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Comparison of Classification for Grading Red Dragon Fruit (Hylocereus Costaricensis) Zilvanhisna Emka Fitri; Ari Baskara; Abdul Madjid; Arizal Mujibtamala Nanda Imron
JURNAL NASIONAL TEKNIK ELEKTRO Vol 11, No 1: March 2022
Publisher : Jurusan Teknik Elektro Universitas Andalas

Pitaya is another name for dragon fruit which is currently a popular fruit, especially in Indonesia. One of the problems related to determining the quality of dragon fruit is the postharvest sorting and grading process. In general, farmers determine the grading system by measuring the weight or just looking at the size of the fruit, of course, this raises differences in grading perceptions so that it is not by SNI. This research is a development of previous research, but we changed the type of dragon fruit from white dragon fruit (Hylocereus undatus) to red dragon fruit (Hylocereus costaricensis). We also adapted the image processing and classification methods in previous studies and then compared them with other classification methods. The number of images in the training data is 216, and the number of images in the testing data is 75. The comparison of the accuracy of the three classification methods is 84% for the KNN method, 85.33% for the Naive Bayes method, and 86.67% for the Backpropagation method. So that the backpropagation method is the best classification method in classifying the quality grading of red dragon fruit. The network architecture used is 4, 8, 3 with a learning rate of 0.3 so that the training accuracy is 98.61% and the testing accuracy is 86.67%.

Pengaruh Penggunaan Beberapa Stimulansia Terhadap Produksi Berberapa Klon Karet (Hevea brasilliensis Muell Arg.) Eka Renitasari; Titien Fatimah; Abdul Madjid
Agriprima : Journal of Applied Agricultural Sciences Vol 3 No 1 (2019): MARET
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/agriprima.v3i1.132

Salah satu penunjang produksi tanaman karet dalam menghasilkan getah lateks adalah pengaplikasian stimulansia. Penelitian ini bertujuan untuk mengetahui interaksi antara klon karet dengan stimulansia terhadap produksi tanaman karet. Penelitian ini dilakukan di PTP N XII Kebun renteng Ajung Kabupaten Jember pada 26 desember 2017 – 15 Januari 2018. Penelitian ini mengguunakan Rancangan Acak Kelompok(RAK) dengan dua faktor. Faktor pertama adalah faktor klon menggunakan 4 taraf yaitu, taraf K1 (PB 260), K2 (GT 1), K3 (RRIC 100), K4 (BPM 24). Faktor kedua adalah stimulansia dengan 3 taraf yaitu, S1 (Amcotrel 10 PA), S2 (karet full), S3 (non stimulansia). Hasil penelitian menunjukkan bahwa interaksi yang baik ditunjukkan oleh kombinasi perlakuan antara klon RRIC 100 dengan stimulansia karet full dan kombinasi perlakuan GT 1 dengan stimulansia amcotrel 10 PA. Namun, hasil produksi getah lateks menunjukkan bahwa perlakuan kontrol lebih tinggi dari semua perlakuan stimulansia.

Pemanfaatan Power Sprayer Guna Mengendalikan Hama Kopi di Desa Klungkung Jember Abdul Madjid; Abdurrahman Salim; Anni Nur Aisyah; Zilvanhisna Emka Fitri
Journal of Community Development Vol. 3 No. 1 (2022): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v3i1.70

Coffee is one of the plantation commodities that are in great demand in Indonesia. Coffee production in East Java is the largest in Indonesia, one of the coffee-producing areas in East Java, namely Jember Regency. Some of the factors causing it, one of them from cultivation techniques and inadequate care and maintenance. In particular, many coffee pests are not handled properly. In addition, there is a factor in the level of technology absorption and the application of farm management as well as a less efficient and effective marketing system which has an impact on the income level of farmers. Therefore, it is necessary to innovate cultivation techniques and maintain coffee plants in order to maintain optimal coffee growth and produce better fruit, so as to increase farmers' income. The microcontroller-based sprayer battery is an innovative sprayer to increase coffee production in Klungkung village. The stages of this service activity start from the stage of preparation and coordination with partners, digging information (literature studies) in compiling counseling and training materials from controlling plant pest organisms, especially coffee from spraying techniques according to SOPs, coffee production management, to the coffee marketing system. The results of this dedication is the farmer of Klungkung village get benefits in good coffee cultivation techniques and in spraying pests using Power Sprayer technology.

Red Dragon Fruit (Hylocereus costaricensis) Ripeness Color Classification by Naïve Bayes Algorithm Zilvanhisna Emka Fitri; Mega Silvia; Abdul Madjid; Arizal Mujibtamala Nanda Imron; Lalitya Nindita Sahenda
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 5 No 1 (2022): June
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v5i1.3690

Dragon fruit is a unique fruit that is popular in Indonesia. besides having a sweet taste, this fruit also contains fiber, vitamins and minerals that are good for health. Dinas Pertanian Kabupaten Banyuwangi noted that the total dragon fruit production was 906,511.61 tons and the total productivity was 261.14 Kw/Ha in 2018. This shows that Kabupaten Banyuwangi is one of the largest producers of red dragon fruit in East Java Province. One of the problems in determining the quality of dragon fruit is choosing the harvest time, considering that dragon fruit is a non-climatic fruit. Non-climateric fruit is when we harvest fruit in its raw state, the fruit will never become ripe, so determining the harvest time for dragon fruit is very important. The determination made by paying discoloration and sizes of dragon fruit that is considered less effective. To overcome this, a system was created that was able to determine the level of dragon fruit maturity automatically by utilizing digital image processing techniques and intelligent systems. The parameters used are color features and GLCM texture features using angles 0°, 45°, 90° and 135° These features are parameters in the classification process using the Naïve Bayes method. Naïve bayes is able to classify the level of maturity of red dragon fruit (Hylocereus costaricensis) with an accuracy rate of 87.37%.

PENGARUH JENIS MEDIA PUPUK KANDANG DAN PEMBERIAN PUPUK ORGANIK CAIR DAUN LAMTORO TERHADAP PERTUMBUHAN BIBIT VANILI (Vanilla planifolia) Abdurrahman Salim; Ujang Setyoko; Abdul Madjid; Hasyim Asyari
Jurnal Penelitian Pertanian Terapan Vol 23 No 1 (2023)
Publisher : Politeknik Negeri Lampung.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/jppt.v23i1.2306

Provision of nutrients is one of the important things in plant cultivation. One of the nutrients that can be obtained from organic fertilizers. Manure is one type of organic fertilizer that can increase soil nutrients. The manure used in the media is cow and goat manure. In addition to manure, the application of Liquid Organic Fertilizer (POC) of lamtoro leaves can also provide nitrogen elements in the soil. The element nitrogen has good benefits for nurseries because it can accelerate vegetative growth in plants. The purpose of this study was to determine the effect of adding manure media by giving lamtoro leaf POC to vanilla seeds. This research was carried out at the Jember State Polytechnic in July – November 2020. This study used a factorial randomized block design with two factors, namely the first factor was 3 types of planting media consisting of control, addition of cow kendang fertilizer and addition of cow kendang fertilizer. Then the second factor was giving lamtoro leaf liquid organic fertilizer with three levels consisting of control, 25%, and 50%.. The results showed that goat manure showed the best results in increasing shoot length, shoot diameter, leaf width and wet weight of vanilla plants. Application of liquid organic fertilizer with a concentration of 50% gave the best results for increasing shoot length, shoot diameter and wet weight of vanilla plants. Meanwhile, the interaction does not show a significant effect. Keywords:Lamtoro Leaves; Manure; POC; Vanilla plant

Comparison of Neural Network Methods for Classification of Banana Varieties (Musa paradiasaca) Zilvanhisna Emka Fitri; Wildan Bakti Nugroho; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Every region in Indonesia has a very large diversity of banana species, but no system records information about the characteristics of banana varieties. The purpose of this research is to make an encyclopedia of banana types that can be used for learning by classifying banana varieties using banana images. This banana variety classification system uses image processing techniques and artificial neural network methods as classification methods.The varieties of bananas used are pisang merah, pisang pisang mas kirana, pisang klutuk, pisang raja and pisang cavendis. The parameters used are color features (Red, Green, and Blue) and shape features (area, perimeter, diameter, and length of fruit). The intelligent system used is the Backpropagation method and the Radial Basis Function Neural Network. The results showed that both methods were able to classify banana varieties with an accuracy rate of 98% for Backpropagation and 100% for the Radial Basis Function Neural Network.

Penerapan Neural Network untuk Klasifkasi Kerusakan Mutu Tomat Zilvanhisna Emka Fitri; Rizkiyah Rizkiyah; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

The decrease in quality and productivity of tomatoes is caused by high rainfall, bad weather and cultivation so that the tomatoes become rotten, cracked, and spotting occurs. The government is trying to provide training to improve the quality of tomatoes for farmers. However, the training was not effective so the researchers helped create a system that was able to educate farmers in the classification of damage to tomato quality. This system serves to facilitate farmers in recognizing tomato damage thereby reducing the risk of crop failure. In this study, the classification method used is backpropagation with 7 input parameters. The input consists of morphological and texture features. The output of this classification system consists of 3 classes are blossom end rot, fruit cracking and fruit spots caused by bacterial specks. The best accuracy level of the system in classifying tomato quality damage in the training process is 89.04% and testing is 81.11%.

Comparison of Neural Network Methods for Classification of Banana Varieties (Musa paradiasaca) Zilvanhisna Emka Fitri; Wildan Bakti Nugroho; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i2.20806

Every region in Indonesia has a very large diversity of banana species, but no system records information about the characteristics of banana varieties. The purpose of this research is to make an encyclopedia of banana types that can be used for learning by classifying banana varieties using banana images. This banana variety classification system uses image processing techniques and artificial neural network methods as classification methods.The varieties of bananas used are pisang merah, pisang pisang mas kirana, pisang klutuk, pisang raja and pisang cavendis. The parameters used are color features (Red, Green, and Blue) and shape features (area, perimeter, diameter, and length of fruit). The intelligent system used is the Backpropagation method and the Radial Basis Function Neural Network. The results showed that both methods were able to classify banana varieties with an accuracy rate of 98% for Backpropagation and 100% for the Radial Basis Function Neural Network.

Penerapan Neural Network untuk Klasifkasi Kerusakan Mutu Tomat Zilvanhisna Emka Fitri; Rizkiyah Rizkiyah; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i1.15535

The decrease in quality and productivity of tomatoes is caused by high rainfall, bad weather and cultivation so that the tomatoes become rotten, cracked, and spotting occurs. The government is trying to provide training to improve the quality of tomatoes for farmers. However, the training was not effective so the researchers helped create a system that was able to educate farmers in the classification of damage to tomato quality. This system serves to facilitate farmers in recognizing tomato damage thereby reducing the risk of crop failure. In this study, the classification method used is backpropagation with 7 input parameters. The input consists of morphological and texture features. The output of this classification system consists of 3 classes are blossom end rot, fruit cracking and fruit spots caused by bacterial specks. The best accuracy level of the system in classifying tomato quality damage in the training process is 89.04% and testing is 81.11%.

Penerapan Fitur Warna dan Tekstur untuk Identifikasi Kerusakan Mutu Biji Kopi Arabika (Coffea Arabica) di Kabupaten Bondowoso Zilvanhisna Emka Fitri; Brilyan Andi Syahbana; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Ilmiah Teknologi Informasi Asia Vol 15 No 2 (2021): Volume 15 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v15i2.593

Plantation crops are also a source of foreign exchange Indonesia is coffee. There are only two types of coffee that have economic value for cultivation, namely Arabica coffee and Robusta coffee. Bondowoso is a district in East Java that develops Arabica coffee. The problem is that farmers still use direct observation (manual) on each coffee bean to determine the quality of coffee beans so that this research is expected to be able to assist farmers in sorting the damage to the quality of coffee beans based on color and texture. The features used are color features and GLCM texture features at 0̊ and 45̊ angles. The total number of data is 198. The Backpropagation method is able to classify quality damage to Arabica coffee beans with a training accuracy rate of 100% and a testing accuracy rate of 97.5% at a learning rate variation of 0.5.

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