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MAPPING POTENTIAL REGION OF THE AGRICULTURAL SECTOR  AREA TO INCREASE ECONOMIC DEVELOPMENT IN PENAJAM PASER UTARA REGENCY Kumalawati, Rosalina; Pratomo, Rahmat Aris; Budiman, Puput Wahyu; Saputra, Erlis; Susanti, Ari; Rijanta, Rijanta; Raharjo, Jany Tri; Danarto, Wisnu Putra; Murliawan, Karnanto Hendra; Yuliarti, Astinana; Muhtar, Ghinia Anastasia; Anggraini, Rizki Nurita
International Conference On Social Science Education Vol 1 (2023): 1st International Conference On Social Science Education
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/9ms4w716

Abstract

Indonesia is an agricultural country and a developing country which has the potential for inequality in development. Inequality in development is increasingly felt in several areas, including Jakarta. As Jakarta becomes more densely populated with increasingly complex problems, there is talk of moving the nation's capital to East Kalimantan Province. North Penajam Paser Regency is one of the locations for moving the new national capital. It is hoped that the relocation can overcome population problems and development inequality. Developmental inequality will continue to occur if it does not receive serious attention. Development inequality can be overcome by paying attention to regional potential, especially in the agricultural sector. Seeing this, it is very necessary to carry out research with the title "Mapping Potential Region of the Agricultural Sector to Increase Economic Development in Penajam Paser Utara Regency". The research was conducted in Penajam Utara Paser Regency using quantitative research methods. The types of data used are primary data and secondary data. Data collection techniques include documentation, observation, interviews, and interview guides, while analysis techniques use Location Quotient (LQ) and Shift Share analysis. The research results show that the agricultural sector's production results are quite varied, from the production of rice, secondary crops, vegetables, and biopharmaceuticals. The highest production result was rice production reaching a total production of 65,534.9 tons over 10 years. Babulu District is the region that produces the largest rice with a total production of 56,688.1 tons over 10 years. Several types of plants have basic commodities so they have the potential to be developed to help improve the community's economy, even though their growth rate is relatively slow. The relatively slow growth rate for each existing commodity means that none of the agricultural sector's commodities are considered superior or mainstay commodities. As we know, the largest average contribution to GRDP comes from the mining and quarrying sector, like other areas in East Kalimantan that are famous for their natural resources, not the agricultural sector.
Distribusi Sebaran Hotspot Berdasarkan Data Modis Aqua Dan Terra untuk Deteksi Dini Kebakaran Kumalawati, Rosalina; Nugroho, Arief Rahman; Murliawan, Karnanto Hendra; Anggraeni, Rizky Nurita
Jurnal Penelitian Geografi (JPG) Vol 11, No 2 (2023): Jurnal Penelitian Geografi (JPG)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpg.v11i2.26787

Abstract

Hotspot dapat diketahui menggunakan bantuan teknologi penginderaan jauh yaitu satelit Terra/Aqua dengan bantuan sensor MODIS. Hotspot jumlah banyak dan memiliki tingkat kepercayaan tinggi memiliki potensi kebakaran. Dampak kebakaran cukup besar, sangat diperlukan adanya sistem deteksi dini, jadi penting dilakukan penelitian dengan judul “Distribusi Sebaran Hotspot berdasarkan Data MODIS Aqua dan Terra untuk Deteksi Dini Kebakaran”. Metode yang digunakan adalah analisis time series untuk mendapatkan informasi jumlah hotspot dari Citra Modis Aqua dan Terra tahun 2012-2019. Analisis untuk menemukan distribusi sebaran hotspot berupa titik koordinat yang di tumpang susun ke peta administrasi menggunakan Arc GIS. Hasil penelitian diketahui Kecamatan paling tinggi jumlah hotspotnya dari perekaman data Aqua dan Terra Modis adalah Kecamatan Candi Laras Utara; Jumlah hotspot paling banyak berada pada tingkat kepercayaan Tinggi dan Sedang sehingga dapat diketahui Kabupaten Tapin memiliki potensi tinggi terjadi kebakaran; dan Deteksi dini, koordinasi, kerjasama dan komunikasi dengan pemerintah pusat, daerah maupun swasta untuk meminimalkan korban jiwa dan harta benda akibat kebakaran.Kata kunci: Distribusi, Sebaran Hotspot, Modis aqua dan Terra, Deteksi Dini KebakaranDOI: http://dx.doi.org/10.23960/jpg.v11.i2.26787ReferencesA. Sandhyavitri, M. A. Perdana, S. Sutikno, and F. H. Widodo, “The roles of weather modification technology in mitigation of the peat fires during a period of dry season in Bengkalis, Indonesia,” in TALENTA-CEST, IOP Conf. 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University of Maryland.Giglio L, Schroeder W, Justice C O. (2016). The Collection 6 MODIS Active Fire Detection Algorithm and Fire Products. Remote Sensing of Environtment. 178: 21-34.Harmain, A., Paiman, P., Kurniawan, H., Kusrini, K., & Maulina, D. (2021). Normalisasi Data Untuk Efisiensi K-Means Pada Pengelompokan Wilayah Berpotensi Kebakaran Hutan Dan Lahan Berdasarkan Sebaran Titik Panas. TEKNIMEDIA: Teknologi Informasi dan Multimedia, 2(2), 83-89.Hamzah A.S., Darmawan, Sumawinata B., dkk., 2019.Spatial analysis of hotspot data for tracing the source of annual peat fires in South Sumatera, Indonesia. IOP Conf. Series: Earth and Environmental Science,393<doi:10.1088/1755-1315/393/1/012068>Handayani, Tri, Albertus Joko Santoso, dan Yudi Dwiandiyanta. 2014. Pemanfaatan Data Terra MODIS untuk Mengidentifikasi Titik Api pada Kebakaran Hutan Gambut (Studi Kasus Kota Dumai Provinsi Riau). Jurnal. Seminar Nasional Teknologi dan Komunikasi.Heryalianto, S. C. (2006). 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Yulianto, Evaluasi Hasil Estimasi Suhu Udara dari Data Satelit NOAA-18 AVHRR di Pulau Sumatera, Kalimantan dan Jawa. JAKARTA TIMUR: LAPAN, 2015. Accessed: Dec. 24, 2022. [Online]. Available: https://onesearch.id/Rec-ord/IOS4589.slims-4617Kumalawati, R., Nasruddin, N., & Elisabeth, E. (2019). Strategi penanganan hotspot untuk mencegah kebakaran di Kabupaten Barito Kuala, Kalimantan Selatan. In Prosiding Seminar Nasional Lingkungan Lahan Basah. 4(2): 351-356.Khairani, N. A., & Sutoyo, E. (2020). Application of k-means clustering algorithm for determination of fire-prone areas utilizing hotspots in West Kalimantan Province. International Journal of Advances in Data and Information Systems, 1(1), 9-16. DOI: 10.25008/ijadis. v1i1.13.(LAPAN) Lembaga Penerbangan dan Antariksa Nasional. 2016. Informasi Titik Panas (Hotspot) Kebakaran Hutan/Lahan. Jakarta. [LAPAN] Lembaga Penerbangan dan Antariksa Nasional. 2016. Informasi Titik Panas (Hotspot) Kebakaran Hutan/Lahan. Jakarta. Sumber Daring. 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SPATIAL DISTRIBUTION OF HOTSPOTS USING S-NPP VIIRS FOR EARLY DETECTION OF POTENTIAL FIRE Kumalawati, Rosalina; Dewi, Avela; Yuliarti, Astinana; Anggraini, Rizky Nurita; Murliawan, Karnanto Hendra
GeoEco Vol 9, No 1 (2023): GeoEco January 2023
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ge.v9i1.61379

Abstract

Fire is a disaster and its frequency is increasing every year. Seeing this, it is very important to know the spatial distribution of hotspots to determine the potential for fires in each area. Based on this, it is necessary to conduct research with the title "Spatial Distribution of Hotspots Using S-NPP VIIRS for Early Detection of Potential Fires". This research includes the type of descriptive research. The population in the study were all hotspots in Banjar Regency, South Kalimantan Province. Hotspots were taken from the results of the S-NPP VIIRS satellite imagery recording from 2012-2021. The number of samples is equal to the number of populations. The data analysis technique uses nearest neighbor analysis and descriptive analysis which is processed using Arc GIS software. The research results show that fires occur during the dry season, namely in July, August, September and October. Spatial distribution of hotspots from the results of S-NPP VIIRS satellite imagery based on the accuracy of the most confidence level in July, August, September and October. If the spatial distribution of hotspots is known, it can be used as an early detection effort. Early detection is carried out as an effort to prevent and control fires with a greater negative impact. In addition, with the existence of an early warning system, the community is better prepared to deal with fires so that the negative impacts that may arise due to fires can be minimized, including loss of life and property.