Enthusiastic : International Journal of Applied Statistics and Data Science
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
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<![CDATA[Research on Decision-Making Strategies of Regional Geography Teaching in High School Based on Data-Driven ]]>
<![CDATA[Yuan, Rui]]>;
<![CDATA[Gao, Yaqi]]>;
<![CDATA[Li, Jiansheng]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art4
<![CDATA[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.]]>
<![CDATA[Prediction of PM2.5 in DKI Jakarta Using Ordinary Kriging Method ]]>
<![CDATA[Salsabilla, Shafira]]>;
<![CDATA[Fitri Syaharani, Amadea]]>;
<![CDATA[Chamidah, Nur]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art5
<![CDATA[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.]]>
<![CDATA[Forecasting Population Mortality Rates Using Generalized Lee-Carter Model ]]>
<![CDATA[Yudi Hartawan , I Gusti Nyoman]]>;
<![CDATA[Pujawan, I Gusti Ngurah]]>;
<![CDATA[Mardika Pranata, Kadek]]>;
<![CDATA[Jayanta, Kadek]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art2
<![CDATA[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.]]>
<![CDATA[Causality Effect Among ASEAN-5 Stock Markets in COVID-19 Pandemic: VAR Model Approach ]]>
<![CDATA[Fatah, Bintang Izzatul]]>;
<![CDATA[Jody, Jody]]>; Budiasih, Budiasih
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art3
<![CDATA[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.]]>
<![CDATA[Key Agreement Scheme Based on Smart Cards ]]>
<![CDATA[Ekal, Graygorry Brayone]]>;
<![CDATA[Shahril Ismail, Eddie]]>;
<![CDATA[Farhan bin Sabdin, Abdul Rahman]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art1
<![CDATA[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.]]>
<![CDATA[Predict Farmer Exchange Rate in the Food Crop Sector Using Principal Component Regression ]]>
<![CDATA[Effendi, Melody]]>;
<![CDATA[Ardhyatirta, Ricardo]]>;
<![CDATA[Angelina, Sheila Gracia]]>;
<![CDATA[Ohyver, Margaretha]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art7
<![CDATA[Farmer Exchange Rate (FER) in Indonesia is very concerning. According to BPS data, there are various regions that experience increases and decreases every year. The goal of this paper is to predict Farmer Exchange Rate in the food crop sector using Principal Component Regression (PCR) since there is multicollinearity in the data. Therefore, with the PCR method using data based on 33 different provinces in Indonesia can determine the Farmer Exchange Rate with supporting factors. The model used can help farmers to be able to improve the welfare and economic growth of Indonesia as it depends on farmers. Further analysis found that the Harvest Area, production, and Human Development Index had an effect on farmer exchange rate. By using this model, it is expected that farmers in Indonesia have an increasing level of welfare and solve multicollinearity problem.]]>
<![CDATA[Marketability Study of Mathematical Sciences Students in Universiti Kebangsaan Malaysia (UKM) ]]>
<![CDATA[Lim Chui Ting]]>;
<![CDATA[Ong Wen Xuan]]>;
<![CDATA[Muhammad Aris Fadzilah, Nurulain Nabilah Binti]]>;
<![CDATA[Nora Binti Muda]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art9
<![CDATA[Higher Education Institute (HEI) has a vital role in developing human capital of a country. Measuring the quality of teaching and learning system in HEI and also industry’s satisfaction level is important to ensure the marketability of HEI graduates. This study examined Universiti Kebangsaan Malaysia (UKM) Mathematical Sciences students’ marketability by determining industry’s satisfaction level on students’ skills and abilities during industrial training and identifies factors that affect students’ marketability. There were 22 student attributes that were categorized into four factors. Mean scores and Relative Importance Analysis determined the satisfaction and importance level of each attribute studied respectively. Besides, Penalty-Reward Contrast Analysis (PRCA) showed that affective factor was categorized as a basic factor where its existence did not increase but its absence decreased the industry’s satisfaction level. For Importance Performance Analysis (IPA), cognitive, affective, and cognitive & psychomotor factors were observed in the first quadrant which had high importance level but low performance level. Lastly, all four factors were found in the loyal customer zone and at an excellent level through Customer Satisfaction Index (CSI) analysis. In conclusion, UKM Mathematical Sciences students have high marketability in general, but preservation and improvement should be implemented on important attributes to enhance their marketability.]]>
<![CDATA[Feasibility Analysis of Smart Wheelchairs Based on Voice Recognition for People with Disability ]]>
<![CDATA[Fathanah Muntasir, Nurul]]>;
<![CDATA[Muhammad Risafli Raif]]>;
<![CDATA[Rahmat Hermawan]]>;
<![CDATA[Muh. Anshar]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art8
<![CDATA[Technological developments have accelerated the advancement of assistive technology, hence increasing human life feasibility. One of which is smart wheelchairs with a voice recognition to facilitate people with disability. However, from various smart wheelchair developments, there have been no detailed test results related to the efficiency analysis, the feasibility of the voice recognition feature on the smart wheelchair, and the satisfaction of users in using it. In this study, observations were conducted using a simple regression method, and test user satisfaction using the USE questionnaire. Based on calculation results, the learnability score was 78.81%, indicating that the wheelchair was easy to understand. The efficiency score was 85%, meaning that users found it easy to carry out their daily activities. The memorability score was 85%, indicating that it was easy to remember. The error score was 77.38%, meaning that smart wheelchairs were easy to use. The satisfaction score was 88.57%, meaning that the users felt very comfortable. The conclusion is users are satisfied with smart wheelchairs using voice recognition, meaning that it provides feasible use for a variety of people with disability. The results can be used as a foundation in continuing the development of technological features in smart wheelchairs.]]>
<![CDATA[Exploring Daily Activity Pattern Using Spatio-Temporal Statistics with R for Predicting Trip Production ]]>
<![CDATA[Willdan, Muhamad]]>;
<![CDATA[Ramadhan, Raihan Iqbal]]>;
<![CDATA[Kresnanto, Nindyo Cahyo]]>;
<![CDATA[Putri, Wika Harisa]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art6
<![CDATA[Spatio-temporal data modelling is one of the methods in data analysis that uses space (spatial) and time (temporal) approaches. This study used Spatio-temporal statistical modelling to observe the daily activity patterns of people. Spatio-temporal modelling selected for support activity-based transportation demand. This research identifies community mobility patterns that will provide trip production data for transportation demand prediction. Using Spatio-temporal statistical modelling benefit this study because statistical this model can make model components in a physical system appearing to be random. Even if they are not, the models are helpful as they have accurate and precise predictions. In this study, descriptive analysis was used. Incorporating statistical distributions into the model is a natural way to solve the problem. This research collects daily activity data from 400 respondents recorded every 15 minutes. From this data, a pattern of respondents’ daily activities was formed, which was analyzed using R. Software R also visualizes data on daily activities of the community in Spatio-temporal modelling. This research aims to depict the daily activity patterns to predict trip production. This research found three clusters of trip production patterns with specific groups member and specific patterns between workdays and holidays.]]>
<![CDATA[MSME Sales Clustering Based on Business Aid Distribution Priority Using K-Affinity Propagation ]]>
<![CDATA[Tarisya Qurrota A'yuni]]>;
<![CDATA[Baiq Nina Febriati]]>;
<![CDATA[Lazuardy Ilham Effendie]]>;
<![CDATA[Muhammad Muhajir]]>;
<![CDATA[Yotenka , Rahmadi]]>
<![CDATA[ Enthusiastic : International Journal of Applied Statistics and Data Science Volume 3 Issue 1, April 2023 ]]>
Publisher : <![CDATA[Universitas Islam Indonesia ]]>
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DOI: 10.20885/enthusiastic.vol3.iss1.art10
<![CDATA[In rural areas of Indonesia, micro, small, and medium enterprises (MSMEs) are often isolated; however, they have been proven to play an important role as the economic backbone of millions of communities. In fact, the sluggish development of MSMEs in Indonesia become a severe problem for the community welfare. The government continues to strive for the welfare of the local communities, one of which is by supporting the existing MSMEs. However, the provision of government assistance may not be optimal for the incorrect target of the MSMEs. This study informs the government and other related parties regarding subdistrict groups whose MSMEs are considered to be their target. The k-affinity propagation method was used to find a set of representative examples, called exemplars, that best summarize the data. The result shows that sub-districts clusters based on general welfare in five commodities. K-affinity propagation algorithm clusters vary by commodity. Data fluctuation from each commodity’s three factors causes this. From this research, it can be determined which subdistricts have the most or least prosperous MSMEs in each of the five commodities analyzed.]]>
