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Prototipe Deteksi PEN dalam Tubuh Menggunakan B-Mode Ultrasonic Scanning Chandra Edy Prianto; Agus Indra Gunawan; Niam Tamami
Jurnal Rekayasa Elektrika Vol 15, No 2 (2019)
Publisher : Universitas Syiah Kuala

Internal fixation is a method of healing fractures by connecting them using metal called pen. Pen metal in the body isn’t permanent, when the bone was strong the pen must be removed to avoid infection. In finding the pen, X-Ray are usually used. But X-Ray has bad effect, so not everyone is allowed to use it. The solution given by make prototype to detect pen location using B-Mode ultrasonic scanning method, it uses 5MHz single transducerultrasonic. Objects measurement is the animal bones connected with metals placed in the jelly with different heights. From the two transducers, the concave surface transducer has a better result and smaller percentage error than the flat surface transducer. The concave surface transducer has a focal length area 1.94cm above the transducer surface. The maximum slope angle of the object is 20o, which more than that makes the echo signal unreadable the object.The measurement results of objects displayed in the B-Mode 1 dimensional on PC that displays the structure of the bottom surface of an object, based on comparison between the actual object and the B-Mode display an error less than 6%, meaning B-Mode can represent the surface structure bottom of the actual object.

Prototipe Deteksi PEN dalam Tubuh Menggunakan B-Mode Ultrasonic Scanning Chandra Edy Prianto; Agus Indra Gunawan; Niam Tamami
Jurnal Rekayasa Elektrika Vol 15, No 2 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v15i2.13893

Internal fixation is a method of healing fractures by connecting them using metal called pen. Pen metal in the body isn’t permanent, when the bone was strong the pen must be removed to avoid infection. In finding the pen, X-Ray are usually used. But X-Ray has bad effect, so not everyone is allowed to use it. The solution given by make prototype to detect pen location using B-Mode ultrasonic scanning method, it uses 5MHz single transducerultrasonic. Objects measurement is the animal bones connected with metals placed in the jelly with different heights. From the two transducers, the concave surface transducer has a better result and smaller percentage error than the flat surface transducer. The concave surface transducer has a focal length area 1.94cm above the transducer surface. The maximum slope angle of the object is 20o, which more than that makes the echo signal unreadable the object.The measurement results of objects displayed in the B-Mode 1 dimensional on PC that displays the structure of the bottom surface of an object, based on comparison between the actual object and the B-Mode display an error less than 6%, meaning B-Mode can represent the surface structure bottom of the actual object.

Analysis of Students’ Errors in Solving Social Arithmetic Word Problems in terms of the Learning Styles Agus Indra Gunawan; Yuni Tri Astuti
Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education Vol. 1 No. 2 (2021): October 2021
Publisher : Pusat Studi Pengembangan Pembelajaran Matematika Sekolah UIN Sunan Kalijaga Yogyakarta Jl. Marsda Adisucipto, Yogyakarta 55281

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/quadratic.2021.012-03

Some abilities are needed to solve word problems, one of which is the ability to understand sentences and symbols in the problem. One factor that affects the ability of each student is learning style. Learning style is a person's tendency to receive and process information to the maximum, learning styles can be grouped into three, namely visual, auditory, and kinesthetic learning styles. The purpose of this study is to analyze and describe the forms of errors made by students in solving social arithmetic word problems in terms of the learning styles. Data collection procedures in this study are giving learning style questionnaire, written test, and interview. The research subjects are two VII grade students at SMP Negeri 1 Malang from each learning styles. The results of the analysis of this research are that students with visual learning style error occurs at the step of devising a plan, carriying out the plan, and looking back. While students with auditory and kinesthetic learning style error occurs at the understanding the problem, devising a plan, carriying out the plan, and looking back. The error forms occur in all learning styles.

Platform Budidaya Perairan Ekosistem Tambak Berbasis Internet Of Things Arisdiawan, Rossi; Setiawardhana; Agus Indra Gunawan
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3627

Indonesia has a potential pond area of 2,963,717 hectares. Ponds are a place for breeding ecosystems such as shrimp. The digitalization system in ponds is very necessary for management and development and has an impact on economic growth. Development in the field of aquaculture involves extensification and intensification. One of the intensification programs is to utilize Internet of Things (IoT) technology to identify various parameters from the Pond which are sent to the Webserver. This research is to produce a webserver-based platform to serve as a data center and monitor several IoT devices on the farm. This platform uses an internet network with HTTP and MySql protocols. Operations related to web servers and devices refer to standard quality settings from pond farmers.

Web-Based Smart Aquaculture: Comparative Analysis of Mamdani, Sugeno, and Tsukamoto Fuzzy Inference Systems for Shrimp Pond Water Quality Assessment Santi santi; Arna Fariza; Agus Indra Gunawan
Jurnal Teknologi Informasi dan Terapan Vol 13 No 1 (2026): June
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v13i1.493

Indonesia possesses vast marine and aquaculture potential; however, national shrimp production in 2024 achieved only 56.67% of its target, largely due to suboptimal water quality management. To address this issue, an intelligent classification system capable of handling uncertainty in aquaculture environments is required. This study presents a comparative evaluation of three fuzzy inference systems (FIS), namely Mamdani, Sugeno, and Tsukamoto, for shrimp pond water quality classification based on four key parameters: temperature, pH, salinity, and dissolved oxygen (DO). Water quality conditions were categorized into four classes: Good, Medium, Bad, and Very Bad using trapezoidal membership functions and expert-defined reference labels derived from aquaculture water quality standards. The dataset consisted of 994 water quality records collected from shrimp ponds in Surabaya, Indonesia, during the period from December 2024 to April 2025. Experimental results indicate that the Mamdani method produced the highest consistency with the expert-defined reference rules, achieving an agreement accuracy of 0.800, precision of 0.825, recall of 0.800, and F1-score of 0.797. In comparison, both Sugeno and Tsukamoto produced lower performance with an accuracy of 0.700 and F1-score of 0.728, although they achieved slightly higher precision values of 0.880. The findings indicate that the Mamdani fuzzy inference system provides more stable and consistent inference behavior relative to the predefined aquaculture reference rules for shrimp pond water quality assessment. Furthermore, the proposed web-based monitoring system demonstrates the practical potential of fuzzy logic approaches in supporting sustainable smart aquaculture management and environmental monitoring.

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