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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 Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan 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
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : The Indonesian Journal of Computer Science

 1 
Penerapan Composite Performance Index (CPI) Sebagai Metode Pada Sistem Pendukung Keputusan Seleksi Penerima Beasiswa Satria, Budy; Sidauruk, Acihmah; Wardhana, Raditya; Al Akbar, Abdussalam; Ihsan, M. Arinal
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3056

Abstract

The selection process for scholarship recipients in higher education requires a measurable system. The problem that has been happening is that the procedures carried out by the scholarship provider still use a manual file examination system. Composite performance index is the method used in this study. The purpose of this study is to create a decision support system for the selection of scholarship recipients to be more systematic and time efficient in the process. There are 10 alternatives and 4 criteria, namely parental income, GPA, electricity usage ,and semesters. The results of this study were obtained 5 highest values are A7 t with a value of 235.00 rank 1, A4 with a value of 200.00 rank 2, A1 with a value of 134.14 rank 3 sequences, A5 with a value of 120.00 ranks 4, and A8 with a value of 91.67 sequences 5.
Diagnosis Penyakit Tanaman Kopi Robusta Menggunakan Metode Dempster Shafer Berbasis Sistem Pakar Acihmah Sidauruk; Panggih Suseno; Budy Satria; Mulia Sulistiyono
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3953

Abstract

Robusta coffee is a coffee variety that has unique characteristics, a strong taste and a different level of bitterness from Arabica coffee because Robusta coffee contains lower sugar and 2.2% more caffeine than Arabica coffee so that Robusta coffee production is quite helpful for the economy. several coffee producing countries in the world. The quality and productivity of coffee plants can decrease due to several factors such as pests and disease. However, the limitations of experts regarding coffee plant diseases are a factor and obstacle. The aim of this research is to create an expert-based intelligent system to identify pests and diseases in robusta coffee plants. The method that will be applied is Dempster Shafer. Data on disease names amounted to 13 and data on symptoms amounted to 27. The final result was that Robusta coffee plants were tested for expertise on the system with an average accuracy of diagnosis results of 94% from 13 test cases on pests and diseases of coffee plants, so it can be concluded that the system Experts can diagnose coffee plant pests and diseases 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 Kharisma, Rizqi Sukma 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