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Lack of physical activity is one of the top ten risk factors for death. People who are not physically active have a greater risk than those who do physical activity regularly. Nowadays, there is a phenomenon of decreasing physical activity in Indonesia. It turns out that a similar thing happened among employees of the Ministry of Health as seen from a decrease in employees who carried out physical fitness measurements. The measurement of physical fitness is still done manually, both in the measurement and in the database system. Measurements are made using a stopwatch and the distance is measured manually. The database system used is a single system, this makes data processing more difficult. Studying such conditions, this research will propose a mobile-based application model. This study aims to build a physical fitness measurement information system that can increase awareness of the importance of measuring fitness and foster employee interest in measuring physical fitness. The system development method used in this physical fitness measurement information system uses a prototyping model approach. Testing applications using Blackbox Testing and acceptance of system technology using the Technology Acceptance Model (TAM) trial. The system developed based on the research stages has been as expected, namely optimizing the process of implementing physical fitness measurements that have been running manually.
Quality basic health services are still facing obstacles in Indonesia. One of the efforts that can be done is to carry out accreditation of puskesmas. The District/City Health Office plays an important role in implementing the accreditation of puskesmas as a companion in charge of preparing puskesmas to face the accreditation survey by the Accreditation Committee. Accreditation assistance activities are part of the guidance, supervision and control activities which are the main tasks of the City Service Office. Unfortunately, this activity encountered many obstacles because manual scheduling, recording and reporting caused difficulties in terms of coordination, storage, monitoring and determining follow-up plans. This study aims to design a prototype of the E-Binwasdal application for puskesmas accreditation which is able to ensure the availability of quality data and information on mentoring activities that are quickly and easily accessible so as to facilitate efforts to develop, supervise and control the accreditation status of puskesmas. The research consists of system requirements analysis, prototype design and user acceptance test. The result of the research is a prototype of E-Binwasdal accreditation of puskesmas with a web-based platform. The developed information system can provide easy access to accurate, relevant and up-to-date information; save costs; ensure the control of data storage and security; flexible, easy and convenient for users to use in accreditation assistance activities. The information system provides a solution in identifying information on the achievement of the accreditation status of puskesmas in Central Jakarta
Studi observasionad dengan desain cross-sectional senng menimbulkan masalah akibat potensial confounding, yaitu suatu kondisi yang menyiratkan texjadinya ketidaktepatan perbandingan antara kelompok terpajan dan kontrol serta potensial menghasilkan bias pada estimasi cfek Estimasi efek yang paling ideal adalah membandingkan outcome pada satu subyck saat mendapat pajanan dan saat tidak mendapat pajanan pada saat bersamaan, hal ini tidak mungkin terjadi karena outcome dari satu peristiwa hanya ada satu, dan disebut sebagai counte1j`actuaI]5-ameworlc Regresi sebagai analisis multivariat yang paling umum dipakai hanya melakukan aeiusnnent pada variabel confounder dalam menghasilkan estimasi, sehingga parameter yang dihasilkan bukan berdasaxkan atas perbandingan antar subyek meiainkan nilai kelompok. Hal ini yang membuat hasil Estimasi analisis regresi masih memiliki bias akibat seleksi subyek pada kelompok Propensity score marching adalah analisis yang menggunal-can pemadanan berdasarkan nilai propensity dari kelompok tcrpajan dan kontrol, sehingga masing-masing subjek pada kelompok terpajan akan memiliki padanan dengan karakteristik yang sama pada kelompok kontrol. Pemadanan mengakibatkan asumsi excharzgeability dalam cozmterfactual fiamework terpenuhi, sehingga dapat mereduksi bias seleksi. Penelitian ini bertujuan mcmbandingkan hasil analisis regresi logistik dengan analisis propensity score matching (PSM) dalam melihat pengaruh tingkat aktivitas olahraga terhadap kebugaran jasmani berdasarkan data Sport Development Indeks (SDI) 2006. Pcrbandingan dilakukan dengan memodelkan variabel berdasarkan regrcsi logistik. Model akhir yang didapat pada regrcsi logistik akan dianalisis kembali menggunakan analisis propensity score matching (PSM). Desain penclitian yang digunakan adalah cross-sectional 66113811 menggunakan data sekunder dari sutvei SDI 2006. Model yang digunakan dalam penelitian ini arhlah model faktor resiko yang berusaha untuk menilai pajanan tingkat aktivitas olahraga terhadap status kebugaran dengan faktor yang menjadi potensial confounder adalah variabel ruang terbuka olahraga, sumber daya manusia olahraga, usia, gender, Indeks Massa Tubuh, pekeljaan, propinsi dan sosial ekonomi kabupaten. Dari hasil penelitian di dapat dua perbandingan yaitu perbandingan nqgrcsi logistik dengan PSM tanpa interaksi dan dengan intexaksi. Pada kedua jcnis perbandingan, PSM berhasil memadankan 100% responden. OR dari PSM tanpa interaksi 1,28 sedangkan OR daxi regresi logistik l,3. Perbedaan yang tidak begitu besar ini dimungkinkan karena variasi dari variabel oovariat dari kelompok texpajan dan kontrol tidak terlalu besar sehingga a¢#u.s'nnen1 pada regresi logistik mampu menjaga keséimbangan variasi antara kedua kelompok. Pada pcrbandingan PSM dengau interaksi, dilakukan stratifikasi pada data berdasarkan variabel yang berintemksi pada regresi Iogistik. Analisis PSM kemudian dilakukan untuk masing-masing strata Hanya ada satu OR yang berhasil didapai pada analisis PSM dari tiap strata, tiga OR lain tidak dapat dihitung karena nilai nol pada mean of marched control setelah proses pemadanan. S6C8I`3 statistik terdapat hubungan antara tingkat aktititas olahraga dan kebugaran jasmani meskipun dengan ni [ai efek yang kecil.
Observational study with cross-sectional design often generate problem of potential sffect of confounding, which is a condition that implies improper comparison between 'reated and control group and also yield potentially biased effect estimation. The most ideal effect estimation is, by comparing outcome from one subyek given exposure and not given exposure at the same time, this matter is not possible because outcome &'om one event only happen one, this is call counterfactual framework. Regression as a commonly multivariat analysis only do adjustment for confounder variable in generating estimation, so the parameter yielded not based on comparison betwen subyek but based on group parameter. This make regression analysis still has bias from subjek selection for control group. Propensity Score matching is analysis use matching metode based on propensity score from exposed and control group, so each subjek from exposed group will have match with equivalent characteristic at control group. Matching cause exchangeability asumption in counterfactual framework firllfiled, so that can reduce selection bias. This research aim to compare result from logistic regression analysis with propensity score matching (PSM) analysis in seeing the influence of sport activity level to physical fitness based on data of Sport Development Index (SDI) 2006. Comparison conducted with modeling variable using logistic regression. The final model from logistic regression will be re-analysed using PSM analysis. Research design is cross-sectional and using secondary data from SDI 2006 sim/ey. Model used in this research is risk factor model to assess exposure from sport activity level to physical fitness status with potential confoundef are sport facility, sport human resources, age, gender, body mass Index, work, districk social-economic statins and province variable. The result from this research is earning two comparison, which is comparison betwen logistic regression by PSM without interaction and with interaction. At both types of comparison, PSM succeed to match 100% responder. OR from PSM without interaction 1,28 while OR iiom regresi logistics l,3. The OR difference is not so big because eovariat variation variable from exposed and control group is not too big so that adjustment of logistic regression able to balance variation among both group. The PSM comparison with interaction, conducted by stratification of data using variable which have interaction at logistic regression Alter that PSM Analyse is conduct to each strata. There is only one OR successfully got from PSM analysis of each strata, three other OR can’t be compute because zero value at mean of matched control after matching process. Statistically there are relation between sport activity level and the physical fitness though with small effect value.