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All Journal Jurnal Fokus Manajemen Bisnis JRAP (Jurnal Riset Akuntansi dan Perpajakan)
Santosa, Suhari
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Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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Mapping the Wuling vehicle market with K-Means Clustering: An effective digital marketing strategy Ardiansyah, Giri Teguh; Hasibuan, Muhammad Satir; Santosa, Suhari; Heikal, Jerry
Jurnal Fokus Manajemen Bisnis Vol. 14 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/fokus.v14i2.10026

Abstract

This study focuses on Indonesia’s automotive industry sector, which is currently experiencing growth, particularly in terms of Wuling's contribution to the economy through sales. The aim is to identify customer clusters for Wuling vehicle and the marketing mix strategy after the most dominant customer cluster for Wuling vehicle. The research method used was a quantitative survey, which involved collecting data from 111 potential Wuling customer using purposive sampling and data collection through questionnaires. The analysis included an F-Test to examine the differences between clusters. The results show that the clustering of Wuling customer using the K-Means Clustering method successfully divided them into three different clusters, namely Perfectionist, Easy Going, and Beginner, with the Easy Going being the most dominant. Therefore, it is necessary to adjust marketing strategies to focus more on the needs and preferences of the Easy Going, including optimizing the use of promotion channels that have been proven effective, such as direct marketing and sales websites. Thus, this study emphasizes the importance of applying the K-Means Clustering method in automotive market segmentation, providing valuable insights for Wuling to formulate more effective and relevant marketing strategies to meet the diverse needs of customer in a dynamic market.
Analysis of Global Bank’s Financial Performance with the Clustering K-Means Model Santosa, Suhari; Heikal, Jerry
JRAP (Jurnal Riset Akuntansi dan Perpajakan) Vol 11 No 2 (2024): July - December
Publisher : Magister Akuntansi Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35838/jrap.2024.011.02.022

Abstract

Purpose: The purpose of this study is to find out the financial performance of global banks in each cluster for the years 2019 and 2023. In addition, this study is also to find out the position of Indonesia's banks compared to global and ASEAN banks in 2019 and 2023. Methodology: The analysis model used is that the formation of clusters is based on the ratio of CAR, LDR, NIM, ROA and ROE. Testing was carried out with the K-Means model using SPSS. Findings: The results of the study show that in general, global banking performance in 2023 is better than in 2019 in 4 clusters out of 5 clusters. However, the number of banks in the Very Good and Good cluster has decreased in 2023 compared to 2019. In addition, the number of banks in the Very Bad cluster also increased in 2023 compared to 2019. Implication: The increase in the number of banks in the Very Bad cluster needs to be a concern, because the improvement in performance is not as good as other global banks. Local bank supervisory authorities, including the Financial Services Authority in Indonesia, need to pay attention to the performance of banks in the Very Poor cluster. Originality: This study provides additional information about the condition of banks compared to their peers in 2019 and 2023 at the global, ASEAN and Indonesia levels for bank management, investors and also authorities.
Co-Authors Ardiansyah, Giri Teguh Hasibuan, Muhammad Satir Heikal, Jerry