Analysis of the 2022 Shallot Price Grouping in the Areas of Arengka, Cikpuan, Incense, and Suka Ramai Using the Hierarchical Clustering Method

This study aims to analyze the price grouping of shallots in four regions, namely Arengka, Cikpuan, Incense, and Suka Ramai in 2022 using the Hierarchical Clustering method. The data used is secondary data on the price of shallots from each region. The analysis was carried out with a multivariate statistical approach to identify price patterns and form clusters based on price similarities between regions. The results of the study show that the price of shallots in the four regions can be grouped into two main clusters. The first cluster consists of areas with lower shallot prices (<66.67 rupiah), while the second cluster consists of areas with higher prices (>66.67 rupiah). The distance between the clusters of 5.22715 shows a significant difference in price characteristics. These findings provide strategic benefits for industry players and policy makers in optimizing distribution and developing marketing strategies that are more targeted in each region. Overall, the Hierarchical Clustering method has proven to be effective in identifying shallot price patterns and can be used as a basis for data-driven decision-making in the agricultural sector

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Publication Details

Journal
Indonesian Council of Premier Statistical Science.
Published
2025-08-31
DOI
https://doi.org/10.24014/icopss.v4i2.37870
Primary Topic
Livestock Farming and Management
Type
article
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article

Analysis of the 2022 Shallot Price Grouping in the Areas of Arengka, Cikpuan, Incense, and Suka Ramai Using the Hierarchical Clustering Method

Mohammad Rizki Akbar, Muhammad Angga Piansyah Hasibuan, Restu Prasetyo
Indonesian Council of Premier Statistical Science.
Livestock Farming and Management
article

Analysis of the 2022 Shallot Price Grouping in the Areas of Arengka, Cikpuan, Incense, and Suka Ramai Using the Hierarchical Clustering Method

Mohammad Rizki Akbar, Muhammad Angga Piansyah Hasibuan, Restu Prasetyo
article en

Abstract

This study aims to analyze the price grouping of shallots in four regions, namely Arengka, Cikpuan, Incense, and Suka Ramai in 2022 using the Hierarchical Clustering method. The data used is secondary data on the price of shallots from each region. The analysis was carried out with a multivariate statistical approach to identify price patterns and form clusters based on price similarities between regions. The results of the study show that the price of shallots in the four regions can be grouped into two main clusters. The first cluster consists of areas with lower shallot prices (<66.67 rupiah), while the second cluster consists of areas with higher prices (>66.67 rupiah). The distance between the clusters of 5.22715 shows a significant difference in price characteristics. These findings provide strategic benefits for industry players and policy makers in optimizing distribution and developing marketing strategies that are more targeted in each region. Overall, the Hierarchical Clustering method has proven to be effective in identifying shallot price patterns and can be used as a basis for data-driven decision-making in the agricultural sector

Indonesian Council of Premier Statistical Science.Vol. 4(2)
Riau University (ID)
Openalex Percentile: Top 65%
Livestock Farming and Management
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Analysis of the 2022 Shallot Price Grouping in the Areas of Arengka, Cikpuan, Incense, and Suka Ramai Using the Hierarchical Clustering Method — Mohammad Rizki Akbar, Muhammad Angga Piansyah Hasibuan, et al. · Indonesian Council of Premier Statistical Science. (2025) | TGRS Research Map | TGRS