Suhartono Suhartono

State University of Makassar

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Co-Authors

Sri Mulyaningsih

Institut Sains & Teknologi Akprind Yogyakarta

Dina Tania

Institut Sains & Teknologi Akprind Yogyakarta

Nur Widi Astanto Agus Tri Heriyadi

Institut Sains & Teknologi Akprind Yogyakarta

Achmad Syafiuddin

Universitas Nahdlatul Ulama Surabaya

Heri Kuswanto

Sepuluh Nopember Institute of Technology

Ahmad Beng Hong Kueh

Universiti Malaysia Sarawak

Tony Hadibarata

Curtin University Sarawak

Nurwidi Astanto Agus Tri Heriyadi

Institut Sains & Teknologi Akprind Yogyakarta

Riefki Chiesa Athella

Moch Romli

Direktorat Jenderal Peternakan dan Kesehatan Hewan

Cooperative Institutions

National Research and Innovation Agency

National Nuclear Energy Agency of Indonesia

Badan Pengkajian dan Penerapan Teknologi

Badan Pusat Statistik

Sepuluh Nopember Institute of Technology

University of Indonesia

Indonesian Agency for Agricultural Research and Development

Badan Penelitian dan Pengembangan Kesehatan

University of Technology Malaysia

Institut Sains & Teknologi Akprind Yogyakarta

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Implementation of Convolutional Neural Network Algorithm for Detecting Empty Parking Area Based on Raspberry Pi

Jurnal E-Komtek (Elektro-Komputer-Teknik) (2024)

Suhartono Suhartono Satria Gunawan Zain Ayu Futri Sadaruddin

This study aims to implement a convolution neural network algorithm to detect empty parking areas based on Raspberry Pi 4 and use the Convolutional Neural Network (CNN) method of the YOLO V5 model. This research consists of several stages, starting from the potential and problem stages, needs analysis, literacy studies, building prototypes, system design, and system testing. The datasets collected were taken using smartphone cameras and webcams with a total of 645 image datasets which were divided into two categories, namely training data and validation. System testing is carried out in two conditions, namely during the day and at night. The results of the detection test for observing variations in the position of filled and unfilled vehicles obtained the highest average accuracy during daytime conditions, while for observing cars entering and leaving the parking lot during day and night conditions, the results were the same percentage of success.

Raspberry Pi

10.37339/e-komtek.v8i1.1220

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Opportunities and Challenges for Sustainable Bioremediation of Natural and Synthetic Estrogens as Emerging Water Contaminants Using Bacteria, Fungi, and Algae

Water Air & Soil Pollution (2021)

Anisa Ratnasari Achmad Syafiuddin Ahmad Beng Hong Kueh Suhartono Suhartono Tony Hadibarata

10.1007/s11270-021-05183-3

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Citations (19)

IDENTIFIKASI JELAJAH GEOLOGI GUNUNG API PURBA GUNUNG IRENG DESA PENGKOK, KABUPATEN GUNUNGKIDUL

Jurnal Pariwisata (2019)

Sri Mulyaningsih Nur Widi Astanto Agus Tri Heriyadi Dina Tania Suhartono Suhartono

Gunung Ireng di Desa Pengkok adalah destinasi wisata baru geologi gunung api purba di Kecamatan Patuk, Kabupaten Gunungkidul, di samping Gunung Nglanggeran. Selain aglomerat, sebagaimana penciri geologi Gunung Api Purba Nglanggeran, breksi vulkanik, lava bersruktur meniang, dike, dan blocky lava berkomposisi andesit menyusun Gunung Ireng. Makalah ini disusun untuk mengidentifikasi kealamian jelajah alam geologi gunung api purba Gunung Ireng sebagai destinasi wisata minat khusus geowisata. Metode yang digunakan adalah studi dan analisis konektivitas Gunung Ireng terhadap destinasi-destinasi wisata lain di sekitarnya dan identifikasi keragaman data geologinya. Penelitian menjumpai morfologi bukit melingkar berbentuk kubah, yang dikelilingi lembah berslope ~30-55o yang melandai ke baratlaut. Dari atas bukit terlihat Gunung Wayang (Nglanggeran di ujung timur), karst Selopamioro di arah selatan, Sudimoro di arah barat dan tinggian Patuk di sebelah utara. Jalur konektivitas telah menghubungkan Gunung Ireng dengan Gunung api Nglanggeran-Oro-Oro, Dlingo, Selopamioro dan Kali Ngalang-Gedangsari. Promosi dan dukungan sepenuhnya dari pemerintah Kabupaten Gunungkidul, serta optimisme pengelola adalah kunci keberhasilan Gunung Ireng untuk disejajarkan dengan destinasi-destinasi wisata minat khusus lain di sekitarnya; mendukung keberlanjutan Geopark Gunung Sewu.

Geopark

10.31311/par.v6i2.6162

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IMPLEMENTASI PROGRAM KEUANGAN BERKELANJUTAN DALAM UPAYA MITIGASI RISIKO BENCANA DAMPAK TSUNAMI MELALUI PERLUASAN HUTAN MANGROVE

EJOIN Jurnal Pengabdian Masyarakat (2023)

Rukaesih A. Maolani Achmad Sudiyar Dalimunthe I Made Indra Antonius Anton Lie Suhartono Suhartono

Implementasi program keuangan berkelanjutan dalam upaya mitigasi risiko bencana dampak tsunami melalui perluasan hutan mangrove dengan beberapa langkah: (1). Mitigasi bencana; (2). Penilaian Risiko Bencana; (3). Implementasi program pembiayaan berkelanjutan; dan (4). Perluasan hutan bakau;(5). Kegiatan PKM. Mengingat kegiatan penanaman bibit pohon Mangrove Menerapkan program keuangan berkelanjutan untuk memitigasi risiko bencana tsunami melalui perluasan hutan mangrove melibatkan beberapa langkah. Berikut adalah beberapa kemungkinan langkah yang dapat diambil: (1). Mengembangkan peta jalan keuangan berkelanjutan; (2). Prioritaskan program keuangan berkelanjutan; (3). Mengembangkan kapasitas internal; (4). Melibatkan pemangku kepentingan; (5). Pantau dan evaluasi program. Hasil dari kegiatan pengabdian kepada masyarakat ini dapat mencakup pelacakan dampak program terhadap konservasi dan restorasi mangrove, serta penyerapan produk dan layanan keuangan berkelanjutan antara lain: (1). Berhasilnya pelaksanaan penanaman bibit Mangrove sebanyak 2.500 pohon di lokasi Elang Laut Muara Angke Jakarta Utara; (2). Terjalinnya Kerjasama yang saling menguntungkan antara Perguruan Tinggi dengan pihak di luar Perguruan Tinggi terutama dengan perusahaan-perusahaan Asuransi dalam melakukan kegiatan Mitigasi Risiko dampak dari “Pemanasan Global “dan “Perubahan Iklim”.

10.55681/ejoin.v1i8.1437

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Pengusulan dan Asesmen Kawasan Cagar Alam Geologi Gunung Ireng, Pengkok, Gunungkidul

JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) (2022)

Sri Mulyaningsih Nur Widi Astanto Agus Tri Heriyadi Dina Tania Suhartono Suhartono

Kegiatan pengabdian kepada masyarakat ini membantu POKDARWIS Dusun Srumbung, Desa Pengkok, Kecamatan Patuk, Kabupaten Gunungkidul menyusun usulan destinasi wisata Gunung Ireng sebagai Kawasan Cagar Alam Geologi (KCAG). Melalui kajian sebelumnya, Gunung Ireng telah diidentifikasi sebagai kawah purba gunung api. Kekhususan Gunung Ireng adalah sebagai kepundan berumur Tersier yang terletak di bawah dasar laut. Tujuan pengabdian adalah untuk meningkatkan frekuensi dan intensitas kunjungan wisatawan. Metode pengabdian adalah dokumentasi, pendaftaran dan proses asesmen. Pendaftaran Gunung Ireng sebagai KCAG telah dilakukan secara daring melalui http://kcag.pag.geologi.esdm.go.id/index.php/trxp/-c_status/list_status_ajax, pada November 2019. Pra-asesmen dilakukan oleh pemerintah daerah tingkat Provinsi dan Kabupaten pada tanggal 20 Februari 2020. Asesmen telah dilakukan pada tanggal 27 Februari 2020 dengan tim asesor terdiri atas Tim Verifikator KCAG Badan Geologi (Direktorat Energi dan Sumber Daya Mineral) dan Tim Pendamping Akademik Universitas Pembangunan Nasional “Veteran”. Tuan Rumah KCAG Gunung Ireng terdiri atas Tim Pengabdi, Provinsi DIY (terdiri atas wakil Dinas Pariwisata dan Administrasi Pemerintahan SETDA DIY), Kabupaten Gunungkidul, Camat Patuk, Lurah Desa Pengkok dan Pengelola dan POKDARWIS Gunung Ireng. Dokumen yang telah disiapkan meliputi data hasil identifikasi geologi gunung api purba Gunung Ireng, daftar fasilitas pemanfaatan KCAG sebagai destinasi geowisata dan ekowisata, dokumen POKDARWIS dan kegiatan pariwisata yang telah dikelola, dan dokumen tata kelola dan organisasi Gunung Ireng. Hasil verifikasi dikatakan spektakuler dan telah diumumkan, kini menunggu Surat Keputusan Kementerian Sumber Daya Mineral dan Energi.

10.30595/jppm.v6i1.7024

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Social vulnerability to natural hazards in Indonesia: driving factors and policy implications

Natural Hazards (2013)

Tiodora Hadumaon Siagian Purhadi Purhadi Suhartono Suhartono Hamonangan Ritonga

Natural hazard

Social vulnerability

Vulnerability

Preparedness

10.1007/s11069-013-0888-3

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Citations (218)

Removal of Silver Nanoparticles from Water Environment: Experimental, Mathematical Formulation, and Cost Analysis

Water Air & Soil Pollution (2019)

Achmad Syafiuddin Salmiati Salmiati Tony Hadibarata Mohd Razman Salim Ahmad Beng Hong Kueh

10.1007/s11270-019-4143-8

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Citations (31)

GUNUNG IRENG MENUJU KAWASAN CAGAR ALAM GEOLOGI (KCAG)

Dina Tania Sri Mulyaningsih Nurwidi Astanto Agus Tri Heriyadi Suhartono Suhartono

The potential of Mount Ireng is not only a beautiful romance on the face of the earth, butalso the geological peculiarity of the facies of ancient volcanic centers based on the volcanic and volcanic rocks spread over 7 (seven) clusters in the form of andesitic blocky lava, andesitic lava, massive andesitic lava and basaltic andesite lava cushions scattered in 7 (seven) clusters in the form of blocky andesitic lava, andesitic lava, massive andesitic lava and basaltic andesite lava cushions spread over 7 (seven) clusters in the form of blocky andesitic lava, andesitic lava lava, massive andesitic lava andesite dike with the presence of pyrite and sulfur minerals which are carried by andesitic breccias and agglomerates, besides being supported by tourism potential as the location of the best sunrise in Yogyakarta. This became the foundation taken by the Gunung Ireng Geotourism Academic Advisory Team from IST AKPRIND Yogyakarta in the form of submission of Mount Ireng to a Geological Nature Reserve (KCAG) in order to increase the development of sustainable community-based geotourism management concepts.Verification is carried out through geological observations by exploring 7 (seven) clusters from the top to the foot of Mount Ireng to verify 53 Assessment Matrices including Criteria, Comparisons, Classifications (Scientific Values, Education and Tourism), Threat of Damage / Risk of Degradationand Utilization Recommendations. Hope is Mount Ireng, in the Srumbung Hamlet, Pengkok Village, Patuk Subdistrict, Gunung Kidul Regency, Special Region of Yogyakarta, which is believed to be the Ancient Volcanic Center Faces can become a Geological Nature Reserve Area (KCAG).

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The comparison of Bayesian model averaging with gaussian and gamma components for probabilistic precipitation forecasting

AIP conference proceedings (2019)

Defi Yusti Faidah Heri Kuswanto Suhartono Suhartono

Ensemble forecasting has relatively good predictive abilities, especially in the field of climatology. However, the results of ensemble predictions are often underdispersive or overdispersive. Therefore, it is necessary to calibrate the ensemble forecasting. The Bayesian model averaging (BMA) method with gaussian or gamma distribution is commonly used to calibrate ensemble forecasting. This research reveals that there have been extreme precipitation in the observed periods. This has an impact on the pattern of rainfall that is asymmetric but has a longer tail on one side. This research examined the monthly rainfall data in Juanda Station in East Java Province generated by the North American Multi-Model Ensemble (NMME) models and further calibrated them with BMA. The purpose of this research is to assess the performance of the calibration results using the BMA Gaussian and Gamma. Both calibration results were evaluated using the continuous range probability score (CRPS) and the percentage of captured observations. The calibration with BMA Gaussian produced an average CRPS of 8.27 with 58.16% coverage, while with BMA-Gamma an average CRPS of 7.23 with 62.11% coverage was obtained. This result suggests using BMA-Gamma to generate more accurate probabilistic forecasts.

Ensemble forecasting

Probabilistic Forecasting

10.1063/1.5139173

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Citations (3)

Ensemble method based on ARIMA-FFNN for climate forecasting

Bambang Widjanarko Otok Dwi Ayu Lusia Suhartono Suhartono Ria Faulina Sutikno Sutikno

Ensemble forecasting is one of relatively new modern methods for time series forecasting that employs averaging or stacking from the results of several methods. This paper focuses on the development of ensemble ARIMA-FFNN for climate forecasting by using averaging method. Two data about monthly rainfall in Indonesia, i.e. Wagir and Pujon region, are used as case study. Root mean of squares errors in training and testing datasets are used for evaluating the forecast accuracy. The results of ensemble ARIMA-FFNN are compared to one classical statistical method, i.e. individual ARIMA, and two modern statistical methods, namely individual FFNN and ensemble FFNN. The results show that ARIMA yields more accurate forecast in training datasets than other methods, whereas in testing datasets show that FFNN is the best method. Additionally, this conclusion in line with the results of M3 competition, i.e. modern methods or complex methods do not necessarily produce more accurate forecast than simpler one.

Ensemble Learning

Ensemble forecasting

Moving average

10.1109/icssbe.2012.6396565

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Citations (3)