Technology is everyplace we go in moment's life. So, scholars of seminaries or sodalities, or universities bear an operation that supports smartphones to get all types of information related to ...examination, lecture notes, placement, systems regarding announcement, events, transportation, etc. Rather of calling systems because nearly all mobile druggies have smartphones currently. This being system takes a pupil list and allocates administrators to scholars. Using a manual system in the management and allocation of projects to students is characterized by many problems, including the Inability of the project Guide to know that a title has been approved already for a student. Difficulty and inappropriate documentation of allocated project topics. Ineffective in entering, updating, and retrieving records of allocated projects. Difficulty in accessing the project Guide for approval of the topic. Duplication in project topics approved for students. We designed an operation to attain the demand of scholars. The main ideal of the pupil design allocation system is to make a system that will give information for each pupil. Projects can efficiently be allocated to students without delay, and topic conflict between students in the same department will not arise here. Pupil updates can be fluently penetrated if the database system is enhanced. This design will give a fruitful way to manage data at a low cost. The Student Project Allocation contains colorful options similar as login/logout, viewing and streamlining data, etc. It'll be secure. Data can be used by only those with an id and word while maintaining the data.
Recognition and mastery of the hijaiyah letters which are the basis for reading and studying the Holy Qur'an from an early age is very important, because if at the time of reading the hijaiyah ...letters you are accustomed to the wrong words it will cause different meanings so that we are required to read properly and correctly. The method in learning hijaiyah letters is usually given by traditional (conventional) reciting teachers or people often call it the sequential method. With this kind of teaching, children tend to be passive in accepting their teaching lessons, because the Koran teacher explains the children in learning to read hijaiyah letters orally, in writing and in body language. The application of recognizing hijaiyah letters is very effective and easy to use for students of paud al fina in recognizing and writing hijaiyah letters because the design of the learning aid program to read hijaiyah letters is a method in the form of visualization in the form of images, text and sound. To implement this method, the author uses Android Studio programming which acts as a tool (programming system) used to build an application, this application program is expected to generate interest for early childhood or adults who want to learn how to learn to read hijaiyah letters properly and correctly. accommodated.
Online Marketing For Farming Using Android Baskar, Dr.Radhika; Saleem, S.
International journal of engineering and advanced technology,
09/2019, Volume:
8, Issue:
6s
Journal Article
Open access
Our nation is a developing based making country. Data spread to the learning rise agribusiness development zone is dismantle by ready to give the specialist information organizations and quick ...advancement of convenient correspondence. It traverses any boundary between the openness of cultivating data and transport of horticulture development yields and agribusiness system. Versatile handling, appropriated processing, AI and fragile figuring is the immerging strategies which are being used in for all intents and purposes all fields of research. Besides this, they are in a like manner important in our regular activities, for instance, guidance, remedial and agribusiness development. This undertaking inspects how Android Apps of green associations have impacted the ranchers in their creating exercises
In Indonesia, the problems of pregnant women and newborns have not been resolved. The reason is that there is no monitoring system for pregnant women and newborns. This study aims to build a ...monitoring system for pregnant women and newborns. The monitoring system that will be made is mobile-based that can monitor and provide information about the health of pregnant women and children. The model used to create an information system uses the waterfall model. Meanwhile, to test the system built using the Blackbox test model. The plan that was created was tested directly to the user. As a result, the sequence in the waterfall model is proven to build a monitoring system for pregnant women and newborns. The black box model also showed if the built system did not have errors and was ready to be used. Combining the waterfall and BlackBox models results in a monitoring system for pregnant women and newborns whose entire menu can be used properly. The test was carried out on 25 pregnant women users, and it was found that the accumulated ratings were 89, 87, 88, and 89%. In this case, it is classified as Very Eligible.
Papaya plant disease can lead to substantial harvest and financial losses for crop owners, potentially affecting the overall income of Malaysia’s agriculture sector. Integrating Artificial ...Intelligence into the agriculture sector can be a significant leap in attracting young agropreneurs and assisting both existing and young farmers in identifying papaya plant diseases. In line with these challenges, this project proposes papaya plant disease identification using a Convolutional Neural Network (CNN). A total of 225 images were collected from Google sources and real-life captured images, consisting of 3 different classes: Healthy, Ring Spot, and Black Spot. After the preprocessing and augmentation process, a total of 600 images were obtained. Out of 25 Keras API pre-trained CNN models, InceptionV3 was selected as the best base model, as it achieved the highest validation accuracy during a 10-epoch run through Google Colab. Hyperparameters were tuned to obtain the best results by inputting the training images from the top of the base model and extracting 2048 output features from the last layer of the Inception V3 model. The extracted features were saved in the form of NumPy arrays to be employed in the pipeline for hyperparameter tuning, thereby improving the tuning efficiency. The results show the tuned training data achieved a validation accuracy of 1.0 using a batch size of 4, a learning rate of 0.01, and 50 epochs with the SGD optimizer. With this set of hyperparameters, a full model training was conducted with training images as input, resulting in a training accuracy of 1.0 and validation accuracy of 0.96. The trained model was exported in the form of tflite file format and used in the app development through Android Studio. Testing the app’s accuracy involved importing selected 15 images from each class into the designed app, resulting in a precision of 0.8889, recall of 0.8889, f1-Score of 0.8889, and accuracy of 0.8889. These results demonstrate that the accuracy of identifying papaya plant disease through papaya leaves using the designed Android-based app was relatively high.
In the dynamic landscape of technology, the intersection of Smart Buildings and Internet of Things (IoT) devices continues to hold substantial promise. The integration of billions of smart devices ...with computing systems empowers the identification, analysis, and influence of various actions in our daily lives. A prevalent approach in IoT implementation involves leveraging Android systems, where Android applications play a pivotal role in front-end management. This paper introduces an innovative Android application designed for the comprehensive management of smart buildings, providing users with real-time data monitoring and control capabilities. The application serves as a bridge, bringing users closer to the operational intricacies of smart building systems. Notably, the application is equipped to send timely alerts when predefined limits for humidity, temperature, or light consumption are surpassed, as well as during specific time periods with detected motion. These alerts prompt users to make informed adjustments and decisions, enhancing overall user engagement and responsiveness. The proposed system architecture comprises five distinct layers: Python scripts for sensor data generation, JSON files for data storage, a Flask-based Application Programming Interface (API) for data analysis and conversion, SQLite for efficient data storage, and the Android application for user interaction. This multi-layered framework ensures seamless integration and robust functionality throughout the smart building management process.
Jasa rental kendaraan ringan dan alat berat merupakan jasa yang memiliki resiko kehilangan yang tinggi, kebanyakan saat ini sistem tracking kendaran mobil masih berbasis web sehingga sulit untuk ...melakukan pelacakan dan kebutuhan informasai update unit rental kendaraan. Pada penelitian ini penulis melakukan beberapa tahapan yaitu wawancara dengan pihak terkait dan mengikuti proses tracking kendaraan melalui system yang sedang berjalan . Kemudian dilanjutkan dengen analisis keperluan pengembangan sistem yang sedang berjalan. Bahasa program yang digunakan dalam pengembangan sistem ini adalah Android studio, Goggle Maps dan dan pemanfaatan GPS yang di perlukan serta menggunakan database MySql. Pengembangan aplikasi tracking kendaraan akan memaksimalkan GPS yang ada pada kendaraan dan fungsi dari Google Maps. Dengan adanya aplikasi tracking kendaraan Berbasis Android diharapkan dapat memudahkan karyawan serta kosumen untuk melakukan proses pencarian data dan informasi, serta pelacakan unit yang berjalan secara singkat.
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