IMPLEMENTASI METODE CLUSTERING UNTUK PEMETAAN WILAYAH PRODUKSI DAN EKSPOR KOPI DI INDONESIA

Authors

  • Arya Dwi Saputra Universitas Tarumanagara
  • Jefri Jaya Universitas Tarumanagara
  • Teny Handhayani Universitas Tarumanagara
  • Manatap Sitorus Dolok Lauro Universitas Tarumanagara

DOI:

https://doi.org/10.33480/inti.v20i1.6903

Keywords:

agglomerative , coffee , clustering , export , k-means

Abstract

Coffee is one of the main agricultural commodities in Indonesia, but the distribution of production and export contribution is still uneven. This study aims to map the patterns of coffee production and export in Indonesia using clustering methods, namely K-Means and Hierarchical Agglomerative Clustering (AHC). The data used includes coffee production by province and regency (2015–2022), as well as coffee export data by destination country (2016–2023), obtained from BDSP and BPS. The system is developed in the form of an interactive website that allows users to upload datasets, select clustering methods, and view analysis results in the form of tables, graphs, and interactive maps. Clustering quality is evaluated using the Silhouette Score and Davies-Bouldin Index (DBI). The testing results show that the optimal number of clusters is two for all datasets, with the highest Silhouette score reaching 0.85 and the lowest DBI of 0.21, indicating good clustering quality. AHC is more effective in analyzing export and provincial-level production data, while K-Means performs better for regency-level data. This system is expected to provide insights into the distribution patterns of coffee production and exports and support decision-making in the agricultural sector, particularly for coffee commodities.

Downloads

Download data is not yet available.

References

Abiodun M. Ikotun and Absalom E. Ezugwu and Laith Abualigah and Belal Abuhaija and Jia Heming. (2023). K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data. Information Sciences, 622, 178–210. https://doi.org/https://doi.org/10.1016/j.ins.2022.11.139

Adetya, A., Rifin, A., & Nurmalina, R. (2025). Posisi Pasar Ekspor Biji Kopi Indonesia Di Pasar Internasional: Pendekatan Almost Ideal Demand System (AIDS). Forum Agribisnis, 15(1), 114–123. https://doi.org/10.29244/fagb.15.1.114-123

Apriyani, P., Dikananda, A. R., & Ali, I. (2023). Penerapan Algoritma K-Means dalam Klasterisasi Kasus Stunting Balita Desa Tegalwangi. Hello World Jurnal Ilmu Komputer, 2(1), 20–33. https://doi.org/10.56211/helloworld.v2i1.230

Ashardiono, F., & Trihartono, A. (2024). Optimizing the potential of Indonesian coffee: a dual market approach. Cogent Social Sciences, 10(1). https://doi.org/10.1080/23311886.2024.2340206

Chhabra, Anshuman and Mohapatra, P. (2022). Fair Algorithms for Hierarchical Agglomerative Clustering. International Conference on Machine Learning and Applications (ICMLA), 206–211. https://doi.org/10.1109/ICMLA55696.2022.00036

Emmendorfer, Leonardo Ramos; Canuto, A. M. de P. (2021). A generalized average linkage criterion for Hierarchical Agglomerative Clustering. Applied Soft Computing, 100, 106990. https://doi.org/https://doi.org/10.1016/j.asoc.2020.106990

Fahrudin, T. M., Riyantoko, P. A., Hindrayani, K. M., & Swari, M. H. P. (2021). Cluster Analysis of Hospital Inpatient Service Efficiency Based on BOR, BTO, TOI, AvLOS Indicators using Agglomerative Hierarchical Clustering. Telematika, 18(2), 194. https://doi.org/10.31315/telematika.v18i2.4786

Farag, M. A., Mohamed, T. A., El-Hawary, E. A., & Abdelwareth, A. (2023). Metabolite Profiling of Premium Civet Luwak Bio-Transformed Coffee Compared with Conventional Coffee Types, as Analyzed Using Chemometric Tools. Metabolites, 13(2), 173. https://doi.org/10.3390/metabo13020173

Febrianto, N. A., & Zhu, F. (2023). Coffee bean processing: Emerging methods and their effects on chemical, biological and sensory properties. Food Chemistry, 412, 135489. https://doi.org/10.1016/j.foodchem.2023.135489

Fiqhry, A. T., Santoso, T. N. B., & Ardiani, F. (2023). Kajian Produksi Kopi Arabika (Coffea arabica) pada Berbagai Ketinggian Tempat di Kabupaten Temanggung. Jurnal Agro Industri Perkebunan, 81–90. https://doi.org/10.25181/jaip.v12i2.3497

Freitas, V. V., Borges, L. L. R., Vidigal, M. C. T. R., dos Santos, M. H., & Stringheta, P. C. (2024). Coffee: A comprehensive overview of origin, market, and the quality process. Trends in Food Science & Technology, 146, 104411. https://doi.org/10.1016/j.tifs.2024.104411

Handhayani, T., & Lewenusa, I. (2024). An Analysis of Meteorological Data in Sumatra and Nearby using Agglomerative Clustering. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 8(2), 234–241. https://doi.org/10.29207/resti.v8i2.5663

Handhayani, T., & Rusdi, Z. (2023). K-Means Using Dynamic Time Warping For Clustering Cities in Java Island According to Meteorological Conditions. 2023 Eighth International Conference on Informatics and Computing (ICIC), 1–6. https://doi.org/10.1109/ICIC60109.2023.10381899

Harun, S. (2022). Analisis Produksi Kopi di Indonesia Tahun 2015-2020 Menggunakan Metode Cobb-Douglass. Jurnal Ilmiah Ekonomi Pembangunan, 1(2), 102–109.

Hasan, Y. (2024). Pengukuran Silhouette Score dan Davies-Bouldin Index pada Hasil Cluster. KAKIFIKOM (Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer), 06(01), 60–74.

Ishak, Y. A., Handhayani, T., Sitorus, M. D. L., William, W., Pragantha, J., & Lewenusa, I. (2024). Advanced Clustering Approach for Mapping Regions of Paddy Productivity in Indonesia Using Intelligent K-Means. IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS), 269–274.

Li, T., Rezaeipanah, A., & Tag El Din, E. M. (2022). An ensemble agglomerative hierarchical clustering algorithm based on clusters clustering technique and the novel similarity measurement. Journal of King Saud University - Computer and Information Sciences, 34(6), 3828–3842. https://doi.org/10.1016/j.jksuci.2022.04.010

Miraftabzadeh, Seyed Mahdi and Colombo, Cristian Giovanni and Longo, Michela and Foiadelli, F. (2023). K-Means and Alternative Clustering Methods in Modern Power Systems. IEEE Access, 11. https://doi.org/10.1109/ACCESS.2023.3327640

Monath, N., Dubey, K. A., Guruganesh, G., Zaheer, M., Ahmed, A., McCallum, A., Mergen, G., Najork, M., Terzihan, M., Tjanaka, B., Wang, Y., & Wu, Y. (2021). Scalable Hierarchical Agglomerative Clustering. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1245–1255. https://doi.org/10.1145/3447548.3467404

Pratama Simanjuntak, K., & Khaira, U. (2021). Hotspot Clustering in Jambi Province Using Agglomerative Hierarchical Clustering Algorithm. MALCOM: Indonesian Journal of Machine Learning and Computer Science, 1(1), 7–16.

Putra, I. K. N. (2023). Implementasi Metode K-Means Clustering Pada Ekspor Kopi Berdasarkan Negara Tujuan. Jurnal Ilmu Komputer Dan Bisnis, 14(1), 45–55. https://doi.org/10.47927/jikb.v14i1.332

Suraya, S., Sholeh, M., & Lestari, U. (2023). Evaluation of Data Clustering Accuracy using K-Means Algorithm. International Journal of Multidisciplinary Approach Research and Science, 2(01), 385–396. https://doi.org/10.59653/ijmars.v2i01.504

Suryadi Muzahidi Aziz, & Nur Azizah Komara Rifai. (2022). Pengelompokkan Ekspor Kopi Menurut Negara Tujuan Menggunakan Metode K-Means Clustering dengan Silhouette Coefficient. Bandung Conference Series: Statistics, 2(2), 416–424. https://doi.org/10.29313/bcss.v2i2.4536

Umagapi, I. T., Umaternate, B., Komputer, S., Pasca Sarjana Universitas Handayani, P., Kepegawaian Daerah Kabupaten Pulau Morotai, B., & Riset dan Inovasi, B. (2023). Uji Kinerja K-Means Clustering Menggunakan Davies-Bouldin Index Pada Pengelompokan Data Prestasi Siswa. Seminar Nasional Sistem Inform asi Dan Teknologi (SISFOTEK), 7(1), 303–308.

Downloads

Published

2025-08-13

How to Cite

Dwi Saputra, A. ., Jaya, J. ., Handhayani, T., & Sitorus Dolok Lauro , M. . (2025). IMPLEMENTASI METODE CLUSTERING UNTUK PEMETAAN WILAYAH PRODUKSI DAN EKSPOR KOPI DI INDONESIA . INTI Nusa Mandiri, 20(1), 18–25. https://doi.org/10.33480/inti.v20i1.6903

Issue

Vol. 20 No. 1 (2025): INTI Periode Agustus 2025

Section

Articles

License

Copyright (c) 2025 Arya Dwi Saputra, Jefri Jaya, Teny Handhayani, Manatap Sitorus Dolok Lauro

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Penulis yang menerbitkan jurnal ini menyetujui ketentuan berikut:

1. Penulis memegang hak cipta dan memberikan hak jurnal mengenai publikasi pertama dengan karya yang dilisensikan secara bersamaan di bawah Creative Commons Attribution 4.0 International License. yang memungkinkan orang lain untuk berbagi karya dengan pengakuan atas karya penulis dan publikasi awal pada jurnal.

2. Penulis dapat memasukkan pengaturan kontrak tambahan yang terpisah untuk distribusi non-eksklusif dari versi jurnal yang diterbitkan (misalnya, mengirimkannya ke repositori institusional atau menerbitkannya dalam sebuah buku), dengan pengakuan atas publikasi awalnya pada Jurnal.

3. Penulis diizinkan dan didorong untuk memposting karya mereka secara online (misalnya, dalam penyimpanan institusional atau di situs web mereka) sebelum dan selama proses pengiriman, karena hal itu dapat menghasilkan pertukaran yang produktif, serta kutipan dari karya yang diterbitkan sebelumnya.