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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmu Komputer Jurnal INKOM Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi IJoICT (International Journal on Information and Communication Technology) Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING International Journal of Technology And Business Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Sistem Informasi Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital

Aniati Murni Arymurthy

Fakultas Ilmu Komputer, Universitas Indonesia

Author-ID : 234535

Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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PENERAPAN BASIS DATA CITRA PADA SISTEM PENCARIAN CITRA BERBASIS ISI: MENGGUNAKAN FASILITAS JAVA OBJECT SERIALIZATION DAN MENGGUNAKAN FASILITAS MYSQL Aniati Murni Arymurthy; Eliza Margaretha; Ade Azurat; Maruli Manurung
Jurnal Sistem Informasi Vol. 4 No. 1 (2008): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Makalah ini membahas dua pilihan penerapan struktur basis data citra pada sistem pencarian citra berbasis isi. Pendekatan pertama menggunakan folder untuk menyimpan berkas citra dan Java object serialization untuk menyimpan data citra. Pendekatan kedua menggunakan basis data Data Base Management System MySQL untuk menyimpan berkas dan data citra. Kedua pendekatan dibahas dari aspek penerapan struktur basis data untuk tujuan pengembangan sistem pencarian citra berbasis isi yang efisien. Data yang tidak terstruktur dan proses clustering data lebih mudah ditangani dengan struktur basis data dari pendekatan pertama. Data yang jumlahnya besar dan terstruktur serta proses indexing lebih mudah ditangani dengan struktur basis data dari pendekatan kedua. Sistem pencarian citra berbasis isi lebih banyak melakukan kueri jenis select dibandingkan dengan insert dan update data, dalam hal ini kedua pendekatan dapat memenuhinya dengan baik. Secara umum, pendekatan kedua dianggap memberikan dukungan yang baik dalam penyimpanan dan manipulasi data, serta dapat mengurangi upaya dan waktu yang dibutuhkan pada pengembangan sistem.

USULAN PENGEMBANGAN SISTEM BALITAROT UNTUK MENDUKUNG PERENCANAAN BERKELANJUTAN Andreas Febrian; Aniati Murni
Jurnal Sistem Informasi Vol. 5 No. 2 (2009): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Sistem pemerintahan di Indonesia pada saat ini masih berbasis kerja manual. Mekanisme ini mengakibatkan pembangunan di beberapa wilayah terabaikan. Selain itu, metode ini sering tidak didukung dengan standar pengerjaan yang jelas. Salah satu efek yang dirasakan adalah kurang terpenuhinya kebutuhan masyarakat. Permasalahan yang berbeda muncul di wilayah yang sudah dibangun dengan pesat. Pada daerah ini pengawasan dan peremajaan fasilitas yang sudah dibangun jarang sekali dilakukan. Hal ini memperpendek umur fasilitas tersebut. Hal-hal tersebut disebabkan karena perencanaan yang kurang matang dan tidak adaptif terhadap waktu. Penelitian ini mengusulkan sebuah sistem yang bernama Sistem BALITAROT (Perbaikan Lingkungan dan Tata Ruang Kota). Sistem ini dapat membantu pemerintah dan instansi terkait dalam menentukan kebijakan mengenai perbaikan lingkungan dan tata ruang kota. Government system in Indonesia is still based on manual work. These mechanisms lead to the development in some neglected areas. In addition, this method is often not supported by clear standards of work man ship. One effect that is felt is failed to fulfill community needs. Different problems arise in areas that have been built at a rapid pace. In this area, supervision and rejuvenation of facilities that already built is rarely done. It is shortening the life span of the facility. Those things are caused by unfinished planning and not adaptive to time. This study proposes a system called System BALITAROT (Restoration of Environment and City Layout). This system can help governments and relevant agencies in determining policy on environmental improvement and city layout.

ANALISIS TOPOLOGI DAN POPULASI PENDUDUK PEMUKIMAN MISKIN MENGGUNAKAN TEKNOLOGI REMOTE SENSING Aniati Murni Arymurthy; Edina Putri Purwandari
Jurnal Sistem Informasi Vol. 6 No. 1 (2010): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Wilayah perkotaan di Indonesia memiliki karakteristik yang sama dengan wilayah perkotaan di negara-negara berkembang. Beberapa karakteristik tersebut seperti: (1) penurunan fungsi alam dengan berkurangnya ruang hijau atau vegetasi, (2) penumpukan bangunan beratap pada wilayah yang dekat dengan akses transportasi, industri dan pasar, (3) lokasi pemukiman pada zona yang berbahaya karena dekat dengan terminal, sepanjang aliran sungai, sepanjang jalur rel kereta api, dan tempat pembuangan sampah akhir. Keterkaitan antara nilai indeks kemiskinan dengan morfologi fisik dan vegetasi suatu wilayah dapat diketahui dengan pemanfaatan teknologi remote sensing (RS). Keakuratan analisis pemukiman miskin dengan teknologi RS bergantung pada kualitas citra satelit Very High Resolution (VHR) dan kelengkapan dataset Sistem Informasi Geografis (SIG). Teknologi Geospasial yang terintegrasi seperti RS, SIG, dan Global Positioning System (GPS) dapat berkontribusi secara interaktif dalam penilaian, pemahaman dan pemetaan untuk memecahkan masalah pemukiman penduduk yang kompleks di Indonesia. Urban areas in Indonesia have the same characteristics with urban areas in developing countries. Some characteristics such as: (1) decreased of the function of nature with the reduced the number of natural green space or vegetation, (2) accumulation of roofed buildings in the area close to transportation access, industry and market, (3) the location of housing in the dangerous zone as close to the terminal, along the river side, along the railway lines, and the final waste disposal sites. The linkage between poverty index values with the physical morphology and vegetation of an area can be identified by the use of technology and remote sensing (RS). The accuracy of the analysis of poor housing with RS technology relies on the image quality of Very High Resolution (VHR) satellite and the completeness of the dataset Geographic Information Systems (GIS). Geo-spatial technologies are integrated as RS, GIS, and Global Positioning System (GPS) can contribute interactively in the assessment, understanding and mapping to solve the complex problem of residential in Indonesia.

Using Histogram Extracted From Satelite Imagery and Convolutional Network to Predict GRDP in Java Region Oemar Syarief Wibisono; Aniati Murni Arymurthy
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5092

Inequality is one of the problems faced by all countries in the world, including Indonesia. The data used to measure development inequality between regions mostly use GRDP data. However, the GRDP data issued by BPS has a deficiency, it was released after the current year, and this figure is provisional. Therefore, a new data source is needed that can be used to estimate the value of economic activity so that it can be used to measure the level of inequality in development in a region. Nighttime Light (NTL) satellite imagery data can be an alternative to see socioeconomic activity in an area and have been shown to have a strong correlation with socioeconomic activity. In this study, we used VIIRS NTL satellite imagery data and Dynamic World land cover data to estimate GRDP. Rather than using statistical features for each area of interest, we use features in the form of histograms extracted from NTL images and land cover images for each area of interest. Using a histogram, we do not lose spatial information from satellite imagery. Then we proposed a deep learning method in the form of a one-dimensional convolutional neural network using the Huber loss function. This model obtained good precision with an R-square value of 0.8549, beating the baseline method with two-dimensional convolutional networks. The use of the Huber loss function can improve the performance of the model, which has a smaller total loss and has a smoother gradient.

New Generation Indonesian Endemic Cattle Classification: MobileNetV2 and ResNet50 Ahmad Fikri; Aniati Murni
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.26659

Cattle are an essential source of animal food globally, and each country possesses unique endemic cattle races. However, categorizing cattle, especially in countries like Indonesia with a large cattle population, presents challenges due to costs and subjectivity when using human experts. This research utilizes Computer Vision (CV) for image data classification to address this urgent need for automatic categorization. The main objective of this study is to develop a mobile-friendly model using CV techniques that can accurately detect and classify Indonesian endemic cattle races, such as Limosin, Madura, Pegon, and Simental. To achieve this, an object localization approach is employed to extract multiple features from distinct regions of each cattle image, including the head, ear, horn, and muzzle areas. The authors evaluate two CV algorithms, ResNet50 and MobileNetV2, to assess their performance in cattle race classification. The dataset used is facial photos of 147 cows. The results indicate that ResNet50 outperforms MobileNetV2, achieving a training data accuracy of 83.33% compared to MobileNetV2's 77.08%. Moreover, the validation accuracy of ResNet50 (76.92%) significantly surpasses MobileNetV2's (38.46%). The novel contribution of this research lies in developing a cost-effective and efficient solution for identifying endemic cattle breeds in Indonesia. The mobile-friendly model based on ResNet50 demonstrates superior accuracy, enabling cattle farmers and researchers to categorize cattle races with higher precision, reducing manual effort, and minimizing costs. In conclusion, this research provides a valuable advancement in automatic cattle categorization using CV techniques. By offering a practical and accurate model that considers Indonesia's specific cattle breeding conditions, this study contributes to the sustainable management and conservation of endemic cattle races while enhancing the efficiency of cattle farming practices.

Triangular fuzzy number for similarity measurement of Y chromosome DNA profile Dewi, Meira Parma; Arymurthy, Aniati Murni; Setiawan, Suryana; Soedarsono, Nurtami
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5304

This study measures the similarity of the short tandem repeat (STR) profile of human DNA. The similarity measurement had been done to the STR value of the allele loci in DNA profile between the query’s DNA to the reference’s DNA profile. The measurements were conducted on 27 DNA profile loci including the Y chromosome loci (YSTR). The YSTR loci were used as the main comparison of similarity measurements to determine the biological kinship relationship between the query DNA profile and the alleged male biological family. To measure the similarity of two STR values that have shifted due to several factors in the DNA source extraction process, a fuzzy similarity measure was used. The STR values of the DNA profile loci are described as triangular fuzzy numbers. Similarity value of the STR is the intersection of two isosecle that been compared. To conclude that the query has a biological relationship with the male reference, the similarity of the YSTR locus is equal or more than 0.75 and the similarity value of the other 24 DNA profile loci is greater or equal to 0.5. From the trial that have been done, 90% give the right results.

Face Spoofing Detection using Inception-v3 on RGB Modal and Depth Modal Yuni Arti; Aniati Murni Arymurthy
Jurnal Ilmu Komputer dan Informasi Vol. 16 No. 1 (2023): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v16i1.1100

Face spoofing can provide inaccurate face verification results in the face recognition system. Deep learning has been widely used to solve face spoofing problems. In face spoofing detection, it is unnecessary to use the entire network layer to represent the difference between real and spoof features. This study detects face spoofing by cutting the Inception-v3 network and utilizing RGB modal, depth, and fusion approaches. The results showed that face spoofing detection has a good performance on the RGB and fusion models. Both models have better performance than the depth model because RGB modal can represent the difference between real and spoof features, and RGB modal dominate the fusion model. The RGB model has accuracy, precision, recall, F1-score, and AUC values obtained respectively 98.78%, 99.22%, 99.31.2%, 99.27%, and 0.9997 while the fusion model is 98.5%, 99.31%, 98.88%. 99.09%, and 0.9995, respectively. Our proposed method with cutting the Inception-v3 network to mixed6 successfully outperforms the previous study with accuracy up to 100% using the MSU MFSD benchmark dataset.

Forest and Land Fire Vulnerability Assessment and Mapping using Machine Learning Method in East Nusa Tenggara Province, Indonesia Wijaya, Hans Timothy; Arymurthy, Aniati Murni
Jurnal Ilmu Komputer dan Informasi Vol. 18 No. 1 (2025): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v18i1.1304

Forest and land fires are severe disasters for forest ecosystems, diminishing their functionality. Accurate prediction of fire-prone areas aids in effective management and prevention. Machine learning methods have shown promise in this regard. By 2022, East Nusa Tenggara (NTT) had the highest incidence of such fires. This study aims to assess NTT's forest and land fire vulnerability using seven machine learning methods: Gaussian Naive Bayes, Support Vector Machine, Logistic Regression, Artificial Neural Network, Random Forest, Gradient Boosting Machine, and Extreme Gradient Boost. A geospatial dataset integrating NTT's 2022 fire data and fourteen fire-related factors were created using ArcGIS. Feature selection, employing the Information Gain Ratio, identified nine key features: Degree of Slope, Land Cover, NDVI, Annual Rainfall, Distance to Road, Distance to River, Distance to Buildings, Wind Speed, and Solar Radiation. The Random Forest model emerged as optimal, with AUC values of 0.864 and 0.742 for training and testing, respectively. The resulting vulnerability map highlighted factors contributing to NTT's forest fires, including gentle slopes, forest cover, unhealthy vegetation, low rainfall, human activities, remote water access, soil moisture, distant firefighting facilities, low wind speeds, and high solar radiation. Recommendations include land management, fire-resistant vegetation, policy enforcement, community education, and infrastructure enhancement.

Enhancing Remote Sensing Image Quality through Data Fusion and Synthetic Aperture Radar (SAR): A Comparative Analysis of CNN, Lightweight ConvNet, and VGG16 Models Anggreyni, Desynike Puspa; Indriatmoko; Arymurthy, Aniati Murni; Setiyoko, Andie
JOIN (Jurnal Online Informatika) Vol 9 No 2 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i2.1321

Remote sensing technology benefits many parties, especially for carrying out land surveillance with comprehensive coverage without needing to move the equipment close to photograph the area. However, this technology needs to improve: the image quality depends on natural conditions, so objects such as fog, clouds, and smoke can interfere with the image results. This study uses data fusion techniques to enhance the quality of remote-sensing images affected by natural conditions. The method involves using Synthetic Aperture Radar (SAR) to combine adjacent satellite images from different viewpoints, thereby improving image coverage. Three image classification models were evaluated to process the fused data: Convolutional Neural Network (CNN), Lightweight ConvNet, and Visual Geometry Group 16 (VGG16). The results indicate that all three models achieve similar accuracy and execution speed, namely 0.925, with VGG16 demonstrating a slight superiority over the others, namely 0.90.

Indonesian License Plate Detection and Recognition System using Gaussian YOLOv7 Wijaya, Juan Thomas; Arymurthy, Aniati Murni
Jurnal Ilmu Komputer dan Informasi Vol. 18 No. 2 (2025): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v18i2.1320

In recent years, Automatic License Plate Recognition (ALPR) systems have garnered attention in computer vision research. However, practical applications face challenges such as inconsistent lighting, diverse license plate designs, and environmental variations, which increase the complexity of the task and lead to more false detections. To address these issues, we proposed Gaussian YOLOv7 for license plate detection and character recognition within ALPR systems, along with the Spatial Transformer Network (STN) for rectifying license plate orientation, aiming to enhance performance and adaptability to real-world scenarios. Additionally, we introduced a novel dataset for Indonesian ALPR systems to ensure robust detection and a balanced class distribution. Evaluation results indicate that Gaussian YOLOv7 improves precision and reduces false positives by 37.5% in the detection stage, albeit with poorer performance in other metrics. Conversely, the implementation of STN results in decreased character recognition accuracy, underscoring its limited effectiveness. Despite these challenges, Gaussian YOLOv7 excels in license plate rectification, achieving a recall of 83.8% and reducing false positives by 50.13% compared to YOLOv7. Moreover, post-processing techniques introduced by our approach further enhance precision by 5.3% and recall by 1%. Overall, our approach offers promising advancements in Indonesian ALPR systems, addressing fundamental challenges and enhancing performance.

Co-Authors Achmad Nizar Hidayanto Ade Azurat Ade Azurat Agus Harjoko Ahmad Fikri Ahmad Sutanto Ahmad Sutanto, Ahmad Andie Setiyoko, Andie Andreas Febrian Anggreyni, Desynike Puspa Bambang Trisakti Bambang Trisakti Chahyati, Dina Desta Sandya Prasvita Devi Fitrianah Edina Putri Purwandari Edina Putri Purwandari Edina Putri Purwandari Edward Citrahadi Edy Winarno Eliza Margaretha Eliza Margaretha Eliza Margaretha Fanany, M. Ivan Fanany, Mohamad Ivan Fauzan Muhammad Febri Maspiyanti Herwanto Herwanto Hisar Maruli Manurung Hisyam Fahmi I Gusti Agung Gede Arya Kadyanan Indriatmoko Intan Nurma Yulita, Intan Nurma Irham Muhammad Fadhil Ivan Fanany Kardawi, Muhammad Yusuf Katmoko Ari Sambodo LM Rasdi Rere LM Rasdi Rere Mahdi Kartasasmita Manurung, Hisar Maruli Manurung, Maruli Margaretha, Eliza Maruli Manurung Maruli Manurung Maruli Manurung Maspiyanti, Febri Meira Parma Dewi Mohamad Ivan Fanany Mohamad Ivan Fanany Muhamad Soleh Muhammad Iqbal Izzul Haq Nurtami Soedarsono Oemar Syarief Wibisono Pang Ning-Tan Persada, Bayu Satria Purwandari, Edina Putri Rahadianti, Laksmita Ratih Dewanti Retno Kusumaningrum Rian Josua Masikome Saragih, Frederic Morado Sesa Wiguna Setiawan, Suryana Sri Hartati Wijono Sunarno Sunarno Susanto, Muhammad Rifqi Priyo Tieta Antaresti Vina Ayumi Wahyudi - Wijaya, Hans Timothy WIJAYA, JUAN THOMAS Winarko, Edi Yohanes Gultom Yuni Arti

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