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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Science and Technology Indonesia Jurnal Matematika UNAND
Des Alwine Zayanti
Jurusan Matematika FMIPA, Universitas Sriwijaya, Sumatera Selatan, Indonesia
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Library & Information Science Materials Science & Nanotechnology Mathematics Physics Other

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Segmentasi Paru-Paru Pada Citra Thorax Dada Dengan Menggunakan Metode Cnn U-Net Anisa Aulia Kusmareni; Anita Desiani; Sugandi Yahdin; Mutiara Saviera; Ajeng Islamia Putri; Des Alwine Zayanti
Jurnal Sistem Informasi Vol 14, No 2 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v14i2.16771

Abstract

Paru-paru merupakan salah satu organ terpenting dari tubuh manusia. Apabila terjadi keabnormalan pada kinerja paru-paru, akan dapat menimbulkan penyakit pernafasan yang dapat membuat tubuh tidak dapat menjalankan kinerjanya dengan normal. Untuk mendeteksi keabnormalan pada paru-paru, dapat dilakukan dengan melihat ukuran dari paru-paru tersebut. Penelitian ini menyajikan metode untuk segmentasi paru-paru pada foto thorax dada pasien dengan metode CNN U-Net. Pada langkah awal pada metode CNN U-Net dilakukan resize lalu segmentasi menggunakan keras optimizer Nadam. Didapatkan nilai rata-rata akurasi sebesar 0.9632, sensitifitas sebesar 0.9586, dan spesifisitas sebesar 0.9675, F1-Skor sebesar 0.9920, dan koefisien Jaccard sebesar 0.9842. 
Improved the Cans Waste Classification Rate of Naïve Bayes using Fuzzy Approach Yulia Resti; Firmansyah Burlian; Irsyadi Yani; Des Alwine Zayanti; Indah Meiliana Sari
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (926.547 KB) | DOI: 10.26554/sti.2020.5.3.75-78

Abstract

Cans is one type of inorganic waste that can take up to hundreds of years to be decomposed on the ground so that recycling is the right solution for managing cans waste. In the recycling industry, can classification systems are needed for the sorting system automation. This paper discusses the cans classification system based on the digital images using the Naive Bayes method, where the input variables are the pixel values of red, green, and blue (RGB) color, and the image of the can is captured by placing it on a conveyor belt which runs at a certain speed. The average accuracy rate of the k-fold cross-validation which is less satisfactory from the classification system obtained using the original Naive Bayes model is corrected using the fuzzy approach. This approach succeeded in improving the average accuracy of the can classification system which was originally from 52.99% to 88.02% or an increase of 60.2%, where the standard deviation decreased from 15.72% to only 3%. Cans is one type of inorganic waste that can take up to hundreds of years to be decomposed on the ground so that recycling is the right solution for managing cans waste. In the recycling industry, can classification systems are needed for the sorting system automation. This paper discusses the cans classification system based on the digital images using the Naive Bayes method, where the input variables are the pixel values of red, green, and blue (RGB) color, and the image of the can is captured by placing it on a conveyor belt which runs at a certain speed. The average accuracy rate of the k-fold cross-validation which is less satisfactory from the classification system obtained using the original Naive Bayes model is corrected using the fuzzy approach. This approach succeeded in improving the average accuracy of the can classification system which was originally from 52.99% to 88.02% or an increase of 60.2%, where the standard deviation decreased from 15.72% to only 3%.
OPTIMASI SISTEM PERENCANAAN PERSEDIAAN BUAH MENGGUNAKAN MODEL PROBABILISTIC FUZZY INVENTORY MULTI-ITEM DENGAN FUZZY LEAD-TIME Novi Rustiana Dewi; EKA SUSANTI; DES ALWINE ZAYANTI; ELI WIDIYANTI; BONGOT R. PURBA; ABDUL AZIZ ARROHMAN
Jurnal Matematika UNAND Vol 12, No 1 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.1.86-94.2023

Abstract

Abstrak:  Perencanaan kebijakan persediaan sangat penting terutama untuk produk-produk yang mudah rusak. Buah-buahan adalah jenis produk yang tidak tahan lama jika tidak disimpan di dalam pendingin.Tingkat kerusakan buah akan semakin meningkat jika disimpan lebih lama tanpa menggunakan ruang khusus. Hal ini berakibat menurunnya pada permintaan buah sehingga diasumsikan tingkat permintaan mengikuti distribusi eksponensial negatif. Waktu pengiriman buah ke pedagang juga tidak diketahui dengan pasti, maka nilai parameter leadtime dinyatakan dengan bilangan fuzzy. Pada makalah ini dibahas pemasalahan optimasi persediaan buah untuk meminimumkan total biaya persediaan. Terdapat 2 jenis buah yang dipertimbangkan yaitu jeruk dan salak. Model persediaan probabilistic fuzzy multi item dapat digunakan untuk menyelesaikan masalah persediaan. Berdasarkan parameter yang ditentukan diperoleh waktu peninjauan awal buah jeruk adalah 1,75 hari dan buah salak adalah 2,83 hari. Total biaya persediaan dengan variasi nilai beta semakin kecil untuk nilai beta semakin mendekati satu.Kata kunci: Fuzzy, , Inventori multi item, Probabilistik
Co-Authors ABDUL AZIZ ARROHMAN Ajeng Islamia Putri Anisa Aulia Kusmareni Anita Desiani BONGOT R. PURBA Eka susanti ELI WIDIYANTI Firmansyah Burlian Indah Meiliana Sari Indrawati Indrawati Irsyadi Yani Mutiara Saviera Novi Rustiana Dewi Oki Dwipurwani SITI NATASYA MUNAWAROH Sugandi Yahdin Yulia Resti