Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

3.914

P-Index

This Author published in this journals

All Journal International Journal of Electrical and Computer Engineering International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Telematika SISFOTENIKA INOVTEK Polbeng - Seri Informatika Jurnal Informatika Universitas Pamulang RESEARCH : Computer, Information System & Technology Management Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Telematika Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Elektronika Listrik dan Teknologi Informasi Terapan Amalee: Indonesian Journal of Community Research & Engagement Jurnal Teknika Jurnal Sistem Komputer dan Informatika (JSON) KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Joutica : Journal of Informatic Unisla Insand Comtech : Information Science and Computer Technology Journal Jurnal Informatika: Jurnal Pengembangan IT Jurnal Ilmiah Sistem Informasi

Nafiiyah, Nur

Prodi Teknik Informatika Fakultas Teknik Universitas Islam Lamongan

Author-ID : 2662524

Aerospace Engineering Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Neuroscience Public Health Social Sciences Transportation Other

Published : 34 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4

A convolutional neural network for skin cancer classification Nur Nafi'iyah; Anny Yuniarti
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp76-84

Skin diseases can be seen clearly by oneself and others. Although this disease is visible on the skin, sometimes we worry if this skin disease is not mild. Some people experience skin diseases directly and quickly go to a dermatologist to have their complaints and symptoms checked. This skin protects the body, especially from the sun, so it can lead to death if something goes wrong. One example of a skin disease that can be deadly is skin cancer or skin tumors. In this research, we classified skin cancer into Benign and Malignant using the convolution neural network (CNN) algorithm. The purpose of this research is to develop the CNN architecture to help identify skin diseases. We used a dataset of 3,297 skin cancer images which are publicly available on the Kaggle website. We propose two CNN architectures that differ in the number of parameters. The first architecture has 6,427,745 parameters, and the second architecture has 2,797,665. With both architectures, the accuracy of the first model is 93%, and the second model is 74%. The first model with the number of parameters 6,427,745 We save for use in the creation of the website. We created a web-based application with the Django framework for skin disease identification.

Implementasi SOM Dalam Clustering Hasil Ikan Laut Kabupaten Pekalongan Bagus Nur Bakti Aji; Nur Nafiiyah; Miftahus Sholihin
Jurnal Elektronika, Listrik, dan Teknologi Informasi Terapan Vol 2 No 1 (2020): Jurnal ELTI III
Publisher : LPPM Politeknik Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37338/e.v2i1.114

Data from sea fish in Pekalongan Regency can be processed, one of which is clustered. Clusters are grouping data based on the same criteria. The purpose of doing clustering is to be able to help in sorting and dividing a situation based on the same criteria. Clustering of marine fish products in Pekalongan Regency will be grouped into three groups, namely: a small group of marine fish products, a medium group of marine fish products, and a large group of marine fish products. The clustering process uses the SOM algorithm, and the data is taken from the website data.go.id/dataset. Data is processed in order to show which fish yields are small, medium and large. The processing process uses variable types of fish, years and results of sea fish that are stored in Excel files and then processed using Matlab. The results show that there are fish species that are classified as low and moderate clusters, namely shrimp, squid, serimping, grouper, turmeric, and ray species. The types of fish that enter the cluster and many are Tigawaja. The types of fish that enter the medium cluster are Beloso, Pihi, Pepetek, and those who enter the low cluster are 18 fish species, while those who enter the low, medium and many clusters are Petek.

CNN Architecture for Classifying Types of Mango Based on Leaf Images Nur Nafi'iyah; Jauharul Maknun
Telematika Vol 14, No 2: August (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i2.1262

In such conditions, it is necessary to have a system that can automatically classify plant species or identify types of plant diseases using either machine learning or deep learning. The plant classification system for ordinary people who are not familiar with the field of crops is not an easy job, it requires in-depth knowledge of the field from the experts. This study proposes a system for identifying mango plant species based on leaves using the CNN method. The reason for proposing the CNN method from previous research is that the CNN method produces good accuracy. Most previous studies to classify plant species use the leaves of the plant. The purpose of this study is to propose a CNN architectural model in classifying mango species based on leaf imagery. The input image of colored mango tree leaves measuring 224x224 is trained based on the CNN architectural model that was built. There are 4 CNN architectural models proposed in the study and 1 transfer learning InceptionV4. Based on the evaluation test results of the proposed CNN architectural model, that the best architectural model is the third. The number of parameters of the third CNN architecture is 1,245,989 with loss values and accuracy during evaluation are 1,431 and 0.55. The largest number of parameters is transfer learning InceptionV3 21,802,784, but transfer learning shows the lowest accuracy value and the highest loss, namely 0.2, and 1.61.

Algoritma SVM untuk Memprediksi Pengunjung Wisata Musium di Jakarta Nur Nafi'iyah
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 1, No 1 (2020)
Publisher : Institut Teknologi Adhi Tama Surabaya

Berbagai macam tempat wisata yang ada di Jakarta menjadi tujuan berlibur atau bermain, mulai dari wisata alam, mall, bioskop, taman hiburan, atau musium. Setiap individu mempunyai aktivitas dan rutinitas bermacam-macam, sehingga membutuhkan hiburan dan waktu untuk melepaskan kejenuhan. Dari website data.jakarta.go.id didapatkan dataset kunjungan wisata musium baik dari wisatawan Indonesia maupun luar Indonesia. Dari dataset tersebut dapat dimanfaatkan untuk diolah dan digali informasinya. Menggali dan mengolah dataset adalah suatu kegiatan data mining, yaitu menerapkan suatu algoritma untuk menggali pengetahuan. Algoritma SVM digunakan untuk memprediksi kunjungan wisata musium di Jakarta, di mana terdapat variabel tempat destinasi, bulan, jenis pengunjung dan jumlah pengunjung. Tempat destinasi ada 10 jenis wisata, dan jenis pengunjung ada 2, yaitu wisatawan dalam negeri dan luar negeri. Di mana hasil prediksi dari SVM pada data 222 baris pengunjung wisata musium di Jakarta jelek. Dibuktikan dari nilai selisih data nyata dengan hasil prediksi sangat tinggi, dan nilai errornya sangat tinggi 2838303,5.

ANALISIS ALGORITMA BACKPROPAGATION DENGAN SVM DALAM HASIL PREDIKSI NILAI UJIAN NASIONAL PADA SEKOLAH TINGKAT PERTAMA Nur Nafi'iyah
I N F O R M A T I K A Vol 12, No 1 (2020): MEI 2020
Publisher : STMIK DUMAI

Dalam menyikapi ujian nasional tingkat SMP beberapa sekolah dan dinas pendidikan di daerah selalu berusaha mendadakan try out. Tujuan diadakan try out dan bimbingan belajar adalah siswa agar dapat lulus di ujian nasional. Usaha yang dilakukan tersebut agar siswa bisa memenuhi grade kelulusan ujian nasional. Selain dengan cara tersebut, dapat dilakukan dengan membuat suatu sistem yang dapat memprediksi nilai ujian nasional siswa SMP. Penelitian ini bertujuan untuk membandingkan hasil prediksi nilai ujian nasional siswa SMP dengan algoritma backpropagation dan SVM. Di mana dataset yang digunakan adalah dataset nilai ujian nasional pada mata pelajaran Bahasa Indonesia, Bahasa Inggris, Matematika, dan Ilmu Pengetahuan Alam siswa SMP. Kami membuat arsitektur algoritma backpropagation dengan 2 model. Model pertama dengan 5 node hidden layer, dan model kedua dengan 7 node hidden layer. Input dari kedua algoritma adalah 7 variabel, dengan 701 baris dataset, 561 baris untuk pelatihan dan 140 baris pengujian, dan outputnya adalah nilai ujian nasional. Hasil pengujian antara backpropagation dan algoritma SVM menghasilkan nilai MSE terendah, yaitu backpropagation dengan MSE rata-rata 103,3. Di mana struktur yang digunakan dalam algoritma backpropagation dengan 7 node input layer, 5 node hidden layer dan 1 node output layer. Sedangkan jika menggunakan struktur algoritma backpropagation dengan 7 node input layer, 7 node hidden layer, dan 1 node output layer MSE adalah 106,6. Jika menggunakan algoritma SVM, nilai MSE rata-rata adalah 200. Kata kunci : Nilai Ujian Nasional SMP, Backpropagation, SVM

SISTEM PENILAIAN KINERJA GURU PADA MI TARBIYATUS SHIBYAN MENGGUNAKAN BOOTSTRAP FRAMEWORK Moh Muslikh; Retno Wardhani; Nur Nafiiyah
Joutica Vol 1, No 2 (2017)
Publisher : Universitas Islam Lamongan

Teacher performance assessment system is a system that can help the problem of teacher assessment in the schools in in delivering the value of accurate and right on target, one of them is MI Tarbinyatus Shibyan Kemantren Paciran Lamongan which implement the performance appraisal of teachers to know the process of teaching is good and right for all student and for the promotion of teacher. Performance assessment of the teacher themselves were taken from the four criteria, namely Pedagogic, social, personality, there are four criteria of Professional the fourteen competencies. Thus is created the system of teacher performance assessment based on login step, the content of the data content of the teacher, the teacher's grades, report the results of the result value. Teacher performance assessment system is made as easy as possible, the system can be easily dioprasikan to assist the principal in the giving of value accurate and right on target.

PENILAIAN KINERJA TU (TATA USAHA) UNIVERSITAS ISLAM LAMONGAN Nur Nafiiyah
Joutica Vol 2, No 1 (2017): Jurnal Informatika UNISLA
Publisher : Universitas Islam Lamongan

The performance assessment of administration staff in the college did in order to improve the quality of the service process and internal continuous quality improvement. This study aims at the development of information systems web-based performance assessment. This system was built using the programming language PHP (Hypertext Processor) and MySql database, which is expected to provide a more efficient and effective in conducting this evaluation, all the colleges are trying to have an information system that not only presents a variety of important information, but also can perform the data processing. Assessmentof the performance is measurements made on various activities with the questioner. The results of the study give a rank of accumulation is obtained by calculating the second component of the assessment, the results of this can be seen anyone to find the highest rank to lowest. It is hoping that every values obtained can push Employees the administration in Lamongan Islamic university to improve its performance.

APLIKASI PEMBELAJARAN PERALATAN TANJIDOR BERBASIS ANDROID Yusuf Permadi; Nur Nafiiyah
Joutica Vol 1, No 2 (2017)
Publisher : Universitas Islam Lamongan

Smartphone is the manifestation of the technological developments that can narrow space and time. Smartphone is not only used as a means of communication but as a means of entertainment for many kinds of applications that is presented by the developers. Android is an operating system that is widely used by several manufacturers of smartphones today. Application is a program which is designed to perform a function with specific goals and purposes. Tanjidor is the musical art of Betawi. Tanjidor did not come originally from Indonesia, but from Portuguese language in a word Tangedor which means “stringed musical instruments”. Tanjidor itselfis played in several musical instruments category, namely wind instruments (in particular instrument it is called as mouthpiece) like clarinet, trombone, tuba, saxophone, and trumpet. In addition, there is also wind instrument musical which played by hit it (in a particular type it is called a percussion), like snare drum, tenor drum, bass drum, cymbals and drums. Android-based Tanjidor equipment learning application is used as the entertainment media and also aims to preserve the Indonesian art heritage by inserting Tanjidor instruments in Android smartphon. Therefore, Tanjidor musical art does not disappear over the time.

Klasifikasi Jenis Pisang Berdasarkan Fitur Warna, Tekstur, Bentuk Citra Menggunakan SVM dan KNN Yusuf Eka Yana; Nur Nafi'iyah
RESEARCH : Journal of Computer, Information System & Technology Management Vol 4, No 1 (2021)
Publisher : UNIVERSITAS PGRI MADIUN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/research.v4i1.6687

Di Indonesia mempunyai beragam jenis tanaman, buah yang dapat ditanam di berbagai daerah Indonesia. Contohnya buah Pisang mempunyai beragam jenis Pisang, dan beberapa masyarakat kurang memahami jenis-jenis Pisang yang ada di Indonesia. Dengan kondisi itu maka kami akan melakukan suatu penelitian terkait mengklasifikasikan jenis Pisang berbasis komputer. Tujuan penelitian ini, yaitu mengidentifikasi atau mengklasifikasi jenis Pisang berdasarkan fitur citra (warna, tekstur, bentuk) dengan algoritma SVM dan KNN. Data yang digunakan adalah citra Pisang total 399, yang diklasifikasi menjadi 7 jenis, Pisang ambon, Pisang kepok, Pisang susu, Pisang raja, Pisang mas, Pisang raja nangka, Pisang cavendish. Dari citra Pisang diambil fitur warna nilai rata-rata RGB, standar deviasi RGB, skewness RGB, entropy RGB. Fitur tekstur nilai rata-rata citra grayscale, standar deviasi grayscale, dan gray level co-occurance matrix (kontras, energi, korelasi, homogeneity). Serta fitur bentuk dari citra biner nilai area, perimeter, metric, major axis, minor axis, eccentricity. Hasil ujicoba menunjukkan algoritma SVM nilai akurasi mengklasifikasi jenis Pisang secara berturut-turut dari fitur warna, tekstur, bentuk adalah 41,67%, 33,3%, 8,3%. Dan hasil klasifikasi jenis Pisang dengan algoritma KNN, nilai K terbaik adalah 2 pada fitur warna 55,95%, fitur tekstur 58,33%, dan fitur bentuk 45,24%.

Prediksi Jumlah Penjualan pada Toko Makmur Jaya Elektronik dengan Regresi Linier Nur Nafi'iyah
RESEARCH : Journal of Computer, Information System & Technology Management Vol 2, No 2 (2019)
Publisher : UNIVERSITAS PGRI MADIUN

Toko Makmur Jaya Elektronik merupakan toko yang bergerak di toko elektronik. Karena jumlah permintaan barang di setiap bulan kurang menentu, maka membuat pemilik toko kesulitan dalam menyediakan stok barang setiap bulan. Jika persediaan stok barang kurang maka membuat toko kehilangan laba dari perjualan. Tujuan penelitian ini untuk menentukan stok persediaan barang di bulan berikutnya menggunakan algoritma regresi linier berganda. Metode yang digunakan dalam penelitian ini adalah regresi linier berganda dengan inputan jenis barang, bulan, dan outputnya adalah stok barang. Barang yang akan diprediksi adalah kulkas dan televisi selama 3 tahun, sebanyak 72 baris dataset. Hasil perhitungan menunjukkan bahwa metode regresi linier nilai MAPE sebesar 27,291 dan MAD sebesar 9,916.

Co-Authors ., Ichsan Yudistura Agus Setia Budi, Agus Setia Agus Subhan Akbar, Agus Subhan Alhidayati Asymal Anny Yuniarti Ayu Ismi Hanifah Bagus Nur Bakti Aji Chastine Fatichah edy susanto Eha Renwi Astuti Eko Sulistiono Sulistiono Husnul Khotimah Ika Purnama Sari Irma Dwi Rohmawati Jauharul Maknun Khoiruddin, Muhammad Ubay Khotim Hidayati Hidayati M Sholihul Hadi Masruroh Masruroh Miftahus Sholihin Moh Muslikh Muchammad Khudori Muhammad Ali Haydar Munir Munir, Munir Nela Nevrivanti Aulia Prasetyo, Puguh Rouf Purnomo Hadi Susilo, Purnomo Hadi Putra, Ramadhan Hardani Retno Wardhani Rizki Ardhian Ahmad Sholikah Indrawati Sholikha, Ni'matus Siti Mujilahwati Yusuf Eka Yana Yusuf Permadi Zuhri, Ahmad Syafiq Maulana

Title

Found 34 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 34 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 34 Documents
Search