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All Journal Jurnal Fortech SinarFe7
Achmad Fiqhi Ibadillah
Universitas Trunojoyo Madura, Bangkalan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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RANCANG BANGUN MESIN PRES KAOS MENGGUNAKAN MIKROKONTROLER BERBASIS ANDROID Riza Alfita; Achmad Fiqhi Ibadillah; Ivan Dwi Cahyo; Kunto Aji Wibowo; Haryanto
SinarFe7 Vol. 4 No. 1 (2021): SinarFe7-4 2021
Publisher : FORTEI Regional VII Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (551.79 KB)

Abstract

Mesin pres kaos merupakan mesin pres yang dipakai untuk cetak sablon pada media datar. Sistem kerjanya menggunakan panas dan disebut dengan Mesin Heat/Hot Pres. Dalam kegiatan produksi UKM yang bergerak di bidang konveksi terdapat suatau hal yang menjadi perhatian yaitu penggunaan pres sablon dengan mesin digital heat pres besuhu tinggi yang mana dapat meningkatkan pendapatan dan pencapaian produktivitas tinggi dalam suatau industri terutama industri rumahan. Android merupakan sistem operasi berbasis Linux yang mana hampir semua smartphone jaman sekarang memakai sistem operasi tersebut dengan segudang fitur yang canggih. Pada penelitian ini menggunakan smartphone android sebagai alat untuk mengontrol sistem kerja dari mesin pres kaos. Hal ini dilakukan agar dapat memudahkan manusia untuk memberikan perintah secara wireless (tanpa kabel) dengan menggunakan bluetooth sebagai komunikasinya. Sehinga alat yang akan dibuat ini mampu di operasikan secara otomatis dan bisa dikontrol melalui android smartphone. Selain penggunaan android smartphone dan juga bluetooth, pada penelitian ini juga membutuhkan beberapa komponen pendukung yang digunakan untuk menjalankan proses pengepresan mesin pres kaos antara lain mikrokontroler STM32F103, sensor thermocouple & modul MAX6675, pneumatic, kompressor, relay 1 channel, sensor infrared, boost converter stepup, buck converter stepdown, limit switch, buzzer, dan LCD (Liquid Crystal Display).
Sistem Identifikasi Kesegaran dan Jenis Ikan dengan Metode K-Nearest Neighbor Berdasarkan Citra Mata dan Bentuk Ikan Febrianto Hadi Kusuma; Achmad Ubaidillah Ms; Achmad Fiqhi Ibadillah; Vivin Nahari Vivin Nahari; Koko Joni; Adi Kurniawan Saputro
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 Ubaidillah Ms Adi Kurniawan Saputro Ayu Dian Lestari Diana Rahmawati Febrianto Hadi Kusuma Hanifuddin Sukri Haryanto Ivan Dwi Cahyo Koko Joni Kunto Aji Wibowo Riza Alfita Vivin Nahari Vivin Nahari