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All Journal International Journal of Advances in Data and Information Systems Jurnal Multidisiplin Indonesia
Pindarwati, Atut
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Computer Science & IT Education Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Veterinary

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Implementasi Penggunaan Cctv Berbasis Internet Of Things (Iot) Sebagai Smart Security Untuk Menanggulangi Angka Kejahatan Studi Kasus: Smk Insan Cita Pindarwati, Atut; Nurfebrian, Adji; Ray H, Bobby; Hidayat, Rian; Salsabillah, Al Mahira; MilaFikriyah, MilaFikriyah; Dwiyanti, Rosyidah; Anisa, Sofi; Damayanti, Elisa; I. L, Stefanus; Nurfiqih, Nurfiqih
Jurnal Multidisiplin Indonesia Vol. 1 No. 2 (2022): Jurnal Multidisiplin Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jmi.v1i2.45

Abstract

BPS (Badan Pusat Statistik) Indonesia mencatat setidaknya jenis kejadian pencurian merupakan kejahatan yang paling banyak terjadi pada sektor desa/kelurahan di Indonesia, jumlahnya mencapai lebih dari 36-45 persen dari seluruh desa/kelurahan sepanjang tahun 2010-2018 dan tercatat setidaknya di era pandemi covid-19 kenaikan persentase angka kejahatan sebesar 23,46 persen meningkat jika dibandingkan dengan tahun sebelumnya. Pentingnya strategi yang tepat yang mampu menanggulangi angka kejahatan tersebut, melalui pemberian edukasi kepada kaum muda di Indonesia. Pada penelitian ini fokus untuk upaya menanggulangi angka kejahatan dengan menggunakan CCTV berbasis IoT (Internet of Things) dengan keunggulan yang memiliki tingkat sekuritas tinggi dan pintar, serta terhubung aplikasi di smartphone yang dapat diakses kapanpun dan dimanapun. Kelebihan dari teknologi ini yang tidak dapat dijumpai di CCTV pada umumnya yakni memiliki fitur pencegahan aktif, dengan lampu sorot internal dan suara sirine keamanan 110 dB menakuti orang asing yang tidak diinginkan sebelum memasuki area. Kemudian deteksi PIR mengurangi peringatan palsu, mampu mengikuti objek yang bergerak, serta kecanggihan kamera, jaringan, antarmuka, video dan audio yang dilengkapi deteksi manusia,wilayah yang dapat dikonfigurasi dan alarm suara tidak normal. Mampu memberikan gambar yang jelas saat malam hari. Perangkat ini juga mengirimkan peringatan instan ke smartphone setiap mendeteksi gerakan, membuat user tetap mengetahui apa yang terjadi dari mana saja. Speaker dan mikrofon internal adalah fitur komunikasi dua arah memungkinkan berinteraksi dengan hewan peliharaan ataupun untuk menghalangi tamu yang tidak diinginkan. Semua hasil tangkapan tadi terhubung langsung ke penyimpanan cloud secara otomatis. Dalam Penelitian ini menerapkan manfaat dengan ruang lingkup di SMK Insan Cita, Jakarta, Indonesia.
Integrating Satellite Imagery and Multicriteria Decision Analysis for High-Resolution Flood Vulnerability Mapping: A Case Study of Jakarta, Indonesia Pindarwati, Atut; Wijayanto, Arie Wahyu; Rosyani, Perani; Maghfiroh, Meilinda F. N.
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1388

Abstract

Jakarta, Indonesia, ranks among the most flood-prone megacities in the world, with hydrometeorological factors placing up to 98% of its area at flood risk. Its population density—approximately 15,900 individuals per square kilometer—compounds the impacts of flooding through intensified exposure and socio-economic vulnerability. This study presents a novel, data-driven methodology for flood vulnerability assessment in the Jakarta Special Capital Region (DKI Jakarta), integrating satellite remote sensing and geospatial analysis with a Multicriteria Decision Analysis (MCDA) framework. Employing the Analytical Hierarchy Process (AHP) to systematically weight environmental and socio-economic criteria, a Flood Vulnerability Index (FVI) was developed and spatially modeled at a 500-meter grid resolution. The resulting FVI map categorizes vulnerability into five levels: very low, low, moderate, high, and very high. Findings indicate an index range between 0.36 and 0.70, highlighting predominantly moderate to high vulnerability zones across the region. This high-resolution assessment provides actionable insights for disaster risk reduction, urban resilience planning, and targeted policy interventions to mitigate flood-related hazards in Jakarta.
Automated Oil Palm Health Assessment Using Object-Based Deep Learning and High-Resolution UAV Imagery in Indonesia Pindarwati, Atut; Wijayanto, Arie Wahyu; Karmawan, I Putu Agus; Yeza, Ardhan; Sakka, Asriadi
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1391

Abstract

Indonesia, as the world’s largest crude palm oil (CPO) producer, faces challenges in plantation monitoring due to reliance on manual data collection methods that are time-consuming, costly, and prone to human error. This study proposes an automated approach for assessing oil palm tree health using high-resolution UAV imagery (5–10 cm) and object-based deep learning models. We evaluate five state-of-the-art detectors—YOLOv5s, Faster R-CNN, Mask R-CNN, SSD, and RetinaNet—to classify individual trees into four health categories: Healthy, Moderately Healthy, Needs Improvement, and Urgent Condition. Using a dataset of 14,749 labeled trees from Kendawangan, Indonesia, YOLOv5s achieved the highest performance with a precision of 0.784, recall of 0.752, and mAP of 0.764. Our findings demonstrate the potential of AI-driven monitoring to enhance plantation management through rapid, accurate, and cost-effective health assessments—contributing a scalable solution to support precision agriculture and sustainable CPO production.
Co-Authors Anisa, Sofi Arie Wahyu Wijayanto Damayanti, Elisa Dwiyanti, Rosyidah I. L, Stefanus Karmawan, I Putu Agus Maghfiroh, Meilinda F. N. MilaFikriyah, MilaFikriyah Nurfebrian, Adji Nurfiqih, Nurfiqih Perani Rosyani Ray H, Bobby Rian Hidayat Sakka, Asriadi Salsabillah, Al Mahira Yeza, Ardhan