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All Journal Jurnal Fortech Journal of Student Research Exploration Jurnal FORTECH
Ubaidillah Ms, Achmad
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Sistem Identifikasi Kesegaran dan Jenis Ikan dengan Metode K-Nearest Neighbor Berdasarkan Citra Mata dan Bentuk Ikan Hadi Kusuma, Febrianto; Ubaidillah Ms, Achmad; Fiqhi Ibadillah, Achmad; Vivin Nahari, Vivin Nahari; Joni, Koko; Kurniawan Saputro, Adi
Jurnal FORTECH Vol. 4 No. 1 (2023): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v4i1.383

Abstract

Fish is a food commodity that needs attention, to improve the quality of food production, especially the fish itself. The level of freshness of fish greatly affects the quality of food production both at the household and industrial levels, as well as determining the feasibility of the fish for processing and consumption. Currently, to determine the level of quality of fish freshness, it is still done conventionally by humans, while those who have used tools but still have deficiencies in both the level of accuracy and also the features they have are still small. In this study, a tool or system design was carried out that could identify the freshness level of a fish based on eye images taken using a webcam camera or the like as input from data to be processed using image processing. In addition, the system is given additional features to be able to identify the type of fish. So that this additional feature can help facilitate identification all at once. To classify the method used is the K-Nearest Neighbor method. The results of the data processing will be displayed in the form of a sorting system for output. In the research results obtained from the system this time from 280 datasets for identification of freshness were tested on 50 images with a success rate of 96% for fresh and 84% for rotten. While the results of identification of fish species from 50 images of test data from three types of fish obtained a success rate of 97.7% with a value of k = 5.
The application of the tsukamoto fuzzy method in controlling the dryer for shrimp cracker hygienization Tyas, Kusumaningtyas; Ubaidillah Ms, Achmad; Rahmawati, Diana
Journal of Student Research Exploration Vol. 1 No. 2: July 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v1i2.143

Abstract

The process of drying crackers is traditionally carried out on the side of the road and open places. The impact of drying on product quality, especially hygiene because it is directly contaminated with dust, pollutants and pathogenic microbes. Drying depends on the sun's heat which affects the continuity of production and the level of drought. How to identify food hygiene using an inductive proximity sensor functions as a metal content detector. Because the metal content when ingested by humans is very dangerous. Drying is affected by temperature, moisture content and capacity. Oven drying application is equipped with an inductive proximity sensor and a DS18B20 temperature sensor. The Fuzzy Tsukamoto method for weight problems is grouped into a separate set. So that it can process oven temperature data. The control system for drying 3 shelves of crackers totaling 250 takes 25.6 minutes, drying 5 shelves of crackers totaling 410 takes 31.6 minutes. The drying process temperature is 30OC-70OC, the temperature used is a minimum of 60OC and a maximum of 65OC. Drying near the maximum temperature experiences a slowdown. If drying is done traditionally with the help of sunlight it takes longer.
Sistem Identifikasi Kesegaran dan Jenis Ikan dengan Metode K-Nearest Neighbor Berdasarkan Citra Mata dan Bentuk Ikan Hadi Kusuma, Febrianto; Ubaidillah Ms, Achmad; Fiqhi Ibadillah, Achmad; Vivin Nahari, Vivin Nahari; Joni, Koko; Kurniawan Saputro, Adi
Jurnal FORTECH Vol. 4 No. 1 (2023): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v4i1.383

Abstract

Fish is a food commodity that needs attention, to improve the quality of food production, especially the fish itself. The level of freshness of fish greatly affects the quality of food production both at the household and industrial levels, as well as determining the feasibility of the fish for processing and consumption. Currently, to determine the level of quality of fish freshness, it is still done conventionally by humans, while those who have used tools but still have deficiencies in both the level of accuracy and also the features they have are still small. In this study, a tool or system design was carried out that could identify the freshness level of a fish based on eye images taken using a webcam camera or the like as input from data to be processed using image processing. In addition, the system is given additional features to be able to identify the type of fish. So that this additional feature can help facilitate identification all at once. To classify the method used is the K-Nearest Neighbor method. The results of the data processing will be displayed in the form of a sorting system for output. In the research results obtained from the system this time from 280 datasets for identification of freshness were tested on 50 images with a success rate of 96% for fresh and 84% for rotten. While the results of identification of fish species from 50 images of test data from three types of fish obtained a success rate of 97.7% with a value of k = 5.
Co-Authors Achmad Fiqhi Ibadillah Diana Rahmawati Hadi Kusuma, Febrianto Koko Joni Kurniawan Saputro, Adi Tyas, Kusumaningtyas Vivin Nahari, Vivin Nahari