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All Journal Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Infolitika Journal of Data Science Grimsa Journal of Business and Economics Studies
Khairul, Mhd
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Public Health Social Sciences

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Decision Tree versus k-NN: A Performance Comparison for Air Quality Classification in Indonesia Sasmita, Novi Reandy; Ramadeska, Siti; Kesuma, Zurnila Marli; Noviandy, Teuku Rizky; Maulana, Aga; Khairul, Mhd; Suhendra, Rivansyah
Infolitika Journal of Data Science Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i1.179

Abstract

Air quality can affect human health, the environment, and the sustainability of ecosystems, so efforts are needed to monitor and control air quality. The Plume Air Quality Index (PAQI) is one of the indices to measure and determine the level of air quality. In measuring the accuracy of the air quality level, it is necessary to do the right classification. Some previous studies have conducted classification analysis using the decision tree and K-Nearest Neighbor (k-NN) methods, but only evaluated using accuracy values. Therefore, this study uses both methods to evaluate the results of air quality level classification not only with accuracy but also with precision, recall, and F1-score. Secondary data of pollutant concentration values and PAQI categories based on particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) derived from Plume Labs for 33 provincial capitals in Indonesia in the time period from July 1 to December 31, 2022, were used in this study. From the results of comparing the performance of the two methods, it is found that the decision tree has a greater performance value than the performance value of k-NN. The decision tree performance values for accuracy, precision, recall and F1-score are 90.67%, 90.61%, 90.67%, and 90.63%, respectively. So, it can be concluded that the decision tree performs better than k-NN in classifying PAQI categories with better overall evaluation metric values.
Relative Risk and Distribution Assessment of Tuberculosis Cases: A Time-Series Ecological Study in Aceh, Indonesia Sasmita, Novi Reandy; Khairul, Mhd; Fikri, Mumtaz Kemal; Rahayu, Latifa; Kesuma, Zurnila Marli; Mardalena, Selvi; Kruba, Rumaisa; Chongsuvivatwong, Virasakdi; Asshiddiqi, M. Ischaq Nabil
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 8 No. 6: JUNE 2025 - Media Publikasi Promosi Kesehatan Indonesia (MPPKI)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v8i6.7264

Abstract

Introduction: Tuberculosis (TB) remains a critical public health issue, particularly in high-incidence regions like Aceh Province, Indonesia. This study aimed to estimate the Relative Risk (RR) and analyze significant differences in the temporal distribution of TB cases across Aceh Province. Methods: A time-series ecological study was conducted using TB case and population data from 23 districts/cities in Aceh Province between 2016 and 2022. Data were analyzed using R software, applying descriptive and inferential statistics. The Standardized Morbidity Ratio (SMR) method estimates RR and is categorized into five risk levels. The Kolmogorov-Smirnov test assessed data normality, guiding the selection of statistical tests. The Friedman and Wilcoxon Signed-Rank tests examined differences in TB case distribution trends. Results: Significant spatial and temporal variations in TB risk were identified. Districts such as Banda Aceh (RR = 2.29–2.13) and Lhokseumawe (RR = 1.89–2.21) consistently demonstrated high RR from 2016 to 2022, reflecting persistent TB transmission. A general upward trend in TB cases was observed across districts, with significant spatial variation (p < 0.001), highlighting a worsening TB burden. Conclusions: The study emphasizes the urgent need for targeted public health interventions tailored to TB's unique spatial and temporal dynamics in Aceh Province, Indonesia. Applying SMR and robust statistical analyses provides valuable insights to inform localized TB control policies and strengthen management strategies in high-burden areas.
Statistical Assessment of Human Development Index Variations and Their Correlates: A Case Study of Aceh Province, Indonesia Sasmita, Novi Reandy; Phonna, Rahmatil Adha; Fikri, Mumtaz Kemal; Khairul, Mhd; Apriliansyah, Feby; Idroes, Ghalieb Mutig; Puspitasari, Ayu; Saputra, Fachri Eka
Grimsa Journal of Business and Economics Studies Vol. 1 No. 1 (2024): January 2024
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjbes.v1i1.14

Abstract

The Human Development Index (HDI) provides a holistic measure of human development in a country or locality. This study aims to identify factors correlated with changes in the Human Development Index and analyze changes in the distribution of the Human Development Index in Aceh Province from 2012 to 2022. Apart from the Human Development Index as the variable used in this study, five variables are used in this study as indicators: Life Expectancy, Gross Regional Domestic Product (GRDP), Per Capita Expenditure, Average Years of Schooling, and Expected Years of Schooling as socioeconomic factors. This research uses an ecological study design. Data was sourced from the "Aceh in Figures" report by the Central Bureau of Statistics of Aceh Province. The statistical methods used were descriptive statistics, the Shapiro-Wilk test for normality, the Spearman test for correlation analysis, the Wilcoxon one-sample test for data distribution, and the Kruskal-Wallis test to compare distributions. Based on the correlation analysis, the study revealed that the five socioeconomic variables tested showed a significant positive correlation with changes in the HDI in Aceh Province (p-value < 0.05). In addition, the difference analysis showed a significantly different distribution of HDI across the years studied (p-value < 0.05), with a pattern of increasing HDI observed from the beginning to the end of the study period. The recommended based on finding of the study is policymakers and stakeholders focus on strategies that enhance the positive correlates identified Finally, these results provide important and structured insights into the role of factors in HDI change.
Co-Authors Apriliansyah, Feby Asshiddiqi, M. Ischaq Nabil Ayu Puspitasari, Ayu Chongsuvivatwong, Virasakdi Fikri, Mumtaz Kemal Idroes, Ghalieb Mutig Kruba, Rumaisa Mardalena, Selvi Maulana, Aga Phonna, Rahmatil Adha Rahayu, Latifa Ramadeska, Siti Saputra, Fachri Eka Sasmita, Novi Reandy Suhendra, Rivansyah Teuku Rizky Noviandy Zurnila Marli Kesuma