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All Journal WIDYA TEKNIKA Jurnal Teknologi dan Manajemen Informatika DINAMIKA DOTCOM TEKNOLOGI INFORMASI Prosiding SNATIKA Vol 01 (2011) International conference on Information Technology and Business (ICITB) SMATIKA JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Conference on Innovation and Application of Science and Technology (CIASTECH) Journal on Education Jurnal Masyarakat Merdeka (JMM) Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS Jurnal Pendidikan dan Keluarga Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Community Development Journal: Jurnal Pengabdian Masyarakat Among : Jurnal Pengabdian Masyarakat International Journal of Business, Law, and Education Jurnal Simki Pedagogia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) ETAM: Jurnal Pengabdian kepada Masyarakat Prosidia Widya Saintek Jurnal Pengabdian Masyarakat dan Riset Pendidikan El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Journal of Ekonomics, Finance, and Management Studies JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
MARIFANI FITRI ARISA
Universitas Negeri Yogyakarta
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Journal : Buana Information Technology and Computer Sciences (BIT and CS)

 1 
Detection of Diseases and Pests on The Leaves of Sweet Potato Plants sing Yolov4 nisti, Melita; Yuniar Rahman, Aviv; Marisa, Fitri
Buana Information Technology and Computer Sciences (BIT and CS) Vol 5 No 1 (2024): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v5i1.6065

Abstract

Sweet potato (Ipomea batats) is a root plant that can live in all weather, in mountainous areas and on the coast.. This plant is one of the important food crops in Indonesia, and makes Indonesia the second largest sweet potato producer after China. However, according to data from the Central Statistics Agency (BPS), sweet potato production in Indonesia in 2018 decreased by 5.63% when compared to production in 2017 which reached 1,914,244 tons (Gultom, 2021). Based on these data, it is important to conduct research on pest and disease detection in plants. Therefore, the author conducted a study related to this problem entitled Detection of Diseases and Pests on the Leaves of Sweet Potato Plants using Yolov4 with the aim of helping educate farmers in recognizing diseases on the leaves of sweet potato plants and how to overcome them. In this study the dataset was sweet potato leaves with a total of 1500 data divided into three classes, namely aspidomorpha, yellow spot and normal leaves with 4000 iterations. The best training results on 1500 data with 75% accuracy. The Yolov4 algorithm produces high accuracy in detecting diseases in the leaves of sweet potato plants.
A Detection of Malacca Woven Fabric Motifs Using the YOLOv4 Method Neno, Adi; Yuniar Rahman, Aviv; Marisa, Fitri
Buana Information Technology and Computer Sciences (BIT and CS) Vol 5 No 1 (2024): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v5i1.6081

Abstract

Malacca is one of the districts that has a weaving culture and also produces woven cloth in East NusaTenggara. The large number of types of woven cloth from each Malacca tribe means that outsiders andeven native Malacca people are not yet familiar with typical Malacca motifs, therefore a system isneeded that can help make it easier for people to recognize the types of woven fabric motifs. Malaccawoven fabric in this study was used to detect the types of woven fabric motifs in Malacca district usingthe YOLOv4 method. The results of detecting Malacca woven fabric motifs correspond to each type ofwoven fabric. Apart from that, the Malacca woven fabric motif detection system with YOLOv4technology is an effective and efficient solution in recognizing Malacca woven fabric motifs. Malaccawoven fabric is classified into four classes with an impressive mAP score of 100%.
Co-Authors Addian Nur Rijal Adi Masliardi Ahmad, Sharifah Sakinah Syed Akbar, Ismail Ali muhajir, Ali Alifia Nandira Maharani Anastasia Lidya Maukar Andy Hardianto Anik Vega Vitianingsih Anjani, Sofia Puspa Araujo, Aprilio Demetrius De Arie Restu Wardhani Arisanti, Diah Aviv Yuniar Rahman Badrussalam, Nanda Bagas Imadani Putra, Alif Bambang Amir Alhakim Bura, Audyel Umbu Christine Ulina Tarigan Dahlia Denny Bernardus Dewa Oka Suparwata Dini Kristianti, Dini Domingos Sinorio de Araujo, Domingos Dwi Fita Heriyawati Dwi Purnomo Efendi, Dedi Usman Elok Novita Fatmawati, Amelia Firman Hidayat Firman Nurdiyansyah, Firman Hajar Mukaromah Hamzah Al Imran Hardiyanto, Andy Haryanto, Kurniawan Wahyu Ika Pranita Siregar Indah Dwi Mumpuni Indra Dharma Wijaya, Indra Dharma Istiadi jauhar, afif KRISTIAWAN KRISTIAWAN Kushariyadi Kushariyadi Ladopurab, Bartolomeus Wadan Larasati, Isbalaikana Luruk, Maria Ovalia Margaret Stevani Marilaeta Nurak, Yulita Maukar, Anastasia Maukar, Anastasia L Maukar, Anastasya Lidya Mausa Agrevinna Meidy Diliana Agustin Nahak, Redemtus Neno, Adi nisti, Melita Nova Ch. Mamuaya NURDIANSYAH, FIRMAN Nurfitri, Indah Karminia Pradana, Teguh Pramisela, Intan Yosa Pramudita, Atanasia Prissiani Andi Ningrum Purnamasari, Putri Indah Puspitarini, Erri Wahyu Putra, Dimas Rossiawan Hendra Putra, Rangga Pahlevi Putri, Avira Maresa Putri, Chauliyah Fatma Putri, Jessica Ananda Rena Augia Putrie Rini Agustina Rivaldiknas Gampar, Philipus Rochmawati, Sofi Nur Rosario, Maria Madalena Do Salmanarrizqie, Ageng Sidi, Husri Slamet Riyadi, Slamet Riyadi Sofyan Rachma Danni, Muhammad Sufa, Siska Armawati Sufianto, Dani Suprianto Suprianto Susti Rumianti Ulfah Rahamawati, Ulya Un, Fransiskus Deni Wahyu Iriananda, Syahroni Warda Indadihayati Wardianto, Wardianto Wijaya, Indra Darma Yudi Kristyawan, Yudi