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All Journal Journal of the Medical Sciences (Berkala Ilmu Kedokteran) Jurnal Riset Kesehatan Berita Kedokteran Masyarakat Infolitika Journal of Data Science Proceeding Mulawarman International Conference on Tropical Public Health

Ahmad Watsiq Maula

Departemen Biostatistik, Epidemiologi Dan Kesehatan Populasi, Fakultas Kedokteran, Kesehatan Masyarakat Dan Keperwatan, Universitas Gadjah Mada

Author-ID : 2970493

Computer Science & IT Decision Sciences, Operations Research & Management Engineering Health Professions Immunology & microbiology Neuroscience Nursing Public Health

Published : 9 Documents Claim Missing Document

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Articles

Healthcare-associated infections (HAI) research in Asian countries: a bibliometric analysis . cahyadin; Ahmad Watsiq Maula; Anis Fuad
Journal of the Medical Sciences (Berkala Ilmu Kedokteran) Vol 50, No 1 (2018): SUPPLEMENT
Publisher : Journal of the Medical Sciences (Berkala Ilmu Kedokteran)

Health care-associated infections (HAI) are the most frequent adverse event in health-care delivery worldwide, including in Asian countries. Asian countries produced 4,819 HAI publications. Majority of the publications (68%) appeared in the last decade. The average annual growth rate was 14.8%. Japan was the most productive country that contributes about 13.5% of total publications, followed by China (11.7%), and Taiwan (11.6%). Asian HAI research were cited in 76,737 articles with an average of 15.9 citations per publication. The top two most highly cited articles were published in the New England Journal of Medicine followed by the Journal of Clinical Microbiology. The top three productive journals were Journal of Hospital Infection (309 papers; 6.4%), American Journal of Infection Control (198 papers; 4.1%) and Infection Control and Hospital Epidemiology (170 papers; 3.5%). The ten top journals contained 25% of the HAI literatures. Emerging research topics in the last years include ventilator-associated pneumonia, MRSA (methicillin-resistant staphylococcus aureus), acinetobacter baumannii, carbapenems, Republic Korea and tertiary care center.

BLOCKCHAIN TECHNOLOGY IMPLEMENTATION ON MEDICAL RECORDS DATA MANAGEMENT: A REVIEW OF RECENT STUDIES Dian Budi Santoso; Anis Fuad; Guntur Budi Herwanto; Ahmad Watsiq Maula
Jurnal Riset Kesehatan Vol 9, No 2 (2020): NOVEMBER 2020
Publisher : Poltekkes Kemenkes Semarang

Blockchain first introduced and implemented in digital currency management and transactions. Its application to medical records data management is a novelty. This paper described the implementation of blockchain technology in the healthcare industry, especially in medical records data management A literature review was conducted on three popular databases, ScienceDirect, SpringerLink, and IEEE Xplore with the keywords "health", "medical record" and "blockchain" with "research article" and "conference proceeding" filters. There are a few articles that meet the criteria to review indicated that the implementation of blockchain technology in medical records data management is a novelty and still in the early phase. Blockchain is a potential technology in supporting the implementation of electronic medical records, especially related to data integration and privacy. Several scientific publications related to the implementation of blockchain for medical records data management shown that the implementation of this technology will make the patient have full control over their health data. Yet there are still many challenges in the implementation both from the user side and the technology infrastructure.

Waktu yang dihabiskan oleh kepala puskesmas keluar kantor untuk kegiatan administrasi versus program lapangan: analisis data fasilitas komunitas dari IFLS East 2012 Veronika Suka; Ahmad Watsiq Maula; Dian Mawarni; Retna Siwi Padmawati; Mubasysyir Hasanbasri
Berita Kedokteran Masyarakat (BKM) Vol 34, No 3 (2018)
Publisher : Fakultas Kedokteran Universitas Gadjah Mada

Health center manager time spending for outside administrative versus field work in East Indonesian region: an analysis of community facility of 2012 IFLS East PurposeThis study evaluates time spent on administrative and field public health program of physician or non-physician community health center managers in East Indonesian region. MethodThe study used 85 community health center managers from 7 provinces of East Nusa Tenggara, East Kalimantan, Southeast Sulawesi, Maluku, North Maluku, West Papua, and Papua from which the data was available in the community facility section of Indonesian Family Life Survey East (IFLS East) 2012.ResultsPhysician managers spent more hours than non-physician managers for administrative matters. In addition, non-physician managers had more hours per week for field program activities as compared to physician managers.ConclusionResearch shows that physician managers have potential lost of their time in performing their medical service functions, which they are trained for. Policy should be directed to improve the management skills of non physician health workers so that physicians can maximize their time to solve medical problems in health centers.

Demographic representativeness of Twitter data: Is it valid for public health surveillance? Ahmad Watsiq Maula
BKM Public Health and Community Medicine PHS8 Accepted Abstracts
Publisher : Universitas Gadjah Mada

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Objective: Twitter data were frequently used for public health purposes such as surveillance. Compared to traditional data sources, Twitter data benefits are less expensive, could support Spatio-temporal analysis, track population health outcomes and outbreaks, track health behavior and attitude, and collect real-time data. However, in surveillance, three basic information of person, place, and time should be available for analysis. Twitter, in this case, could provide the place and time data, but many arguments doubted the availability of the "person" data and demographic representativeness of the data. Content: The missing information on gender, age, and lack of socioeconomic status in Twitter data are the main reasons for skepticism in Twitter data as a surveillance tool. The advanced methods in machine learning and artificial intelligence could answer the skepticism. The M3 model (multimodal, multilingual, and multi-attribute), combining profile image, username, screen name, and biography of Twitter users to predict gender, showed 91.8% accuracy to predict gender. The language detection method, which detects words in Twitter posts using lexicon from the World Well-Being Project (WWBP), combined with metadata such as number of followers, number of friends, and tweeting frequency, results in 74% accuracy in predict age groups. Twitter users' social network analysis method found that users tend to have homophilic behavior when selecting friends. Combining the social network analysis, other data (language analysis and user profile), and machine learning method could predict the occupational class (accuracy of 52%) and income information of users. Twitter, as a big data source, has potentials for health and diseases surveillance. As long as the demographic profiles of Twitter data are reported, it will be valid for surveillance purposes. Furthermore, the growth of advanced methods in artificial intelligence possibly diminishes current skepticism in the usability of Twitter for surveillance and other public health activities.

The utility of student interest in a particular specific program, presentation in professional meetings, and open science collaborative writing in mastering health management and policy tools in MPH training Dian Mawarni; Ahmad Watsiq Maula; Mubasysyir Hasanbasri
BKM Public Health and Community Medicine PHS8 Accepted Abstracts
Publisher : Universitas Gadjah Mada

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ies Trying out a presentation in a professional symposium is difficult for a beginner. Even novice writers have difficulty imagining what they will tell conference attendees. They even have difficulty distinguishing what questions they want to be answered and shared in scientific meetings. For example, they find it difficult to focus on something general (conceptual) or specific (operational); specific case stories different from others, failed cases, or best practice cases. This paper explores the importance of observing a preferred program and the potential of an open science approach in overcoming the difficulties of students and lecturers in starting their development as professionals. The primary failure of beginners is that they do not yet have a collection of one type of program from various countries, which they collect from day to day by comparing with each other. The second failure is that they do not have a discussion partner, which makes them open to finding hot points from their program, encouraging them to explore more exciting things. We emphasize that programming games and creating class assignments through an open science approach should be a writing strategy for students who analyze and apply the theory and framework of projects to help improve health programs in the field.

Performance Evaluation of EWARS (Early Awareness and Response System) for Leptospirosis Cases in Kebumen District Health Office in 2023 Tumiat; Akhmad Mukhibin; Ahmad Watsiq Maula
BKM Public Health and Community Medicine The 12th UGM Public Health Symposium
Publisher : Universitas Gadjah Mada

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Purpose: To evaluate the performance of the early warning and response system (EWARS) in the Kebumen District Health Office in 2023 in general and specifically for early detection of leptospirosis cases. Method: This study was a descriptive evaluation study using secondary data from EWARS platform. The data was retrieved from the website web.skdr.surveilans.org. Results: The timeliness of EWARS reporting at community health centers and hospitals levels in 2023 were 95.42% and 96.23%, respectively. The completeness of EWARS reports at community health centers and hospitals levels in 2023 were 98.11%, respectively. A total of 314 alerts were reported by community health centers, while 413 alerts reported from hospitals during 2023. The most frequently reported alert from hospitals was leptospirosis. In the EWARS, 66 cases of leptospirosis were reported at week 11. Alerts from hospital reports from week 1 to week 11 have an increasing trend. An alert from the health center report appeared in the 9th week. The response that has been made is improving a health awareness on a leptospirosis around the affected community health centers and hospitals in the Kebumen area. In term of verification, 93.46% of the alerts reported by hospitals were verified within 24 hours. Conclusion: The timeliness and completeness of EWARS reporting in Kebumen District have surpassed the national targets of 80% and 90%, respectively. In the case of leptospirosis, community health centers need to increase early detection of symptoms and risk factors for leptospirosis.

Sociodemographic Characteristics of Tuberculosis Cases From Rural Areas in Yogyakarta Sri Purwanti; Andri Setyo Dwi Nugroho; Ahmad Watsiq Maula
BKM Public Health and Community Medicine The 12th UGM Public Health Symposium
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/bkm.v0i0.13597

Purpose: Tuberculosis (TB) remains a public health challenge. In 2023, the number of TB cases in Yogyakarta reached 6079 cases, of which 1,166 (19.2%) were in rural areas. Being in rural areas is often a risk factor for TB incidence due to several aspects. An initial step to determine the sociodemographic characteristics of TB patients in Yogyakarta is important to analyze the situation in control efforts. Methods: This study is a descriptive cross-sectional study using secondary data based on SITB (Tuberculosis Information System) of the Yogyakarta Provincial Health Office. Data were collected from January to December 2023. The classification of rural areas is based on the classification of data from the Central Statistic Agency (BPS). Results: Based on the analysis conducted, it is known that the majority of 665 (57%) TB patients in rural areas are male, 26 (2.23%), 300 people (29%) are not working, 535 (45.8%) from Gunung Kidul, 703 (60.29%) seek treatment at the hospital, 450 (38.6%) at the health center, and others at clinics / independent practitioners. A total of 1038 (89.02%) were diagnosed with Pulmonary TB and 128 (10.98%) were diagnosed with Extra Pulmonary TB, 752 (64.49%) were clinically confirmed and 414 (35.51%) were bacteriologically confirmed, 717 (61.49%) TB patients in rural areas did not know their Diabetes, 973 (83.45) did not know their HIV status and 26 (2.23%) had not received standards TB treatment. Conclusion: The problem of Tuberculosis in rural areas still needs attention considering the high economic burden due to the inability of TB patients to work, as well as the low proportion of Diabetes and HIV testing as a leading collaborative program in TB control.

A Statistical Clustering Approach: Mapping Population Indicators Through Probabilistic Analysis in Aceh Province, Indonesia Sasmita, Novi Reandy; Khairul, Moh; Sofyan, Hizir; Kruba, Rumaisa; Mardalena, Selvi; Dahlawy, Arriz; Apriliansyah, Feby; Muliadi, Muliadi; Saputra, Dimas Chaerul Ekty; Noviandy, Teuku Rizky; Watsiq Maula, Ahmad
Infolitika Journal of Data Science Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v1i2.130

The clustering, one of statistical analysis, can be used for understanding population patterns and as a basis for more targeted policy making. In this ecological study, we explored the population dynamics across 23 districts/cities in Aceh Province. The study used the Aceh Population Development Profile Year 2022 data, focusing on the total population, in-migrants, out-migrants, fertility, and maternal mortality as variables. The study employed descriptive statistics to ascertain the data distribution, followed by the Shapiro-Wilk test to evaluate normality, which is crucial for selecting the appropriate statistical methods. The Spearman test was used to determine correlations between the total population and the variable as indicators. Probabilistic Fuzzy C-Means (PFCM) method is used for clustering. To optimize clustering, the silhouette coefficient was calculated using the Euclidean Distance and the elbow method, with the results analyzed using R-4.3.2 software. This study's design and methods aim to provide a nuanced understanding of demographic patterns for targeted policy-making and regional development in Aceh, Indonesia. Based on the data normality test results, only fertility (p-value = 0.45), while the other variables are not normally distributed. Spearman test was used, and the results showed that only in-migrants (p-value = 1.78 x 10-6) and out-migrants (p-value = 2.30 x 10-6) correlated to the Aceh Province population. Using the population variable and the two variables associated with it, it was found that 4 is the best optimum number of clusters, where clusters 1, 2, 3, and 4 consist of three districts/city, nine districts/city, four districts/city and seven districts/city respectively.

EVALUATION OF THE COMPLETENESS AND TIMELINESS PERTUSSIS SURVEILLANCE SYSTEM IN YOGYAKARTA IN 2023 Purwanti, Sri; Maula, Ahmad Watsiq; Nugroho, Andri Setyo Dwi; Oktaviani, Wiwid
Mulawarman International Conference on Tropical Public Health Vol. 1 No. 1 (2025): The 3th MICTOPH
Publisher : Faculty of Public Health Mulawarman University, Indonesia

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Background : Pertussis cases in Yogyakarta showed an upward trend in 2022 with 11 cases, after no cases in the previous 2 years. Surveillance as one of the tools of control efforts is an important to produce representative data as a guide in decision making. Objective : Evaluation related to completeness and timeliness was carried out to determine the quality of the records and identify delays in diagnosis and notification. Research Methods/ Implementation Methods : This study used secondary data based on the DIY Pertussis form. Timeliness was calculated based on diagnostic delay from symptom onset to the date the specimen was taken. Notification delay was calculated from the date of symptom onset to the date the public health center received notification. Results : 59 laboratory confirmed cases were obtained. 29% of cases were adult, 25.4% infant, 51% female, 34% from Bantul, 27% hospitalized, 64.4% not fully vaccinated. 100% completeness was found in the variables of place of residence and source of reporting, 51% had known first symptoms, 93% had known notification date, 100% had known specimen collection date. The median diagnosis delay was 19 days and the median notification delay was 19 days. Conclusion/Lesson Learned : Sociodemographic data is complete, but there needs an effort to improve by grouping cases based on the epidemiological status and distinguishing positive confirmation of close contact and asymptomatic from symptomatic cases. Long notification times mean that public health actions are not implemented quickly and can lead to widespread transmission. The longer time to make a diagnosis can result in patients seeking treatment in many health services.

Co-Authors Akhmad Mukhibin Andri Setyo Dwi Nugroho Anis Fuad Apriliansyah, Feby Cahyadin Cahyadin Dahlawy, Arriz Dian Budi Santoso Dian Mawarni Dimas Chaerul Ekty Saputra Guntur Budi Herwanto Hizir Sofyan Khairul, Moh Kruba, Rumaisa Lisma Evareny, Mohammad Hakimi, Retna Siwi Padmawati Mardalena, Selvi Mubasysyir Hasanbasri Muliadi Nugroho, Andri Setyo Dwi Oktaviani, Wiwid Sasmita, Novi Reandy Sri Purwanti Sri Purwanti Teuku Rizky Noviandy Tumiat Veronika Suka

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