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All Journal Jambura Journal of Mathematics International Journal of Research in Community Services Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research International Journal of Humanities, Law, and Politics International Journal of Health, Medicine, and Sports International Journal of Linguistics, Communication, and Broadcasting
Yuningsih, Siti Hadiaty
Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, National University Of The Republic Of Indonesia, Bandung, Indonesia
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Maternal and Child Health: The Key to a Better South African Future Yuningsih, Siti Hadiaty; Yohandoko, Setyo Luthfi; Pirdaus, Dede Irman
International Journal of Research in Community Services Vol. 5 No. 2 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i2.628

Abstract

South Africa, a country rich in history and natural beauty, also faces serious challenges in the health sector, especially maternal and child health. Maternal and infant mortality rates are still high, inequality in access to health services, low levels of education and knowledge of reproductive health, as well as problems of malnutrition and HIV/AIDS are the main focus of discussion. Although the government has launched programs to improve maternal and child health, funding challenges and disparities in health resources between regions still hinder the achievement of equitable health coverage. This article highlights the importance of increasing health budget allocations, building first-level health facilities, improving the skills of health workers, reproductive health education, nutritional interventions, and multi-stakeholder cooperation to overcome these health challenges. 
Analysis of Multistability of Financial Risk Chaos Systems and Its Application to Voice Cryptography Yuningsih, SIti Hadiaty; Hidayana, Rizki Apriva; Nurkholipah, Nenden Siti
International Journal of Research in Community Services Vol. 5 No. 3 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i3.699

Abstract

In the chaos literature, the application of modeling and control of dynamic systems in chaos theory arising in several fields is investigated. In this article we analyze complex financial chaos systems with countries as interest rates, investment demand, and price indices. The proposed chaotic flow's dynamic behavior is examined using phase portraits, eigenvalues, bifurcation diagrams, and Lyapunov exponent spectra. A significant quantity of research on secure communication systems has been published in recent years as a result of the major advancements in communications equipment and encryption techniques. A new voice encryption algorithm design is given using a financial chaos model. An application for voice encryption is conducted using the suggested algorithm, and the outcomes are described.
Strategic Management Practices of PT Bank Central Asia Tbk: Navigating Challenges and Leveraging Opportunities in Indonesia's Banking Sector , Kalfin; Yuningsih, Siti Hadiaty; Halim, Nurfadhlina Abdul
International Journal of Research in Community Services Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v5i4.715

Abstract

This paper provides an in-depth analysis of strategic management practices employed by PT Bank Central Asia Tbk (BCA), one of Indonesia's leading banks. The study investigates BCA's strategic initiatives across multiple dimensions including organizational strategy, competitive positioning, customer service enhancement, digital transformation, and sustainability efforts. Through a strategic management lens, the analysis examines how BCA has navigated challenges and capitalized on opportunities in the dynamic banking landscape of Indonesia. Key strategic decisions, such as market segmentation, product innovation, and technology adoption, are explored to understand their impact on BCA's market leadership and financial performance. Additionally, the paper discusses the role of corporate governance and leadership in driving BCA's strategic objectives forward.
Analysis of Factors Inhibiting Students in Speaking English as a Foreign Language: Qualitative Study in Classes VIII and IX at Mts Darul Falah Cibungur Abdul Hali, Nurfadhlina; Yuningsih, Siti Hadiaty; Suhaimi, Nurnisaa binti Abdullah
International Journal of Ethno-Sciences and Education Research Vol. 4 No. 1 (2024): International Journal of Ethno-Sciences and Education Research (IJEER)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v4i1.571

Abstract

This research investigates the factors that hinder students from speaking English as a foreign language in the classroom. Through qualitative research methods involving students and teachers, the findings show that there are two main factors that influence students' speaking abilities, namely affective factors and cognitive factors. Affective factors include eleven subfactors such as shyness, nervousness, and lack of self-confidence, while cognitive factors involve problems with grammar, pronunciation, and vocabulary. In addition, the influence of teachers and peers also has a significant role in overcoming or exacerbating these factors. This research has implications for designing more effective speaking learning and a supportive environment for students in overcoming speaking barriers.
Strategic Transformation at PT Bank Central Asia Tbk: Lessons in Market Adaptation and Leadership Yuningsih, Siti Hadiaty; Saputra, Moch Panji Agung; Halim, Nurfadhlina Abdul
International Journal of Ethno-Sciences and Education Research Vol. 4 No. 3 (2024): International Journal of Ethno-Sciences and Education Research (IJEER)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijeer.v4i3.720

Abstract

This paper provides an in-depth analysis of strategic management practices employed by PT Bank Central Asia Tbk (BCA), one of Indonesia's leading banks. The study investigates BCA's strategic initiatives across multiple dimensions including organizational strategy, competitive positioning, customer service enhancement, digital transformation, and sustainability efforts. Through a strategic management lens, the analysis examines how BCA has navigated challenges and capitalized on opportunities in the dynamic banking landscape of Indonesia. Key strategic decisions, such as market segmentation, product innovation, and technology adoption, are explored to understand their impact on BCA's market leadership and financial performance. Additionally, the paper discusses the role of corporate governance and leadership in driving BCA's strategic objectives forward.
Comparison of Machine Learning Models for Breast Cancer Diagnosis Classification Ibrahim, Riza; Yuningsih, Siti Hadiaty; Ismail, Muhammad Iqbal Al-Banna
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.v6i4.431

Abstract

Breast cancer remains one of the most pressing global public health challenges, with approximately 2.3 million women diagnosed worldwide in 2022 and around 670,000 deaths attributed to the disease. Despite the widespread application of machine learning algorithms for breast cancer classification, findings across studies remain highly varied, and there is still no consistent conclusion regarding which algorithm is most superior for breast cancer diagnosis. This study aims to analyze and compare the performance of four machine learning algorithms Logistic Regression, Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbors (KNN) in predicting breast cancer. The dataset used was the Breast Cancer Wisconsin (Diagnostic) Data Set obtained from Kaggle, containing morphological characteristics of tumor cells. Data preprocessing involved cleaning, label encoding, feature normalization using StandardScaler, and an 80:20 train-test split. Model performance was evaluated using confusion matrix, precision, recall, F1-score, accuracy, and ROC-AUC. The results showed that all four models achieved excellent performance with overall accuracy ranging from 95.61% to 97.37%. SVM emerged as the most accurate model (97.37%) with perfect recall (1.00) for the Benign class. Logistic Regression demonstrated the highest ROC-AUC value (0.9960), indicating excellent discriminative ability. Random Forest and KNN showed slightly lower performance, particularly in detecting Malignant cases with recall of 0.90. These findings confirm that machine learning can serve as an effective tool to support breast cancer diagnosis, with algorithm selection depending on data characteristics and clinical priorities.
Application of Conditional Trajectory Generation on Stewart Platform Robot as a CNC Machine Drive Khoerunnisa, Ahshonat; Nur Jamiludin R; Setiawan, Aan Eko; Yuningsih, Siti Hadiaty; Hòe Nguyễn Đình
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.v6i4.433

Abstract

The development of industrial automation technology in recent decades has been very rapid. One of the technologies that supports industrial automation is robot manipulators. Robots can work with high precision, speed, and safety so that by using robots, industrial processes become more productive. The type of robot itself is divided into two, namely serial and parallel structures. Robots with parallel structures tend to be less studied, developed, and used in industry compared to serial structures even though there are several advantages of these parallel structures. Parallel structures have a kinematic configuration with a closed chain type, or it can be interpreted that each arm is connected to the point of origin. This relationship will result in robots having high precision and speed. Kinematic parallel manipulators perform better when compared to serial kinematics in terms of angular accuracy, acceleration at high speeds, and high stiffness. Therefore, this type of robot is very suitable for use in industries that require high-speed applications. In this study, a robot system was developed as a driving force for a CNC machine with its movements using a trajectory tracking control system. This system was chosen because this control has a point where each point contains position and speed information that is certainly needed for the CNC machine movement system.
Wireless Chaos-Based Communication System: Literature Review Siti Hadiaty Yuningsih; Sudradjat Supian; Sukono Sukono; Subiyanto Subiyanto
International Journal of Quantitative Research and Modeling Vol. 2 No. 1 (2021): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v2i1.128

Abstract

Since the early 1990s, a slew of chaotic-based communication systems have been proposed, all of which take advantage of chaotic waveform properties. The inspiration stems from the substantial benefits that this form of nonlinear signal offers. Many communication schemes and applications have been specifically designed for chaos-based communication systems to achieve this goal, with energy, data rate, and synchronization awareness being taken into account in most designs. However, non-coherent chaos-based systems have recently received a lot of attention in order to take advantage of the benefits of chaotic signals and non-coherent detection while avoiding the use of chaotic synchronization, which has poor performance in the presence of additive noise. This paper provides a thorough examination of all wireless radio frequency chaos-based communication systems. It begins by describing the difficulties of chaos implementations and synchronization processes, then moves on to a thorough literature review and study of chaos-based coherent techniques and their applications.
Applying Machine Learning Algorithms to Predict Employee Turnover Intention: A Comparative Model Analysis Siti Hadiaty Yuningsih; Fahmi Sidiq; Yasir Salih
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1344

Abstract

Employee turnover represents a major challenge for organizations because it increases recruitment and training costs, disrupts operational continuity, and reduces organizational performance. Although machine learning has been widely applied to employee attrition prediction, most studies focus on comparing algorithms using the complete feature set, with limited attention to the predictive contribution of different employee information domains. This study aims to identify the most informative attribute domains for turnover prediction, compare the performance of ANN, RF, and SVM, and evaluate whether reduced-domain models can achieve performance comparable to full-feature models. The study utilized the IBM HR Analytics Employee Attrition dataset containing 1,470 employee records. Thirty predictive attributes were organized into six conceptual domains: Personal Information, Job Characteristics, Compensation, Work Environment, Career Development, and Relationship & Supervision. Twelve domain-based model configurations were developed and evaluated using ANN, RF, and SVM. Model development employed SMOTE to address class imbalance and repeated 10-fold cross-validation, while final evaluation was conducted on an independent holdout validation dataset. The results show that multi-domain models consistently outperform single-domain configurations. Compensation and Career Development emerged as the strongest standalone domains, while Work Environment was present in all top-performing models. The highest validation accuracy was achieved by M0-SVM (84.01%), whereas M11-SVM achieved comparable performance (82.65%) using only 16 attributes. M11-ANN produced the highest ROC AUC (0.782), indicating superior discriminative capability. Feature importance analysis identified OverTime, MonthlyIncome, Age, TotalWorkingYears, and YearsAtCompany as the most influential predictors. These findings demonstrate that domain composition is as important as algorithm selection in employee turnover prediction and highlight the importance of work environment, compensation, and career development factors in supporting data-driven employee retention strategies.
Socialization And Counseling on How yo Use Appropriate Technology for Wood Crushing Machines in Sukaluyu Village, Pangalengan District, Bandung Regency Siti Hadiaty Yuningsih; Ilham Ali; Haris Setiawan
International Journal of Research in Community Services Vol. 7 No. 1 (2026): International Journal of Research in Community Service (IJRCS)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v7i1.1151

Abstract

The purpose of this community service program is to (1) Provide knowledge to village communities about how to utilize appropriate technology in everyday life. (2) Provide guidance in completing the utilization of appropriate technology according to the needs desired by the village community properly and correctly. The method of implementing this community service activity is carried out by providing guidance on how to apply and complete the tools that will be used at the village, sub-district, district, provincial, and national levels. (1) At the beginning of the activity, provide basic knowledge and concepts about the material on how to make the tools that will be used. (2) Provide training and examples in completing an activity about appropriate technology that will be used. (3) The final stage, the community is asked to be able to apply it in everyday life properly and correctly, so that from this community service activity the community can utilize existing resources for the common good, namely in oyster mushroom cultivation.
Co-Authors , Kalfin Abdul Gazir Syarifudin Abdul Hali, Nurfadhlina Agung Prabowo Alim Jaizul Wahid Amelia, Rika Azahra, Astrid Sulistya binti Abdullah Suhaimi, Nurnisaa Chayandri, Rini Chun Wang Endang Rusyaman Fahmi Sidiq Hadikaryana, Oscar Halim, Nurfadhlina Abdul Haris Setiawan Hidayana, Rizki Apriva Hòe Nguyễn Đình Ibrahim, Riza Ibrahim, Riza Andrian Ilham Ali Ismail, Muhammad Iqbal Al-Banna Jaizul, Alim Josua, Lancelot Julsen kalfin Kalfin Khoerunisa, Ahshonat Khoerunnisa, Ahshonat Lianingsih, Nestia Nenden Siti Nurkholipah, Nenden Siti Nur Jamiludin R Nurfadhlina Abdul Hali Nurnisaa binti Abdullah Suhaimi Pirdaus, Dede Irman Prawiro, Meivin Mulyo Ridwan, Ridwan Rini Cahyandari Rizki Apriva Hidayana Saputra, Jumadil Setiawan, Aan Eko Subiyanto Subiyanto Sudradjat Supian Suhaimi, Nurnisaa binti Abdullah Suharto, Istiqomah Sukono Sukono Sulistya A, Astrid Sulistya Azahra, Astrid Surya, Dhika Suryaman Suryaman Vaidyanatahan, Sundarapandian Vimelia, Willen Yasir Salih Yohandoko, Setyo Luthfi Zakaria, Kiki