Article Per Year (5 Year)
p-Index From 2020 - 2025
0.947
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Masyarakat Informatika Journal on Mathematics Education (JME) Journal on Mathematics Education (JME) CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Register: Jurnal Ilmiah Teknologi Sistem Informasi Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics Jurnal Sistem Cerdas MATHunesa: Jurnal Ilmiah Matematika Edukasia: Jurnal Pendidikan dan Pembelajaran Jurnal Sistem Informasi Journal on Mathematics Education Limits: Journal of Mathematics and Its Applications
Elly Matul Imah
Universitas Negeri Surabaya
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
PENGENALAN CITRA EKSPRESI WAJAH MENGGUNAKAN ALGORITMA PRINCIPAL COMPONENT ANALYSIS (PCA) DAN EXTREME LEARNING MACHINE (ELM) ANDY RIZKI WIYONO; ELLY MATUL IMAH
MATHunesa: Jurnal Ilmiah Matematika Vol 6 No 2 (2018)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.801 KB)

Abstract

Dewasa ini pengembangan ilmu teknologi semakin berkembang pesat,terutama dalam aspek keamanan, ilmu teknologi digunakan untuk pencarian identitas individu pada database kepolisian yang melibatkan data berupa citra digital ekspresi wajah manusia. Ekspresi wajah dapat dibedakan menjadi 7, yaitu senang, sedih, marah, jijik, takut, terkejut dan netral. Untuk mengenali citra ekspresi wajah pada penelitian ini digunakan algoritma Principle Component Analyst (PCA) dan Extreme Learning Machine (ELM). Algoritma PCA digunakan untuk mengekstraksi fitur, sedangkan ELM untuk melakukan pengenalan ekspresi. Dataset yang digunakan diambil dari JAFFE Dataset, berjumlah 210 citra ekspresi wajah, yang terdiri dari 10 orang masing-masing dengan 7 citra ekspresi berbeda, pengambilan foto dilakukan setiap 3 kali. Ratio datatrain : datates yang digunakan adalah 4:1. Penelitian dilakukan dengan menggunakan jumlah fitur yang berbeda mulai dari 50, 60, 70, 80 dan 90 serta 100. Pengenalan ekspresi menggunakan fungsi sigmoid dengan epoch hingga 100 kali tiap fitur, serta menggunakan hidden neuron sebanyak 65. Hasil terbaik menggunakan 90 fitur dengan epoch 65 kali diperoleh testing akurasi sebesar 0.715 (71.5%) dan training akurasi sebesar 0.931 (93.1%) dengan training time selama 0.062 detik dan testing time selama 0.015 detik. Kata kunci : ekspresi wajah, PCA, ELM
SISTEM INFORMASI RUTE WISATA DI KOTA SURABAYA MENGGUNAKAN ALGORITMA DIJKSTRA DENGAN GRAF REDUKSI ALFATARA NURUS SAADAH; ELLY MATUL IMAH
MATHunesa: Jurnal Ilmiah Matematika Vol 6 No 2 (2018)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.843 KB)

Abstract

Salah satu manfaat dari perkembangan teknologi adalah penggunaan Google Maps, yang membuat tempat wisata di Kota Surabaya sudah banyak dieksplor oleh para wisatawan.Namun, kemacetan yang terjadi di Kota Surabaya menjadi masalah para wisatawan.Pencarian rute wisata terpendek untuk mengunjungi suatu tempat wisata adalah solusi yang sangat tepat.Masalah ini dapat diselesaikan dengan algoritma Dijkstra dengan graf reduksi. Dalam proses pencarian rute wisata terpendek, sebuah graf yang merepresentasikan 25 tempat wisata di Surabaya harus direduksi menggunakan aturan reduksi fork closed rule terlebih dahulu untuk mempercepat proses pencarian menggunakan algoritma Dijkstra. Dengan adanya sistem informasi rute wisata terpendek di kota Surabaya, pencarian rute wisata lebih cepat dan efisien dengan kompleksitas waktu sebesar O(78+13^2) = 247dan dapat memudahkan masyarakat umum yang membutuhkan lintasan terpendek untuk menuju tempat – tempat wisata di Kota Surabaya.
Studi Steganografi Pada Citra Digital Menggunakan Shuffled Singular Value Decomposition (SSVD) Ainiya Aziza; Elly Matul Imah
Limits: Journal of Mathematics and Its Applications Vol 16, No 1 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (41.838 KB) | DOI: 10.12962/limits.v16i1.4675

Abstract

Stegangraphy is a technique for embed secret message in original image. It has an important role in the field of information hiding for secret communication. Many research about steganography tecniques have been developed, one of them is singular value decomposition (SVD). SVD method is popular discused in many tecnique such us steganography and watermarking. In addition to SVD there is a method which can give better result than SVD on watermaring technique that is Shuffled SVD. The differences between SSVD and SVD is in shuffle process which applied before applying SVD. The popularity of SSVD in the watermarking technique made the writer intererest to propose an image steganography tecnique using shuffled singular value decomposition (SSVD). The data used are two original RGB imaage and a message RGB image. Quality measured by PSNR and Correlation Coefficient. The experimental result show that the shuffling process on the secret message caused embedded message can’t  read easyly so the secret message is more secure.
Studi Komparasi Algoritma Klasifikasi Mental Workload Berdasarkan Sinyal EEG Dessy Kusumaningrum; Elly Matul Imah
Jurnal Sistem Cerdas Vol. 3 No. 2 (2020): Riset dan Inovasi Sistem Cerdas pada Penanggulangan Wabah Covid-19
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v3i2.69

Abstract

Kondisi psikologis dan fisik manusia dapat memengaruhi proses berpikir. Apabila kondisi individu mengalami kelelahan, maka dapat memengaruhi penurunan tingkat produktivitas maupun penurunan proses berpikir yang menyebabkan timbulnya mental workload. Workload yang dimiliki harus seimbang terhadap kemampuan dan keterbatasan yang dimiliki. Mental workload yang berlebih berdampak buruk bagi individu karena menimbulkan penurunan produktivitas kerja. Perangkat khusus yang dapat digunakan untuk mengetahui tingkat mental workload seorang individu adalah Electroencephalogram (EEG). EEG adalah perangkat khusus yang digunakan untuk mengukur sinyal potensi listrik dari otak. Dataset yang digunakan dalam penelitian ini adalah STEW: Simultaneous Task EEG Dataset dengan 45 subjek. Dalam penelitian ini, telah dilakukan studi komparasi algoritma Random Forest, K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), dan Support Vector Machine (SVM) untuk klasifikasi mental workload berdasarkan sinyal EEG. Studi dilakukan untuk menentukan algoritma terbaik dalam klasifikasi dilihat dari segi nilai akurasi dan penggunaan memori saat proses klasifikasi. Dataset telah melalui beberapa tahapan, diantaranya pra-pemrosesan data, ekstraksi fitur, dan proses klasifikasi. Pra-pemrosesan data menerapkan pembagian data menjadi beberapa chunk. Untuk mendapatkan ciri dalam ekstraksi fitur, diterapkan metode Principal Component Analysis (PCA). Pada proses klasifikasi menggunakan pendekatan k-fold cross validation. Hasil studi penelitian ini adalah algoritma terbaik dari sisi akurasi adalah algoritma KNN, algoritma terbaik dari sisi waktu pembuatan model adalah algoritma Random Forest, serta algoritma terbaik dari sisi penggunaan memori adalah algoritma MLP.
Tweets Emotions Analysis of Community Activities Restriction as COVID-19 Policy in Indonesia Using Support Vector Machine Abi Nizar Sutranggono; Elly Matul Imah
CommIT (Communication and Information Technology) Journal Vol. 17 No. 1 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i1.8189

Abstract

With the rising number of COVID-19 cases in Indonesia, the government has implemented the Imposition of Restrictions on Emergency Community Activities (Pemberlakuan Pembatasan Kegiatan Masyarakat - PPKM) as Indonesia’s COVID-19 policy. Several controversies and protests have colored the implementation of this emergency policy. Some netizens on Twitter voice their opinions about the policy in their tweets. Emotions in tweets can be recognized through text-based emotion detection or emotion analysis. However, textbased emotion detection is a challenging task. One of the main issues in classifying text with a machine learningbased approach deals with the feature dimensions. As a result, appropriate methods for accurately identifying emotion based on the text are required. The research studies an emotions analysis task on Indonesians’ PPKMrelated tweets to understand their emotional state while implementing the PPKM. The machine learning classification algorithms used are Support Vector Machine (SVM) and random forest. The total number of tweets is 4,401. The results show that SVM with linear kernel function combined with the TF-IDF and Chi-Square methods outperforms other classifiers with an accuracy of 0.7528. The accuracy value is higher than those obtained by previous studies. Moreover, the results of the emotion classification on PPKM tweets reveal that most Indonesians are unhappy with the implementation of the PPKM policy.
IMPLEMENTASI ALGORITMA INTEGER LINEAR PROGRAMMING UNTUK SISTEM INFORMASI PENJADWALAN RUANGAN DI FAKULTAS ILMU KOMPUTER UNIVERSITAS INDONESIA Elly Matul Imah; A.R. Hutomo; A. Fitrananda; A. Marshadiany; G.P. Prikarti
Jurnal Sistem Informasi Vol. 7 No. 1 (2011): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1029.822 KB) | DOI: 10.21609/jsi.v7i1.291

Abstract

Permasalahan konflik penjadwalan ruangan (timetabling) sering dihadapi hampir sebagian besar institusi akademis di Indonesia, salah satunya di Fakultas Ilmu Komputer Universitas Indonesia (Fasilkom UI). Peningkatan jumlah mahasiswa setiap tahun yang tidak diikuti oleh peningkatan jumlah dan kapasitas kelas menjadi faktor penyebab utama. Selama ini sistem penjadwalan masih dilakukan secara manual, sehingga membutuhkan waktu yang relatif lama dan menyebabkan optimasi pengalokasian kebutuhan ruangan menjadi kurang efisien. Penelitian ini bertujuan untuk menemukan pendekatan yang sesuai dalam menyelesaikan masalah timetabling tersebut. Beberapa pendekatan yang dapat digunakan untuk menyelesaikan masalah ini antara lain algoritma Tabu Search, Simmulated Annealing, Graph Coloring, dan Integer Linear Programming (ILP). Dalam penelitian ini, peneliti menggunakan algoritma ILP karena ILP merupakan model yang paling tepat untuk menyelesaikan masalah timetabling di Fasilkom UI. Algoritma ini dapat meminimalkan waktu yang diperlukan untuk melakukan penjadwalan dari sebulan menjadi hitungan menit. Room scheduling conflict issues (timetabling) are facing most of the academic institutions in Indonesia, one is in the Faculty of Computer Science (Fasilkom) Universitas Indonesia (UI). In the number of students each year followed by no increase in the number and capacity of the class became the main factor. During this scheduling system is still done manually so it takes a relatively long time so that the optimization is less efficient allocation of space requirements. This study aims to find an appropriate approach in solving the timetabling problem. Several approaches can be used to solve these problems include Tabu Search algorithm, Simmulated Annealing, Graph Coloring, and Integer Linear Programming (ILP). In this study we used the ILP algorithm for ILP is the most appropriate model to solve the timetabling problem in Fasilkom UI. This algorithm can minimize the time required to perform the scheduling of a month becomes a matter of minutes.
Detecting violent scenes in movies using Gated Recurrent Units and Discrete Wavelet Transform Elly Matul Imah; Ivan Kurnia Laksono; Karisma Karisma; Atik Wintarti
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.2541

Abstract

The easiness of accessing video on various platforms can negatively impact if not done wisely, especially for children. Parental supervision is needed so that movies platforms avoid inappropriate displays such as violence. Violent scenes in movies can trigger children to commit acts of violence, which is not desired. Unfortunately, it is not easy to supervise them fully. This study proposed a method for automatic detection of violent scenes in movies. Automatic violence detection assists the parents and censorship institutions in detecting violence easily. This study uses Gated Recurrent Units (GRU) algorithm and wavelet as feature extraction to detect violent scenes. This paper shows comparative studies on the variation of the mother wavelet. The experimental results show that GRU is robust and deliver the best performance accuracy of 0.96 while combining with mother wavelet Symlet and Coiflets8. The combination of GRU with wavelet Coiflets8 shows better results than the predecessor.
Combined VGG-Long Short Term Memory with Gamma Correction for Pneumonia Type Classification based on Chest X-Rays Nia Amelia; Riskyana Dewi Intan Puspitasari; Hasanuddin Al-Habib; Elly Matul Imah
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 9, No 2 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v9i2.15743

Abstract

Pneumonia is the second disease with the most patients being treated in the emergency department. Pneumonia can be distinguished based on its severity into viral and bacterial pneumonia. The coronavirus (COVID-19) has become a pandemic that spread globally. Panic during the pandemic has caused many people to self-diagnose and acknowledge common pneumonia as COVID-19. Despite having almost similar symptoms, not all pneumonia is COVID-19. Pneumonia is an inflammation of the lungs caused by bacteria, viruses, or fungi. In contrast, pneumonia in COVID-19 is caused by the SARS-CoV-2 virus. Early diagnosis of COVID-19 and pneumonia is crucial to perform the optimal treatment. A chest x-ray is a common way to detect pneumonia and is recommended for COVID-19. This study proposes a Pneumonia classification including a COVID-19 system based on X-Rays images using VGG-long short-term memory (LSTM) on chest X-ray images. This study applied gamma correction image enhancement to the thorax X-ray image. In the proposed system, VGG is used for feature extraction, and LSTM is used as a classifier. The experimental results show that the proposed system got an accuracy of 96.88% compared to previous state-of-the-art methods for pneumonia classification
Identifikasi Penalaran Kreatif-Imitatif Siswa dengan Gaya Kognitif Reflektif Durrotun Nabilah; Ismail; Elly Matul Imah
EDUKASIA: Jurnal Pendidikan dan Pembelajaran Vol. 4 No. 1 (2023): Edukasia: Jurnal Pendidikan dan Pembelajaran
Publisher : LP. Ma'arif Janggan Magetan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62775/edukasia.v4i1.229

Abstract

This research is aimed to describe the creative and imitative reasoning of students with reflective cognitive styles on math problem solving. The study uses a qualitative approach with a data collection instrument used of Matching Familiar Figure Tests, math ability test, mathematical problem-solving tasks, and interview guidelines. The research result studies indicate that a student with reflective cognitive style that have imitative reasoning in problem solving is less able to provide comprehensive information, still using a problem-solving strategy previously known, nor does he make a return check on the results received. It is different with reflective subjects that have proven creative reasoning capable of delivering well-known information, that can provide novel and thought-provoking solutions. Moreover, he also looking back the resulting solutions to the problem.
Students’ cognitive processes in solving problem related to the concept of area conservation Ekawati, Rooselyna; Kohar, Ahmad Wachidul; Imah, Elly Matul; Amin, Siti Maghfirotun; Fiangga, Shofan
Journal on Mathematics Education Vol. 10 No. 1 (2019): Journal on Mathematics Education
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aimed to determine the cognitive process employed in problem-solving related to the concept of area conservation for seventh graders. Two students with different mathematical ability were chosen to be the subjects of this research. Each of them was the representative of high achievers and low achievers based on a set of area conservation test. Results indicate that both samples performed more cyclic processes on formulating solution planning, regulating solution part and detecting and correcting error during the problem-solving. However, it was found that the high achiever student performed some processes than those of low achiever. Also, while the high achiever student did not predict any outcomes of his formulated strategies, the low achiever did not carry out the thought process after detecting errors of the initial solution gained. About the concept of area conservation, the finding also reveals that within the samples’ cognitive processes, the use of area formula come first before students decided to look for another strategy such as doing ‘cut-rotate-paste’ for the curved planes, which do not have any direct formula. The possible causes of the results were discussed to derive some recommendation for future studies.
Co-Authors A. Fitrananda A. Fitrananda A. Fitrananda A. Marshadiany A. Marshadiany A. Marshadiany A.R. Hutomo A.R. Hutomo A.R. Hutomo Abi Nizar Sutranggono Ahmad Wachidul Kohar Ainiya Aziza AINIYA FAHRUROSI AZIZA Alexander Agung Gunawan ALFATARA NURUS SAADAH ANDY RIZKI WIYONO Atik Wintarti Awalah, Ervi Anisatul Budiarto, Mega T. Dessy Kusumaningrum Diane Fitria Durrotun Nabilah Febrian Rachmadi Fiangga, Shofan Fitrananda, A. G.P. Prikarti G.P. Prikarti G.P. Prikarti Hasanuddin Al-Habib Hutomo, A.R. Ismail Ivan Kurnia Laksono Karisma Karisma KURNIA LAKSONO, IVAN Mahdiyah, Umi Marshadiany, A. Mohammad Isa Irawan Muhammad Anwar Ma'sum Muhammad Athoillah, Muhammad Nia Amelia NURUS SAADAH, ALFATARA Prikarti, G.P. R. Sulaiman Riskyana Dewi Intan P, Riskyana Dewi Riskyana Dewi Intan Puspitasari RIZKI WIYONO, ANDY Rooselyna Ekawati Siti Maghfirotun Amin T. Basaruddin Zumrotun Nafisah