Article Per Year (5 Year)
p-Index From 2021 - 2026
2.87
P-Index
This Author published in this journals
All Journal TEKNIK INFORMATIKA ARABIYAT Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri International Journal of Technology And Business MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer MULTINETICS JISKa (Jurnal Informatika Sunan Kalijaga) Cyber Security dan Forensik Digital (CSFD) Jurnal E-Komtek Journal of Applied Data Sciences Science, Technology, and Communication Journal
Siti Ummi Masruroh
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Social Sciences

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Selection of Home Wifi Internet: Machine Learning Implementation With Decision Tree C4.5 Algorithm Method Dewi Khairani; Muhammad Ammaridho Romdhan Siregar; Siti Ummi Masruroh; Miftakhul Nuuril Azizah
JURNAL TEKNIK INFORMATIKA Vol 15, No 2 (2022): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v15i2.27741

Abstract

The multiple bandwidths that internet service providers offer make it difficult for people to choose, especially for regular people unfamiliar with the internet; therefore, most people choose because the price is reasonable. Numerous users also lament the difficulty and slow internet usage. The issue is then concentrated on internet service providers, who are thought to be poor at offering services. The quantity of bandwidth consumed, which does not correspond to the user’s needs, is one factor contributing to slow internet. As a result, the appropriate bandwidth must be chosen based on the requirements of each user. Compared to other algorithms, the C4.5 decision tree method can deliver the best and correct decision, according to the current literature. As a result, this project will develop a web application based on the C4.5 decision tree algorithm that can assist in determining bandwidth and internet following community needs. Using this C4.5 Decision Tree, decisions are based on patterns identified in previously collected data. Predictions about various forms of internet use in the neighborhood may subsequently be produced from these patterns. Based on the calculation, the accuracy obtained is 0.54, or a percentage of 54%. The black box testing indicated that the bandwidth determination application was functioning correctly
Convolutional Neural Network for Colorization of Black and White Photos Siti Ummi Masruroh; Andrew Fiade; Muhammad Ikhsan Tanggok; Rizka Amalia Putri; Luigi Ajeng Pratiwi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 2 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2652

Abstract

People today are very fond of capturing moments by taking pictures. Various photo functions are used to document all forms of information that you want to store. In photos with digital images that have black and white, the information obtained is less than optimal, so an image processing process is needed to get color photos. Based on this, the author wants to change photos from black and white to color photos. The method used in this research is Convolutional Neural Network (CNN). This study uses Atlas 200 DK hardware and Ascend 310 processor. The data used in this study are 32 black and white photos in .jpg format as training data and perform 6 experimental scenarios with different numbers of black and white photos in each experiment. The total black and white photos used to experiment were 81 photos. The results obtained are models that successfully perform processing in the form of color photos with the appropriate color results in predicting the possible color of the object in each pixel in the photo. Based on this research, the trend of artificial intelligence can be implemented in changing the color of photos according to color predictions.
The Effect of Social Support and Self-Efficacy on Interest in Arabic Learning for College Students Zikri Neni Iska; Kaula Fahmi; Ilham Maulana Amyn; Siti Ummi Masruroh
Arabiyat : Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban Arabiyat : Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban | Vol. 10 No. 1 June 2023
Publisher : Syarif Hidayatullah State Islamic University of Jakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/a.v10i1.30409

Abstract

This study aims to determine the effect of social support and self-efficacy on interest in learning Arabic in students of the general faculty of UIN Jakarta. This study used quantitative research method, and the population were students of general studies at UIN Jakarta. The samples used in this study were 152 students of the General Study Program of UIN Jakarta. The sampling technique in this study uses a non-probability sampling technique. The measuring tools used in this study are the interpersonal support evaluation list – shortened version, (GSES-12), and Interest in Academic Domain. Test the validity of the measuring instrument used using the (CFA) technique. The results of the hypothesis test show that the value of R Square = 0.50, which means that the proportion of the variance of interest in learning Arabic which is explained by all independent variables is 50.3%, while the other 49.7% is influenced by other variables not examined. Two variables positively and significantly affect interest in learning Arabic, namely tangible support and self-efficacy.
Aplikasi Prediksi Penjualan dan Persediaan Barang Menggunakan Metode SES dan EOQ (Studi Kasus: UD. Sumber Alam Stone) Galang Ardian Sugianto; Arini Arini; Siti Ummi Masruroh
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 5 No. 1 (2020): Mei 2020
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (267.055 KB) | DOI: 10.14421/jiska.2020.51-03

Abstract

UD. Sumber Alam Stone merupakan usaha dagang yang menjual berbagai jenis batu alam. Dalam proses usaha dagang terdapat kendala berupa kurangnya persediaan barang. Untuk mengatasinya diperlukan solusi manajemen yang baik berupa peramalan terhadap penjualan dan persediaan barang. Dalam penelitian ini, penulis membangun aplikasi prediksi dengan menggunakan metode SES untuk memprediksi penjualan tahun 2019 dan metode EOQ untuk mengelola persediaan barang berupa pemesanan optimal, pemesanan ekonomis, biaya persediaan, safety stock dan reorder point pada tahun 2019. Data yang digunakan dalam penelitian ini adalah data penjualan batu alam dari tahun 2012 sampai 2018. Pengujian yang dilakukan pada aplikasi ini menggunakan pengujian blackbox. Hasil prediksi penjualan pada tahun 2019 adalah 2059 , dari prediksi tersebut diperoleh pemesanan optimal sebesar 258  untuk setiap pemesanan ekonomis yang berjumlah 8 kali pemesanan, dengan total biaya persediaan batu alam sebesar Rp. 4.868.322. safety stock atau persediaan pengamanan pada setiap kali melakukan stok barang sebanyak 30  dan reoder point atau titik pemesanan kembali pada lead time tercepat 3 hari sebanyak  32 , sedangkan untuk lead time terlama 7 hari sebanyak 71 .
Klasifikasi Mazhab Menggunakan Metode Naïve Bayes (Studi Kasus: Salat) Siti Ummi Masruroh; Siti Hanna; Nadia Azza; Kamarusdiana Kamarusdiana; Nanda Alivia Rizqy Vitalaya
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 8, No 1 (2022): Volume 8 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v8i1.51418

Abstract

Salat dimulai dengan gerakan takbir dan diakhiri dengan gerakan salam berdasarkan rukun dan syarat pada ketentuan hukum Islam. Dunia fikih penuh dengan perbedaan pendapat, termasuk dalam pembahasan salat. Perbedaan dalam fikih terwujud dalam bentuk mazhab-mazhab. Sebagai umat islam dianjurkan untuk mengetahui mazhab siapa yang diterapkandalam beribadah kepada Allah SWT. Klasifikasi fikih dalam salat bertujuan untuk mengetahui kecenderungan mazhab yang diikuti oleh seseorang.Naïve Bayes adalah salah satu jenis metode untuk melakukan klasifikasi data. Penelitian ini akan membuat suatu aplikasi pengklasifikasian mazhab fikih salat yang berbasis android dengan 4 mazhab dan menggunakan metode naïve bayes. Sistem ini dibangun dengan Flutter dan database MySQL. Teknologi aplikasi mobile android ini diharapkan dapat memberikan solusi alternatif untuk mengklasifikasikan mazhab dalam fikih salat. Teknik pengujian dilakukan dengan pengujian alpha oleh user (ustadz) dan uji akurasi sistem dilakukan dengan membandingkan hasil antara perhitungan manual dan perhitungan oleh sistem yang dibuat. Pengujian alpha menunjukkan hasil bahwa aplikasi mampu bekerja dengan baik, dan sesuai dengan pengujian akurasi yang menunjukkan akurasi sistem pada aplikasi adalah 100%.
Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

Abstract

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.
DESIGN OF AN AUTOMATIC STERILIZATION GATE TOOL USING PIR MOTION SENSOR Amrullah, Faiq Fawwaz; Khairani, Dewi; Masruroh, Siti Ummi
Jurnal Pilar Nusa Mandiri Vol 17 No 1 (2021): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v17i1.1937

Abstract

This automatic sterilization gate tool is a simple tool that changes the manual method to a systemized and more efficient way. This tool uses an infrared motion sensor in which there is a main component, namely the PIR (Pyroelectric Infra-Red) sensor, which is a material that reacts to radiation and movement in front of it. This tool also uses a 12v dc pump which is used to draw out the disinfectant liquid stored in the container. This gate tool is designed using the main material and some additional materials, the automatic gate can discharge about 11 seconds of liquid from objects or people that pass through the sensor range, 11 seconds is the minimum time for this tool to work while a distance of 6 meters is the range from where the sensor is located. From that time it proved that this gate tool has 100% accuracy and runs well. This gate tool is used every day, turned on from the morning, and turned off at night. Every 17.00 hours this gate tool is always replenished with supplies of disinfectant liquid. The automatic gate has helped the community to reduce the risk of transmission of the coronavirus, it also raises the awareness of the covid-19 pandemic. The whole system is implemented and is tested for real-time operation. It is found working satisfactorily. The gate tool can be further improved by adding a scanning device to perform tracing for passersby.
Performance comparison of the Naive Bayes algorithm and the k-NN lexicon approach on Twitter media sentiment analysis Azhar, Azhar; Masruroh, Siti Ummi; Wardhani, Luh Kesuma; Okfalisa, Okfalisa
Science, Technology and Communication Journal Vol. 3 No. 2 (2023): SINTECHCOM Journal (February 2023)
Publisher : Lembaga Studi Pendidikan and Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v3i2.229

Abstract

Sentiment analysis or opinion mining is a natural language that processes words to find out opinions, attitudes, or moods about certain things. Word processing in this study related to the process of classification in textual documents, which was classified into three classes, positive, negative, and neutral. Data obtained from social media Twitter were related to netizens' comments as many as 1000 comments. These data were crawled using keywords of the “Pilpres2019” and “Jokowi”. This study compared the performance of the Naive Bayes and k-Nearest Neighbor (k-NN) algorithms with the lexicon approach in classification. The aim of this study was to compare the level of accuracy, precision, and recall of Naive Bayes and the k-NN algorithm with the lexicon approach. From the evaluation, we concluded that the combination of the k-NN algorithm and the lexicon approach could improve accuracy in this sentiment analysis case. Generally, the k-NN algorithm with lexicon approach in which the k value is k = 5 has better performance with a 77% of accuracy level, followed by Naive Bayes with an accuracy of 81% of accuracy level.
Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

Abstract

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.
Transformer Architectures for Automated Brain Stroke Screening from MRI Images Abstract Sukmana, Husni Teja; Hasibuan, Zainal Arifin; Rahman, Abdul Wahab Abdul; Bayuaji, Luhur; Masruroh, Siti Ummi
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.736

Abstract

Early and accurate detection of stroke is critical for timely medical intervention and improved patient outcomes. This study explores the application of deep learning models, particularly the Vision Transformer (ViT), for the automated classification of brain stroke from medical images. A curated dataset of brain scans was used to train and evaluate the ViT model, which was benchmarked against a widely used convolutional neural network (CNN), ResNet18. Both models were trained using transfer learning techniques under identical preprocessing and training configurations to ensure fair comparison. The results indicate that the ViT model significantly outperforms ResNet18 in terms of validation accuracy, class-wise precision, and recall, achieving a peak accuracy of 99.60%. Visual analyses, including confusion matrices and sample prediction comparisons, reveal that ViT is more robust in detecting subtle stroke patterns. However, ViT requires more computational resources, which may limit its deployment in real-time or low-resource settings. These findings suggest that transformer-based architectures are highly effective for medical image classification tasks, particularly in stroke diagnosis, and offer a viable alternative to traditional CNN-based approaches.
Co-Authors Aditya Mirza Bahari Ahmad Akmaluddin Ahmad Arya Swaraja Ahmad Mukhlis Jundulloh Amrullah, Faiq Fawwaz Amyn, Ilham Maulana Andrew Fiade Arini Arini Arini Arini Arini Arini Ariq Cahya Wardhana Armenia, Ivan Gustra Manca Asep Taufik Muharram Azhar Azhar Farhanah, Titi Febrianus, Doni Fitri Mintarsih Galang Ardian Sugianto Hapsari Tiaraningtias Hendra Bayu Suseno Hendra Bayu Susueno Herlino Nanang Husni Teja Sukmana Ilham Maulana Amyn Imam Tri Wibowo Iska, Zikri Neni I’im Umamil Khoiri Jundulloh, Ahmad Mukhlis Kamarusdiana Kamarusdiana Karimi, Husain Faiz Kaula Fahmi Khairani, Dewi Luh Kesuma Wardhani Luhur Bayuaji, Luhur Luigi Ajeng Pratiwi Miftakhul Nuuril Azizah Muhamad Nur Gunawan Muhamad Nur Gunawan Muhammad Ammaridho Romdhan Siregar Muhammad Ikhsan Tanggok Muhammad Yusuf Nurpariz Munthaha, Firman Nadia Azza Nafdik Zaydan Raushanfikar Nanda Alivia Rizqy Vitalaya Nenny Anggraini Nenny Anggraini Nenny Anggraini, Nenny Nguyen, ⁠Cong Dai Nurbojatmiko Nurbojatmiko, Nurbojatmiko Nurhayati NURUL FAIZAH Okfalisa Okfalisa Putri, Rizka Amalia Rahman, Abdul Wahab Abdul Raushanfikar, Nafdik Zaydan Rizka Amalia Putri Rizka Amalia Putri Rona Nisa Sofia Amriza Shofi, Imam Marzuki Siti Hanna Syahid, Muhammad Fikri Titi Farhanah Velia Handayani Victor Amrizal Viva Arifin Viva Arifin Wisnu Ari Mukti Zainal Arifin Hasibuan