English is the most widely used international language in communication and is the second language after Indonesian. English will be taught more easily and effectively to children from an early age. But it needs learning media that suits the needs of children’s growth. Learning media should be fun and able to get the child moving to explore the surrounding environment. This research aims to create an English learning application by applying Tensor flow machine learning that is able to recognize objects around us and package them in a learning application in which there is a game that is able to attract the attention of children to learn English. This research was built using the RUP (Rational Unified Process) system development method which consists of 2 dimensions. The first dimension consists of dynamic aspects in development consisting of inception, elaboration, construction, and transition phases. The second dimension represents static aspects which are grouped into 4 important elements, namely who is doing, what, how, and when. The machine learning process consists of 3 stages, namely data input (object image capture), preprocessing, and the training process. The results of this study are in the form of a learning media application that can recognize surrounding objects by applying Tensor Flow-based deep learning. The application consists of 2 parts, namely vocabulary learning and a quiz for the introduction of surrounding objects. Parents have a role to be able to add names and objects to the quiz in the application. The results of the research can be used as a learning medium according to the needs of the child.

The Leuweung Buah Lambosir area of Mount Ciremai National Park is included in the rehabilitation zone, the plant diversity index in Lambosir is in the medium category. Increased knowledge and skills regarding the introduction of plant species for officers in Mount Ciremai National Park is often carried out, but for some officers there are some difficulties in identifying plants quickly and accurately. Deep learning is a branch of machine learning (ML) that uses deep neural networks to solve problems in the ML domain. This study aims to create a leaf detection application using a deep learning Convolutional Neural Network (CNN) approach. The types of leaves used in this study were 6 types of leaves including Sonokeling (Dalbergia latifolia Roxb.), Kuray (Trema orientalis), Bungur (Lagerstroemia sp) , Kibeusi (Rhodamnia cinerea), Guava Rivet (Syzygium densiflorum), and Huni (Antidesma Bunius). Tests were carried out with a total of 600 images: 400 images as training data and 200 images as testing data. Testing of each object produces an accuracy rate above 80%.

Sebagai salah satu perwujudan Undang-Undang 1945 pasal 28b ayat 2, maka anak berhak mendapatkan Pendidikan sejak usia dini melalui Pendidikan Anak Usia Dini (PAUD). Salah satu PAUD yang terdapat di desa ciputat kec. Ciawigebang Kab. Kuningan adalah PAUD Hidayatul Ikhwan. Permasalahan pada PAUD Hidayatul Ikhwan adalah siswa masih mengalami kesulitan dalam belajar mengenal huruf serta membaca dikarenakan jumlah guru pengajar yang terbatas sehingga membutuhkan waktu pembelajaran yang lama untuk mengajari per siswa. Karena itu dibutuhkan sebuah pelatihan dan pendampingan bagi siswa, orang tua dan guru mengenai pemanfaatan teknologi sebagai salah satu media alternatif pembelajaran yang dapat digunakan dimana saja dan kapan saja. Serta pendampingan penggunaan media pembelajaran digital salah satunya dalam bentuk game edukasi agar siswa PAUD lebih mudah dalam belajar mengenal dan membaca huruf karena didukung oleh audio serta tampilan visual yang menarik sehingga siswa tidak merasa jenuh dalam belajar dengan didampingi oleh orang tua di rumah serta guru di sekolah