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All Journal Jurnal Elektronika Listrik dan Teknologi Informasi Terapan JE-Unisla Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Masruroh
Universitas Islam Lamongan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Transportation

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Analisa Algoritma C4.5 untuk Prediksi Penjualan Obat Pertanian di Toko Dewi Sri Kiki Rosita Dewi; Kemal Farouq Mauladi; Masruroh
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 4 No. 3 (2020): PROSIDING SEMNAS INOTEK Ke-IV Tahun 2020
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v4i3.72

Abstract

Pestisida merupakan zat atau bahan kimia yang digunakan unuk membunuh hama pada tanaman yang dapat menghambat pertumbuhan tanaman sehingga berdampak pada hasil panen yang kurang baik. Toko Dewi Sri merupakan salah satu toko obat pertanian yang ada di Desa Beru Kecamatan Sarirejo yang menyediakan berbagai macam obat-obat pertanian yang dibutuhkan oleh para petani di Desa Beru Kecamaan Sarirejo. Adapun tujuan dari penelitian ini adalah untuk memprediksi penjualan obat pertanian. Dimana metode ini bekerja dengan membentuk suatu pohon keputusan. Berdasarkan hasil perhitungan yang telah dilakukan didapatkan hasil Akurasi sebesar 75%.
Klasifikasi Kematangan Buah Mangga Berdasarkan Citra HSV dengan KNN Husnul Khotimah; Nur Nafi’iyah; Masruroh
Jurnal Elektronika Listrik dan Teknologi Informasi Terapan Vol. 1 No. 2 (2019): ELTI Desember
Publisher : LPPM Politeknik Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37338/elti.v1i2.175

Abstract

identification or classification using image processing and computer vision requires pattern recognition from the training dataset. The process of image processing and pattern recognition becomes a highly developed research study. Starting from the process of recognizing an object, or classification of objects and about detecting the level of fruit maturity. This research will classify the level of maturity of mangoes with HSV images. Where the RGB input image is converted to HSV. Then the average values of HSV intensity, skewness, and kurtosis are taken. The process of classification comes into 4 classes: raw, fairly ripe, ripe and very ripe. With the KNN classification method, and the dataset used 129 training data, and 40 testing data. The highest accuracy value at k = 2 is 80%. The tool used to develop the system is matlab.
STUDI METODE CRAMER DAN METODE INVERS MATRIK PADA PERSOALAN RANGKAIAN LISTRIK Ulul Ilmi; Rifky Aisyatul Faroh; Ayu Ismi Hanifah; Nur Indah Mukhoyyaroh; Masruroh
Jurnal JE-UNISLA : Electronic Control, Telecomunication, Computer Information and Power System Vol 8 No 2 (2023): JE-UNISLA
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/elektro.v8i2.1079

Abstract

In the world of engineering, one example of using a matrix is to find a solution to a system of linear equations (SLE). In the scientific field that studies electrical circuits, it is not uncommon to use matrices to calculate the quantities or values in an electric circuit. To make it easier to find these values, an operation process based on the Cramer and inverse methods based on Matlab is used so that finally the values contained in the electrical circuit are obtained. These values are electric current and electric voltage. In this study, it can be concluded that the use of the Matlab-based matrix inverse method is better in terms of the accuracy of the research results, when compared to the manual use of the Cramer method, which has an accuracy difference of 0.0006%. For the calculation of the current variable i3. and 0.81% for the calculation of the electric voltage variable at node AB.
Co-Authors Hanifah, Ayu Ismi Husnul Khotimah Kemal Farouq Mauladi Kiki Rosita Dewi Nur Indah Mukhoyyaroh Nur Nafi’iyah Rifky Aisyatul Faroh Ulul Ilmi