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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) International Journal of Informatics and Communication Technology (IJ-ICT) Bulletin of Electrical Engineering and Informatics Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab SISFOTENIKA JURNAL INTEGRASI JRST (Jurnal Riset Sains dan Teknologi) JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Teknoinfo ILKOM Jurnal Ilmiah Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) METIK JURNAL Jurnal Informatika dan Rekayasa Elektronik Sains, Aplikasi, Komputasi dan Teknologi Informasi TEPIAN Jurnal Sistem Informasi dan Sistem Komputer Jurnal Teknik Informatika (JUTIF) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Inovasi Teknologi Masyarakat
Tejawati, Andi
Program Studi Informatika, Fakultas Teknik, Universitas Mulawarman, Indonesia
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
COMPARISON OF K-NEAREST NEIGHBOR AND NAIVE BAYES METHODS FOR CLASSIFICATION OF NEWS CONTENT Andi Tejawati; Anindita Septiarini; Rondongalo Rismawati; Novianti Puspitasari
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.676

Abstract

With the development of technology, news reading via the internet or digital tends to increase. In addition, there are about 300 to 400 news articles in one month and many categories of news articles in a web portal. It makes the editor's performance more and more because an editor must be able to edit articles from various channels and at the same time have to categorize articles one by one manually into several specified categories. This study aims to compare the K-Nearest Neighbor (KNN) and Naive Bayes methods to classify news content in order to obtain the best method. The data used in this study are news articles from the web portal kaltimtoday.co from January 2022 to March 2022. Therefore 576 data are obtained. The results showed that the application of the KNN and Naive Bayes methods could be used to classify news content. The KNN method is able to produce a higher accuracy value than Naïve Bayes, reaching 86% and 51% with test data of 100 news articles.
COMBINATION OF WP AND TOPSIS METHODS IN A DECISION SUPPORT SYSTEM FOR WATERMELON SEED RECOMMENDATION Tejawati, Andi; Puspitasari, Novianti; Pasorong, Hillary Bella; Masa, Amin Padmo Azam
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2317

Abstract

Watermelon is a horticultural plant that can be cultivated by the wider community with adequate profits. In Indonesia, watermelon production is still unable to meet the huge market demand and has not been able to be met by local watermelon-producing areas. One of the reasons why watermelon production is insufficient is because the fruit is easily damaged due to inappropriate watermelon seeds. The right watermelon seeds can be selected using a Decision Support System. This study uses two combination methods, namely Weighted Product (WP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to be applied in the Decision Support System for watermelon seed recommendations. The WP method is used to determine the weight of the criteria, while TOPSIS is used to determine the order of watermelon seed recommendations. The data used in this study were twenty alternative watermelon seeds with five criteria, namely land recommendations, yield potential, fruit weight, harvest age, and disease resistance. Of the five criteria determined by the WP method, the largest criterion value is in the land recommendation. The results of the implementation with both methods produced recommendations for watermelon seeds, with the first ranking result being the F1 Series (3n) watermelon seeds with a preference value of 0.85442, and black box testing showed that this system was able to provide recommendations for quality watermelon seeds according to their functionality based on the application of the WP and TOPSIS methods.
Co-Authors Achmad, Rayhan Zidane Ade Chrisvitandy Ahmad Wahbi Fadillah Alameka, Faza Anam, M Khairul Andi Azza Az-Zahra Andi Muhammad Redha Putra Hanafiah Anindita Septiarini, Anindita Anjas, Andi Anton Prafanto Arba, Muhammad Hendra Arief Hidayat Bambang Cahyono Budiman, Edy Budiman, Edy Damayanti, Elok Didit Suprihanto, Didit Eddy Kurniawan Pradana Eka Priyatna, Surya Ery Burhandenny, Aji Fadli Suandi Fahrul Yamani Fairil Anwar Fajar Fatimah Faza Alameka Fernando Elda Pati Ferry Miechel Lubis Firdaus, Muhammad Bambang Friendy Prakoso Hairah, Ummul Hairah, Ummul Hamdani Hamdani Hanif Aulia Hasman, Firnawan Azhari Heni Sulastri indrajit, Indrajit Irfan Putra Pratama Irsyad, Akhmad Joan Angelina Widians, Joan Angelina Kamila, Vina Zahratun Lathifah Lathifah Lathifah Lathifah Lubis, Ferry Miechel M Syauqi Hafizh Masa, Amin Padmo Azam Masna Wati Medi Taruk Muhammad Bambang Firdaus Muhammad Budi Saputra Muhammad Nopri Fauzi Muhammad Nur Ihwan Nariza Wanti Wulan Sari Novianti Puspitasari Pakpahan, Herman Santoso Pasorong, Hillary Bella Pohny Pohny Puspita Octafiani Puspitasari, Novianti Ramadhan, Khefyn Rantetana, Stevie Falentino Renol Sulle Richard Giovanni Ardie Wong Riyayatsyah, Riyayatsyah Rizqi Saputra Rondongalo Rismawati Rosmasari Rosmasari, Rosmasari Saipul, Saipul Setyadi, Hario Jati Sofiansyah Fadli Sukma Dewi Hardi Yanti Syahbana, Syarif Nur Taruk, Medi Wahyudianto, Mochamad Rizky Wahyudin Wahyudin Waksito, Alan Zulfikar Wardhana, Reza Wati, Masna Wenty Dwi Yuniarti, Wenty Dwi Widians, Joan Angelina Zainal Arifin Zainal Arifin