IPTEK Journal of Proceedings Series No. (7) (2020), ISSN (2354-6026) The 2 nd International Conference on Global Development - ICODEV December 5 th , 2020, Online Conference 31 Abstract―Nowadays internet traffic using cellular telecommunication network is increasing very rapidly. Good LTE (Long-Term Evolution) cellular network performance is very important for any telecommunication operator to maintain customer satisfaction. Poor network performance can also cause customers to switch to other operators. One of the indicator variables in observing the radio quality of the LTE cellular network is Penetration using 64QAM Modulation. 64QAM modulation can transmit higher bitrates with lower power usage. 64QAM modulation will be used if the Channel Quality Index (CQI) condition is very good. Network quality improvement can be done by adding new BTS or optimizing existing BTS. The addition of new BTS will increase coverage, quality, and capacity but cost is high, and the time required to build BTS is also long, while improving network quality by optimizing BTS can be done by purchasing LTE features and costs incurred still relatively low. In increasing the penetration of using 64QAM modulation, it is necessary to analyze the other variables. The traditional method to improve this Key Performance Indicator (KPI) requires an expert and professional but is often inaccurate and spends a lot of time finding the factors that cause it. To solve this problem, Random forest method is proposed. By knowing the variables that have a significant effect on network quality, the capital costs incurred by cellular operators for improving network quality will be more effective and efficient because the capital costs invested only focus on influencing variables such as purchasing LTE network features only done for those related to these variables. The results of this study, we make CQI improvement flow based on the classification of the random forest method that produces feature/variable importance. Keywords―LTE, Channel Quality Index, CQI, Random Forest, Base Transceiver Station, BTS, QPSK, 16QAM, 64QAM, AUC. I. INTRODUCTION N this digital era, the development of technology is very rapid, and the internet is one of the most important needs for society. The industrial revolution 4.0 has grown in recent years, such as the existence of the internet of things (IoT), block chains, and others which have resulted in the emergence of various new business models and managed in new ways. According to the results of a survey conducted by the Indonesian Internet Service Providers Association (APJII), internet users in Indonesia in 2018 reached 171.17 million people. LTE is an evolution of cellular technology that can provide an increase in internet access speeds that are far more than previous technologies, namely 3G (HSDPA) and 2G. In theory, 4G technology can reach data access speeds / throughput of 1 Gbps. This technology is a solution to the increasing need for data communication. In LTE network, the modulation systems used are QPSK, 16QAM, and 64QAM in the downlink and uplink directions. 64QAM modulation can transmit higher bitrates with lower power usage. The modulation will change dynamically depending on the network quality conditions Channel Quality Index (CQI) condition. 64QAM modulation will be used if the network quality is very good (CQI!10). The quality of the LTE cellular network will greatly affect retaining customers or getting new customers for telecommunications operators. Poor network quality such as difficult internet access, low internet speed will trigger complaints from customers and when this problem is left too long it will cause customers to switch to another telecommunication operator. In a study conducted by [1]. Porter Five Forces Analysis on cellular operators, industry competitors and buyers have a high category as illustrated in Figure 1. This means that these two factors greatly influence the company to achieve success. In increasing the penetration of using 64QAM modulation, it is necessary to analyze the other variables. The procedures Analysis of Factors Affecting the Use of the 64QAM Modulation on the Long-Term Evolution Network by Using Random Forest Method Mochammad Jainul 1 , Raden Mohamad Atok 2 1Department of Technology Management, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia 2 Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia e-mail: mochammadjainul.19092@mhs.its.ac.id I Figure 1. Porter's Five Forces Analysis on Cellular Operators.