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All Journal International Journal of Global Operations Research Hipotenusa: Journal of Mathematical Society Indonesian Journal of Statistics and Its Applications J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Yanti, Yusma
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Other

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Robust Anomaly Detection in Network Traffic Using Bagging with Majority Voting Ensemble Sultan Ilham Seftiansyah, Muhammad; Chairunnas, Andi; Yanti, Yusma
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 8 No 1 (2025): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v8i1.03

Abstract

Anomaly detection in computer networks is a crucial aspect of ensuring system security and availability. One of the most common and disruptive threats is Distributed Denial of Service (DDoS) attacks, which can overload servers and compromise service continuity. Traditional Intrusion Detection Systems (IDS) often struggle to detect sophisticated and evolving attack patterns, leading to reduced detection performance. This research proposes the use of ensemble learning with Bagging and Majority Voting to enhance anomaly detection. The dataset used in this study was CIC-DDoS2019, consisting of 33,066 rows and 88 features, processed through data cleaning, label encoding, and normalization. Three base classifiers—Decision Tree, Random Forest, and XGBoost—were integrated using Bagging with Majority Voting. Experiments were conducted with different train-test split ratios of 70:30, 75:25, 80:20, and 90:10. The results showed that the 70:30 split achieved the best performance with an accuracy of 93.58%, an F1-score of 90.51%, and the fastest evaluation time of 142.86 seconds. Additional tests on spam and phishing datasets confirmed the robustness of the Bagging approach, achieving accuracy above 96%. These findings demonstrate that Bagging with Majority Voting can effectively improve IDS performance and provide a reliable solution for detecting various types of cyberattacks.
Utilization of Geogebra Application as Learning Media in Learning The Three-Dimensional to Increase Students' Interest in Learning Widyastiti, Maya; Yanti, Yusma; Sumarsa, Amar; Durrotul Faizah, Layla
Hipotenusa: Journal of Mathematical Society Vol. 6 No. 1 (2024): Hipotenusa: Journal of Mathematical Society
Publisher : Program Studi Tadris Matematika Universitas Islam Negeri (UIN) Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18326/hipotenusa.v6i1.815

Abstract

This activity aims to describe students' interest in learning, learning outcomes, and the benefits of using GeoGebra in learning the three-dimensional. The data collected were analyzed using descriptive analysis. The research subjects were 59 students of SMA Negeri 1 Megamendung. Data collection techniques used tests and questionnaires. This research consists of 2 cycles. In cycle 1, the results obtained based on students' interest in learning showed that on average students strongly agreed 18.6%, agreed 31.1%, moderately 44.3%, and disagreed 5.9%. In cycle 2 after using the GeoGebra application, student interest increased to strongly agree 30.9%, agree 48.7%, moderately 18.6% and disagree 1.7%. Based on the learning outcomes in cycle 1, it shows 42.37% of students can solve problems well, while in cycle 2 there is an increase in the percentage of learning outcomes to 56.59%. Based on the results of the above analysis, it can be concluded that GeoGebra is very useful as a learning media and there is an increase in student interest and learning outcomes in learning the three-dimensional using GeoGebra.
Spatio-temporal Clustering Analysis of Dengue Hemorrhagic Fever Cases in West Java 2016 – 2021: Analisis Penggerombolan Spasio-temporal Kasus DBD di Jawa Barat Tahun 2016 – 2021 Yanti, Yusma; Rahardiantoro, Septian; Dito, Gerry Alfa
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p56-63

Abstract

In 2020, WHO included dengue as a global health threat among 10 other diseases. This is also a problem in Indonesia, especially the province of West Java. Based on data from the Ministry of Health for 2022, West Java is the largest contributor to cases of Dengue Hemorrhagic Fever (DHF) in Indonesia. The spread of dengue fever is through mosquitoes, but climate also greatly influences the spread of this disease. The spread of West Java is quite wide, consisting of 27 city districts and a relatively high population density. This greatly influences the increase in the number of dengue fever cases. In this research, we will group years with the same dengue fever cases and identify groups of districts/cities in West Java with the same pattern of dengue fever cases for 2016 to 2021. The results obtained are that 2016 is the group with the highest number of cases. Meanwhile, from 27 city districts in West Java, three groups were obtained. Group 1 is the group with the highest number of cases consisting of Sukabumi City, Bandung City, Cimahi City, Depok City, Tasikmalaya City.
Decision Support System for Indibiz Package Selection Using K-Means Clustering and Analytic Hierarchy Process Martika, Karina; Tosida, Eneng Tita; Yanti, Yusma
International Journal of Global Operations Research Vol. 6 No. 4 (2025): International Journal of Global Operations Research (IJGOR), November 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i4.434

Abstract

The rapid development of digital business in Indonesia has encouraged telecommunication providers to improve their services, particularly for small and medium-sized enterprises (SMEs). PT. Telkom Indonesia, through its Indibiz program, offers a wide variety of internet packages to support business operations. However, the diversity of available packages often leads to decision-making difficulties for both customers and internal stakeholders when determining the most suitable service based on customer needs, business scale, and financial capability. This study proposes a web-based Decision Support System (DSS) for Indibiz package selection by combining K-Means Clustering and the Analytic Hierarchy Process (AHP). K-Means is used to segment customers based on sales and usage behavior, while AHP prioritizes criteria such as speed, price, and call quota to produce recommendations. A dataset containing 6,192 Indibiz sales records from July to November 2023 was analyzed. The hybrid model was then implemented into a web-based application that enables decision-makers to visualize clustering results and determine package recommendations interactively. The experimental results demonstrate that the combination of K-Means and AHP produces more objective and consistent recommendations compared to manual selection. The DSS can help both customers and PT. Telkom Indonesia improve decision efficiency and reduce subjective bias in selecting internet packages.
Co-Authors Andi Chairunnas Dito, Gerry Alfa Durrotul Faizah, Layla Eneng Tita Tosida Martika, Karina Maya Widyastiti, Maya Rahardiantoro, Septian Sultan Ilham Seftiansyah, Muhammad Sumarsa, Amar