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Klasifikasi Sinyal EEG Dengan Power Spectra Density Berbasis Metode Welch Dan MLP Backpropagation Husain, Nursuci Putri; Aji, Nurseno Bayu
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol 3 No 1 (2019)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (452.162 KB) | DOI: 10.31961/eltikom.v3i1.99

Abstract

Electroencephalogram (EEG) signal is a signal that could become an information for study about disorders of brain function such as Epilepsi. EEG that detected in epileptic seizures produce patterns that allow doctors to distinguish it from normal conditions. However, a visual analysis can not be done continuously. This study proposed a new hybrid method of EEG signal classification using Power Spectral Density (PSD) based on Welch method, Principle Component Analysis (PCA), and Multi Layer Perceptron Backpropagation.There are 3 main stages in this study, firstly preprocessing the dataset of EEG signals by Power Spectral Density (PSD) based on Welch method, then Principle Component Analysis (PCA) as a method of dimensionallity reduction of the EEG signal data and the Multi Layer Perceptron Backpropagation for classifying a signal. Based on experimental results, the proposed method is successfully obtain high accuracy for the 80-20% training-testing partition (99.68%).
PEMANFAATAN HISTOGRAM EQUALIZATION PADA LOCAL TRI DIRECTIONAL PATTERN UNTUK SISTEM TEMU KEMBALI CITRA Husain, Nursuci Putri; Aji, Nurseno Bayu
SPECTA Journal of Technology Vol 4 No 1 (2020): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v4i1.164

Abstract

Abstract   Local tri-directional pattern (LtriDP) is a method of extracting local intensity features from each pixel based on direction. However, this method has not been able to provide good performance in extracting features for image retrieval. One reason that makes image retrieval performance worse is the effect of lighting. Lighting can cause large variations between images. This study proposed utilization of Histogram Equalization (HE). Histogram equalization is a functional method of stretching gray degrees and expanding image contrast. This will make variations in the gray level of the original image can be controlled. There are several main stages in this study, firstly query image and image dataset will be preprocessed with histogram equalization. After that, the image is extracted by a tri-directional pattern and magnitude pattern are searched. A tri-directional pattern will produce two histograms, while a magnitude pattern produces one histogram. The three histograms are combined or joint histogram is performed. Histogram that has been joint is a feature vector. The feature vector will be calculated using a similarity measurement Canberra. After that, an image similar to the query image will be obtained. The experiment was conducted using 3 face datasets namely ORL, BERN, and YALE. The average recall value was 0.422 for the ORL dataset, 0.50 for the BERN dataset, and 0.63 for the YALE dataset. The evaluation show, the proposed method can be used as a process of improving the quality of image datasets in the image retrieval system.  Keywords: Image retrieval system, Local tri-directional pattern, Streching Image, Histogram Equalization, Similarity Measurement Canberra. Abstrak   Local tri-directional pattern (LtriDP) merupakan salah satu metode ekstraksi fitur intensitas lokal dari setiap piksel berdasarkan arah. Namun, metode ini belum mampu memberikan performa yang baik dalam mengekstrak fitur untuk temu kembali citra. Salah satu alasan yang membuat performa temu kembali citra tidak baik adalah pengaruh pencahayaan. Pencahayaan dapat menyebabkan variasi besar antar citra. Penelitian ini mengusulkan pemanfaatan Histogram Equalization (HE). HE merupakan metode fungsional dalam peregangan derajat keabuan dan memperluas kontras citra. Hal ini akan membuat variasi level keabuan dari citra asli dapat terkendali. Ada beberapa tahapan utama dalam penelitian ini, yang pertama citra query dan citra dataset akan terlebih dahulu di preprocessing dengan histogram equalization. Setelah itu, citra tersebut diekstrak fiturnya, dicari pola tri-directional dan pola magnitude. Pola tri-directional akan menghasilkan dua histogram, sedangkan pola magnitude menghasilkan satu histogram. Ketiga histogram tersebut kemudian disatukan atau dilakukan joint histogram. Histogram yang telah dijoint merupakan vektor fitur. Vektor fitur tersebut akan dihitung rankingnya menggunakan pengukuran jarak canberra. Setelah itu, akan didapatkan citra yang mirip dengan citra query. Uji coba dilakukan dengan menggunakan 3 dataset wajah yaitu ORL, BERN, dan YALE. Nilai rata-rata recall yang di dapatkan 0,422 untuk dataset ORL, 0,50 untuk dataset BERN, dan 0,63 untuk dataset YALE. Dari hasil evaluasi tersebut, dapat disimpulkan metode yang diusulkan dapat digunakan sebagai proses peningkatan kualitas dataset citra pada system temu kembali citra.  Keywords: Sistem Temu Kembali Citra, Local tri-directional pattern, Peregangan Kontras, Histogram Equalization, Perhitungan Jarak Canberra.  
Klasifikasi Sinyal EEG Dengan Power Spectra Density Berbasis Metode Welch Dan MLP Backpropagation Nursuci Putri Husain; Nurseno Bayu Aji
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 3 No. 1 (2019)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v3i1.99

Abstract

Electroencephalogram (EEG) signal is a signal that could become an information for study about disorders of brain function such as Epilepsi. EEG that detected in epileptic seizures produce patterns that allow doctors to distinguish it from normal conditions. However, a visual analysis can not be done continuously. This study proposed a new hybrid method of EEG signal classification using Power Spectral Density (PSD) based on Welch method, Principle Component Analysis (PCA), and Multi Layer Perceptron Backpropagation.There are 3 main stages in this study, firstly preprocessing the dataset of EEG signals by Power Spectral Density (PSD) based on Welch method, then Principle Component Analysis (PCA) as a method of dimensionallity reduction of the EEG signal data and the Multi Layer Perceptron Backpropagation for classifying a signal. Based on experimental results, the proposed method is successfully obtain high accuracy for the 80-20% training-testing partition (99.68%).
LEAST SQUARES SUPPORT VECTOR MACHINES PARAMETER OPTIMIZATION BASED ON IMPROVED ANT COLONY ALGORITHM FOR HEPATITIS DIAGNOSIS Nursuci Putri Husain; Nursanti Novi Arisa; Putri Nur Rahayu; Agus Zainal Arifin; Darlis Herumurti
Jurnal Ilmu Komputer dan Informasi Vol 10, No 1 (2017): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (205.767 KB) | DOI: 10.21609/jiki.v10i1.428

Abstract

Many kinds of classification method are able to diagnose a patient who suffered Hepatitis disease. One of classification methods that can be used was Least Squares Support Vector Machines (LSSVM). There are two parameters that very influence to improve the classification accuracy on LSSVM, they are kernel parameter and regularization parameter. Determining the optimal parameters must be considered to obtain a high classification accuracy on LSSVM. This paper proposed an optimization method based on Improved Ant Colony Algorithm (IACA) in determining the optimal parameters of LSSVM for diagnosing Hepatitis disease. IACA create a storage solution to keep the whole route of the ants. The solutions that have been stored were the value of the parameter LSSVM. There are three main stages in this study. Firstly, the dimension of Hepatitis dataset will be reduced by Local Fisher Discriminant Analysis (LFDA). Secondly, search the optimal parameter LSSVM with IACA optimization using the data training, And the last, classify the data testing using optimal parameters of LSSVM. Experimental results have demonstrated that the proposed method produces high accuracy value (93.7%) for  the 80-20% training-testing partition.
Pelatihan Budidaya Jamur Dan Pembuatan Media Tanam Jamur Tiram Di Sulawesi Selatan Muh. Ichwan K; Nursuci Putri Husain
Patria Artha Journal of Community (PKM) Vol 1, No 2 (2021): Patria Artha Journal of Community (PKM)
Publisher : Universitas Patria Artha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2079.744 KB) | DOI: 10.33857/pajoco.v1i2.484

Abstract

 Oyster mushroom is one of the most commonly processed mushrooms as food ingredients and has high economic value. Many people in the South Sulawesi area are interested in cultivation of oyster mushrooms, but inexperience about cultivation and making oyster mushroom growing media (baglog) in the South Sulawesi area has made people unable to cultivation the oyster mushrooms independently. The purpose of engagement was to provide training in the cultivation and manufacture of oyster mushroom growing media to the community, so that people can cultivate and make mushroom growing media. This training begins with the provision of cultivation materials and the manufacture of growing media for oyster mushrooms, as well as business prospects for oyster mushrooms. Then, the practice of guidance on making oyster mushroom growing media, sterilization and mushroom inoculation was carried out. After that, simulation and evaluation were carried out, where participants were formed in groups and did independent practice of making mushroom growing media. This activity was carried out in one of the oyster mushroom cultivation sites in the City of Parepare, South Sulawesi, namely "Sahabat Jamur". This activity is also supported by the Corporate Social Responsibility (CSR) Program of PT PLN Persero – Sulselrabar Region. The training was conducted from 2 to 4 July 2021, and continued post-training monitoring via Whatsapp Group. The evaluation results from this training show that the cultivation and manufacture of oyster mushroom growing media can be done independently by the community, especially in the South Sulawesi area. The prospect of oyster mushroom cultivation and its processing has a very big opportunity in South Sulawesi.Keywords: Cultivation, Baglog, Oyster mushroom, South Sulawesi, Sahabat Jamur
BEST FIRST FEATURE SELECTION DAN RADIAL BASIS FUNCTION UNTUK KLASIFIKASI PENYAKIT DIABETES Nursuci Putri Husain
JURNAL ILTEK Vol 16, No 1 (2021): ILTEK : Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (172.362 KB) | DOI: 10.47398/iltek.v16i1.588

Abstract

Diabetes merupakan salah satu penyebab kematian terbesar di dunia. Penyakit diabetes dapat menyebabkan komplikasi seperti stroke, gagal ginjal, kebutaan yang bisa menyebabkan kecacatan. Sehingga diperlukan model prediksi untuk mengklasifikasikan seseorang mengidap penyakit diabetes atau tidak secara otomatis. Pada penelitian ini diajukan metode kombinasi Best First Feature Selection (BF Feature Selection) dan Radial Basis Function (RBF) untuk mengklasifikasikan penyakit diabetes. BF Feature Selection sebagai metode untuk mereduksi fitur-fitur pada dataset diabetes. BF Feature Selection mendapatkan 5 fitur yang paling relevan. Selanjutnya, dilakukan klasifikasi terhadap fitur-fitur tersebut menggunakan metode RBF.  Uji coba dilakukan dengan menggunakan dataset diabetes dari UCI repository. Pengujian dilakukan dengan membandingan hasil klasifikasi metode yang diajukan dengan metode yang berbeda pada penelitian sebelumnya. Berdasarkan hasil uji coba, metode yang diajukan mendapatkan nilai akurasi yang tinggi untuk 70-30% training testing partisi yaitu 82,17%. Dari hasil evaluasi tersebut dapat disimpulkan bahwa metode yang diajukan dapat digunakan sebagai metode klasifikasi penyakit diabetes secara otomatis.
PERANCANGAN SISTEM MANAJEMEN PENJUALAN MOTOR CASH DAN CREDIT BERBASIS WEB (STUDI KASUS PADA TOKO RAYA MOTOR KOTA PAREPARE) Nursuci Putri Husain
JURNAL ILTEK Vol 16, No 2 (2021): ILTEK : Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (352.495 KB) | DOI: 10.47398/iltek.v16i2.644

Abstract

Sistem manajemen penjualan merupakan suatu sistem yang berfungsi untuk memudahkan pelaku usaha dalam mengolah data-data penjualan. Sistem manajemen penjualan dapat dilakukan secara manual yaitu menggunakan buku sebagai pusat informasinya. Namun, sistem secara manual membutuhkan waktu yang lumayan lama apabila ingin mengelola suatu data penjualan. Sehingga, pada penilitian ini diusulkan sistem manajemen penjualan berbasis web. Penelitian ini merupakan penelitian pengembangan perangkat lunak menggunakan metode pengembangan SDLC (System Development Life Cycle) yaitu prototyping yang terdiri dari beberapa tahapan-tahapan: pengumpulan kebutuhan, membangun  prototipe, evaluasi prototipe, mengkodekan sistem, menguji sistem, evaluasi sistem, dan menggunakan sistem. Dalam penelitian ini diuraikan penerapan sistem manajemen penjualan dalam sebuah toko jual beli motor secara credit maupun cash. Sistem ini menggunakan bahasa pemrograman web PHP serta database MySQL. Sistem manajemen penjualan berbasis web ini telah diuji coba menggunakan blackbox testing dan divalidasi oleh pakar dan mendapat kategori “Baik”, sehingga diperoleh kesimpulan bahwa sistem ini layak untuk digunakan.
Perancangan Sistem Pengambilan Keputusan Promosi Jabatan Pada Kantor Camat Masalle Kab. Enrekang Menggunakan Metode S.A.W (Simple Additive Weighting) Suradi Suradi; Nursuci Putri Husain; Siti Eti Tridamayanti; Mutmainnah Mutmainnah
JURNAL ILTEK Vol 17, No 1 (2022): ILTEK : Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (800.202 KB) | DOI: 10.47398/iltek.v17i1.680

Abstract

Sistem pengambilan keputusan promosi jabatan sebagai salah satu daya pendorong agar pegawai dapat meningkatkan semangat kerjanya. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pengambilan keputusan promosi jabatan pada kantor camat masalle kab. Enrekang.  Metode pada penelitian ini adalah Simple Additive Weighting (S.A.W) dengan pengembangan sistem yang digunakan yaitu SDLC Waterfall. Metode System Development Life Cycle (SDLC) yaitu prototiping terdiri dari beberapa tahapan yaitu login, menginputkan data pegawai, output berupa informasi ranking. Waterfall digunakan dalam pengembangan software dimana pengerjaannya harus dilakukan secara berurutan yang dimulai dari tahap perencanaan konsep, pemodelan (design), implementasi, pengujian dan pemeliharaan.   Hasil penelitian ini menampilkan beberapa menu yaitu halaman login, halaman user, halaman kriteria, halaman data pegawai dan halaman ranking serta hasil perancangan di impelementasikan dan diterapkan pada kantor Camat masalle Kab. Enrekang. Kesimpulan dari aplikasi menggunakan metode Simple Additive Weighting (S.A.W) telah berhasil dirancang dan dapat digunakan dengan baik untuk mendukung pengambilan keputusan promosi jabatan pada kantor Camat Masalle Kab.  Enrekang.
Rancang Bangun Pendeteksi Jarak Aman Mata Dengan Layar Monitor Televisi Berbasis Arduino Uno Nursuci Putri Husain; Herlinah B; Mithahul Khairah; M Akbar
Jurnal Teknologi dan Komputer (JTEK) Vol 2 No 02 (2022): DESEMBER
Publisher : Teknik Informatika Universitas Islam Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56923/jtek.v2i02.96

Abstract

Mata adalah indera penglihatan yang berfungsi mempersepsikan bentuk, ukuran, maupun kedudukan suatu objek. Menonton layar televisi dengan jarak 0–119 cm, dapat menyebabkan kerusakan pada mata seperti mata minus, mata juling dan penyempitan pembuluh darah. Paparan dari cahaya televisi akibat menonton terlalu dekat akan berefek pada mata seperti sakit kepala, mata rabun, mata perih, mata kering dan mata berair. Tujuan penelitian merancang bangun pendeteksi jarak aman mata dengan layar monitor televisi berbasis arduino uno guna mencegah menonton layar televisi terlalu dekat yang mengakibatkan kerusakan pada mata. Metode penelitian Research and Development berfungsi menghasilkan, mengembangkan produk tertentu serta menguji keefektifan produk (alat pendeteksi jarak aman mata). Pengujian sistem yang dilakukan adalah pengujian arduino uno, sensor HY-SRF05, LCD, push button, relay, buzzer. Hasil pengujian alat menggunakan arduino uno terdiri dari dua proses yaitu input proses dan output proses, ketika sensor HY-SRF05 mendeteksi jarak objek mata <120 cm maka relay akan memutuskan tegangan terminal selama 10 detik dan televisi OFF, sebaliknya jika jarak objek mata ≥120 cm relay akan meyambungkan tegangan ke terminal dan televisi ON. Kesimpulan sensor pendeteksi objek pada alat pengatur jarak aman mata beroperasi dengan lancar dan akurat.
Aplikasi Pendeteksi Dini Kanker Serviks Berbasis Android Herlinah B; Nursuci Putri Husain
Journal of System and Computer Engineering (JSCE) Vol 4 No 1 (2023): JSCE: Januari 2023
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47650/jsce.v4i1.684

Abstract

Cervical cancer is the growth of a group of abnormal cells in the cervix (mouth of the womb). The lack of knowledge in diagnosing women against cervical cancer is around 60% - 77%. Lack of diagnostic knowledge about cervical cancer symptoms so that many women do not know the symptoms of cervical cancer and have two possibilities whether it is cervical cancer symptoms or symptoms of other diseases. The purpose of the study was to design an Android-based cervical cancer early detection application to monitor cervical cancer early in helping women diagnose independently. The R&D (Research and Development) research method functions to generate, develop and test the effectiveness of the product (an android-based cervical cancer early detection application) and the forward chaining method functions in making decisions based on the facts that are inputted so as to produce conclusions. home menu, diagnoses, diagnostic results and profiles, starting with the user clicking the diagnosis menu in selecting the symptoms he is experiencing, then the user clicking the diagnostic results menu to see the results of the symptoms that have been diagnosed and have 4 criteria, namely cervical cancer stage 1, cervical cancer stage 2, cervical cancer stage 3 and cervical cancer stage 4. The conclusion of the application where the functional input and output runs well in accordance with the basic concepts that have been made and can be implemented.