A COMPARISON ANALYSIS OF KNN AS A PREDICTIVE MODEL FOR SCOPE-1 GHG EMISSIONS FROM INDONESIAN CEMENT MANUFACTURERS TO RANDOM FOREST, AND MLR

KAUTSARINA, DINDA FATIMAH (2025) A COMPARISON ANALYSIS OF KNN AS A PREDICTIVE MODEL FOR SCOPE-1 GHG EMISSIONS FROM INDONESIAN CEMENT MANUFACTURERS TO RANDOM FOREST, AND MLR. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Despite being a significant contributor to the nation's GDP and expected to grow, the cement industry poses substantial environmental challenges, contributing significantly to GHG emissions and climate change. This study is aimed at developing and comparing three predictive models, namely the K-Nearest Neighbor (KNN), Random Forest, and Multivariable Linear Regression (MLR) to create Scope-1 CO₂ emissions projection from Indonesian cement manufacturers. Using five years of historical data from cement plants across Indonesia, this study has identified key emission factors and the most suitable machine learning model to predict Scope-1 CO₂ emissions. Each model was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R2 to assess their accuracy. Furthermore, this study also proposed an integration of these machine learning models into conventional emission calculation methods to provide a robust emissions projection framework that supports the Indonesian Net Zero goal. Key words: GHG Emission, K-Nearest Neighbors (KNN), Machine Learning, Emission Prediction

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 25 165
NIM/NIDN Creators:	41521010114
Uncontrolled Keywords:	GHG Emission, K-Nearest Neighbors (KNN), Machine Learning, Emission Prediction
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.31 Machine Learning/Pembelajaran Mesin 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.32 Neural Nets (Neural Network)/Jaringan Saraf Buatan 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma 600 Technology/Teknologi > 660 Chemical Engineering and Related Technologies/Teknologi Kimia dan Ilmu yang Berkaitan > 662 Technology Of Explosives, Fuels, Related Products, Firework, Pyrotechnics/Teknologi Industri Bahan Peledak,Bahan Bakar,Teknologi Petasan, Piroteknik > 662.6 Non Fuels/Teknologi Industri Bahan Bakar Non Bensin
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	26 Aug 2025 08:19
Last Modified:	26 Aug 2025 08:19
URI:	http://repository.mercubuana.ac.id/id/eprint/97113

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