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All Journal ComEngApp : Computer Engineering and Applications Journal SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Zaqqi Yamani
Universitas Sriwijaya
Computer Science & IT Education Engineering Social Sciences Other

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Author Matching Classification with Anomaly Detection Approach for Bibliomethric Repository Data Zaqqi Yamani; Siti Nurmaini; Dian Palupi Rini
Computer Engineering and Applications Journal Vol 9 No 2 (2020)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.294 KB) | DOI: 10.18495/comengapp.v9i2.335

Abstract

Authors name disambiguation (AND) is a complex problem in the process of identifying an author in a digital library (DL). The AND data classification process is very much determined by the grouping process and data processing techniques before entering the classifier algorithm. In general, the data pre-processing technique used is pairwise and similarity to do author matching. In a large enough data set scale, the pairwise technique used in this study is to do a combination of each attribute in the AND dataset and by defining a binary class for each author matching combination, where the unequal author is given a value of 0 and the same author is given a value of 1. The technique produces very high imbalance data where class 0 becomes 98.9% of the amount of data compared to 1.1% of class 1. The results bring up an analysis in which class 1 can be considered and processed as data anomaly of the whole data. Therefore, anomaly detection is the method chosen in this study using the Isolation Forest algorithm as its classifier. The results obtained are very satisfying in terms of accuracy which can reach 99.5%.
ANALYSIS OF DEMOGRAPHIC AND SOCIOECONOMIC FACTORS ON THE INCIDENCE OF DIABETES MELLITUS IN DKI JAKARTA USING LOGISTIC REGRESSION M. Ilham Fahlevi; Jackson Imanuel Manurung; Mohd Rizky Putra Pratama; M Naufal Hisyam; Allsela Meiriza; Ken Ditha Tania; Zaqqi Yamani
SOSIOEDUKASI Vol 15 No 1 (2026): SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan Universaitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/sosioedukasi.v15i1.7722

Abstract

Diabetes mellitus (DM) is a non-communicable disease with a significant global impact and an increasing incidence rate. Indonesia records one of the highest diabetes rates, particularly in the province of DKI Jakarta, which shows the highest national prevalence. This observational study with a cross-sectional design aims to evaluate the factors influencing the onset of DM in the Jakarta area using data from the 2023 Indonesia National Health Survey (SKI). This research involves participants over the age of 15. Analysis was conducted using univariate, bivariate (chi-square test), and multivariate methods with the Logistic Regression method, while considering the complexity of the research design. Research findings indicate that age, education level, and comorbidities are factors that significantly influence the incidence of DM. Those below the productive age group are at a higher risk of experiencing DM (OR = 2.268). Secondary education lowers the risk compared to higher education (OR = 0.611). Comorbidity is the main risk factor, increasing the probability of DM incidence by 6.229 times. These findings emphasize the importance of managing comorbidities and implementing appropriate preventive measures for at-risk individuals in efforts to manage diabetes in major cities.
Co-Authors Allsela Meiriza, Allsela Dian Palupi Rini Jackson Imanuel Manurung Ken Ditha Tania M Naufal Hisyam M. Ilham Fahlevi Mohd Rizky Putra Pratama Siti Nurmaini