How to cite this paper
Tosida, E., Setiawan, R., Anggraeni, I., Jayawinangun, R., Sukono, S & Saputra, J. (2023). Modeling of citizen science cluster in making decision for readiness towards bogor smart village: An application of fuzzy c-means algorithm.Decision Science Letters , 12(3), 617-628.
Refrences
Andria, F., Rahmi, A., Sunarzi, M., Nuramanah, S., Selatan, A. I., Salmah, S., Tosida, E. T., & Harsani, P. (2022). Community-Based Local Wisdom Development: Strengthening Accounting and Production Management Skills "Batik Village New Normal Bogor." International Journal of Research in Community Services, 3(2), 63–70. https://doi.org/10.46336/ijrcs.v3i2.268
Ardiansyah, D., Harsani, P., Tosida, E. T., Saputra, A. O., & Bhayangkari, A. (2022). Development of A Village Information System for Acceleration of Village Services in Desa Tegal Kecamatan Kemang Bogor. Jurnal Informatika dan Sains, 5(1), 54–57. https://doi.org/10.31326/jisa.v5i1.1113
Assumpcao, T. H., Jonoski, A., Theona, I., Tsiakos, C., Krommyda, M., Tamascelli, S., Kallioras, A., Mierla, M., Georgiou, H. V., Miska, M., Pouliaris, C., Trifanov, C., Cimpan, K. T., Tsertou, A., Marin, E., Diakakis, M., Nichersu, I., Amditis, A. J., & Popescu, I. (2019). Citizens' campaigns for environmental water monitoring: Lessons from field experiments. IEEE Access, 7, 134601–134620. https://doi.org/10.1109/ACCESS.2019.2939471
Astuti, F. D. (2017). Seleksi Atribut Menggunakan Information Gain Untuk Clustering Penduduk Miskin Dengan Validity Index Xie Beni. Teknika, 6(1), 61–65. https://doi.org/10.34148/teknika.v6i1.58
Azhagusundari, B., & Thanamani, A. S. (2013). Feature Selection Based on Information Gain. 2, 18–21.
Beza, E., Steinke, J., Van Etten, J., Reidsma, P., Fadda, C., & Mittra, S. (2017). What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers. PLoS ONE, 12(5), 1–26. https://doi.org/10.1371/journal.pone.0175700
Christyanti, R. D., Sulaiman, D., Utomo, A. P., & Ayyub, M. (2022). Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas. International Journal of Natural Science and Engineering, 6(3), Article 3. https://doi.org/10.23887/ijnse.v6i3.53048
Deng, H., & Runger, G. (n.d.). Feature Selection via Regularized Trees.
Dinata, R. K., Novriando, H., Hasdyna, N., & Retno, S. (2020). Reduksi Atribut Menggunakan Information Gain untuk Optimasi Cluster Algoritma K-Means. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 6(1), 48. https://doi.org/10.26418/jp.v6i1.37606
Ella, S., & Andari, R. N. (2018). Developing a Smart Village Model for Village Development in Indonesia. Proceeding - 2018 International Conference on ICT for Smart Society: Innovation Toward Smart Society and Society 5.0, ICISS 2018. https://doi.org/10.1109/ICTSS.2018.8549973
Ghosh, S., & Dubey, S. K. (2013). Comparative analysis of k-means and fuzzy c-means algorithms. International Journal of Advanced Computer Science and Applications, 4(4).
Hadian, N., & Susanto, T. D. (2022). Pengembangan Model Smart Village Indonesia: Systematic Literature Review. Journal of Information System,Graphics, Hospitality and Technology, 4(2), Article 2. https://doi.org/10.37823/insight.v4i2.234
Hendalianpour, A., Razmi, J., & Gheitasi, M. (2017). Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach. Accounting, 3(2), 81–94. https://doi.org/10.5267/j.ac.2016.8.003
Karsito, & Monika Sari, W. (2018). Prediksi Potensi Penjualan Produk Delifrance Dengan Metode Naive Bayes Di Pt. Pangan Lestari. Jurnal Teknologi Pelita Bangsa, 9(1), 67–78.
Kirschke, S., Bennett, C., Bigham Ghazani, A., Franke, C., Kirschke, D., Lee, Y., Loghmani Khouzani, S. T., & Nath, S. (2022). Citizen science projects in freshwater monitoring. From individual design to clusters? Journal of Environmental Management, 309, 114714. https://doi.org/10.1016/j.jenvman.2022.114714
Lusiana, E. D., Astutik, S., Nurjannah, N., & Sambah, A. B. (2023). Spatial delineation on marine environmental characteristics using fuzzy c-means clustering method. Global Journal of Environmental Science and Management, 9(3). https://doi.org/10.22034/gjesm.2023.03.07
Maja, P. W., Meyer, J., Member, S., & Solms, S. V. O. N. (2020). Development of Smart Rural Village Indicators in Line With Industry 4. 0. IEEE Access, 8(152017), 152017–152033. https://doi.org/10.1109/ACCESS.2020.3017441
Maulana, M. R., & Karomi, M. A. Al. (2015). Information Gain Untuk Mengetahui Pengaruh Atribut. Jurnal Litbang Kota Pekalongan, 9, 113–123.
Nayak, J., Naik, B., & Behera, H. (2015). Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014. In Computational Intelligence in Data Mining-Volume 2: Proceedings of the International Conference on CIDM, 20-21 December 2014 (pp. 133-149). Springer India.
Nugraha, G. S., & Riyandari, B. A. (2020). Implementasi Fuzzy C-Means Untuk Pengelompokan Daerah Berdasarkan Indikator Kesehatan. Jurnal Teknologi Informasi, 4(1), 52–62. https://doi.org/10.36294/jurti.v4i1.1222
Ozyigit, T., Yavuz, C., Egi, S. M., Pieri, M., Balestra, C., & Marroni, A. (2019). Clustering of recreational divers by their health conditions in a database of a citizen science project. Undersea & Hyperbaric Medicine: Journal of the Undersea and Hyperbaric Medical Society, Inc, 46, 171–183.
Phuc, N. H. T., & Chi, H. T. X. (2021). Customer Segmentation Based on Fuzzy C-Means and Weighted Interval-Valued Dual Hesitant Fuzzy Sets.
Ponti, M., & Seredko, A. (2022). Human-machine-learning integration and task allocation in citizen science. Humanities and Social Sciences Communications, 9(1), 48. https://doi.org/10.1057/s41599-022-01049-z
Prasetyo, S. S., Mustafid, M., & Hakim, A. R. (2020). Penerapan Fuzzy C-Means Kluster Untuk Segmentasi Pelanggan E-Commerce Dengan Metode Recency Frequency Monetary (Rfm). Jurnal Gaussian, 9(4), 421–433. https://doi.org/10.14710/j.gauss.v9i4.29445
Radius, T. V., Song, J., Li, F., Li, R., Plants, A., Particle, U., Algorithm, K., Anam, S., Jumadi, B., Sitompul, D., Sitompul, S., & Sihombing, P. (2020). Analysis of determining centroid clustering x- means algorithm with davies-bouldin index evaluation. https://doi.org/10.1088/1757-899X/725/1/012128
Rajput, A., & Kumaravelu, V. B. (2021). FCM clustering and FLS based CH selection to enhance sustainability of wireless sensor networks for environmental monitoring applications. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1139–1159. https://doi.org/10.1007/s12652-020-02159-9
Reddy, B. R., Vijay Kumar, Y., & Prabhakar, M. (2019). Clustering large amounts of healthcare datasets using fuzzy c-means algorithm. 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 93–97. https://doi.org/10.1109/ICACCS.2019.8728503
Ruiz-Martínez, I., & Esparcia, J. (2020). Internet Access in Rural Areas: Brake or Stimulus as Post-Covid-19 Opportunity? Sustainability, 12(22), 9619. https://doi.org/10.3390/su12229619
Setiawan, K. E., Kurniawan, A., Chowanda, A., & Suhartono, D. (2023). Clustering models for hospitals in Jakarta using fuzzy c-means and k-means. Procedia Computer Science, 216, 356–363. https://doi.org/10.1016/j.procs.2022.12.146
Shamir, L., Diamond, D., & Wallin, J. (2016). Leveraging Pattern Recognition Consistency Estimation for Crowdsourcing Data Analysis. IEEE Transactions on Human-Machine Systems, 46(3), 474–480. https://doi.org/10.1109/THMS.2015.2463082
Shi, D., Guan, J., Zurada, J., & Levitan, A. S. (2015). An Innovative Clustering Approach to Market Segmentation for Improved Price Prediction. Journal of International Technology and Information Management, 24(1). https://doi.org/10.58729/1941-6679.1033
Shrestha, N. (2021). Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4–11. https://doi.org/10.12691/ajams-9-1-2
Silvertown, J. (2009). A new dawn for citizen science. Trends in ecology & evolution, 24(9), 467-471.
Surarso, B., & Gernowo, R. (2020). IMPLEMENTATION OF K-MEDOIDS CLUSTERING FOR HIGH. 10(3), 119–128.
Tangirala, S. (2020). Evaluating the Impact of GINI Index and Information Gain on Classification using Decision Tree Classifier Algorithm *. 11(2), 612–619.
Tosida, E. T., Herdiyeni, Y., Marimin, & Suprehatin, S. (2022). Investigating the effect of technology-based village development towards smart economy: An application of variance-based structural equation modeling. International Journal of Data and Network Science, 6(3), 787–804. https://doi.org/10.5267/j.ijdns.2022.3.002
Tosida, E. T., Herdiyeni, Y., Suprehatin, S., & Marimin. (2020, September 16). The potential for implementing a big data analytic-based smart village in Indonesia. 2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020. https://doi.org/10.1109/ICOSICA49951.2020.9243265
Tosida, E. T., Solihin, I. P., Jayawinangun, R., & Ardiansyah, D. (2022). Implementation of Multiple Discriminant Analysis (MDA) for Clustering Smart Village in West Java Based Podes (Potensi Desa) Database. 2022 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 451–456. https://doi.org/10.1109/ICIMCIS56303.2022.10017815
Tosida, E. T., Suprehatin, S., Herdiyeni, Y., Marimin, & Solihin, I. P. (2020). Clustering of Citizen Science Prospect to Construct Big Data-based Smart Village in Indonesia. Proceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020, 58–63. https://doi.org/10.1109/ICIMCIS51567.2020.9354323
Watulangkouw, J. (2022). Application of Data Mining to Determine Promotion Strategy Using Algorithm Clustering at SMK Yadika 1. JISA(Jurnal Informatika Dan Sains), 5(1), 35–49. https://doi.org/10.31326/jisa.v5i1.1107
Wiharto, W., & Suryani, E. (2020). The Comparison of Clustering Algorithms K-Means and Fuzzy C-Means for Segmentation Retinal Blood Vessels. Acta Informatica Medica, 28(1), 42–47. https://doi.org/10.5455/aim.2020.28.42-47
Zhang, J., & Shen, L. (2014). An Improved Fuzzy c -Means Clustering Algorithm Based on Shadowed Sets and PSO. Computational Intelligence and Neuroscience, 2014, 1–10. https://doi.org/10.1155/2014/368628
Ardiansyah, D., Harsani, P., Tosida, E. T., Saputra, A. O., & Bhayangkari, A. (2022). Development of A Village Information System for Acceleration of Village Services in Desa Tegal Kecamatan Kemang Bogor. Jurnal Informatika dan Sains, 5(1), 54–57. https://doi.org/10.31326/jisa.v5i1.1113
Assumpcao, T. H., Jonoski, A., Theona, I., Tsiakos, C., Krommyda, M., Tamascelli, S., Kallioras, A., Mierla, M., Georgiou, H. V., Miska, M., Pouliaris, C., Trifanov, C., Cimpan, K. T., Tsertou, A., Marin, E., Diakakis, M., Nichersu, I., Amditis, A. J., & Popescu, I. (2019). Citizens' campaigns for environmental water monitoring: Lessons from field experiments. IEEE Access, 7, 134601–134620. https://doi.org/10.1109/ACCESS.2019.2939471
Astuti, F. D. (2017). Seleksi Atribut Menggunakan Information Gain Untuk Clustering Penduduk Miskin Dengan Validity Index Xie Beni. Teknika, 6(1), 61–65. https://doi.org/10.34148/teknika.v6i1.58
Azhagusundari, B., & Thanamani, A. S. (2013). Feature Selection Based on Information Gain. 2, 18–21.
Beza, E., Steinke, J., Van Etten, J., Reidsma, P., Fadda, C., & Mittra, S. (2017). What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers. PLoS ONE, 12(5), 1–26. https://doi.org/10.1371/journal.pone.0175700
Christyanti, R. D., Sulaiman, D., Utomo, A. P., & Ayyub, M. (2022). Implementation of Fuzzy C-Means in Clustering Stunting Prone Areas. International Journal of Natural Science and Engineering, 6(3), Article 3. https://doi.org/10.23887/ijnse.v6i3.53048
Deng, H., & Runger, G. (n.d.). Feature Selection via Regularized Trees.
Dinata, R. K., Novriando, H., Hasdyna, N., & Retno, S. (2020). Reduksi Atribut Menggunakan Information Gain untuk Optimasi Cluster Algoritma K-Means. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 6(1), 48. https://doi.org/10.26418/jp.v6i1.37606
Ella, S., & Andari, R. N. (2018). Developing a Smart Village Model for Village Development in Indonesia. Proceeding - 2018 International Conference on ICT for Smart Society: Innovation Toward Smart Society and Society 5.0, ICISS 2018. https://doi.org/10.1109/ICTSS.2018.8549973
Ghosh, S., & Dubey, S. K. (2013). Comparative analysis of k-means and fuzzy c-means algorithms. International Journal of Advanced Computer Science and Applications, 4(4).
Hadian, N., & Susanto, T. D. (2022). Pengembangan Model Smart Village Indonesia: Systematic Literature Review. Journal of Information System,Graphics, Hospitality and Technology, 4(2), Article 2. https://doi.org/10.37823/insight.v4i2.234
Hendalianpour, A., Razmi, J., & Gheitasi, M. (2017). Comparing clustering models in bank customers: Based on Fuzzy relational clustering approach. Accounting, 3(2), 81–94. https://doi.org/10.5267/j.ac.2016.8.003
Karsito, & Monika Sari, W. (2018). Prediksi Potensi Penjualan Produk Delifrance Dengan Metode Naive Bayes Di Pt. Pangan Lestari. Jurnal Teknologi Pelita Bangsa, 9(1), 67–78.
Kirschke, S., Bennett, C., Bigham Ghazani, A., Franke, C., Kirschke, D., Lee, Y., Loghmani Khouzani, S. T., & Nath, S. (2022). Citizen science projects in freshwater monitoring. From individual design to clusters? Journal of Environmental Management, 309, 114714. https://doi.org/10.1016/j.jenvman.2022.114714
Lusiana, E. D., Astutik, S., Nurjannah, N., & Sambah, A. B. (2023). Spatial delineation on marine environmental characteristics using fuzzy c-means clustering method. Global Journal of Environmental Science and Management, 9(3). https://doi.org/10.22034/gjesm.2023.03.07
Maja, P. W., Meyer, J., Member, S., & Solms, S. V. O. N. (2020). Development of Smart Rural Village Indicators in Line With Industry 4. 0. IEEE Access, 8(152017), 152017–152033. https://doi.org/10.1109/ACCESS.2020.3017441
Maulana, M. R., & Karomi, M. A. Al. (2015). Information Gain Untuk Mengetahui Pengaruh Atribut. Jurnal Litbang Kota Pekalongan, 9, 113–123.
Nayak, J., Naik, B., & Behera, H. (2015). Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014. In Computational Intelligence in Data Mining-Volume 2: Proceedings of the International Conference on CIDM, 20-21 December 2014 (pp. 133-149). Springer India.
Nugraha, G. S., & Riyandari, B. A. (2020). Implementasi Fuzzy C-Means Untuk Pengelompokan Daerah Berdasarkan Indikator Kesehatan. Jurnal Teknologi Informasi, 4(1), 52–62. https://doi.org/10.36294/jurti.v4i1.1222
Ozyigit, T., Yavuz, C., Egi, S. M., Pieri, M., Balestra, C., & Marroni, A. (2019). Clustering of recreational divers by their health conditions in a database of a citizen science project. Undersea & Hyperbaric Medicine: Journal of the Undersea and Hyperbaric Medical Society, Inc, 46, 171–183.
Phuc, N. H. T., & Chi, H. T. X. (2021). Customer Segmentation Based on Fuzzy C-Means and Weighted Interval-Valued Dual Hesitant Fuzzy Sets.
Ponti, M., & Seredko, A. (2022). Human-machine-learning integration and task allocation in citizen science. Humanities and Social Sciences Communications, 9(1), 48. https://doi.org/10.1057/s41599-022-01049-z
Prasetyo, S. S., Mustafid, M., & Hakim, A. R. (2020). Penerapan Fuzzy C-Means Kluster Untuk Segmentasi Pelanggan E-Commerce Dengan Metode Recency Frequency Monetary (Rfm). Jurnal Gaussian, 9(4), 421–433. https://doi.org/10.14710/j.gauss.v9i4.29445
Radius, T. V., Song, J., Li, F., Li, R., Plants, A., Particle, U., Algorithm, K., Anam, S., Jumadi, B., Sitompul, D., Sitompul, S., & Sihombing, P. (2020). Analysis of determining centroid clustering x- means algorithm with davies-bouldin index evaluation. https://doi.org/10.1088/1757-899X/725/1/012128
Rajput, A., & Kumaravelu, V. B. (2021). FCM clustering and FLS based CH selection to enhance sustainability of wireless sensor networks for environmental monitoring applications. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1139–1159. https://doi.org/10.1007/s12652-020-02159-9
Reddy, B. R., Vijay Kumar, Y., & Prabhakar, M. (2019). Clustering large amounts of healthcare datasets using fuzzy c-means algorithm. 2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 93–97. https://doi.org/10.1109/ICACCS.2019.8728503
Ruiz-Martínez, I., & Esparcia, J. (2020). Internet Access in Rural Areas: Brake or Stimulus as Post-Covid-19 Opportunity? Sustainability, 12(22), 9619. https://doi.org/10.3390/su12229619
Setiawan, K. E., Kurniawan, A., Chowanda, A., & Suhartono, D. (2023). Clustering models for hospitals in Jakarta using fuzzy c-means and k-means. Procedia Computer Science, 216, 356–363. https://doi.org/10.1016/j.procs.2022.12.146
Shamir, L., Diamond, D., & Wallin, J. (2016). Leveraging Pattern Recognition Consistency Estimation for Crowdsourcing Data Analysis. IEEE Transactions on Human-Machine Systems, 46(3), 474–480. https://doi.org/10.1109/THMS.2015.2463082
Shi, D., Guan, J., Zurada, J., & Levitan, A. S. (2015). An Innovative Clustering Approach to Market Segmentation for Improved Price Prediction. Journal of International Technology and Information Management, 24(1). https://doi.org/10.58729/1941-6679.1033
Shrestha, N. (2021). Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4–11. https://doi.org/10.12691/ajams-9-1-2
Silvertown, J. (2009). A new dawn for citizen science. Trends in ecology & evolution, 24(9), 467-471.
Surarso, B., & Gernowo, R. (2020). IMPLEMENTATION OF K-MEDOIDS CLUSTERING FOR HIGH. 10(3), 119–128.
Tangirala, S. (2020). Evaluating the Impact of GINI Index and Information Gain on Classification using Decision Tree Classifier Algorithm *. 11(2), 612–619.
Tosida, E. T., Herdiyeni, Y., Marimin, & Suprehatin, S. (2022). Investigating the effect of technology-based village development towards smart economy: An application of variance-based structural equation modeling. International Journal of Data and Network Science, 6(3), 787–804. https://doi.org/10.5267/j.ijdns.2022.3.002
Tosida, E. T., Herdiyeni, Y., Suprehatin, S., & Marimin. (2020, September 16). The potential for implementing a big data analytic-based smart village in Indonesia. 2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020. https://doi.org/10.1109/ICOSICA49951.2020.9243265
Tosida, E. T., Solihin, I. P., Jayawinangun, R., & Ardiansyah, D. (2022). Implementation of Multiple Discriminant Analysis (MDA) for Clustering Smart Village in West Java Based Podes (Potensi Desa) Database. 2022 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 451–456. https://doi.org/10.1109/ICIMCIS56303.2022.10017815
Tosida, E. T., Suprehatin, S., Herdiyeni, Y., Marimin, & Solihin, I. P. (2020). Clustering of Citizen Science Prospect to Construct Big Data-based Smart Village in Indonesia. Proceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020, 58–63. https://doi.org/10.1109/ICIMCIS51567.2020.9354323
Watulangkouw, J. (2022). Application of Data Mining to Determine Promotion Strategy Using Algorithm Clustering at SMK Yadika 1. JISA(Jurnal Informatika Dan Sains), 5(1), 35–49. https://doi.org/10.31326/jisa.v5i1.1107
Wiharto, W., & Suryani, E. (2020). The Comparison of Clustering Algorithms K-Means and Fuzzy C-Means for Segmentation Retinal Blood Vessels. Acta Informatica Medica, 28(1), 42–47. https://doi.org/10.5455/aim.2020.28.42-47
Zhang, J., & Shen, L. (2014). An Improved Fuzzy c -Means Clustering Algorithm Based on Shadowed Sets and PSO. Computational Intelligence and Neuroscience, 2014, 1–10. https://doi.org/10.1155/2014/368628