Article Per Year (5 Year)
p-Index From 2021 - 2026
1.244
P-Index
This Author published in this journals
All Journal Maneggio Journal of Public Health Indonesian
Isah Fitriani
Universitas Ahmad Dahlan
Decision Sciences, Operations Research & Management Health Professions Medicine & Pharmacology

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search

 1 
Cloud-Based Transportation Management System (TMS) Implementation for Distribution Efficiency in National E-Commerce Kasrim; Berilian Ayu Kusuma; Isah Fitriani
Maneggio Vol. 2 No. 5 (2025): OCTOBER-MJ
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/dc5de563

Abstract

This study aims to analyze the implementation of a cloud-based Transportation Management System (TMS) in enhancing distribution efficiency within Indonesia’s national e-commerce sector using a Systematic Literature Review (SLR) approach. The adoption of cloud-based TMS has become an integral component of Indonesia’s digital logistics transformation, emphasizing efficiency, transparency, and sustainability. The findings indicate that TMS can reduce transportation costs by 15–25%, accelerate delivery times, and optimize route planning through real-time data integration. Economically, the system strengthens national competitiveness by improving productivity and fostering cross-sector collaboration among logistics providers, government bodies, and e-commerce enterprises. From a sustainability perspective, TMS contributes to carbon emission reduction and energy efficiency in transportation, aligning with the nation’s green logistics initiatives and net-zero emission targets. Nevertheless, its effectiveness remains dependent on digital infrastructure readiness, human resource competence, and policy support for cross-sector data interoperability. This research highlights that the successful adoption of cloud-based TMS requires collaborative governance and inclusive technological integration policies. Therefore, TMS serves as a strategic foundation for enhancing distribution efficiency, e-commerce competitiveness, and sustainable digital economic growth in Indonesia.
Analysis of Factors Influencing Nutritional Status of Children Under Five Year Old Inaya Nur Aini; Isah Fitriani; Tri Budi Rahayu
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/k0nw0m48

Abstract

Nutritional status of children under five is a key indicator of public health and reflects the quality of human resource development. Malnutrition among under-five children remains prevalent in many communities and is influenced by multifactorial determinants. This study aimed to analyze factors influencing the nutritional status of children under five using a quantitative analytic approach. An observational analytic study with a cross-sectional design was conducted involving 240 children and their mothers or caregivers. Data were collected using anthropometric measurements and structured questionnaires. Bivariate and multivariate analyses were performed using logistic regression. The results revealed that household socioeconomic status, feeding practices, maternal education, and sanitation conditions were significantly associated with children’s nutritional status. Multivariate analysis identified household socioeconomic status as the most dominant factor affecting nutritional status, followed by feeding practices and maternal education. These findings indicate that child malnutrition is not solely related to individual behavioral factors but is also strongly influenced by broader socioeconomic and environmental conditions. This study highlights the need for integrated, community-based, and evidence-driven nutrition interventions that address social, economic, and environmental determinants simultaneously.
Utilization of AI-Based Predictive Analytics in Public Health Planning Inaya Nur Aini; Isah Fitriani; Tri Yuniarti
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/xvj79d79

Abstract

The public health planning faces on increasing challenges related to disease burden, limited resources, and the need of more proactive decision-making. In this context, artificial intelligence–based on predictive analytics offers potential support for evidence-based public health planning through data utilization and health trend forecasting. The study aims to analyze the utilization of artificial intelligence–based predictive analytics in public health planning and its role in support of planning quality. A quantitative descriptive-analytical design was employed by structured questionnaires data collection involving stakeholders engaged in public health planning. Data were analyzed by using descriptive statistics and descriptive relational analysis to map patterns of predictive analytics utilization and planning quality. The findings indicate that predictive analytics utilization is a moderate to high level and is positively associated with public health planning quality, particularly in data-driven decision-making and anticipatory capacity for future health needs. However, predictive analytics is more frequently applied to forecasting purposes than for direct resource allocation and operational decision-making. The study concludes that artificial intelligence–based predictive analytics serves as an important decision-support instrument in evidence-based public health planning, while further institutional capacity building and governance improvements data are required to maximize its impact.
Digital Food Environments and Hidden Obesity Risk Among Urban Youth: a Mixed-Methods Study Isah Fitriani; Inaya Nur Aini; Azizatul Hamidiyah
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/3zndn159

Abstract

The development of digital technology has transformed the urban food environment through the increased use of food delivery apps and exposure to digital food promotions, potentially posing latent health risks to young people. This study aimed to analyze the relationship between the digital food environment and the risk of latent obesity among urban youth using a mixed methods approach. A sequential explanatory design was implemented with a quantitative phase involving 240 young people aged 18–30 years, followed by a qualitative phase through in-depth interviews with high-risk participants. Quantitative data were collected through body composition measurements and a digital food environment exposure questionnaire, then analyzed using multivariate statistics. The results showed that 34.6% of respondents with a normal body mass index (BMI) experienced latent obesity, and exposure to a high digital food environment significantly increased the risk of latent obesity. Qualitative findings revealed the normalization of high-calorie food consumption in digital spaces, efficiency-based rationalizations, and low awareness of latent obesity. The integration of findings indicates that the digital food environment not only influences consumption patterns but also shapes youth's perceptions and behavioral justifications. This study confirms that the digital food environment is a structural determinant of latent obesity risk, necessitating prevention strategies that include digital health literacy, regulation of online food promotions, and the use of more comprehensive health indicators.
The Impact of Traditional and Modern Practices on Maternal Health During the Postpartum Period Andi Muhammad Multazam; Isah Fitriani; Annisa Andriyani
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/wa2v2k33

Abstract

This mixed-method study demonstrates that postpartum care practices significantly influence maternal health outcomes, with modern practices and integrated traditional–modern approaches yielding better results than reliance on traditional practices alone. Quantitative findings indicate that mothers who adopted evidence-based postpartum care experienced improved physical recovery and overall health status, while qualitative insights reveal that traditional practices continue to play an important psychosocial and cultural role. The integration of both approaches emerged as the most beneficial model, suggesting that maternal health outcomes are optimized when biomedical care is complemented by culturally meaningful practices that provide emotional support and social reassurance. The findings carry important implications for maternal health policy and practice. Health professionals should avoid framing traditional postpartum practices as inherently harmful and instead adopt culturally sensitive strategies that encourage safe integration with modern care. Training programs for midwives and postpartum care providers should emphasize respectful communication and cultural competence to enhance maternal trust and service utilization. However, this study has limitations. The findings are context-specific and may not be fully generalizable to regions with different cultural or healthcare systems. Additionally, the cross-sectional nature of the quantitative phase limits causal inference, and self-reported health measures may be subject to recall bias. Future research should employ longitudinal designs and broader geographic coverage to further examine the long-term health effects of integrated postpartum care models.
Surveillance Health Society: Ethics, Privicy, and Social Control in Digital Health Systems Hendra Cipta; Isah Fitriani; Ryryn Suryaman Prana Putra
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/4tt4qc09

Abstract

The rapid expansion of digital health systems has transformed healthcare delivery while simultaneously embedding pervasive practices of surveillance within everyday life. Technologies such as electronic health records, wearable devices, and health analytics enable continuous monitoring and data-driven governance of bodies and behaviors. This study critically examines digital health systems through the lens of surveillance society, focusing on the ethical implications of privacy, autonomy, and social control. Employing a qualitative normative–critical approach, the study analyzes policy documents and academic literature from health ethics, surveillance studies, and critical social theory. The findings show that digital health systems function as infrastructures of continuous surveillance that classify risk, normalize behavior, and reshape relations between individuals, states, and technology providers. Ethical challenges arise from weakened informed consent, data commodification, and profound power asymmetries that limit individual control over personal health data. The study further argues that health-based narratives of prevention and security legitimize intrusive forms of governance, positioning digital health as a mechanism of social control rather than purely a tool of care. This research concludes that ethical governance of digital health requires moving beyond technocratic and procedural approaches toward a critical framework that addresses power, justice, and accountability in data-driven health systems
Biostatistical Approach to Predict Disease Risk Using Public Health Data Loso Judijanto; Isah Fitriani
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/zjyppe33

Abstract

The increasing complexity of public health issues demands an analytical approach capable of optimally utilizing data to support disease prevention efforts. The increasing availability of public health data opens up opportunities for the development of evidence-based predictive approaches. This study aims to examine the role of biostatistical approaches in predicting disease risk using public health data and its implications for preventive efforts and health policy. The study employed a qualitative approach using literature review methods, including journal articles, academic books, and relevant policy documents. Data analysis was conducted thematically to identify the role of biostatistics in risk factor analysis, predictive model development, and the associated methodological and policy challenges. The study results indicate that biostatistical approaches play a crucial role in identifying multifactorial relationships between health determinants and disease incidence at the population level. Disease risk prediction models have been shown to support the identification of high-risk groups and the planning of more efficient preventive interventions. Key challenges include data quality, limited human resources, and gaps in the translation of analysis results into health policy. Overall, the biostatistical approach is a strategic foundation for the development of a data- and evidence-based public health system oriented towards disease prevention
Evaluation of Health System Preparedness for Post-Disaster Health Crises Inaya Nur Aini; Isah Fitriani; Ryryn Suryaman Prana Putra
Journal of Public Health Indonesian Vol. 2 No. 5 (2026): JANUARY-JHH
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/pb4m0v31

Abstract

Post-disaster health crises frequently expose structural vulnerabilities within health systems, including disrupted service delivery, limited medical resources, and weak inter-institutional coordination. This study aims to evaluate the level of health system preparedness for post-disaster health crises and to identify the structural barriers that hinder effective response and recovery. A mixed-methods approach was employed using a convergent explanatory design. Quantitative data were collected through a health system preparedness checklist covering human resources, infrastructure, logistics, referral systems, and emergency response protocols. Descriptive statistics and gap analysis were used to assess preparedness levels against established standards. Qualitative data were obtained through in-depth interviews with health policymakers, facility managers, and frontline health workers involved in disaster response, and analyzed thematically to explain quantitative findings.The results indicate that overall health system preparedness is at a moderate level, with relatively strong formal preparedness in emergency protocols but substantial gaps in logistics capacity, human resource availability, and operational coordination. Qualitative findings reveal that fragmented governance, delayed resource mobilization, and limited functional integration across institutions undermine the implementation of preparedness plans during post-disaster conditions. The integration of quantitative and qualitative results highlights a persistent gap between formal preparedness and functional readiness.This study concludes that effective post-disaster health preparedness requires moving beyond administrative compliance toward strengthening functional system capacity. The findings underscore the value of mixed-methods evaluation in generating comprehensive evidence to inform policy reforms aimed at improving health system resilience in disaster-prone settings.
Co-Authors Annisa Andriyani Azizatul Hamidiyah Berilian Ayu Kusuma Hendra Cipta Inaya Nur Aini Kasrim Loso Judijanto Ryryn Suryaman Prana Putra Ryryn Suryaman Prana Putra Tri Budi Rahayu Yuniarti, Tri