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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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Klasifikasi Jenis Kayu Menggunakan Esktrasi Fitur Gray Level Co-Occurence Matrix dan Multilayer Perceptron Wibowo, Deni Wahyu; Erwanto, Danang; Kusumastutie, Diah Arie Widhining
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 1: March 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.416 KB) | DOI: 10.25077/jnte.v10n1.788.2021

Abstract

The type of wood is generally characterized by color, pattern and fiber because wood physically has almost the same characteristics. To determine the type of wood, experience and knowledge about wood are needed. This study applies digital image processing technology using the GLCM (gray level co-occurrence matrix) feature extraction method to produce feature extraction values on wood texture. The parameter values generated in the GLCM feature extraction are correlation, contrast, energy and homogeneity. The results from feature extraction are then used as a data classification of types of wood using MLP (multilayer perceptron) method. There are 4 wood types going to be involved in this research as datasets i.e., teak, sengon, mahogany, and mindi. The results of this study, obtained the best level of accuracy in validation data of 88.75%. The output of this research is softmax data using MLP method with an error value in the training neared target of data by 0.029421 with the epoch 1.000 iterations. Keywords : Digital Image Processing, Feature Extraction, GLCM and MLPAbstrakJenis kayu umumnya dicirikan dari warna, corak dan serat karena kayu secara fisik memiliki ciri yang hampir sama. Untuk menentukan jenis kayu, diperlukan pengalaman dan pengetahuan tentang kayu. Penelitian ini menerapkan teknologi pengolahan citra digital menggunakan metode ekstraksi fitur GLCM (gray level co-occourrence matrix) untuk menghasilkan nilai ekstraksi fitur pada tesktur kayu. Parameter nilai dihasilkan pada ekstraksi fitur GLCM adalah correlation, contrast, energy dan homogeneity. Hasil dari parameter GLCM kemudian digunakan sebagai data untuk klasifikasi jenis kayu menggunakan metode MLP (multilayer perceptron). Dalam penelitian ini digunakan 4 jenis kayu sebagai pengujian dan datasheet, yaitu kayu jati, sengon, mahoni dan mindi. Hasil dari penelitian ini, diperoleh tingkat akurasi terbaik pada data validasi sebesar 88,75 %. Keluaran dari penelitian ini berupa data softmax dengan menggunakan metode MLP dengan nilai error pada data training yang mendekati target sebesar 0.029421 dengan epoch 1.000 iterasi. Kata Kunci : Pengolahan Citra Digital, Ekstraksi Fitur, GLCM dan MLP
Klasifikasi Aroma Teh Dengan Menggunakan Sensor Gas Berbasis Arduino Uno Arisudin; Yahya, Mochtar; Erwanto, Danang
JASEE Journal of Application and Science on Electrical Engineering Vol. 2 No. 02 (2021): JASEE
Publisher : Teknik Elektro Fakultas Teknik Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jasee.v2i02.198

Abstract

Teh adalah salah satu produk minuman yang dibuat dari daun teh muda dan sudah melalui proses pengolahan seperti pelayuan, oksidasi enzimatis, penggilingan, serta pengeringan. Kandungan senyawa kimia yang ada didalam teh adalah katekin, vitamin E, vitamin C, tanin, flavonoid, theofilin, polifenol, dan sejumlah mineral seperti Mg, Ge, Mo, Se dan Zn. Sensor gas (MQ-3, MQ-4, MQ-5 dan MQ-135) serta DHT-22 yang disusun membentuk larik sensor gas diaplikasikan untuk membaca kadar gas pada uap air teh. Dalam penelitian ini sampel teh yang digunakan meliputi teh oolong, teh hitam, teh hijau, dan teh putih. Dari penelitian ini aroma teh dapat dibaca oleh sistem yang telah dibuat dan diklasifikasikan jenis tehnya menggunakan metode Jaringan Syaraf Tiruan dan diperoleh hasil berupa akurasi dengan nilai 0,71, presisi dengan nilai 0,71, Recal dengan nilai 0,72 dan f-measure dengan nilai 0,71.
Ekstraksi Fitur Tekstur dan Warna pada Kulit Katak Menggunakan GLCM dan Momen Warna Kurniasari, Atika; Erwanto, Danang; Rahayu, Putri Nur
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 6 No 1 (2022)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v6i1.287

Abstract

Anura is an order in the Amphibian class consisting of frogs and toads. Anura is very important in the ecosystem, especially its role as part of the food chain. Anura's main role is to maintain the balance of the ecosystem and as a bioindicator agent for changing environmental conditions such as water pollution, habitat destruction, disease and parasites, and climate change. This research applies digital image processing technology which is expected to assist in detecting types of frogs based on color and texture. This research uses 5 types of frogs, namely kongkang gading, kongkang poison, striped trees, small trees and flying trees with 20 images of each type of frog. This research uses the color feature extraction methods such Color Moment and texture extraction GLCM (Gray Level Co-occurance Matrix), then classified using K-Star. The results of the K-Star performance evaluation to classify the 5 types of frogs obtained the Accuracy (Acc) value of 0.93, Precision (Prec) of 0.94, Recall (Rec) of 0.93 and F-measure of 0.93. So that the classification results of frog species on texture and color feature extraction using the GLCM method and the Color Moment with the K-Star classification method have high performance and can work well.
Klasifikasi Kesegaran Daging Sapi Menggunakan Metode Ekstraksi Tekstur GLCM dan KNN Ade Prabowo; Danang Erwanto; Putri Nur Rahayu
Electro Luceat Vol 7 No 1 (2021): Electro Luceat (JEC) - July 2021
Publisher : LPPM Poltek ST Paul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jelekn.v7i1.344

Abstract

Meat is the soft part of the animal that is covered by skin and is attached to the bones which become food ingredients. This research was conducted to classify the types of fresh, inn and rotten beef using 120 samples of beef taken directly by the researcher. Before classifying the type of beef, the texture of the beef image was extracted using the GLCM method to produce texture parameters in the form of contrast, correlation, homogeneity and energy. Texture parameters are classified using the KNN method. The results in this study indicate that the extraction of beef image texture using the GLCM method can produce various values on the 4 parameters of the GLCM texture. In addition, the results of the classification of beef freshness using the KNN method to determine 3 types of meat quality, namely fresh, cooked and rotten beef, obtained an evaluation of the classification performance using the Confusion Matrix table with an Accuracy value of 0.82, Precision of 0.83, Recall of 0.82 and F-Measure of 0.82. So that the parameters of the beef image texture using the GLCM method can be classified properly using the KNN method.
KLASIFIKASI CACAT PADA KALENG KEMASAN MENGGUNAKAN METODE LACUNARITY DAN NAÏVE BAYES Danang Erwanto; Putri Nur Rahayu; Yudo Bismo Utomo
Electro Luceat Vol 7 No 2 (2021): Electro Luceat (JEC) - November 2021
Publisher : LPPM Poltek ST Paul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jelekn.v7i2.398

Abstract

Cans are steel sheets coated with tin (Sn) and used to package food and beverage products. The use of cans as packaging for food products because cans are difficult for microorganisms to pass and cannot be penetrated by ultraviolet light so that the quality of packaged food or beverage products is maintained. The cans selected as packaging must be in a non-defective condition so that an inspection process is needed on the cans. This research implements the Lacunarity and Naïve Bayes Classification methods to classify the types of cans which are grouped into 2 classes, namely Good and Reject. From the implementation of the Lacunarity method, it is able to produce 28 values of texture feature extraction that vary in each image. The results of the evaluation of the classification of the Naïve Bayes Classification method to classify the condition of packaged cans obtained an accuracy value of 0.87, a precision of 0.88, a recall of 0.86 and an f-measure of 0.87, so that the Naïve Bayes Classification method can classify the types of cans packaging in Good and Reject condition based on the value of texture extraction using the Lacunarity method.
MONITORING NILAI SUHU DAN KELEMBABAN UDARA RUANG PERAWATAN PASIEN COVID-19 BERBASIS IoT Fajar Yumono; Danang Erwanto
Electro Luceat Vol 7 No 2 (2021): Electro Luceat (JEC) - November 2021
Publisher : LPPM Poltek ST Paul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32531/jelekn.v7i2.399

Abstract

The Covid-19 outbreak is an unresolved problem because it is a new disease, so that a definite control formula is still being pursued, including by providing vaccines. There are no specific medical prescriptions for Covid-19 patients, and many experiments are carried out to achieve healing. This study offers observations of temperature and humidity in the treatment room for Covid-19 patients because temperature and humidity greatly affect the patient's recovery. The application of the Internet of Things with the nodeMCU ESP8266 module can make observations with location distances for security. These results will empirically obtain an average value for temperature and humidity in the treatment room for Covid-19 patients which can be used as a reference in other treatment rooms, especially for those who are self-isolating. From the test results of the instrument system, good results were obtained, and the percentage change in sensor readings in the temperature test sample was 3.8% and air humidity was 3.2% to the average value, and the instrument system was tested for 15 consecutive days. and the sample was taken 3 days to obtain a stable value.
Klasifikasi Jenis Kayu Menggunakan Esktrasi Fitur Gray Level Co-Occurence Matrix dan Multilayer Perceptron Deni Wahyu Wibowo; Danang Erwanto; Diah Arie Widhining Kusumastutie
JURNAL NASIONAL TEKNIK ELEKTRO Vol 10, No 1: March 2021
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.416 KB) | DOI: 10.25077/jnte.v10n1.788.2021

Abstract

The type of wood is generally characterized by color, pattern and fiber because wood physically has almost the same characteristics. To determine the type of wood, experience and knowledge about wood are needed. This study applies digital image processing technology using the GLCM (gray level co-occurrence matrix) feature extraction method to produce feature extraction values on wood texture. The parameter values generated in the GLCM feature extraction are correlation, contrast, energy and homogeneity. The results from feature extraction are then used as a data classification of types of wood using MLP (multilayer perceptron) method. There are 4 wood types going to be involved in this research as datasets i.e., teak, sengon, mahogany, and mindi. The results of this study, obtained the best level of accuracy in validation data of 88.75%. The output of this research is softmax data using MLP method with an error value in the training neared target of data by 0.029421 with the epoch 1.000 iterations. Keywords : Digital Image Processing, Feature Extraction, GLCM and MLPAbstrakJenis kayu umumnya dicirikan dari warna, corak dan serat karena kayu secara fisik memiliki ciri yang hampir sama. Untuk menentukan jenis kayu, diperlukan pengalaman dan pengetahuan tentang kayu. Penelitian ini menerapkan teknologi pengolahan citra digital menggunakan metode ekstraksi fitur GLCM (gray level co-occourrence matrix) untuk menghasilkan nilai ekstraksi fitur pada tesktur kayu. Parameter nilai dihasilkan pada ekstraksi fitur GLCM adalah correlation, contrast, energy dan homogeneity. Hasil dari parameter GLCM kemudian digunakan sebagai data untuk klasifikasi jenis kayu menggunakan metode MLP (multilayer perceptron). Dalam penelitian ini digunakan 4 jenis kayu sebagai pengujian dan datasheet, yaitu kayu jati, sengon, mahoni dan mindi. Hasil dari penelitian ini, diperoleh tingkat akurasi terbaik pada data validasi sebesar 88,75 %. Keluaran dari penelitian ini berupa data softmax dengan menggunakan metode MLP dengan nilai error pada data training yang mendekati target sebesar 0.029421 dengan epoch 1.000 iterasi. Kata Kunci : Pengolahan Citra Digital, Ekstraksi Fitur, GLCM dan MLP
Utilization of Digital Image Processing in Process of Quality Control of The Primary Packaging of Drug Using Color Normalization Method Danang Erwanto; Sri Arttini Dwi Prasetyowati; Eka Nuryanto Budi Susila
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.042 KB) | DOI: 10.11591/eecsi.v3.1118

Abstract

In the process of quality control, accuracy is required so that the improper drug packaging is not included into the next production process. The automatic inspection system using digital image processing can be applied to replace the manual inspection system done by humans. The image captured from the vision sensor is RGB image which is then converted into grayscale. The process of converting RGB image into grayscale image is performed using the color normalization method to spread the data of RGB colors at each pixel. From the software of image processing using the color normalization method that have been created, it shows grayscale images on the drug object which have degrees of gray higher than the grayscale image section of the background when the degree of the R, G or B color of drug is higher than the degree of the R, G, B color on the background of packaging. The determination of threshold value indicates that the binary image of the drug is white and a binary image of the background of drug packaging is black.
Studi Komparasi Kwh Meter Pascabayar Dengan Kwh Meter Prabayar Tentang Akurasi Pengukuran Terhadap Tarif Listrik Yang Bervariasi Dendi Gunawan; Danang Erwanto; Yanu Shalahuddin
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 7, No 1 (2018): Edisi Juni 2018
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.869 KB) | DOI: 10.36055/setrum.v7i1.3408

Abstract

Pada saat ini ada dua jenis kwh meter yang dipasang PT PLN untuk mengukur konsumsi listrik pelanggannya, yaitu kWh meter pascabayar dan meter prabayar.. Ada asumsi pelanggan bahwa menggunakan meter prabayar akan membuat tagihan listrik meningkat. Karena ada dugaan pelanggan bahwa pada meter prabayar mempunyai pengukuran yang salah. Studi komparasi terhadap kWh meter pascabayar dan kWh meter prabayar pada penilitian ini dimaksudkan untuk mengetahui akurasi pengukuran dari kWh meter pascabayar dan kWh meter prabayar. Sampel penelitian didasarkan pada golongan tarif listrik yang bervarasi yaitu listrik rumah tangga, industri, UMKM dan perkantoran. Dari hasil komparasi tersebut diperoleh hasil analisa yaitu, untuk kWh meter pascabayar analog dan digital mempunyai rata – rata kesalahan akurasi sebesar 3,252 % dan 4,176 %, sedangkan kWh prabayar mempunyai rata rata kesalahan akurasi sebesar 1,186 %. Dari data tersebut dapat disimpulkan bahwa kWh meter prabayar mempunyai tingkat ketelitian yang lebih tinggi daripada kWh meter pascabayar. Kata Kunci : KWh Meter Pascabayar, KWh meter Prabayar, Akurasi
Rancang Bangun Alat Prediksi Kondisi Tubuh Ideal Menggunakan Metode Fuzzy Logic Sugeno Muhammad Azizul Fikri; Danang Erwanto; Dian Efytra Yuliana
Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Vol 7, No 1 (2018): Edisi Juni 2018
Publisher : Fakultas Teknik Elektro - Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1173.88 KB) | DOI: 10.36055/setrum.v7i1.3409

Abstract

Parameter yang digunakan untuk menentukan kondisi tubuh sesorang adalah berat badan serta tinggi badan. Secara manual untuk menentukan Indeks Massa tubuh (IMT) membutuhkan dua langkah, yaitu mengukur berat badan serta tinggi badan kemudian dihitung IMT-nya, sehingga kurang efektif. Dengan Menggunakan metode logika fuzzy sugeno, dapat dirancang alat untuk memprediksi kondisi tubuh manusia berdasarkan Indeks Massa Tubuh dengan cara mengukur berat badan serta tinggi badan hanya dengan satu langkah memggunakan alat tersebut. Dari hasil penelitian yang telah dilakukan, load cell mampu mengukur berat dengan baik, dengan error rata-rata sebesar 3,95 %, dan untuk sensor ultrasonik mampu mendeteksi jarak dengan sangat baik, dengan error rata-rata sebesar 1,5%. Sedangkan untuk pengujian alat secara keseluruhan terdapat error rata-rata hasil IMT sebesar 4,61%. Akan tetapi meskipun terdapat perbedaan hasil IMT dari pengukuran dengan alat manual dan pengukuran dengan alat digital, hasil keduanya masih dalam kategori kondisi tubuh yang sama.
Co-Authors Achmad Arif Alfin Ade Prabowo Agus Maulana Khafi Ahmad Ari Setyawan Kusuma Alfian Danu Ismail Alhadidi, M. Baihaqi Aprilia, Yoga Pebri Arisudin Arisudin Arisudin Asti Riani Putri Atika Kurniasari Ayssa Nurmastika 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 Kusumastutie, Diah Arie Widhining Maulana Alfaruq, Bagoes Maulana F, Delta Mochtar Yahya Mochtar Yahya Mohammad Atif Faiz Muthrofin Mohammad Heri Saputra Mohammad Rangga Nur Faizin Muhammad Azizul Fikri Muhammad Erfan Muhammad Iqsan Fauzi 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 Shalahuddin, Yanu Sri Arttini Dwi Prasetyawati Tiyas, Anis Wahyumulyaning Tomi Sugiarto Tri Handayani Wahyu S., Mas Ilham Wibowo, Deni Wahyu 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