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Journal : Jurnal Teknik Informatika C.I.T. Medicom

Application of color extraction methods and k-nearest neighbor to determine maturity avocado butter Wina Fadia Ardianti; Sriani Sriani; Abdul Halim Hasugian
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 1 (2023): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.375.pp09-20

Abstract

Computerization requires system testing and further system development, namely color feature extraction with KNN. Avocado is one that has a high protein content in it. This research uses the KNN algorithm method and feature extraction in order to get more effective results, the purpose of this research is to make it easier for people to choose the ripeness level of butter avocados because people still don't know about the maturity level of butter avocados. In this study, testing was carried out by bringing the avocado fruit closer to the cellphone camera connected to the researcher's internet, after which the application will automatically match the color of the avocado. to the system, the system will produce output based on that color with output in the form of the ripeness level of the avocado, whether it is ripe, ripe, half ripe, rotten and also generates information on how much longer the avocado will ripen. All stages of system development are carried out by analyzing data first, then taking sample data, training and testing datasets, then the results of the system will become benchmarks. The test data in this study used several types of avocado objects, namely: Raw, Half Ripe, Ripe, Ripe, Rotten. It consisted of 55 data samples consisting of 11 raw avocado samples, 11 half-ripe avocado samples, 11 ripe avocado samples, 11 ripe avocado samples and 11 rotten avocado samples. Obtained euclidean distance values ​​for each type of avocado butter. After that, the sum is done to get the overall level of accuracy by adding up the total euclidean distance with the total euclidean distance for each type of avocado. After getting the added value multiply it by 100%. Then the overall accuracy results obtained are 98.38%.
Application of color extraction methods and k-nearest neighbor to determine maturity avocado butter Wina Fadia Ardianti; Sriani Sriani; Abdul Halim Hasugian
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 1 (2023): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2023.375.pp09-20

Abstract

Computerization requires system testing and further system development, namely color feature extraction with KNN. Avocado is one that has a high protein content in it. This research uses the KNN algorithm method and feature extraction in order to get more effective results, the purpose of this research is to make it easier for people to choose the ripeness level of butter avocados because people still don't know about the maturity level of butter avocados. In this study, testing was carried out by bringing the avocado fruit closer to the cellphone camera connected to the researcher's internet, after which the application will automatically match the color of the avocado. to the system, the system will produce output based on that color with output in the form of the ripeness level of the avocado, whether it is ripe, ripe, half ripe, rotten and also generates information on how much longer the avocado will ripen. All stages of system development are carried out by analyzing data first, then taking sample data, training and testing datasets, then the results of the system will become benchmarks. The test data in this study used several types of avocado objects, namely: Raw, Half Ripe, Ripe, Ripe, Rotten. It consisted of 55 data samples consisting of 11 raw avocado samples, 11 half-ripe avocado samples, 11 ripe avocado samples, 11 ripe avocado samples and 11 rotten avocado samples. Obtained euclidean distance values ​​for each type of avocado butter. After that, the sum is done to get the overall level of accuracy by adding up the total euclidean distance with the total euclidean distance for each type of avocado. After getting the added value multiply it by 100%. Then the overall accuracy results obtained are 98.38%.
Co-Authors Abdillah, Ibnu Faiz Adam Damiri Manurung Adi Hartono Aditya Maulana Azanzi Girsang Afandi Sahputra Aidil Halim Lubis Aidil Halim Lubis Ajeng Dwi Pratiwi Ali Darta Ali Ikhwan Alwy Azyari Harahap Amalia Daulay, Rizki Amelia Amri Yuda S Anggraini, Sindi Annisa Shafira Zuhri Armansyah Armansyah Armansyah Asrul Suwondo Azhar, Joehari Bandaharo, Bandaharo Bermiko Kasah Padang Bunga Nurul Manisa Cindy Ananda Putri Dea Amallia Deni Fahrizal Dewi Afrianti Dina Afriani Dinda Zukhoiriyah Eferoni Ndururu Elsa Azila Rahman Fakhriza, M. Farah Zaida Gema Ramadhan Gilang Armawan Saka Ginting, Masitha Putri Ardhana Gunawan Gunawan Gunawan, Helmi Hanny Puput Eliyarista Saragih Harahap, Muhammad Fitrah Affandi Harahap, Nasywa Al Afif Heni Pujiastuti Heri Santoso Heri Santoso Heri Santoso HERI SUSANTO Hsb, Munawir Siddik Ibnu Rusydi Ilham Ilham Ilka Zufria Imam Zaki Husein Nst Indah Alfitri Lubis Irene Sri Morina Januar, Bagus K Khairunnisa Khaidir Hanafi Khairuna Khairuna Khairunnisa, K Lubis, Akbar Maulana Lubis, Desy Ramadhani M Mahyudi M. Fakhriza M. Khalil Gibran M.Alif Fahrezy Maimunah Rahmadani Maulida, Dzikra Maya Khairani Mhd Furqan Mhd Ikhsan Rifki Mhd. Fakhrozi Arif Mhd. Furqan Mufliha Afiksih Muhammad Aditya Prasetio Muhammad Alfarizi Muhammad Arief Irawan Muhammad Ezar Raditya Muhammad Farhan Alhabib Muhammad Ikhsan Muhammad Ikhsan Muhammad Ridzki Hasibuan Muhammad Sayuthi Muhammad Siddik Hasibuan Muhammad Suhery Mulya Alfan Simatupang Murdani Muthia Ramadhani Nadyah Almirah Simanjuntak Nasution, Yazid Hulaini Habbani Nasution, Yurika Nur Jamilah Aruan Nurmaiyah Nurmaiyah Ong, Russell Pahlevi, Mhd Rafly Syah Pazri Pebriani Putri Prayoga, M. Irsan Pristiwanto Putra, Donny Dwi Putri Hanifah Rahadian Fatta Batubara Rahmad Prayogi Harahap Rahmawati Rahmawati Raissa Amanda Putri Rajani, Attila Rakhmat Kurniawan R Ramadhani, Silvia Rano, Rano Irawan Reza Muhammad Rijal, Mhd. Nanda Khairul Rina Widyasari Rizki Amalia Rizky Pratama Putra Rizky Ramadhan Rizqi Hidayat Tanjung RR. Ella Evrita Hestiandari Ryo Vikri Alif Saefuddin, Anan Sela, Dhea Shania Oktawijaya Sheila Safira Siahaan, Ahmad Taufik Al Afkari Simanjuntak, Salmah Simatupang, Aidil Akbar Siregar, Muhammad Faisal Siregar, Nora Arianti Siti Hayatul Fauziah Ritonga Siti Juhroini Ritonga Siti Nurhaliza Sofyan Siti Sumita Harahap Sitorus, Ridha Saryani Situmorang, Rantouli Solifiah Batubara, Febi Sri Suci Yani Sriani Sriani Sriani Sriani, S Suandi Padang Suendri Suendri, Suendri Suhardi Suhardi Suhardi Suhardi Sulindawaty T. Raihan Yudisthira TONNI LIMBONG Tria Elisa Ulfah, Auliana Wina Fadia Ardianti Windary, Wanda Wirna Rizka Auliani Yusuf Karim Rambe Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Zaidan, Muhammad Zidanul Akbar Ziqra Addilah Zul Attoriq Farhan Wahyudi