fariqM
Web & Mobile Apps Developer | maulana.fariq30@gmail.com
UIN Sunan Ampel SurabayaSidoarjo, Indonesia.
Pinned Repositories
awesome-landing-page
A series of beautiful and practical landing page templates
BankSampah
benchmark.js
A benchmarking library. As used on jsPerf.com.
Best-Flutter-UI-Templates
completely free for everyone. Its build-in Flutter Dart.
BisnisCerdas_PY
Blooddonorprediction
Thanks to digitization, we often have access to large databases, consisting of various fields of information, ranging from numbers to texts and even boolean values. Such databases lend themselves especially well to machine learning, classification and big data analysis tasks. We are able to train classifiers, using already existing data and use them for predicting the values of a certain field, given that we have information regarding the other fields. Most specifically, in this study, we look at the Electronic Health Records (EHRs) that are compiled by hospitals. These EHRs are convenient means of accessing data of individual patients, but there processing as a whole still remains a task. However, EHRs that are composed of coherent, well-tabulated structures lend themselves quite well to the application to machine language, via the usage of classifiers. In this study, we look at a Blood Transfusion Service Center Data Set (Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan). We used scikit-learn machine learning in python. From Support Vector Machines(SVM), we use Support Vector Classification(SVC), from the linear model we import Perceptron. We also used the K.neighborsclassifier and the decision tree classifiers. We segmented the database into the 2 parts. Using the first, we trained the classifiers and the next part was used to verify if the classifier prediction matched that of the actual values.
BMI
This website is a prototype of an information system that is engaged in the inventory sector. This system generally monitors the process of making an item in each part, where users can search for the status of the process of goods at the time of manufacture.
capacitor-google-maps
Capacitor Plugin using native Google Maps SDK for Android and iOS.
crud-generator
Laravel CRUD Generator
RunAway-mobile
A run tracking application with calories calculation based on Android platform using React Native, Maps API, Firebase, Redux.
fariqM's Repositories
fariqM/RunAway-mobile
A run tracking application with calories calculation based on Android platform using React Native, Maps API, Firebase, Redux.
fariqM/awesome-landing-page
A series of beautiful and practical landing page templates
fariqM/Blooddonorprediction
Thanks to digitization, we often have access to large databases, consisting of various fields of information, ranging from numbers to texts and even boolean values. Such databases lend themselves especially well to machine learning, classification and big data analysis tasks. We are able to train classifiers, using already existing data and use them for predicting the values of a certain field, given that we have information regarding the other fields. Most specifically, in this study, we look at the Electronic Health Records (EHRs) that are compiled by hospitals. These EHRs are convenient means of accessing data of individual patients, but there processing as a whole still remains a task. However, EHRs that are composed of coherent, well-tabulated structures lend themselves quite well to the application to machine language, via the usage of classifiers. In this study, we look at a Blood Transfusion Service Center Data Set (Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan). We used scikit-learn machine learning in python. From Support Vector Machines(SVM), we use Support Vector Classification(SVC), from the linear model we import Perceptron. We also used the K.neighborsclassifier and the decision tree classifiers. We segmented the database into the 2 parts. Using the first, we trained the classifiers and the next part was used to verify if the classifier prediction matched that of the actual values.
fariqM/BMI
This website is a prototype of an information system that is engaged in the inventory sector. This system generally monitors the process of making an item in each part, where users can search for the status of the process of goods at the time of manufacture.
fariqM/d2-admin
:rainbow: An elegant dashboard
fariqM/laravel-money
Currency formatting and conversion package for Laravel
fariqM/laravue
Admin dashboard for enterprise Laravel applications built by VueJS and Element UI https://laravue.dev
fariqM/react-native-audio-streaming
iOS & Android react native module to play an audio stream, with background support and media controls
fariqM/react-native-maps
React Native Mapview component for iOS + Android
fariqM/RealTime-Laravel
A simple RealTime chat app using Laravel, Vuex, and Pusher.
fariqM/Shovee-Frontend
Clone Shopee e-commerce built with React Native
fariqM/SOLID_Laravel
A basic concept of solid programming using laravel framework
fariqM/Tugas1_BC