Data Science - Analisis

Kalbe Nutritions Data Scientist Data Modeling and Model Machine Learning

Link Project: GitHub

You are a Data Scientist at Kalbe Nutritionals and are currently getting a new project from the inventory team and the marketing team.

From the inventory team, you are asked to be able to help predict the number of sales (quantity) of the total number of Kalbe products

■ The purpose of this project is to find out the estimated quantity of products sold so that the inventory team can make sufficient daily stock.

■ Predictions must be made daily.

From the marketing team, you are asked to create a customer cluster/segment based on several criteria.

■ The aim of this project is to create a customer segment.

■ This customer segment will later be used by the marketing team to provide personalized promotion and sales treatment.

The tools that you will use in this project are:

■ Python

■ Jupiter Notebooks

■ Tableau

■ Dbeaver

■ PostgreSQL

Aplikasi Android

TENAN (TEman perjalaNAN)

Link Project: GitHub

Bangkit 2023 Product Capstone Team

C23-PC620 Team

Description

TENAN: a travel app that can search for tourist destinations chosen by tourists, accommodation such as hotels will be netted, simple, only one action. the accommodation location is adjusted to the coordinates where the user is located. without having to look for both separately, in contrast to similar travel applications.

Android Development Team:

A220DSX3200 – Irshal Firdeansyah – Universitas Komputer Indonesia - Mobile Development - [Active]

Cloud Computing Team:

C038DSY3275 – Desiana Fitria Nurjanah – Institut Teknologi Sepuluh Nopember - Cloud Computing - [Active]

C304DSX1364 – Muhammad Ferdiansyah – Universitas Pembangunan Nasional Veteran Jakarta - Cloud Computing - [Active]

Machine Learning Team:

M304DSY1803 - Dinar Wahyu Rahman – Universitas Pembangunan Nasional Veteran Jakarta - [Active]

M132DSX1825 – Sabrina Tiara Bachtiar – Universitas Airlangga - [Active]

M251DSX2939 – Muhammad Teguh Prastyo – Universitas Muhammadiyah Malang - [Active]

Recommendation System (Machine Learning Team)

Collaborative Filtering Recommendation system to predict user preferences or interests based on patterns or associations between users and the items they like. The main concept behind collaborative filtering is that if two users have similar preferences or behaviors in the past, then they are likely to have similar preferences in the future. TENAN using Item-Based Collaborative Filtering. This method predicts user preferences by looking at the similarities between the items selected by the user and other items. If two items have similarities in user preferences, it is likely that the item whose preferences are unknown will also be liked by that user.

Aplikasi AR

Simple Car Modelling AR

Link Project: GitHub

This is a simple AR application based on marked targets made by me, using Unity 3D and Vuforia Engine As the final project of the Kominfo DTS-FGA Metaverse Engineer Batch 1 2023. Because it is simple and fast to make. Moreover, if this AR is developed more fully, it can be used as an AR application to view car models that will be sold without having to go to a vehicle showroom/shop.

Application development team:

Dinar Wahyu Rahman (application AR developer and documentation)

Website

Kopi indie.

Link Project: GitHub

Simple Coffee Shop Website for shops or coffee shops to market their products better.

Contains source code for making a simple coffee shop website.

for more projects, you can visit -> dinarrahman30 (Dinar Wahyu Rahman) (github.com)