Ahmad Luthfi Baihaqi, Tegar Palyus Fiqar, Boby Mugi Pratama
{"title":"Klasifikasi Kematangan Musa Paradisiaca L Berbasis Warna Kulit Menggunakan Metode Decision Tree","authors":"Ahmad Luthfi Baihaqi, Tegar Palyus Fiqar, Boby Mugi Pratama","doi":"10.35334/jbit.v3i2.3317","DOIUrl":null,"url":null,"abstract":"Bananas are one of the cultivated products that contribute significantly to domestic fruit production. With the increasing market demand for bananas, farmers have the opportunity to further optimize the quality of bananas they produce in their gardens. In terms of meeting the market share standards in the horticultural sector is a goal that needs to be achieved. The technique used is Hue Saturation Value (HSV) used to classify banana images. Then the maturity is determined using a decision tree. The image data of 150 fruits were divided into 2 categories, namely 100 training data and 50 test data, then the test data were divided as a comparison of 70:30, 80:20 and 90:10. Based on the results of the decision tree analysis, bananas are declared raw if the color mode is =31.5, bananas are declared halfrip. if the color mode is =31.5, bananas are considered ripe if the color mode is =21.5, bananas are said to be overripe if in the shade mode =20.5 and bananas are said to be rotten if in the shade mode =14.5. Based on all comparisons between training data and test data, the best accuracy achieved is 100 with a ratio of 80:20. The calculation in this study was achieved to clearly distinguish banana fruit in terms of its maturity threshold. Pisang merupakan salah satu produk budidaya yang memberikan kontribusi signifikan terhadap produksi buah dalam negeri. Dengan meningkatnya permintaan pasar terhadap pisang, para petani mempunyai peluang untuk lebih mengoptimalkan kualitas pisang yang mereka hasilkan di kebunnya. Dalam hal memenuhi standar pangsa pasar di sektor hortikultura adalah tujuan yang perlu dicapai. Teknik yang dipakai ialah Hue Saturation Value (HSV) dipergunakan mengklasifikasikan citra pisang. Kemudian kematangan ditentukan dengan menggunakan pohon keputusan. Data gambar sebanyak 150 buah tersebut dibagi menjadi 2 kategori yaitu 100 data latih dan 50 data uji, kemudian data uji tersebut dibagi sebagai perbandingan 70: 30, 80:20 dan 90:10. Berdasarkan hasil analisis pohon keputusan, pisang dinyatakan mentah jika modus warnanya =31,5, pisang dinyatakan setengah matang jika modus warnanya =31,5, pisang dianggap matang jika modus warnanya = 21.5, pisang dikatakan terlalu matang jika dalam mode naungan =20.5 dan pisang dikatakan busuk jika dalam mode naungan = 14,5. Berdasarkan seluruh perbandingan antara data latih dan data uji, akurasi terbaik yang dicapai adalah 100 dengan perbandingan 80:20. Perhitungan pada penelitian ini tercapai membedakan secara jelas buah pisang ditinjau dari ambang kematangannya.","PeriodicalId":436910,"journal":{"name":"Jurnal Borneo Informatika dan Teknik Komputer","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Borneo Informatika dan Teknik Komputer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35334/jbit.v3i2.3317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Bananas are one of the cultivated products that contribute significantly to domestic fruit production. With the increasing market demand for bananas, farmers have the opportunity to further optimize the quality of bananas they produce in their gardens. In terms of meeting the market share standards in the horticultural sector is a goal that needs to be achieved. The technique used is Hue Saturation Value (HSV) used to classify banana images. Then the maturity is determined using a decision tree. The image data of 150 fruits were divided into 2 categories, namely 100 training data and 50 test data, then the test data were divided as a comparison of 70:30, 80:20 and 90:10. Based on the results of the decision tree analysis, bananas are declared raw if the color mode is =31.5, bananas are declared halfrip. if the color mode is =31.5, bananas are considered ripe if the color mode is =21.5, bananas are said to be overripe if in the shade mode =20.5 and bananas are said to be rotten if in the shade mode =14.5. Based on all comparisons between training data and test data, the best accuracy achieved is 100 with a ratio of 80:20. The calculation in this study was achieved to clearly distinguish banana fruit in terms of its maturity threshold. Pisang merupakan salah satu produk budidaya yang memberikan kontribusi signifikan terhadap produksi buah dalam negeri. Dengan meningkatnya permintaan pasar terhadap pisang, para petani mempunyai peluang untuk lebih mengoptimalkan kualitas pisang yang mereka hasilkan di kebunnya. Dalam hal memenuhi standar pangsa pasar di sektor hortikultura adalah tujuan yang perlu dicapai. Teknik yang dipakai ialah Hue Saturation Value (HSV) dipergunakan mengklasifikasikan citra pisang. Kemudian kematangan ditentukan dengan menggunakan pohon keputusan. Data gambar sebanyak 150 buah tersebut dibagi menjadi 2 kategori yaitu 100 data latih dan 50 data uji, kemudian data uji tersebut dibagi sebagai perbandingan 70: 30, 80:20 dan 90:10. Berdasarkan hasil analisis pohon keputusan, pisang dinyatakan mentah jika modus warnanya =31,5, pisang dinyatakan setengah matang jika modus warnanya =31,5, pisang dianggap matang jika modus warnanya = 21.5, pisang dikatakan terlalu matang jika dalam mode naungan =20.5 dan pisang dikatakan busuk jika dalam mode naungan = 14,5. Berdasarkan seluruh perbandingan antara data latih dan data uji, akurasi terbaik yang dicapai adalah 100 dengan perbandingan 80:20. Perhitungan pada penelitian ini tercapai membedakan secara jelas buah pisang ditinjau dari ambang kematangannya.