Search

The purpose of this study is to develop ethnosains learning modules that are feasible and practical for use after being validated by several experts and responded by several teachers and students. The research method uses the Borg & Gall development model which consists of 8 stages, namely a preliminary study stage, a research planning stage, a design development stage, an initial trial phase, an initial product revision, a limited field test, a revised stage of the results of a limited field test, and a product stage end. This research is limited to the limited field trial stage namely the feasibility and practicality of the module. The instrument used was a questionnaire for module eligibility and student and teacher response questionnaires to test the practicality of the module. Data from the analysis of the questionnaire by calculating the percentage of achievement in each component of the percentage of achievement criteria of eligibility and practicality of science learning modules based on ethnics that was developed. Ethnographic-based science learning modules developed were declared feasible to be used with a percentage of 90.00% (linguists), 88.00% (material experts), 96.00% (design / media experts) with the very feasible, feasible, and very feasible and the percentage of eligibility of 3 colleagues is 91.46%. Practical to use with the response percentage of 10 students 84.83% (very practical category), and the response of 2 science teachers with a percentage of 93.40% (very practical category). Practical to use with the response percentage a total average of 10 students namely 84.83% are in the interval of 80% ≤ PRM ≤ 100%. And based on the teacher’s questionnaire response that is 93.40% which is included in the category of very practical From the results of these data it can be concluded that the module has been feasible and practical to be used as teaching material in supporting the teaching and learning process on the material interaction of living things with their environment.

One strategy for a company to develop and grow bigger and stronger in competition is by business expansion. According to Moin (2010:2), there are two strategic ways to maintain and expand a business, that is, an internal expansion strategy by building a new business or business unit from scratch and an external expansion strategy in the form of a business merger by buying an existing company through a merger, acquisitions and consolidations which are fast-track to new markets. Profitability is a factor that gets important attention because it can attract investors to make investment in the company. Profit is the gab beetwen revenue and expenses in a certain period in a company. It has very important role for either internal or external of the company. One way to reduce the risk of company losses is by using an estimation method to find out the company’s estimated profit for the next month or next year. In this study the estimation method for travel company was used, that is, by using the Ensemble Kalman Filter (EnKF) and H-infinity, as a policy making chart in order to maintain and increase company profits. Based on the analysis of results computation with 100, 200 and 300 iterations, it showed an error of less than 3%.

Indonesia is a country with a very prominent marine charm, and it is the largest archipelago in the world, covering about 50% of the coral triangle area, providing marine tourist resorts. Therefore tourism development is quite promising. For that purpose, simple boats are of necessity for tourists to enjoy the beauty of such marine tourism. One solution to support such marine tourism sector is the availability of Autonomous Surface Vehicle (ASV). This vehicle will be the interest of this paper. This study used Touristant ASV with dimensions of 1.5 m in diameter, 4 meters in length and 1.3 meters in height. The purpose of this paper is to conduct a study with a focus on the estimation of ASV position with ASV motion influenced by wind speed and wave height by applying the H-infinity method. The position error generated from the simulation shows that the position error has an accuracy of about 96%.

This article aims to test a facial recognition-based front door security system, which can also convey relevant information to the owner’s mobile phone via an SMS gateway. This system is necessary to prevent unwanted criminal activity by the owner. The method used is Hercascade as face recognition for security. Use a set of webcam settings to compare human face objects in the background with face data already stored in the database. Capture images using a Raspberry PI connected to a USB webcam for the sensor, move the front door using a servomotor as a drive, and own the system in the form of a short message from basic communication process data Notify to. There is also an ultrasonic sensor as an activation system to detect human objects when they approach the door and invade. Based on the results of 90 tests on a system with varying distances of objects on the camera (30 cm, 40 cm, 50 cm), the average pass rate of the tests is 91.11%. We can conclude that face recognition by the Hercassette method can be applied as an entrance security system.