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All Journal Prosiding SNATIKA Vol 01 (2011) BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks Jurnal Ilmu Komputer dan Desain Komunikasi Visual
Nafi'iyah, Nur
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Arts Computer Science & IT Education Languange, Linguistic, Communication & Media

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Clustering Keahlian Mahasiswa Dengan SOM (Studi Khusus: Teknik Informatika Unisla) Nafi'iyah, Nur
Prosiding SNATIKA Vol 3 (2015): Prosiding Snatika (Seminar Nasional Teknologi, Informasi, Komunikasi dan Aplikasinya)
Publisher : LPPM STIKI Malang

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Abstract

Program studi Teknik Informatika merupakan salah satu program studi terfavorite di Universitas Islam Lamongan. Jurusan Teknik Informatika sendiri rencananya akan dibagi menjadi 4 bidang keahlian yaitu Keahlian Informatic atau logika, Software Develop and Enginer, Management Database dan Networking atau Infrastucture. Penelitian akan menerapkan metode Clustering dengan algoritam Clustering Neural Network dalam kasus pengelompokkan keahlian mahasiswa berdasarkan transkip nilai mata kuliah sebagai rekomendasi untuk mengambil bidang keahlian yang sesuai dengan kemampuan mahasiswa. Tujuan dari penelitian ini, yaitu untuk memberikan rekomendasi pemilihan bidang keahlian kepada mahasiswa teknik informatika UNISLA. Peneliti melakukan uji coba training clustering sebanyak 10 kali, dan menunjukkan hasil akurasi rata-rata 82%.
K-NN Klasifikasi Kematangan Buah Mangga Manalagi Menggunakan L*A*B dan Fitur Statistik Nafi'iyah, Nur; Sri Pamungkas, Arif Patriot; Nawafilah, Nur Qomariyah
Jurnal Ilmu Komputer dan Desain Komunikasi Visual Vol 4, No 1 (2019): Jurnal Ilmu Komputer dan Desain Komunikasi Visual
Publisher : Universitas Nahdlatul Ulama Sidoarjo

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Abstract

Buah-buahan merupakan bahan pangan sumber vitamin. Buah cepat sekali rusak oleh pengaruh mekanik, kimia dan mikrobiologi sehingga mudah menjadi busuk. Klasifikasi dilakukan pada sekelompok buah mangga yang berbeda-beda jenis kematangannya. Ciri pembeda yang digunakan adalah fitur warna L*A*B. Tujuan penelitian ini yaitu memberikan hasil output klasifikasi kematangan buah mangga manalagi berdasarkan fitur warna menggunakan aplikasi Matlab. Pada penelitian ini akan diusulkan metode GLCM untuk ekstraksi fitur pada buah mangga. Dengan menggunakan K-Nearest Neighboor (KNN) untuk menentukan tingkat kematangan buah mangga. Dataset yang digunakan berjumlah 130 data, terdiri dari 65 data untuk mentah, 15 untuk setengah matang dan 50 untuk matang. Hasil Klasifikasi KNN dengan menggunakan metode GLCM dan L*A*B untuk ekstraksi fitur mendapatkan nilai akurasi sebesar 62.5% pada data uji. Kata kunci: Matlab, Mangga Manalagi, KNN, Lab, GLCM. Fruits are a food source of vitamins. The fruit is quickly damaged by mechanical, chemical and microbiological influences, making it easy to rot. Classification is carried out on a group of mangoes which differ in type of maturity. The distinguishing feature was used is the L*A*B color feature. The purpose of this researchgave the output of the maturity classification ofManalagi mangoes based on color features using the Matlab application. In this research the GLCM method will be proposed for feature extraction in mangoes. By using K-Nearest Neighboor (KNN) to determine the maturity level of the Mango fruit. The dataset used is 130 data, consisting of 65 data for raw, 15 for half-cooked and 50 for mature. The KNN Classification results using the GLCM and L*A*B methods for Feature Extraction get an accuracy value of 62.5% in the test data.Keywords : Matlab, Manalagi Mango, KNN, Lab, GLCM.
Analisis Penghasilan, Pekerjaan, dan Usaha Masyarakat di Masa Pandemi Melalui Penerapan Data Sains Nafi'iyah, Nur; Maghfiroh, Syafaatul
Berdikari: Jurnal Inovasi dan Penerapan Ipteks Vol 9, No 1 (2021): February
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/berdikari.v9i1.9650

Abstract

Activities in some sectors experience a decrease in revenue due to the Covid-19 outbreak, for example, the business of traders who experience a decline turnover. From some respondents who work in the field of trade, entrepreneurship, self-employment experience the impact of the Covid-19 pandemic. This can be seen from the results of questionnaire distributed through google form https://bit.ly/2DiRYzL. Despite the pandemic, work and learning activities still have to run online, for example, conducting online Student Community Service (KKN), with socialization activities to fill out questionnaires related to the impact of the Covid-19 pandemic. In addition, the author also held online KKN activities by promoting tourist attractions in Sekaran village through https://www.youtube.com/watch?v=Ed3bdRIxlpY. The purposes of distributing questionnaire are to know the impact of the pandemic and in order to obtain solutions. This questionnaire was distributed to KKN places, namely Sekaran, Babat, Kebonsari, Turi, Kentong, Tunggul, Priyoso villages in Lamongan Regency, and Bayureno,  Bojonegoro, and Banyulegi Mojokerto. The questionnaires that have been completed were then analyzed using basic statistics such as average value, maximum value, and minimum value. The results of the distribution of questionnaires obtained 990 respondents, with an analysis of 77% of respondents experienced changes in income during the pandemic. Jobs affected by Covid-19 are traders, entrepreneurs, self-employed, farmers and online hired motorcycle drivers. Their incomes decreased by 50% to 68%. There were 43 layoffs out of 990 respondents.
Co-Authors Maghfiroh, Syafaatul Nawafilah, Nur Qomariyah Sri Pamungkas, Arif Patriot