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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer

Hurriyatul Fitriyah, Hurriyatul

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Author-ID : 627125

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 16 Documents Claim Missing Document

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Title

Automatic Measurement of Human Body Temperature on Thermal Image Using Knowledge-Based Criteria Fitriyah, Hurriyatul; Rachmadi, Aditya; Setyawan, Gembong Edhi
Journal of Information Technology and Computer Science Vol. 2 No. 2: November 2017
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Instead of thermometer, an infrared camera could be uti-lized to scan body temperature instantly and non-contact. This paperproposed a non-contact measurement of human body temperature by au-tomatically locating inner-chantus on thermal images. The inner-canthuswere detected in both eyes individually. It located inner-canthi based ontemperature where inner-canthi has the highest temperature in face area.A Thresholding based on 9-highest temperature were applied to detectcandidates of inner-canthus' blob as it must have minimum 9 pixel areaaccording to the Standard. Three knowledge based on characteristic ofeye were also applied in the algorithm as several spot in face usuallyfalls within the temperature threshold. The result show accuracy of al-gorithm to detect eye is 82% whether the eyelids were open or closed.There is no signicant dierent of temperature between closed and openeyes based on paired t-test. The algorithm also showed similar result tothermometer measurement based on paired t-test.

Classification of Physical Soil Condition for Plants using Nearest Neighbor Algorithm with Dimensionality Reduction of Color and Moisture Information Syauqy, Dahnial; Fitriyah, Hurriyatul; Anwar, Khairul
Journal of Information Technology and Computer Science Vol. 3 No. 2: November 2018
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Determining the quality of soil is an important task to perform especially on newly opened agricultural land since it may provide significant impact on the growth of plants. One alternative to determine physical soil quality is by visually observe the color of the soil and measure its moisture. This paper designed an embedded system classify soil condition for plants according to the dimensionality reduction of color and moisture information from the soil using k-NN algorithm. The dimension of attribute information was reduced using correlation analysis to achieve lower computational time and lower memory usage on embedded system. In this study, 39 sample of soil from various location were collected and categorized by soil expert using visual observation. In the accuracy testing on the system that used 4 attributes, 100% accuracy was given by 60:40 ratio with 7 neighbors. In contrast, the system that used only 2 attributes, 100% accuracy was given by 60:40 ratio with 5 nearest neighbors. The resource usage testing shown that by using reduced attributes dimension, the resource usage can be lowered as many as 188 bytes on program storage and 192 bytes on global variable usage. Moreover, the average of computation time performed by the system using reduced attribute dimension achieved 5.4 ms compared to the system that used all attributes which achieved 6.2 ms.

Applying Linear Regression to Estimate Weight of Non Axi-Symmetric fruit Fitriyah, Hurriyatul; Setiawan, Eko; Masruri, Muhammad Rifqi Radifan
Journal of Information Technology and Computer Science Vol. 5 No. 2: August 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Weight is an important parameter in fruitsâ€™ quality identification. Measuring fruitsâ€™ weight using scale is tedious since fruits must be taken from tree and placed on contact to scale. Many researches have proposed non-contact estimation methods of fruitsâ€™ weight using 2D images. The studies were commonly applied in axi-symmetric fruits, such oranges. In this paper, an algorithm to estimate weight of non axi-symmetric fruit is developed. It used a Linear Regression rather than geometric-based methods as proposed by other researches. The non axi-symmetric fruits chosen was star fruits. It is a challenging fruits since its basic shape is not round but irregular star shape. The estimation used pixel count from one-view image of the fruitsâ€™ projection as feature. The proposed method has RMSE of 16.322 Gram and MAPE of 7.089% compare to the expected weights. It also has high Coefficient of Determination, R^2, 0.8829 compare to the weight scale measurement.

Co-Authors Aditya Rachmadi, Aditya Adiwijaya, Benny Alghifary, Fahreza Abuzard Arasy, Rizki Cahya Dahnial Syauqy Dewa, Muklas Isa Edita Rosana Widasari, Edita Rosana Eko Setiawan Erza, Fahmi Fathurrahman, Farhan Firmansyah, Dheni Gembong Edhi Setyawan Hannats Hanafi Ichsan, Mochammad Khairul Anwar Khairunnisa, Putri Masruri, Muhammad Rifqi Radifan Mochammad Hannats Hanafi Ichsan Muhammad Fahrizal, Muhammad Pratama, Muhammad Naufal Rafi Rakhmadhany Primananda, Rakhmadhany Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rizal Maulana, Rizal Siahaan, Arnold Susilo, Faizal Andy

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