Justicia gendarussa Burm.f., a medicinal plant, is Acanthaceae that has many functions. Furthermore, the compounds in gendarussa must be produced in high quantity and quality by applying callus culture method. Accordingly, it is important to study the effects of plant growth regulators (2,4-D, IBA, and BAP) on callus induction of gendarussa leaves. This research design utilized a factorial design with two factors (2,4-D and IBA: 0.5, 1, 1.5 mg/L and BAP: 0.5, 1, 1.5, 2 mg/L). The experiment consisted of 24 treatments, each of which was repeated 3 times. Observation was carried out in 6 weeks. Data on the time of callus formation, percentage of explants formed callus, and callus morphology were analyzed descriptively,while data on fresh and dry weight were analyzed by Two-Way ANOVA (α = 0.5). Interestingly, the results showed that various concentration of plant growth regulators (2,4-D, IBA, and BAP) affected callus induction from leaf explants of gendarussa. We concluded that the most optimal treatment combination of concentration of plant growth regulators in inducing callus from leaf explants of gendarussa is 1.5 mg/L 2,4-D and 2 mg/L BAP with a relatively long period of callus formation at the earliest, i.e. on day 5, 2.247 g of fresh weight, 0.108 gof dry weight, white callus translucent, and friable. Moreover, the optimum treatment will be used to produce secondary metabolite and seed synthetic by cell suspension culture.

Hypertension has become a serious health problem in Indonesia because of its prevalence, however, the causative factors could not be ascertained for about ninety percent of the patients. Various studies have found several risk factors causing hypertension to be obesity, family history, stress levels, heart rate, and an unhealthy lifestyle. In this case, the variables are considered influential on hypertension through a regression curve without a specific pattern. Also, we need to describe the functional relationships between several predictor variables with binary or dichotomous response variables and need to describe locally effect of predictor variables to the response variable. Therefore, in this study, to model the case of hypertension by age, body mass index, heart rate, stress levels we use the additive nonparametric logistic regression approach based on local linear estimators. The results of the study showed that hypertension was most prevalent among respondents over 65 years of age with BMI between 25-30 kg/m2 (obesity) and normal heart rate (60-100) bpm and most of them were found to be experiencing mild stress conditions. The model obtained a classification accuracy of 95 percent (in-sample) and 89.47 percent (out-sample) with a cut off probability value of 0.4.

Hypertension called as the silent killer, is the number one non-infectious disease that causes death in the world every year. There are 185,857 cases recorded in 2018 in Indonesia. In this study, we model the hypertension risk by considering age, heart rate, hypertension history of family, eating salty foods, and smoking or exposure to cigarette smoke as the influence factors of hypertension risk. A cross-sectional survey was conducted in August 2018 at the Haji Hospital of Surabaya. Logistic regression is used to analyse the influence of various risk factors on hypertension and non-hypertension. In addition, we compare between logit and gompit link functions in logistic regression to build the modelling of hypertension risk factors based on the accuracy of the classification model. By using logit and gompit link functions, we obtain percentage of the classification accuracy are 85.2 % and 81.5 %, respectively. It means that the logit link function is better than the gompit link function for modelling hypertension risk factors. For these link functions, the significant factors that influence hypertension are age and heart rate.

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