Article Per Year (5 Year)
p-Index From 2021 - 2026
2.427
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) ILKOM Jurnal Ilmiah Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Journal of Information Systems and Technology Research Wahana Internet of Things and Artificial Intelligence Journal Servire: Jurnal Pengabdian Kepada Masyarakat Journal of Technology Informatics and Engineering The Indonesian Journal of Computer Science
Ratu Mutiara Siregar
Institut Teknologi Sawit Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 16 Documents
Search

 1   2 
Association of single nucleotide polymorphism and phenotype in type 2 of diabetes mellitus using Support Vector Regression and Genetic Algorithm Ratu Mutiara Siregar; Wisnu Ananta Kusuma; Annisa Annisa
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1283.194-202

Abstract

Precision Medicine is used to improve proper health care and patients' quality of life, one of which is diabetes. Diabetes Mellitus (DM) is a multifactorial and heterogeneous group of disorders characterized by deficiency or failure to maintain normal glucose homeostasis. About 90% of all DM patients are Type 2 Diabetes Mellitus (T2DM). Biological characteristics and genetic information of T2DM disease were obtained by looking for associations in Single Nucleotide Polymorphism (SNP) which allows for determining the relationship between phenotypic and genotypic information and identifying genes associated with T2DM disease. This research focuses on the Support Vector Regression method and Genetic Algorithm to obtain SNPs that have previously calculated the correlation value using Spearman's rank correlation. Then do association mapping on the SNP results from the SVR-GA selection and check pastasis interaction. The results produced 14 SNP importance. Evaluation of the model using the mean absolute error (MAE) obtained is 0.02807. If the value of MAE is close to zero, then a model can be accepted. The genes generated from the association can be used to assist other researchers in finding the right treatment for T2DM patients according to their genetic profile.
Analysis and Design of e-Commerce Application “PALMARKET” based on Mobile Android as a Media for Selling Quality Palm Seeds and Seeds Maudy Hellena Harlyn; Fajar Maulana; Ardila; Ratu Mutiara Siregar; Amru Yasir; Tuty Ningsih; Friska Anggraini Barus; Rahmad Dian
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4113

Abstract

In this digital era, the use of e-commerce mobile applications is very useful to reach sales and purchases widely and is easy, fast and convenient to use for the community. Until now, there has not been found e-commerce that is devoted to selling seeds and plant seeds, especially oil palm plants that can be trusted. In fact, there are many farmers who buy the wrong seeds, resulting in long-term problems in the oil palm plantation industry whose production is decreasing. Therefore, the sale of seeds and plant seeds needs support through a trusted e-commerce Mobile Application so that farmers do not need to be afraid to buy quality oil palm seeds. The development method used in this research uses the Waterfall method. The results of this study are in the form of e-commerce Mobile Application as a means of buying and selling oil palm seeds and seeds that are easy and reliable throughout the region
Low-Cost CCTV for Home Security With Face Detection Base on IoT Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Prayogi, Andi; Dian, Rahmad; Siregar, Ratu Mutiara; Aris Sugianto, Raden
Journal of Information Systems and Technology Research Vol. 3 No. 1 (2024): January 2024
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v3i1.769

Abstract

Monitoring is a necessary part of Home surveillance that can be done through the internet network as a security measure. Many CCTV cameras on the market today continue to employ analog and conventional technology, specifically coaxial wire. As a result, extra expenditures for CCTV system wiring are required; besides being more expensive, the installation takes more handling, as the picture data cable and control signal cable cannot be merged. This project aims to develop a security system capable of detecting object movement in real-time utilizing a webcam camera attached to a raspberry pi. The findings of this study enable the development of a low-cost CCTV system that can be monitored remotely via the Internet of Things.
Direct implementation of AI-Based Facial Recognition for ITSI students Prayogi, Andi; Navea, Roy Francis; Dian, Rahmad; Pane, Muhammad Akbar Syahbana; Siregar, Ratu Mutiara; Sugianto, Raden Aris; Simbolon, Hasanal Fachri Satia
Journal of Information Systems and Technology Research Vol. 3 No. 3 (2024): September 2024
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v3i3.898

Abstract

The development of artificial intelligence (AI)-based facial recognition technology has become a significant research topic in the field of computing and security. At the Indonesian Palm Oil Institute (ITSI), AI-based facial recognition is introduced to students to improve their skills in developing AI-based applications. This study aims to implement and test a facial recognition system using a Python program by utilizing a dataset generated independently. This research method involves several stages, namely collecting ITSI students' facial data, data processing, creating a facial recognition model using a machine learning algorithm, and evaluating model performance. The dataset used was developed through a live shooting session involving active student participation. The facial recognition model was trained using a convolutional neural network (CNN) algorithm that was optimized to improve accuracy. The results of the study showed that the developed model was able to achieve high facial recognition accuracy, with an average accuracy rate of 92%. The discussion includes an analysis of factors that affect accuracy, such as variations in lighting and shooting angles, as well as the potential use of this technology in a campus environment, including for attendance and security purposes. The conclusion of this study shows that the implementation of AI-based facial recognition can be effectively applied in an academic environment, as well as providing students with practical experience in developing and testing AI applications. This study also opens up opportunities for further research on improving the performance of facial recognition systems and their application in various real-world scenarios.
IoT Oxymeter Starter Prototype As An Employee Health Monitoring Tool In The Blynk Integrated Palm Industry Muhammad Akbar Syahbana Pane; Rahmad Dian; Ratu Mutiara Siregar; Balqis Nurmauli Damanik; Asnita Yani; Alisarjuni Padang; Khairul Saleh
Journal of Technology Informatics and Engineering Vol 3 No 1 (2024): April : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i1.158

Abstract

One of the main challenges faced by workers in the palm oil industry is routine health monitoring. Therefore, innovation is needed in the form of health monitoring tools that can facilitate and increase the efficiency of employee health monitoring. The Internet of Things (IoT) has become an increasingly popular solution to overcome these challenges. The use of this technology is expected to increase employee health resilience, detect potential health problems early, and provide a quick response to health conditions that require medical attention.
Penggunaan Random Forest dan Analisis Perilaku untuk Prediksi Serangan DDoS dalam Lingkungan Cloud Computing Prayogi, Andi; Pane, Muhammad Akbar Syahbana; Dian, Rahmad; Siregar, Ratu Mutiara; Sugianto, Raden Aris; Simbolon, Hasanal Fachri Satia
Techno.Com Vol. 23 No. 3 (2024): Agustus 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i3.11317

Abstract

Dalam dunia komputasi awan yang semakin berkembang, ancaman serangan Distributed Denial of Service (DDoS) menjadi isu yang sangat krusial. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan model prediksi serangan DDoS menggunakan algoritma Random Forest dan analisis perilaku jaringan. Dataset CICIDS2017 digunakan sebagai sumber data utama untuk melatih dan menguji model prediksi yang dikembangkan. Pemilihan algoritma Random Forest didasarkan pada kemampuannya yang tinggi dalam menangani data besar dan kompleks serta kemampuannya dalam mengenali pola anomali yang sering menjadi indikasi serangan siber. Hasil pengujian menunjukkan bahwa model ini mencapai akurasi yang signifikan dengan precision sebesar 97,8%, recall sebesar 98,2%, dan F1-score sebesar 98,0%. Analisis perilaku jaringan yang diterapkan, melibatkan fitur-fitur dinamis seperti waktu antar paket (Inter-Arrival Time/IAT), ukuran rata-rata segmen, dan jumlah paket per detik, yang terbukti efektif dalam meningkatkan kemampuan deteksi model. Implementasi model dalam lingkungan komputasi awan menunjukkan bahwa metode ini dapat diintegrasikan dengan sistem deteksi intrusi (Intrusion Detection Systems/IDS) yang sudah ada untuk memberikan lapisan perlindungan tambahan terhadap serangan DDoS. Berdasarkan hasil yang diperoleh, penelitian ini merekomendasikan penggunaan kombinasi algoritma Random Forest dan analisis perilaku jaringan sebagai solusi yang efektif untuk mendeteksi serangan DDoS dalam lingkungan komputasi awan. Penelitian lanjutan disarankan untuk mengembangkan dan menguji model dengan dataset yang lebih beragam serta mengoptimalkan algoritma untuk meningkatkan performa deteksi.   Kata kunci: Random Forest, DDoS, Cloud Computing
Implementasi Sistem Pendukung Keputusan Menggunakan Algoritma MOORA untuk Pemilihan Jenis Bibit Cabai Unggul Al Akbar, Abdussalam; Yasin, Alimuddin; Alex Rizky Saputra; Sepriano; Siregar, Ratu Mutiara; Budy Satria; Elfitra
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3464

Abstract

Cultivating chili plants is a business opportunity that has quite a large income. However, many farmers still use traditional concepts in determining which seeds to plant, such as trying out chili seeds without carrying out in-depth analysis or observation. A decision support system (DSS) is a system that is capable of providing decision recommendations using several criteria determined through method processes in the decision making system, namely ARAS, SAW, MOORA, AHP and others. The MOORA method is useful for separating the subjective part of an evaluation process into a decision weight criterion with several decision making attributes. And also the level of selectivity of this method is very good because it can determine objectives from conflicting criteria. Where the criteria can be profitable (benefit) or unprofitable (cost). Based on the results obtained after using the MOORA calculation method, there are 4 types of superior seed varieties that can be recommended for farmers, namely Taro Chili Seeds = 0.2875; Indrapura Chili Seeds = 0.2595 ; Lado Chili Seeds = 0.2490 ; Chili Seeds TM = 0.2154. By creating this decision support system, it is hoped that farmers will be able to use it as a reference in selecting superior chili seeds and be able to get maximum harvest results and increase commodity income for chili farmers.
DESIGN OF CONTROL SYSTEM AND TEMPERATURE IN COFFEE DRYER ARDUINO BASED AUTOMATIC USING FUZZY Ratu Mutiara Siregar; Budi Mulyara; Rahmad Dian; Maisarah Maisarah; Muhammad Akbar Syahbana Pane; Andi Prayogi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6166

Abstract

The coffee bean drying process is a crucial stage in ensuring the final quality of coffee products. Conventional drying methods, which rely on sunlight, face several challenges, such as dependence on weather conditions and prolonged drying times. This study proposes the design of a control and temperature system for an automatic coffee dryer based on the Arduino Mega 2560, aimed at enhancing the efficiency and consistency of the drying process. The system utilizes a semi-enclosed drying technology equipped with DHT22 temperature and humidity sensors, controlled by Arduino-Uno and Fuzzy Logic. This control system monitors temperature and humidity in real-time, maintaining the drying conditions at 55°C and 15% RH. If the temperature or humidity exceeds the set limits, the system activates an LED and buzzer alarm, indicating that the drying process has reached optimal conditions. The prototype was tested under various conditions, and the results demonstrate that the system has a high accuracy level in controlling temperature and humidity, significantly accelerating the drying process compared to traditional methods. By implementing this technology, the coffee industry in Indonesia is expected to achieve the Coffee Drying Operational Standards in accordance with SNI, maintain flavor quality, optimize the use of drying land, and reduce drying duration. This development offers an innovative solution that can enhance the quality and productivity of coffee processing, providing significant economic benefits to farmers and coffee industry stakeholders.
Identification of Tajweed Recognition using Wavelet Packet Adaptive Network based on Fuzzy Inference Systems (WPANFIS) Siregar, Ratu Mutiara; Satria, Budy; Prayogi, Andi; Pane, Muhammad Akbar Syahbana; Awal, Elsa Elvira; Sari, Yessi Ratna
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 1 (2024): Volume 4 Issue 1, 2024 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i1.703

Abstract

This research aims to develop a system capable of processing voice input to recognize Al-Quran reading by recitation of Tajwid, using wavelet signal extraction and classification of Tajwid rules using ANFIS. The process stages include data acquisition, audio data pre-processing, extraction using wavelet packets, division of training data and test data, and classification. The data obtained were 20 observations from 10 observations carried out in data pre-processing. The wavelet decomposition process produces six main features as ANFIS input variables and 64 rules. Then the data was separated into 17 observations for training data and three for testing data. The test results obtained from the training that had been carried out produced plots that were too fit; in this experiment, the WPANFIS classification model got 100% appropriate classification and SSE values that were the same as the training result, 0.00081225.
Sosialisasi Digital Marketing pada UMKM Keripik Selasih di Kelurahan Sentang, Kecamatan Kisaran Timur, Asahan Simbolon, Hasanal Fachri Satia; Pane, Muhammad Akbar Syahbana; Saleh, Khairul; Siregar, Ratu Mutiara; Prayogi, Andi; Sugianto, Raden Aris; Wahyuni, Ritna
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2025): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v4i1.906

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi masyarakat, termasuk di Kabupaten Asahan, Sumatera Utara. Salah satu UMKM yang berpotensi untuk dikembangkan adalah Keripik Selasih, yang memiliki produk unggulan namun masih mengalami kesulitan dalam pemasaran digital. Kurangnya pengetahuan dan keterampilan dalam memanfaatkan teknologi digital menjadi hambatan utama dalam memperluas jangkauan pasar. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan kapasitas pelaku UMKM Keripik Selasih dalam bidang digital marketing, melalui pelatihan yang mencakup penggunaan media sosial, pembuatan konten kreatif, dan pemanfaatan platform promosi daring. Metode pelaksanaan meliputi tahap persiapan, pelatihan tatap muka, praktik langsung, serta evaluasi hasil. Diharapkan melalui kegiatan ini, pelaku UMKM mampu memasarkan produk secara lebih efektif, memperluas jaringan konsumen, dan meningkatkan pendapatan usaha. Kegiatan ini juga menjadi bentuk kontribusi nyata mahasiswa dalam mendukung pemberdayaan ekonomi lokal melalui pendekatan teknologi informasi.
Co-Authors Abdussalam Al Akbar Alex Rizky Saputra Ali Ikhwan Alimuddin Yasin Alisarjuni Padang Aly, Moustafa H. Andi Prayogi Annisa Annisa Ardila Asnita Yani Awal, Elsa Elvira Balqis Nurmauli Damanik Budy Satria Busrizal Faisal Elfitra Fajar Maulana . Friska Anggraini Barus Guntoro, Guntoro Kan, Phak Len Al Eh Khairul Saleh Maisarah Maisarah Maisarah, Maisarah Makhrani Sari Ginting Maudy Hellena Harlyn Muhammad Akbar Syahbana Pane Muhammad Yusuf Dibisono Mulyara, Budi Navea, Roy Francis Prayogi, Andi Rahmad Dian Rahmad Dian Rahmad Dian Ritna Wahyuni Sari, Yessi Ratna Sepriano Sepriano Simbolon, Hasanal Fachri Satia Sri Wahyuna Saragih Tuty Ningsih Wisnu Ananta Kusuma Yasir, Amru