels of PM2.5 in the air. To predict the concentration of PM2.5 in one area could be done by calculating the surrounding PM2.5 concentrations that were not available to measure air quality. In study, we use mean an absolute percentage error ( MAPE ) value to evaluate Ordinary Kriging performance for predicting PM2.5 level in DKI Jakarta.
Forecasting Population Mortality Rates Using Generalized Lee-Carter Model Yudi Hartawan , I Gusti Nyoman; Pujawan, I Gusti Ngurah; Mardika Pranata, Kadek; Jayanta, Kadek
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art2

Abstract

The demographic process cannot be inseparable from the mortality rate. The appropriate models for forecasting mortality rates are essential in assisting governments, companies, and other agencies in formulating policies or making decisions. As one of the countries with the highest death rate, Japan is influenced by several factors. This research uses the Generalized Lee-Carter Model), which is one of the developments of the Lee-Carter (LC) model. The Lee-Carter model was prevalent by Lee and Carter (1995) as an alternative that is suspected to predict the mortality rate of an area. The first step in this research is to formulate the Generalized Lee-Carter function. Through the function formula, the estimator value of the Generalized Lee-Carter model will be searched in the second stage. And the third stage, through the Generalized Lee-Carter model, will find the RMSE value and then use it in the fourth stage, namely forecasting the future period using ARIMA. The data in this study is facilitated through www.mortality.org, which is one of the Japanese population data. The result of the study showed that the RMSE value for females was 0.01670 and 0.016292 for males. So, it concluded that the Generalized Lee-Carter Model is great for forecasting mortality rates.
Causality Effect Among ASEAN-5 Stock Markets in COVID-19 Pandemic: VAR Model Approach Fatah, Bintang Izzatul; Jody, Jody; Budiasih, Budiasih
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art3

Abstract

Financial globalization increase integration degree of capital flow. However, the global shock could impact many countries, either positive and negative. COVID-19 pandemic is one of the shock that affect world including ASEAN-5. This paper apply the Vector Autoregressive (VAR) model to identify the linkage among ASEAN-5 stock markets during the COVID-19 pandemic and it is used because of no spesific theory behind it. The data used in this paper is the weekly return of the composite index of ASEAN-5 stock markets from 11 March 2020 to 29 December 2021. This paper finds that there is a linkage among ASEAN-5 stock markets indicated by decreasing price index consecutive. Therefore, the implication of this paper is that the investors have to switch the investment instrument from stock to other instrument carefully. Once the negative impact begins to taper off, investors could do international stock investment.
Key Agreement Scheme Based on Smart Cards Ekal, Graygorry Brayone; Shahril Ismail, Eddie; Farhan bin Sabdin, Abdul Rahman
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol3.iss1.art1

Abstract

An efficient roaming service over wireless networks is essential for mobile users. It allows mobile users to seamlessly access the services provided by the home agent without losing connectivity when they visit a foreign network. This handover communication happens with the help of a foreign agent. In most cases, the communication between the mobile user and the foreign agent occurs over an unsecured channel. Therefore, researchers have proposed various authentication schemes to protect data transmitted over this unsecured channel. Most of the proposed schemes are focused on key agreement schemes. However, the key agreement schemes researchers have submitted are primarily high in computational and communication costs. Therefore, this research proposed an authenticated key agreement scheme based on passwords and smart cards with lower computational and communication costs without compromising the scheme’s security. This criterion was achieved due to using lower-cost operations and functions in the scheme. Moreover, the scheme’s development is based on the result of analyzing and improving other schemes proposed by other researchers.

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