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All Journal Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Sisfokom (Sistem Informasi dan Komputer) JSiI (Jurnal Sistem Informasi) Krea-TIF: Jurnal Teknik Informatika IJISTECH (International Journal Of Information System & Technology) Jurnal ICT : Information Communication & Technology Health Sciences and Pharmacy Journal Building of Informatics, Technology and Science Madani : Indonesian Journal of Civil Society Jurnal Pengabdian kepada Masyarakat Nusantara Teknika IJISTECH Journal of Soft Computing Exploration Batara Wisnu : Indonesian Journal of Community Services The Indonesian Journal of Computer Science Research SmartComp The Indonesian Journal of Computer Science
Acihmah Sidauruk
Universitas AMIKOM Yogyakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences

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Journal : Building of Informatics, Technology and Science

 1 
Clustering Performance Between K-means and Bisecting K-means for Students Interest in Senior High School Seniwati, Erni; Sidauruk, Acihmah; Haryoko, Haryoko; Lukman, Achmad
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3624

Abstract

The interest of high school students is an important thing to do to see the talents of each student based on the academic scores obtained in the first and second semesters. There are two majors of interest in this case study, namely natural and social studies with criteria for natural studies scores including mathematics, chemistry, biology and physics. Meanwhile, the social studies criteria include history, economics, geography and sociology. This research propose comparing of clustering time and accuracy based on manual data from school as a reference of clustering in SMAN 1 Wonosari for 2011/2012 academic year using two clustering methods namely K-means and Bisecting K-Means. The results of this research compare to manual results interest from class teacher, so this work can demonstrate the run time comparison and accuracy of this study. The accuracy result shows 87.5% for both methods but different run times. For bisecting k-means got 0.0229849 seconds to complete the clustering process faster than k-means only got 0.0929448 seconds
Robusta Coffee Plant Disease Identification using Dempster Shafer Method in Expert Systems Sidauruk, Acihmah; Miftakhurrokhmat, Miftakhurrokhmat; Pujianto, Ade; Salmuasih, Salmuasih
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6272

Abstract

Robusta coffee is one type of coffee that can grow well in Indonesia. Robusta coffee has 2.2% more caffeine and less sugar than Arabica coffee. This coffee may be a more interesting coffee variety from different levels of taste and thickness. In addition, Robusta coffee is very accommodating to the economy of several coffee-producing countries around the world, including Indonesia. A number of factors, especially pests and diseases, can reduce the productivity and quality of coffee plants. This is also confirmed by coffee experts who conducted research on pests and diseases in Robusta coffee plants. This study aims to develop an expert-based system that can identify problems and diseases in Robusta coffee plants using the Dempster Shafer method, and developed in a web-based platform. From the data collected from literature studies, dialogue with farmers, and consultation with an expert, 13 types of pests and diseases were obtained, and 27 symptoms of the disease. The results of this study are the development of a web-based expert system that can diagnose pests or diseases from several symptom inputs filled in by users or coffee farmers. The results of the trial of 13 test cases on the diagnosis of pests and diseases of Robusta coffee plants obtained an average accuracy value of 94%. This shows that this expert system can analyze the types of pests or diseases in Robusta coffee plants very well using the Dempster Shafer method.
Co-Authors Abdullah Abdullah Abdussalam Al Akbar Achmad Lukman, Achmad Ade Pujianto Ade Pujianto, Ade Afifah Nur Latifah Afrianto, Nurdi Afrig Aminuddin Alvy Chasanatussalma Anggita, Sharazita Dyah Arif Dwi Laksito Asro Nasiri Atik Nurmasani Bernadhed, Bernadhed Bister Purba Budy Satria Burhanudin, Nazil Ilham Danang Wijayanto Darmawan, Briga Dwi Rahayu Elsafira Budi Dewantari Erni Seniwati Febri Liantoni, Febri Gita Cahyani Gunawan, Puguh Hasta Hairul Januar Haryoko, Haryoko Hasyim, Jaka Wardana Hendra Kurniawan Ihsan, M. Arinal Ikmah Ikmah Ilyas Ferry Ceasar Widayanto Jamroni Jamroni Khoiruddin, Lukman Liga Mayola M. Arinal Ihsan Miftakhurrokhmat Miftakhurrokhmat, Miftakhurrokhmat Muhammad Iqbal Kusrachmansyah Muhammad Resa Arif Yudianto Mulia Sulistiyono Mulyatun, Sri Ningsih, Lidya Norhikmah Norhikmah Norhikmah, - Nurcholis, Muhammad Tofa Panggih Suseno Pirmansah, Imam Ainudin Proboningrum, Sandyea Rabiatul Adawiyah Raditya Wardhana Raditya Wardhana Rahmi, Alfie Nur Ria Andriani Riza Yulina Amry Robert Marco, Robert Rumini Rumini SAKINAH, PUTRI Salmuasih, Salmuasih Sarni Anggoro Satria, Dhimas Adi Seniwati, Erni Shofi Putri Ekadewi Sutarni, Sutarni Tri Widayanti Trisa Ayunanda Saputri Wardhana, Raditya Waskito, Bimo Wiji Nurastuti Wiji Nurastuti, Wiji Wiwi Widayani Wulandari, Evita Sekar Yoga Pristyanto Yudiyanto, Muhammad Resa Arif Yuli Astuti Yuli Astuti