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PENGGUNAAN FITUR ABSTRAKSI DAN CATATAN PUBLIKASI PENULIS UNTUK KLASIFIKASI ARTIKEL ILMIAH DENGAN METADATA YANG TERBATAS Sa'dyah, Halimatus; Ulinnuha, Nurissaidah
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 11, No 1, Januari 2013
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1865.155 KB) | DOI: 10.12962/j24068535.v11i1.a18

Abstract

Bertumbuhnya jumlah artikel ilmiah membuka ranah penelitian baru di bidang optimasi klasifikasi dokumen berbasis metadata. Dalam ranah ini, persoalan pokok yang harus dijawab adalah bagaimana cara memanfaatkan fitur metadata yang terbatas untuk menghasilkan nilai presisi dan recall yang tinggi dalam proses klasifikasi artikel ilmiah. Dalam makalah ini diusulkan sebuah metode klasifikasi artikel ilmiah dengan menggunakan atribut abstraksi dan catatan publikasi penulis pada metada data sebagai fitur. Hasil uji coba menunjukkan bahwa sistem klasifikasi yang menggunakan abstraksi dan catatan publikasi penulis sebagai fitur menghasilkan nilai presisi tertinggi sebesar 0.87 dan recall 0.59 sedangkan sistem klasifikasi yang menggunakan abstraksi sebagai fitur menghasilkan nilai presisi 0.75 dan recall 0.51. Hasil uji coba juga menunjukkan bahwa nilai presisi dan recall dari sistem klasifikasi stabil ketika nilai.
Application of Fuzzy C-Means in Grouping Districts/Cities Based on Health Service Facilities in East Java Maghfiroh, Wardatul; Ulinnuha, Nurissaidah
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol 3, No 2 (2018)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (375.101 KB) | DOI: 10.25139/inform.v3i2.1070

Abstract

Health is a very important thing for every human being because without good health, then humans will be difficult to do activities. We need health facilities that can support human health or society. This study discussed use of clustering algorithm in grouping districts or cities in East Java according to the number of health care facilities using Fuzzy C-Means. The data source of this research got from Central Bureau of Statistics of East Java. The cluster results obtained then validated with sillhoute coefficient and purity. With the centroid gained in the last iteration, four districts/cities were included in the first cluster, 26 districts/cities included in the second cluster, and 8 districts/cities included in the third cluster. The results of clustering validation is the value of sillhoute coefficient of 0.695 and the purity value of 1. This can be a suggestion to the East Java provincial government, districts / municipalities that are more concerned with having the number of health facilities based on the cluster that has been done.Keywords— data mining; health facilities; clustering; fuzzy c-means; sillhoute coefficient; purity
Perbandingan Metode Single Linkage, Complete Linkage Dan Average Linkage dalam Pengelompokan Kecamatan Berdasarkan Variabel Jenis Ternak Kabupaten Sidoarjo Mu'afa, Sulthan Fikri; Ulinnuha, Nurissaidah
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol 4, No 2 (2019)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (297.183 KB) | DOI: 10.25139/ojsinf.v4i2.1696

Abstract

Livestock products are widely used by the community in their daily lives, for example as food ingredients, industrial material sources, labor resources, fertilizer sources and energy sources. This study aims to cluster livestock potential with data on livestock population in Sidoarjo Regency in 2017 with single linkage, complete linkage and average linkage method and comparing performance of the methods. In this cluster, the data will be grouped into 3 clusters. The results of the three clusters were obtained by sixteen sub-districts in the first cluster with the potential for low livestock and each one in the second and third clusters for single linkage and average linkage. While complete linkage obtained fifteen sub-districts in the first cluster with high potential for livestock, two sub-districts in the second cluster with the potential of medium livestock and one sub-district in the third cluster with the potential for high farm animals. In the comparison of the standard deviation ratio value, the smallest value of 0.222 is obtained by complete linkage, which shows that complete linkage is better than single linkage and average linkage in the case of subgrouping based on Sidoarjo regency livestock types.
Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method Utami, Tri Mar'ati Nur; Novitasari, Dian Candra Rini; Setiawan, Fajar; Ulinnuha, Nurissaidah; Farida, Yuniar; Sari, Ghaluh Indah Permata
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28906

Abstract

Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions. Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error. Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.
Application of Fuzzy C-Means in Grouping Districts/Cities Based on Health Service Facilities in East Java Maghfiroh, Wardatul; Ulinnuha, Nurissaidah
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 3 No. 2 (2018)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (375.101 KB) | DOI: 10.25139/inform.v3i2.1070

Abstract

Health is a very important thing for every human being because without good health, then humans will be difficult to do activities. We need health facilities that can support human health or society. This study discussed use of clustering algorithm in grouping districts or cities in East Java according to the number of health care facilities using Fuzzy C-Means. The data source of this research got from Central Bureau of Statistics of East Java. The cluster results obtained then validated with sillhoute coefficient and purity. With the centroid gained in the last iteration, four districts/cities were included in the first cluster, 26 districts/cities included in the second cluster, and 8 districts/cities included in the third cluster. The results of clustering validation is the value of sillhoute coefficient of 0.695 and the purity value of 1. This can be a suggestion to the East Java provincial government, districts / municipalities that are more concerned with having the number of health facilities based on the cluster that has been done.Keywords— data mining; health facilities; clustering; fuzzy c-means; sillhoute coefficient; purity
Penerapan Fuzzy C-Means dalam Mengelompokkan Kabupaten/Kota Berdasarkan Fasilitas Pelayanan Kesehatan Di Jawa Timur Ulinnuha, Nurissaidah; Maghfiroh, Wardatul; Fanani, Aris
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 4 No. 1 (2019)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.297 KB) | DOI: 10.25139/inform.v4i1.1093

Abstract

Kesehatan adalah hal yang sangat penting basi setiap manusia karena tanpa kesehatan yang baik, maka manusia akan sulit untuk melakukan suatu aktivitas. Untuk menunjang kesehatan pada manusia diperlukan suatu fasilitas kesehatan yang baik. Fasilitas kesehatan ini merupakan tanggung jawab dari pemerintahan yang harus selalu dievaluasi guna meningkatkan pelayanan kesehatan. Dalam penelitian ini dibahas pemanfaatan algoritma clustering dalam mengelompokkan kabupaten atau kota di Jawa Timur menurut jumlah fasilitas pelayanan kesehatan menggunakan Fuzzy C-Means. Dengan analisis klaster akan didapat kelompok-kelompok kabupaten/kota yang memiliki fasilitas yang memadai atau yang kurang memadai. Dengan mengetahui kelompok-kelompok tersebut maka pemerintah Jawa Timur dapat mengetahui kabupaten/kota mana yang harus ditingkatkan fasilitas kesehatannya. Sumber data penelitian ini berasal dari BPS Jawa Timur. Hasil cluster yang didapat kemudian divalidasi dengan sillhoute coefficient dan purity. Dengan centroid yang telah didapatkan pada iterasi terakhir, diperoleh 4 kabupaten/kota termasuk dalam cluster pertama, 26 kabupaten/kota termasuk dalam cluster kedua, dan 8 kabupaten/kota termasuk dalam cluster ketiga. Dari validasi clustering yang dilakukan, didapatkan nilai sillhoute coefficient sebesar 0,695 dan nilai purity sebesar 1.
Perbandingan Metode Single Linkage, Complete Linkage Dan Average Linkage dalam Pengelompokan Kecamatan Berdasarkan Variabel Jenis Ternak Kabupaten Sidoarjo Mu'afa, Sulthan Fikri; Ulinnuha, Nurissaidah
Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi Vol. 4 No. 2 (2019)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (297.183 KB) | DOI: 10.25139/inform.v4i2.1696

Abstract

Livestock products are widely used by the community in their daily lives, for example as food ingredients, industrial material sources, labor resources, fertilizer sources and energy sources. This study aims to cluster livestock potential with data on livestock population in Sidoarjo Regency in 2017 with single linkage, complete linkage and average linkage method and comparing performance of the methods. In this cluster, the data will be grouped into 3 clusters. The results of the three clusters were obtained by sixteen sub-districts in the first cluster with the potential for low livestock and each one in the second and third clusters for single linkage and average linkage. While complete linkage obtained fifteen sub-districts in the first cluster with high potential for livestock, two sub-districts in the second cluster with the potential of medium livestock and one sub-district in the third cluster with the potential for high farm animals. In the comparison of the standard deviation ratio value, the smallest value of 0.222 is obtained by complete linkage, which shows that complete linkage is better than single linkage and average linkage in the case of subgrouping based on Sidoarjo regency livestock types.