PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING

PT Multi Areal Planing Indonesia (MAPID) is a technology company that offer service cloud computing platform that develops Geographic Information System tools to collect, manage, visualize, and analyze geospatial data which has been operating since 2018. Business to Customer (B2C) is one of the s...

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Main Author: Putu Indra Dani Febrianta, I
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/65526
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:65526
spelling id-itb.:655262022-06-23T15:44:47ZPERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING Putu Indra Dani Febrianta, I Indonesia Final Project Freemium, Purchase Decision, Data Mining, Python, Gradient Boosting INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/65526 PT Multi Areal Planing Indonesia (MAPID) is a technology company that offer service cloud computing platform that develops Geographic Information System tools to collect, manage, visualize, and analyze geospatial data which has been operating since 2018. Business to Customer (B2C) is one of the sectors served by PT MAPID. In running it, PT MAPID applies a freemium business model by providing free map access to users who successfully register on the PT MAPID platform. From January 2020 to September 2021, the conversion rate from freemium users to subscriber licenses is very low, at 0.94%. The main reason is that PT MAPID does not yet have a decision support system for provide free map access because it has not utilized user data. This research was conducted to build a predictive model for user purchase decisions using user data. Furthermore, an application prototype will be built that can be used to run the model. The methodology in this study refers to the Cross-Industry Standard Process for Data Mining (CRISP-DM). Alternative algorithms used in the model development process are Support Vector Machine (SVM), Random Forest, and Gradient Boosting. To handle cases of imbalanced data, SMOTE and ADASYN oversampling techniques are applied. The modeling and prototyping process is carried out using Python as a programming language. Based on the research that has been done, the best model is obtained with the Gradient Boosting algorithm, with the ADASYN oversampling dataset, with an accuracy value of 81%, the precision of 83%, recall of 62%, and f1 of 71%. The model is then implemented on an application prototype based on a Graphical User Interface (GUI). The results of this study are predicted to increase the number of users who buy PT MAPID product licenses by 83%. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description PT Multi Areal Planing Indonesia (MAPID) is a technology company that offer service cloud computing platform that develops Geographic Information System tools to collect, manage, visualize, and analyze geospatial data which has been operating since 2018. Business to Customer (B2C) is one of the sectors served by PT MAPID. In running it, PT MAPID applies a freemium business model by providing free map access to users who successfully register on the PT MAPID platform. From January 2020 to September 2021, the conversion rate from freemium users to subscriber licenses is very low, at 0.94%. The main reason is that PT MAPID does not yet have a decision support system for provide free map access because it has not utilized user data. This research was conducted to build a predictive model for user purchase decisions using user data. Furthermore, an application prototype will be built that can be used to run the model. The methodology in this study refers to the Cross-Industry Standard Process for Data Mining (CRISP-DM). Alternative algorithms used in the model development process are Support Vector Machine (SVM), Random Forest, and Gradient Boosting. To handle cases of imbalanced data, SMOTE and ADASYN oversampling techniques are applied. The modeling and prototyping process is carried out using Python as a programming language. Based on the research that has been done, the best model is obtained with the Gradient Boosting algorithm, with the ADASYN oversampling dataset, with an accuracy value of 81%, the precision of 83%, recall of 62%, and f1 of 71%. The model is then implemented on an application prototype based on a Graphical User Interface (GUI). The results of this study are predicted to increase the number of users who buy PT MAPID product licenses by 83%.
format Final Project
author Putu Indra Dani Febrianta, I
spellingShingle Putu Indra Dani Febrianta, I
PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
author_facet Putu Indra Dani Febrianta, I
author_sort Putu Indra Dani Febrianta, I
title PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
title_short PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
title_full PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
title_fullStr PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
title_full_unstemmed PERANCANGAN SISTEM PENENTUAN FREE MAP ACCESS UNTUK FREEMIUM USER PADA PT MAPID DENGAN METODE DATA MINING
title_sort perancangan sistem penentuan free map access untuk freemium user pada pt mapid dengan metode data mining
url https://digilib.itb.ac.id/gdl/view/65526
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