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All Journal Proceedings of KNASTIK Jurnal Ilmu Komputer dan Agri-Informatika JPSriwijaya JOIV : International Journal on Informatics Visualization Jurnal Teknoinfo MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Krea-TIF: Jurnal Teknik Informatika Journal of Science Innovare Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika IJEEIT : International Journal of Electrical Engineering and Information Technology Building of Informatics, Technology and Science Jurnal Leverage, Engagement, Empowerment of Community (LeECOM) JTIK (Jurnal Teknik Informatika Kaputama) Journal Social Science And Technology For Community Service Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Aplikasi Bisnis dan Komputer J-Icon : Jurnal Komputer dan Informatika Bulletin of Informatics and Data Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Artificial Intelligence and Technology Information JIPETIK:Jurnal Ilmiah Penelitian Teknologi Informasi & Komputer Prosiding SeNTIK STI&K
Sufiatul Maryana
Universitas Pakuan
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences Other

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Journal : Jurnal Teknoinfo

 1 
APLIKASI PANDUAN GIZI MAKANAN BALITA BERBASIS ANDROID Yunita Rahma; Dini Suhartini; Sufiatul Maryana
Jurnal Teknoinfo Vol 16, No 2 (2022): Juli
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v16i2.1790

Abstract

Fulfillment of rich nutrition for toddlers is something that needs to be considered in maintaining health because the age of toddlers enters a nutritional sensitive period. The impact of malnutrition in the first 1000 days of life starting from the fetus to the child is two years old, it not only affects physical development, but also affects subsequent cognitive development, which in turn affects the intelligence, dexterity, and efficiency of thinking and working children at the time. mature. Nutritional status refers to the state of the body caused by eating and using nutrients. This is due to maternity factors and poor parenting, especially the behavior and habits of children who do not eat according to their nutritional intake. Parental knowledge regarding a balanced and nutritious menu is the most influential factor in providing nutrition to toddlers. The lack of nutrition education by health workers makes mothers unable to prevent and overcome nutritional problems in their babies. Based on this, an application is needed that can facilitate parents, especially mothers, to control the nutritional status of their toddlers accompanied by nutritional guidelines for appropriate and balanced toddler food according to their age and nutritional adequacy. This research will build a mobile-based application in the form of a nutritional guide for toddlers' food that is appropriate and balanced according to their age and nutritional adequacy and a nutritional calculator for toddlers to control their nutritional status.
EKSTRAKSI CITRA MENGGUNAKAN METODE LAPLACIAN DAN SVM (SUPPORT VECTOR MACHINE) UNTUK IDENTIFIKASI JENIS TANAMAN PAKU BERDASARKAN CITRA SPORA Sufiatul Maryana; Herfina Herfina; Arie Qurania; Herlinda Herlinda
Jurnal Teknoinfo Vol 17, No 2 (2023): Vol 17, No 2 (2023) : JULI
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v17i2.2579

Abstract

Spores are a breeding tool for ferns (Pteridophyta) which are generally found under the surface of each leaf. Research on the characteristics of Pteridophyta spores is generally done by observing their size and shape to see the type of spore. The method that will be carried out in this study requires a lot of understanding, experience, accuracy and time to achieve high accuracy in determining the type. Based on these reasons, it is necessary to develop another technique with modeling to help identify the type of Pteridophyta in the spore. This paper discusses image extraction for fern identification based on spore images using the Laplacian method and SVM. Laplacian method is used to extract features from spore images, while SVM is used to classify ferns. This method requires a lot of understanding, experience, accuracy and time to achieve high accuracy in determining the type. Based on these reasons, it is necessary to develop another technique with modeling to help identify the type of Pteridophyta in the spore. The purpose of this research is to make Support Vector Machine (SVM) modeling to identify fern species based on spore images in Eigen space. The data used are spore images with four classes, each of which has 24 data per class with a total of 96 images. The method used in this research is Laplacian method for feature extraction and SVM for data classification using Gaussian RBF and Polynomial kernel function experiments. The result of this research is the accuracy of each extraction that has been tried. The best result lies in the RBF kernel function with 70% feature extraction and 10 parameters with an accuracy of 98.96%.
Co-Authors Abdat, Misel Umar Agung Prajuhana Putra Agung Prajuhana Putra Agung Prajuhana Putra Alfiansyah Alfiansyah Andi Mulyono Anggraeni, Ade Irma Arie Arie Qur’ania Arshad, Muhammad Waqas Asep Kohar Benny Nofika Benny Rachman Chandra, Iryanto Dian Kartika Utami Dieke Aprianto Edi Santosa Eneng Tita Tosida Fani Susanti Hamzah, Rizki Maulana Heni Sulistiani Herfina Herfina Herlinda Herlinda Hermawan Hermawan Hifshan Riesvicky Iyan Mulyana Kamel Mahdi Lita Karlitasari Lita Karlitasari Mehta, Abhishek Mubarok, Yasir Pahmi mulyono, andi Mutiara Prihatini Nofika, Benny Oktaviani, Nabila Oktaviani Palupiningsih, Pritasari Prajuhana Putra, Agung Putri Dwi Lestari Rahma, Yunita Reno Cahyo Hutomo Setiawan, Andrian Setiawansyah Setiawansyah Sitna Hajar Hadad Soewarto Hardhienata Sri Wahjuni Sudrajat, Cecep Suriansyah, Muhammad Iqbal Tjut Awaliyah Zuraiyah Yudhia Mulya Yuli Wahyuni Yuri Rahmanto Zebua, Mitra Darma Zolla Zolla