Penelitian ini membangun sebuah Smart Home berbasis IoT menggunakan suara pada Google Assistant. Hal ini dibutuhkan sebagai solusi untuk orang sakit yang berada di kursi roda/tempat tidur atau orang disabilitas tetapi dapat berbicara atau orang lanjut usia yang tidak dapat mencapai saklar agar dapat menghidupkan/mematikan perangkat rumah. Selain itu, agar dapat mengontrol perangkat rumah dari jarak yang sangat jauh. Sistem yang dibangun menggunakan perintah suara pada aplikasi Google Assistant di android. Google Assistant mengubah perintah suara menjadi teks. Teks tersebut kemudian diteruskan dari Google Assistant ke Webhooks oleh IFTTT. Webhooks akan melakukan request ke HTTP RESTful API. Dengan library phpMQTT yang terdapat di HTTP RESTful API, perintah di publish ke MQTT Broker. ESP32 Dev Kit sebagai microcontroller yang terhubung dengan internet menerima perintah dari MQTT Broker untuk menyalakan atau mematikan lampu yang ada di rumah. Pada pengujian sistem telah berhasil menyalakan dan mematikan lampu dengan perintah suara menggunakan Google Assistant.
Abstract --Lung is one in control in the circulatory system of air (oxygen) in the human body, so the detection of disorders of the human respiratory urgently needed to detect any disturbance in the lungs used X-ray beam, from the results of x-ray image of the thorax contained information used to analyze and determine the shape of an object from the lungs, in order to obtain such information, a process of segmentation. In this study used methods Distance regularized Levelset Evolution (DLRSE), this method region based models which is an improvement of edge-based models. The purpose of this study to implement segmentation methods DRLSE the lungs of the results of x-ray image of the thorax. The trial results with the system DLRSE method performed on the 20 data from X-ray image of the thorax obtained an average result accuracy of 87.90%, a sensitivity of 76.27% and a specificity of 93.98%.
There has been a trend of utilizing mobile tools in the university. This study is proposed to construct mobile learning media based on Android for Madrasah Ibtidaiyah or Primary School in Learning Strategy courses. The study participants were university students of Madrasah Ibtidaiyah Teacher Education in Malang. The study design was R and D with both quantitative and qualitative data. The study result have been in the form of mobile learning media based on Android. Six expert judgments have validated this product to ascertain the feasibility of the designed prototype. The validation by material experts' validation results were 91% and 89% valid, while validation rates by design experts were 93% and 92%. The validation result by learning experts showed 88% and 89% valid. The design was tested to three students with individual trials, then to a small group trial with ten students, and finally, a field trial on an experimental class of 43 students using a questionnaire. The trials' result on small groups showed 88% valid, and the field trials showed 86% valid. The findings indicated that Android-based mobile learning on learning strategy course material had a better effect than conventional learning on student learning outcomes.
This study aimed to predict the service level agreement travel time for goods and document shipments at PT Pos Indonesia (Persero) from the island of Java to the islands of Kalimantan, Sulawesi, Maluku and Papua. This is very important because of the high competition between the logistics industry which is getting faster and faster. The random forest method was chosen because this method is easy to use and flexible for various kinds of data. The prediction results with Random Forest in this study have a good level of accuracy, namely 83.86% of the average 4 trials. This shows that the Random Forest method is the right choice for managing the existing data model at PT Pos Indonesia.
The aim of this paper is to design a prototype model that can be used to better understand development equity for villages in terms of public monitoring and evaluation. In designing the model, the research has reviewed several techniques of big data analytics as well as alignment of business strategic objectives and technology. The prototype model also tested using several types of data. Although some obstacles have found, as it also found in the reviewed literature, a prototype model which can guide researchers and practitioners to understand ways to capture public monitoring is presented in this paper. Furthermore, Information systems researchers could use this prototype model for further research to get a deeper understanding of big data analytics roles for development, particularly in developing countries.
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