<p><em>Dengue</em><em> Hemorrhagic fever (DHF) is a </em><em>major </em><em>public health problem in Indonesia where the number of reported cases per February 2019 reached 16.692 cases with 169 deaths. North Sumatera is an endemic area of dengue fever with a number of cases in 2017 of 5.454 and an IR number of 49 per 100.000 higher than the national target figure. Challenges on input indicators make the DHF eradication program run</em><em> </em><em>less optimally</em>. <strong><em>Method</em></strong><em>: This research  was an qualitative study, which research design was a case study. The location taken in this study at the North Sumatera Provincial Health Office, the study was conducted from October to December 2018. The informants studied were 2 people. The research subjects were taken based on purposive sampling. Data collection techniques are carried out by in-depth interviews and observations, with research instruments in the form of interview guidelines and observation guidelines. <strong>Results</strong>: Analysis of input indicators in the DHF  eradication program at the North Sumatra Provincial Health Office found findings of Human Resources consisting of 2 doctors, 1 sanitarian staff and 1 expert epidemiologist (S2), still lacking funds in the DHF program. and the infrastructure of the DHF program consists of 2 liters of insecticide, 100 Rapid tests, 300 bottles of larvacide, and extension media in the form of banners. <strong>Conclusions and suggestions</strong>: Input indicators on the eradication program of dengue hemorrhagic fever at the North Sumatra Provincial Health Office have been fulfilled, namely on human resources and infrastructure, while the challenges of the DHF program in the North Sumatra Provincial Health Office are funding and counseling media. Suggestions for the North Sumatra Health Office, the allocation of funds needs to be evaluated as well as requests for allocation of funds to the center according to the ideal funding allocation.</em><em></em></p>

The spread of dengue hemorrhagic fever (DHF) globally with a frequency level that tends to be high in the past 50 years raises a systematic idea of prevention. One of the efforts to prevent DHF is the need for early identification of areas that are potentially epidemic. Early identification is carried out by getting an overview of the incident one step ahead by data forecasting. The focus of the study was the development of area stratification algorithms as an early identification of DHF outbreak areas by using data forecasting methods with surveillance data variables. Surveillance data which became the references for system modeling were DHF case data, rainfall, humidity, air temperature, wind speed and Larva-free Number (ABJ) for the span of 2010-2016 in 17 districts in Sleman Regency, Special Region of Yogyakarta. There were four steps during the study, i.e., 1) Forecasting of DHF case for the period of 12 months, 2) Forecasting of Larva-free Number (ABJ), 3) Determination of DHF case pattern for the last three years and the average of ABJ in the third year and 4) Area classification into stratification class. A method used for data forecasting of DHF case was seasonal autoregressive moving average (SARIMA), and the determination of area class pattern was conducted by using a neural network, meanwhile to obtain area stratification class used rule-based approach referring to guidelines controlling DHF outbreaks of the Ministry of Health of the Republic of Indonesia. Early identification was carried out by dividing into 4 area classes. Area class target included endemic (K1), sporadic (K2), a potential (K3) and free (K4). The testing of accuracy forecasting used relative mean absolute error (RMAE) for 12 months period. The results of the forecasting accuracy test on 17 districts in Sleman Regency showed RMAE average of 1.46 was considered low for it was still below 10%. Furthermore, the results of the early identification of area stratification classes in 2014 and 2015 from 17 districts showed that 3 of the four regions were endemic areas while in 2016 almost all districts were endemic areas and only one area was classified as sporadic.

Potensi tanaman obat yang beragam banyak dimanfaatkan oleh bidang kesehatan karena kandungan senyawa kimia didalamnya. Bunga telang (Clitoria ternatea) merupakan jenis tumbuhan berbunga yang berasal dari suku polong-polongan dengan warna keunguan yang memiliki kandungan senyawa antosianin sebagai sumber antioksidan. Salah satu bentuk pemanfaatan Bunga telang yaitu diolah sebagai minuman kesehatan. Walaupun demikian, informasi pemanfaatan Bunga telang sebagai minuman kesehatan masih sangat jarang diketahui oleh masyarakat, khususnya Desa Manik Maraja. Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan edukasi pemanfaatan Bunga telang sebagai olahan the kepada masyarakat Desa Manik Maraja. Kegiatan ini dilaksanakan pada bulan Maret 2021 dengan metode ceramah berbantuan media Project Still Media. Hasil yang diperoleh dari kegiatan ini yaitu adanya pemahaman masyarakat Desa Manik Maraja terkait proses pembuatan dan peluang usaha teh Bunga telang. Hasil dari kegiatan ini diharapkan dapat menindaklanjuti oleh masyarakat Desa Manik Maraja melalui pembudidayaan dan pemanfaatan teh Bunga telang sebagai salah satu cara pola hidup sehat.

This study aims to determine the effect of discovery learning strategies assisted by smart classroom applications on digital literacy skills in students and to compare the experimental class's digital literacy better than the control class after being given treatment. This type of research is a quasi-experimental research with a pretest-posttest control group research design. Data was collected using an instrument in the form of a questionnaire to measure students' digital literacy skills. The population and sample in this study were students of SMP IT Al-Hijrah 2 Laut Dendang class VIII B totaling 30 students and class VIII C totaling 30 students. In determining the pretest and posttest, the instrument validity test was carried out in the form of a questionnaire that had been validated by the validator. After obtaining data from the results of the pretest and post-test, The post-test results were obtained by class VIII C as the experimental class with an average value of 81 and Class VIII B as the control class with an average value of 65, namely that the calculation of the t-test on the posttesttcount (15.897) > ttable (2.001) and sig. (2-tailed) = 0.000 where (0.000 < 0.05) with a 95% confidence level the data is significant. Then Ha accepted these things showing that 1)There is an effect of using discovery learning strategies assisted by smart classroom applications on students' digital literacy skills,2) The experimental class that uses the discovery learning model on digital literacy skills in students is higher than the control class that uses the conventional learning model, namely the lecture method.