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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Geography Geo Media: Majalah Ilmiah dan Informasi Kegeografian Ecotrophic, Journal of Environmental Science Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Jurnal Ilmu Lingkungan TELKOMNIKA (Telecommunication Computing Electronics and Control) Majalah Geografi Indonesia JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Geografi International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal IMPACT: Implementation and Action GEOGRAPHY : Jurnal Kajian, Penelitian dan Pengembangan Pendidikan Indonesian Journal of Earth Sciences Jurnal Teknik Industri Priviet Social Sciences Journal Jurnal Geografi LIngkungan Tropik (Journal of Geography of Tropical Environments) The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Muhammad Dimyati
Universitas Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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ILLEGAL OIL MINING DETECTION THROUGH REMOTE SENSING IN MUSI BANYUASIN REGENCY, SOUTH SUMATRA, INDONESIA Setiadi, Restu; Supriatna; Dimyati, Muhammad; Arsyad, Ibrahim
International Journal of Remote Sensing and Earth Sciences Vol. 21 No. 2 (2024)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/ijreses.v21i2.13244

Abstract

Illegal oil mining activities present significant environmental, economic, and regulatory challenges, particularly in resource-abundant regions that are difficult to monitor such as Musi Banyuasin Regency in South Sumatra. This study applied an integrated method that combines drone-based remote sensing, visual interpretation, and spatial statistical analysis to detect, map, and evaluate the spatial distribution of illegal shallow oil wells. High-resolution aerial imagery was acquired using DJI Phantom 4 Pro drones, processed into orthomosaic images, and interpreted visually to identify suspected well locations. A total of 2664 illegal oil wells were identified and georeferenced. The results of spatial autocorrelation analysis using Moran’s I indicated a clustered distribution pattern, with significant concentrations found in subdistricts such as Lawang Wetan, Batang Hari Leko, and Tungkal Jaya. The Moran’s I index value of 0.652075 confirmed a statistically significant spatial clustering. Ground validation was conducted through direct field surveys, which verified the presence of the wells and provided supporting photographic documentation and GPS coordinates. The dataset was also compared with official records of legal oil wells to ensure accuracy and distinction between legal and illegal infrastructure. The findings demonstrate that unmanned aerial vehicle-based spatial analysis offers a reliable and scalable solution for monitoring unregulated extraction activities. This approach supports data-driven enforcement, enhances environmental oversight, and informs the development of more effective regulatory policies in regions impacted by informal oil production.
Perancangan Sistem Perencanaan Produksi Berbasis Web untuk Peramalan, Bill of Materials, dan Material Requirements Planning Dimyati, Muhammad; Abiyyu, Ahmad Syaqib; Angga, Angga; Saputra, Angga Jevvika; Syahliantina, Annisa
JURNAL TEKNIK INDUSTRI Vol. 6 No. 02 (2025): JURNAL TEKNIK INDUSTRI : NOVEMBER 2025
Publisher : DPPM UNIVERSITAS PELITA BANGSA

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Abstract

Perkembangan transformasi digital mendorong perlunya sistem perencanaan produksi berbasis web. Penelitian ini bertujuan untuk merancang sebuah sistem web bernama PT Empat Bersaudara yang berfungsi untuk perhitungan Peramalan (Forecasting), Bill of Materials (BOM), dan Material Requirements Planning (MRP). Sistem perhitungan pada web menggunakan tiga metode peramalan, yaitu Moving Average (MA), Weighted Moving Average (WMA), dan Single Exponential Smoothing (SES), bertujuan untuk menganalisis enam periode peramalan dengan metode terbaik yang digunakan. Perancangan dilakukan menggunakan pendekatan User-Centered Design (UCD) dan alat bantu Visual Studio Code untuk pengeditan kode pemrograman. Aplikasi dirancang mencakup fitur dashboard, forecast, data/BOM, MRP, dan fitur tambahan seperti: Produksi dan Log. Hasil penelitian membuktikan bahwa perancangan web untuk perhitungan Forecasting, BOM, dan MRP dalam satu platform mampu meningkatkan akurasi, mengurangi human error, mempercepat proses perencanaan, dan meningkatkan efisiensi pengelolaan persediaan. Sistem ini dinilai sebagai solusi yang praktis dan efektif bagi perusahaan manufaktur untuk memenuhi tantangan era digital dan Industri 5.0.
Harnessing artificial intelligence for census in Nigeria: Advancing accuracy, efficiency, and governance outcomes Inuwa Sani Sani; Muhammad Dimyati; Aliyu Aminu Umar
Priviet Social Sciences Journal Vol. 5 No. 11 (2025): November 2025
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v5i11.662

Abstract

Successful administration of national censuses in Nigeria has been a protracted agony plagued by inherent problems, including logistic, political, and methodological issues, which cumulatively have caused delays in enumeration, undercounting, and inconsistency of data. These defects diminish the credibility of demographic data needed for evidence-based governance, economic planning, and equitable resource allocation._. In this study, we explored opportunities for harnessing Artificial Intelligence (AI) to transform census activities in Nigeria through the injection of state-of-the-art computational approaches into the national enumeration exercise. We showcased a multimodal AI pipeline comprising Convolutional Neural Networks (CNNs) for population density estimation from satellite images, Natural Language Processing (NLP) pipelines for address standardization and matching in various languages, and unsupervised anomaly detection algorithms for real-time data quality verification. AI-based enumeration methods were simulated at both national and sub-national levels. CNN-generated heatmaps revealed population concentration trends in Lagos and other states and enabled the precise delineation of high-density urban agglomerations and underserved rural enclaves. The NLP tool generalized well to the linguistically diverse environments in Nigeria, with F1-scores greater than 0.90 for all but a few states for broken address reconciliation. Anomaly detection models built using Isolation Forest algorithms detected anomalous enumeration patterns as flags for potential undercounts or data manipulation. Population pyramid analysis for Lagos revealed an extremely young population structure, consistent with country-wide age trends. These findings provide empirical evidence that AI integration can promote census accuracy, operational efficiency and government effectiveness in Nigeria.
Co-Authors Abiyyu, Ahmad Syaqib Adlyani Husna Ahmad Fakhruddin Ahmad Zubair Akhmad Fauzy Aliyu Aminu Umar Anang Muchlis Andry Rustanto Angga Angga Anggara Setyabawana Putra Arief Wicaksono Arsyad, Ibrahim Ash Shidiq, Iqbal Putut Astrid Damayanti Astridia Putri Nurhaliza Azis Musthofa Azzahra, Rifdah Octavi Babag Purbantoro Bawiling, Hendry Budianto Budianto Devy Nur Annisa Dewi Susiloningtyas Dimas Bayu Ichsandya Dimas Novandias Damar Pratama Dimyati, Ratih Dewanti Efriana, Anisya Feby Enshito, Grizzly Pradipta Singhasana Evi Anggraheni, Evi Fadhilah, Raina Arfa Farhan Makarim Zein Faris Zulkarnain Faris Zulkarnain Garniwa, Pranda Mulya Gracia, Enrico Hartono Hartono Hartono Hartono Heinrich Rakuasa I Wayan Gede Krisna Arimjaya Inuwa Sani Sani Irma Susanti Isnaini, Eva Nur Khairunnisa, N Kintan Maulidina Kustiyo Kustiyo Kustiyo Kustiyo Legowo, Dewanti Aisyah Logan, Axel Gilbert M. Martono Mamat Suhermat Maranti, Pinta Mardalena, Ayu Marfai, Muh Aris Masita Dwi Mandini Manesa MASITA DWI MANDINI MANESSA, MASITA DWI MANDINI Muhamad Rafli Muhammad Adnan Shafry Untoro Muhammad Haidar Noer, Marwah Nurrokhmah Rizqihandari Nurul Khakhim Nurul Sri Rahatiningtyas Onki Alexander Panji Nurul Achmadi Pranita Giardini Prasetya, Ferdian Adhy Projo Danoedoro Pryanto, Muhammad Bagus Puji Tri Handayani Purbantoro, Babag Putri, Ratih Fitria Raden Ramadhani Yudha Adiwijaya Rahatiningtyas, Nurul Sri Raisya Afifah Ratih Dewanti Ratih Dewanti Dimyati Ratih Dewanti Dimyati Ratih Dewanti Dimyati Ratri Candra Restuti Riza Putera Syamsuddin Rustanto, Andry S. Supriatna Sakina, N C Sani, Inuwa Sani Saputra, Angga Jevvika Satria Indratmoko Setiadi, Hafid Setiadi, Restu Siddiq, Ayyasy Siswanto Siswanto Siti Aisyah Supriatna Supriatna Supriatna Syahliantina, Annisa Taufik Walinono Tito Latif Indra Triarko Nurlambang Triarko Nurlambang Tuty Handayani Umar, Aliyu Aminu Verdyansyah, Aprizal Wahyu Lazuardi Zubair, Ahmad Zulfikri Isnaen Zulkarnain, Faris