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All Journal Teknika: Jurnal Sains dan Teknologi Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Agribisnis Terpadu Informatika Pertanian J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Amerta Nutrition Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Abdi Insani Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) Journal of Artificial Intelligence and Digital Business PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS JUSTE (Journal of Science and Technology) Journal of Information Technology and its Utilization
Budiaji, Weksi
Universitas Sultan Ageng Tirtayasa
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Journal : International Journal of Advances in Intelligent Informatics

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Medoid-based shadow value validation and visualization Weksi Budiaji
International Journal of Advances in Intelligent Informatics Vol 5, No 2 (2019): July 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v5i2.326

Abstract

A silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CSV has an additional unique property where an image of a 2-dimensional neighborhood graph is possible. A new internal validation index is proposed in this article in order to create a medoid-based validation that has an ability to visualize the results in a 2-dimensional plot. The proposed index behaves similarly to the silhouette index and produces a network visualization, which is comparable to the neighborhood graph of the CSV. The network visualization has a multiplicative parameter (c) to adjust its edges visibility. Due to the medoid-based, in addition, it is more an appropriate visualization technique for any type of data than a neighborhood graph of the CSV.
Co-Authors Adi Susanto Ahmad Luthfi Nur Fauzi Ainun Tazkia, Zilda Amaliah, inti Arina, Faula Bangkit Wijaya, Ferdian Delano, M Fabian Dwi Anugrah Pertiwi, Dinda Edo Ahmad Solahudin Herjayanto, Muh. Ikhsan, Aulia Juni La Djumat Juwarin Pancawati, Juwarin Kamaruddin Kamaruddin Kumenap, Patricia M Indra Rumasukun Majahar Ali, Majid Khan Miranda H Hadijah Moch Suryana Muhamad Iqbal Muttaqin Mukhtar, Mukhtar Mulyati, Sri Nada Thalia Permata Adriani Nur ‘Aida Nur Fitria Nur Fitria, Nur Oktarisa, Yuvita Pancawati, Juwarin Pertiwi, Dinda Dwi Anugrah Pratiwi, Widya Priyantama Ramadhan Bagaskara, Rafly Rifqi Ahmad Riyanto Riyanto, Rifqi Robby Zidny Saleh , Khaerul Setiawan Sariyoga Sri Fajriah Suherna Suherna Sukarna, Royan Habibie Sulaeni, Sulaeni Suman Sangadji Syarif Abdullah Syifa Alfiah Vebriana Vebriana WICAKSONO, AGUNG SATRIO Wicaksono, Agung Satrio Wijaya, Ferdian Wijaya, Ferdian Bangkit