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All Journal Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Electro Luceat JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Techne : Jurnal Ilmiah Elektroteknika Multitek Indonesia : Jurnal Ilmiah Jurnal Teori dan Aplikasi Fisika Jurnal Pengabdian Al-Ikhlas JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) JE-Unisla Generation Journal Journal Zetroem JAREE (Journal on Advanced Research in Electrical Engineering) Journal of Electrical Engineering and Computer (JEECOM) JASEE Journal of Application and Science on Electrical Engineering Jurnal Pendidikan dan Teknologi Indonesia Jurnal Techno Bahari JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) SinarFe7 Fuse-teknik Elektro Jurnal Elektro Kontrol (ELKON) Jurnal Informatika Polinema (JIP) Jurnal Ilmiah Sistem Informasi
Erwanto, Danang
Universitas Islam Kadiri
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : Journal Zetroem

 1 
Sistem Electronic Nose Untuk Deteksi Aroma Pada Fasilitas Kamar Mandi Berbasis IoT Danang Erwanto; Deka Wahyudi; Royb Fatkhur Rizal
ZETROEM Vol 5 No 1 (2023): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v5i1.2620

Abstract

Internet of Things (IoT) dan Electronic nose (E-Nose) serta penggunan Fuzzy Logic, merupakan teknologi yang saat ini berkembang. Pada teknologi berbasis IoT, keseluruhan aktivitas yang dikerjakan oleh manusia, bisa dikendalikan dengan memanfaatkan jaringan internet. Hal ini dimanfaatkan untuk metode alternatif mengendalikan bau untuk kebersihan toilet, yang dapat dimonitoring melalui jaringan internet, ESP32 sebagai mikrokontroler, dan sensor MQ-3, MQ-135, MQ-137 dan sensor DHT11. Tujuan dari penelitian ini adalah membangun perangkat lunak untuk memantau kebersihan toilet melalui smartphone menggunakan aplikasi Telegram. Sistem ini digunakan untuk mengetahui efisiensi dalam mengendalikan bau toilet dengan memanfaatkan IoT. Hasil penelitian ini berupa sistem untuk mengontrol kebersihan toilet berbasis IoT dengan memanfaatkan jaringan internet sehingga dapat memantau kebersihan toilet melalui smartphone. Pemantauan ini bisa dilaksanakan dimanapun selama sistem dapat terhubung dengan jaringan internet. Dari penelitian ini sistem mampu mengirim data ke smartphone dengan baik melalui internet tanpa terjadi delay dan error data. Selama kadar alkohol, amonia dan karbondioksida diambang batas wajar tidak akan muncul pemberitahuan lewat telegram ataupun buzzer. Sistem telah berfungsi sesuai dengan yang dirancang, yaitu informasi data yang diperoleh sesuai dengan data yang dikirimkan oleh perangkat keras.
Identifikasi Kematangan Cabai Rawit Menggunakan Metode Momen Warna Dan SVM Ridhovi, Zainul; Erwanto, Danang; Yanuartanti, Iska
ZETROEM Vol 7 No 1 (2025): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v7i1.3626

Abstract

This study focuses on the identification of the ripeness of bird's eye chili (Capsicum annuum L.) using the color moment method and Support vector machine (SVM). Bird's eye chili holds significant economic value in the agricultural industry, but the rapid and accurate identification of ripeness remains a challenge. The color moment method is employed to extract features from images of bird's eye chili, while SVM is used for classification based on the extracted features. This research expands the use of data and optimizes SVM parameters to enhance the accuracy of identification. The results indicate that the classification model using the SVM method successfully classifies the ripeness levels of chili with an accuracy of 82%, categorized as good. Specifically, it achieved a precision of 66.67%, recall of 83.33%, and F-measure of 74.07% for the "ripe" category. The "unripe" category achieved perfect precision and recall, both at 100%, with an F-measure of 100%. Meanwhile, the "half-ripe" category achieved a precision of 80.00%, recall of 77.42%, and F-measure of 78.73%. However, some misclassifications were attributed to color dominance issues in certain images. Therefore, this study contributes to the development of more accurate and efficient techniques for chili ripeness identification. Recommendations for future research involve further evaluation with a broader test dataset, improvements in classification methods, and the consideration of additional features to enhance classification accuracy. This research offers both scientific and practical benefits in image processing, machine learning, and the agricultural industry
Co-Authors Achmad Arif Alfin Ade Prabowo Ahmad Ari Setyawan Kusuma Alhadidi, M. Baihaqi Aprilia, Yoga Pebri Arisudin Arisudin Arisudin Asti Riani Putri Atika Kurniasari Ayssa Nurmastika Azzah Rowani, Eka Cahya AJi Saputra Deka Wahyudi Dendi Gunawan Deni Wahyu Wibowo Diah Arie Widhining K. Diah Arie Widhining Kusumastutie Dian Efytra Dian Efytra Yuliana Dian Efytra Yuliana Dian Septi Nur Afifah Eka Azzah Rowani Eka Nuryanto Budi Susila Eka Rahayu Septiana Fajar Yumono Fajar Yumono Fajarudin Fajarudin Farrady Alif Fiolana Farrady Alif Fiolana Farrady Alif Fiolana Fauzi, Muhammad Iqsan Geston Bakti Muntoha Iska Yanuartanti Ismail, Alfian Danu Khafi, Agus Maulana Kusumastutie, Diah Arie Widhining Maulana Alfaruq, Bagoes Maulana F, Delta Mochtar Yahya Mochtar Yahya Mohammad Heri Saputra Mohammad Rangga Nur Faizin Muhammad Azizul Fikri Muhammad Erfan Muhammad Iqsan Fauzi Muthrofin, Mohammad Atif Faiz Naofal, Ahfan Nur Rifa’i, Wahib Rohman Nuzulul Septiana Devi Putri Nur Rahayu Putri Nur Rahayu Rahayu, Putri Nur Ridhovi, Zainul Rizki Bayu Samudra Rosanti, Aulia Dewi Royb Fatkhur Rizal Ruba’i, Ahmad Salahuddin, Yanu Salahudin, Yanu Shalahuddin, Yanu Sri Arttini Dwi Prasetyawati Tiyas, Anis Wahyumulyaning Tomi Sugiarto Tri Handayani Utomo, Yudo Bismo Wahyu S., Mas Ilham Wibowo, Deni Wahyu Widhining Kusumastutie, Diah Arie Yahya, Miftahul Yahya, Mochtar Yanu Shalahuddin Yudha Dicky Pradana Yudo Bismo Utomo Yudo Bismo Utomo Yudo Bismo Utomo Yudo Bismo Utomo Yudo Bismo Utomo Yudo Bismo Utomo Yuliana, Dian Efytra Yumono, Fajar