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Description Of Characteristics, Diagnosis And Financing Of BPJS Patients In ENT Poly Health Service Facility Level 2 Roesbiantoro, Andi; Budhi Setianto; Adriansyah, Agus Aan; Pulih Asih, Akas Yekti; Setiyowati, Eppy; Bistara, Difran Nobel; Sa'adah, Nikmatus
TEKNOLOGI MEDIS DAN JURNAL KESEHATAN UMUM Vol 6 No 2 (2022): Medical Technology and Public Health Journal September 2022
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/mtphj.v6i2.3081

Abstract

The application of tariff applied in handling BPJS patients references the INA- CBGs and the payment model used by BPJS Kesehatan to replace the total bill by the hospital. Hospitals receive payments based on the INA- CBGs rate, which is the average cost spent by a group of diagnoses. It is expected to improve the quality and efficiency of hospitals. The benefit of implementing INA -CBGs in JKN is the tariffs in the form of packages cover all components of hospital costs. Cost efficiency efforts must be made. That is no deficit from the applicable INA-CBGS tariff. Quality and cost control efforts are very important in the implementation of ENT specialist poly services. This study aims to analyze the demographic characteristics of the patient, the patient's diagnosis, the difference in rates between INA CBGS payments and RSIS rates, the composition of financing and the Unit Cost of ENT Polyclinics. The research type is quantitative observational with cross-sectional design. The research location is at the Surabaya Islamic Hospital with BPJS TXT data, processing in January-December 2019. The results showed, the demographic characteristics of most patients were > 50 years old, and most of them were diagnosed with minor chronic diseases. The difference between Ina-CBGS payments and RSIS rates is Rp. 60,174 which means that each patient contributes a profit of Rp. 60,174. The composition of the financing for implementation of the ENT Polyclinic is the cost of consulting services. The unit cost of ENT Polyclinic patients is Rp. 132,774 per patient.
ANALYSIS OF ELECTRIC CIGARETTE USE BEHAVIOR IN YOUTH AGED 15-24 YEARS IN THE SURABAYA CITY Vivi Iftitah Illaeni; Dwi Handayani; Pulih Asih, Akas Yekti; Ibad, Mursyidul
TEKNOLOGI MEDIS DAN JURNAL KESEHATAN UMUM Vol 7 No 1 (2023): Medical Technology and Public Health Journal March 2023
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/mtphj.v7i1.3566

Abstract

The results of the GATS survey show an increase in the prevalence of electronic smokers up to 10 times, from 0.3% in 2011 to 3% in 2021. East Java Province is one of the provinces with a percentage of electric smokers over the age of 15, as much as 27.28%. This study aimed to analyze the behavior of using e-cigarettes in adolescents aged 15-24 years in Surabaya city. This research method is the quantitative descriptive-analytic cross-sectional approach. The sample of this research is adolescents aged 15-24 years in Surabaya city, with a total of 157 respondents. This research uses an accidental sampling technique. Data analysis is in the form of univariate and bivariate analysis (chi-square). The results showed that the respondents' intention to use e-cigarettes was mostly in the weak category, 59.2%. Support from friends in using e-cigarettes is mostly in the strong category, 61.1%. Family support for using e-cigarettes is mostly in the weak category, 55.8%. Most respondents are in the difficult category of accessing health information related to the dangers of e-cigarettes, which is 62.4%. Access to the affordability of most respondents in the easy category is 65.6%. The conclusions in this study are that there is a strong relationship between the intention and behavior of using e-cigarettes in adolescents, there is a low relationship between friend support, family support, access to health information related to the dangers of using e-cigarettes, access to convenience and behavior of using e-cigarettes in adolescents. It is hoped that healthcare profetionals can provide preventive efforts to educate the public, especially adolescents, regarding the dangers of e-cigarettes for health to prevent chronic diseases caused by e-cigarettes.
COMPARISON OF XGBOOST AND RANDOM FOREST METHODS IN PREDICTING AIR POLLUTION LEVELS Pulih Asih, Akas Yekti; Yudianto, Firman; Triwinanto, Puguh; Sinatriya Marjianto, Rachman; Herlambang, Teguh; Arof, Hamzah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0785-0796

Abstract

Air is one of the elements needed by living things, including humans, to survive. The air quality in an area also affects the health and quality of human life and its surrounding environment. However, with the current phenomenon, the influence of the increasing number and mobility of humans actually degrades air quality, caused by the pollutants produced. For further impacts, poor air quality can reduce human life expectancy. Big cities in Indonesia, such as Surabaya, also experience the same thing due to the lack of public awareness of air pollution. The biggest contributors to air pollution are motor vehicles and industrial activities that emit carbon monoxide (CO), nitrogen oxides (NO), ozone (O3), and other particles (PM10). This condition is addressed by the Surabaya City Government by installing air condition measuring devices at points considered prone to pollution. This device works to measure urban air conditions daily and provides data that can be utilized to establish strategic policies. By utilizing the data, in this research, we implemented two prediction methods from machine learning technology, namely XG Boost and Random Forest. In accordance with the objective of this research, both methods will be compared for accuracy in predicting air pollution levels in Surabaya based on Ozon (O3) substance within the period of January 1, 2020, to December 31, 2020. Both of them have a similarity in that they implement tree-ensemble based, which are appropriate for handling non-linear data. The XG Boost method managed to achieve the best error value of 0.0510, and the Random Forest method reached the best error value of 0.0468.