Khursatul Munibah’s research while affiliated with IPB University and other places

The destruction of rice fields due to changes in their use in various regions of Indonesia affects the national food supply. In the long term, this phenomenon will threaten efforts to fulfill the adequacy of rice and increase the potential for a food crisis. This study analyzes the decline in domestic rice sufficiency due to destroying rice fields in the Banyumas Regency. This study was conducted using spatial modeling and the Micmac method. Respondents and experts were purposively determined based on the roles of 50 respondents and seven experts. The findings revealed that, on average, 103 hectares of rice fields in the Banyumas Regency were lost annually between 2007 and 2019. In 2045, it is estimated that the area of rice fields in Banyumas Regency will be 29,160 hectares, with a conversion rate from 2019 to 2045 of 1,384 hectares. Several driving factors are distance from the district capital, distance from roads, distance from settlements, distance from the irrigation channel, and population density. The essential factors influencing rice self-sufficiency include enforcing rice field preservation regulations, incentivizing measures for protecting rice fields, comprehensive spatial data on rice fields, sufficient access to irrigation water, proactive engagement of farmer collectives, and level of rice productivity.

Konversi lahan pertanian menjadi lahan terbangun merupakan salah satu faktor yang menyebabkan penurunan produksi padi di Kabupaten Majalengka dan Provinsi Jawa Barat. Sektor pertanian masih memainkan peran penting dalam perkembangan ekonomi lokal yang ditunjukkan dengan PDRB sektor pertanian, kehutanan, dan perikanan berada di urutan kedua setelah industri pengolahan. Peraturan Daerah Nomor 11 Tahun 2011 mengenai Rencana Tata Ruang Wilayah (RTRW) Kabupaten Majalengka 2011-2031 menetapkan luasan lahan pertanian pangan berkelanjutan minimal 39.190 ha. Namun, jumlah tersebut berkurang menjadi 30.966 ha dengan adanya Keputusan Bupati Majalengka Nomor 520/KEP.1279-DKP3/2021 tentang Penetapan Lahan Pertanian Pangan Berkelanjutan. Untuk mengatasi dampak negatif dari pengurangan luasan lahan, perlu formulasi kebijakan yang mendukung pelestarian lahan pertanian dan penerapan praktik pertanian berkelanjutan oleh pemerintah daerah dan stakeholder terkait. Upaya ini bertujuan untuk mempertahankan luas lahan pertanian pangan dalam kerangka mewujudkan kemandirian pangan Kabupaten Majalengka. Studi yang dilakukan menunjukkan bahwa untuk memenuhi kebutuhan pangan (beras) hingga tahun 2045 sesuai arah Pembangunan RPJPN, diperlukan luasan lahan sawah dilindungi sebesar 48.235 ha dengan jumlah surplus beras sebesar 4.037 ton.

Upaya menuju kemandirian beras menjadi penting untuk mengurangi ketergantungan pangan pada negara lain, namun ini merupakan tantangan yang berat. Kebutuhan lahan untuk pembangunan menyebabkan berkurangnya lahan pertanian. Kebijakan perlindungan lahan sawah yang ada dan peningkatan produksi padi menjadi sangat strategis dalam sistem pangan, karena mencetak lahan pangan baru dihadapkan pada berbagai kendala. Hasil penelitian menunjukkan bahwa Peraturan Bupati tentang RTRW Kabupaten Banyumas 2011-2031 tidak mampu sepenuhnya mencegah konversi lahan sawah. Konversi lahan sawah ini menyebabkan pasokan beras domestik semakin menurun dan kemandirian beras di Kabupaten Banyumas diperkirakan hanya sampai tahun 2029. Kesinambungan implementasi antar variabel penting, menjadi kunci tercapainya tujuan sistem, yaitu: 1) penetapan Peraturan Bupati tentang Lahan Pertanian Pangan Berkelanjutan (LP2B), 2) penetapan skema insentif perlindungan lahan, 3) membangun database spasial lahan sawah secara detail, dan 4) pengembangan akses air irigasi menjadi variabel yang harus dijalankan pada tahap awal sebagai prioritas pertama, kemudian tahap berikutnya pemberdayaan kelompok tani prioritas kedua, dan peningkatan produktivitas tanaman padi sebagai tahan selanjutnya. Aktor yang menjadi kunci penggerak sistem, yaitu Bupati beserta dinas terkait (Dinas Pertanian dan Ketahanan Pangan, Bappeda Litbang, Dinas Pekerjaan Umum Bidang Pengairan, Dinas Perumahan dan Kawasan Permukiman), DPRD, ATR/BPN.

The Indonesian government has implemented various policies to meet the population’s need to raise staple food. Global food crises and malnutrition issues arise from several factors including population growth, uncontrolled conversion of rice fields, shifting consumption patterns, and climate change. Therefore, efforts to maintain and increase domestic rice production have become crucial to reduce potential food vulnerabilities and dependence on other countries for food. This study aims to analyze the dynamics of domestic rice sufficiency in the Banyumas Regency, analyze key related variables, and formulate policies to maintain it. The research methods used were visual image interpretation, building dynamic models, and conducting prospective analysis using the MICMAC method. The results show that domestic rice sufficiency is decreasing, resulting in a widening gap between the population’s rice needs and the domestic rice supply. The domestic rice supply in the study area can meet the rice needs of the local population by 2025, and in 2026, a deficit will begin to occur. Policies that can be implemented include increasing the planting index, improving rice productivity, food diversification, and implementing regulations to protect the rice fields. Critical variables in its implementation include the Regent’s Regulation on Rice Field Protection, detailed spatial information on rice fields, irrigation water availability, and the active role of farmer groups.

The focus on the growth of modern retail has become increasingly important due to several generated externalities. Therefore, this research aimed to identify spatial distributional pattern of modern retail in order to implement precise policies. Data were obtained from The Department of Licensing Service of Yogyakarta City and supplemented with observation through Google Maps. The global pattern was analyzed using the Moran Index (Moran’s I), while the spatial pattern was evaluated using Local Indicators of Spatial Association (LISA). The analysis resulted in a significant cluster pattern for small and big-scale modern retail. The LISA analysis indicated the existence of agglomeration in the suburban area, which was the urban growth area with a high-high (HH) cluster of both small and big-scale modern retail in exact locations. In conclusion, agglomeration in the suburban area was of great concern for policymakers due to the possibility of conflicts.

The Musi Hydropower-Plant catchment area is susceptible to soil erosion and sedimentation. Therefore, this research aimed to predict land use and land cover changes (LULCC) as well as their impact on soil erosion and sedimentation in the Musi Hydropower-Plant catchment area. The prediction of LULCC was calculated using Land Change Modeler module on IDRISI Terrset, while soil erosion and sedimentation were estimated with the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) models. The result showed that forest cover and paddy fields decreased significantly from 18.580 ha and 4.044 ha to 12.907 ha and 2.019 ha, respectively, in the periods of 1993 to 2019 and were predicted to reduce until 2032. Meanwhile, the built-up area and dry agricultural land increased from 818 ha and 2.116 ha in 1993 to 2.229 ha and 5.778 ha in 2019, which is expected to increase until 2032. The estimation of soil erosion rate also gave an increase from 75 t/ha/year to 113 t/ha/year, continuing to reach 122 t/ha/year until 2032. The escalation of soil erosion rate contributed to the change of sediment yield from 68.048 t/year in 1993 to 103.190 t/year in 2019,which is estimated to reach 111.028 t/year. These results are expected to be used by decision-makers and policymakers for the operation of the Musi Hydropower-Plant and the catchment area maintenance.

South Tangerang City is experiencing a process of suburbanization, where the increase in population causes an increase in the need for space for development. If development activities are not controlled, it will reduce the quality of the environment and people's lives. Land management is an activity that aims to support development programs by utilizing the capacity of land resources. This study aims to analyze the level of regional development and analyze the influence of land administration in supporting regional development in South Tangerang City in 2016 and 2019. The level of regional development is analyzed weighted scalogram with modification of physical, social and economic variables. The relationship between the Y variable (Urban village development index-IPWK) and the X variable (Land administration) was modeled using Geographically Weighted Regression (GWR). The results of the regional hierarchy analysis show that the urban village in South Tangerang City are dominant in Hierarchy 3 with an average IPWK value result 46.25 (2016) and 45.38 (2019), as a hinterland for DKI Jakarta. Land administration activities can have different positive and negative effects locally on the level of development of the urban village area.

Pandeglang Regency, Banten Province, is one of the regions on the island of Java that has great economic potential from a geographical perspective in the fisheries, agriculture, and tourism sectors to support the development and the economy in the area. However, since the tsunami hit this area in 2018, plus the non-natural catastrophe at the beginning of 2020, namely Covid-19, it has paralyzed the joints of the economy, which has an impact on hindering development in Pandeglang Regency. The purpose of this research is to discover the development of the Pandeglang rural area after the establishment of village funds and natural and non-natural disasters, to find out which locations are recommended and what steps are taken to accelerate economic recovery. This study uses analysis techniques of tabular and spatial data time series, descriptive analysis of tabular and spatial data comparisons, spatial pattern analysis using Moran's index value, and LISA method analysis. Based on the study results, three villages were recommended as centers for KPPNs, namely Teluk Village, Caring Village, and Sukacai Village. Based on the analysis results, Teluk Village and Caringin Village are villages affected by the tsunami, and Sukacai Village is a difficult village to develop in the 2015-2021 range.

GIS-based measurements can combine vector and raster data to produce thematic data obtained from remote sensing data. The data used in this study uses data on land use in the city of Pekanbaru. After the data is obtained, the pixel calculation process is carried out using three methods: the cell center method, the maximum area, and the maximum combined area. This data describes information with multiple raster data resolutions and then interprets the level of distortion in the data. The research findings found that in the process of raster data from 8 different resolution levels for the 5x5 meter category, it is able to provide results that are closest to the area of vector data, where PL 1 code produces 404229 pixels, PL 2 code ranges from 225717 pixels, PL 3 code ranges from 160323 pixels, code PL 4 ranges from 92268 pixels, PL 5 code reaches 73384 pixels, PL 6 code reaches 57237 pixels, and PL 7 code reaches 48315 pixels. Meanwhile, of the 3 methods that were compared to determine distortion with vector data, the cell center approach was the closest to raster data by calculation through eight levels of raster resolution compared to the other two methods. In choosing the right pixel resolution for further use in mathematical modeling, it is necessary to pay attention to the level of resolution by generalizing the resolution of satellite imagery data so that the data can have the same resolution. The weakness of the three methods lies in increasing the resolution the greater it will make the data coarser. This research is expected to be used as a consideration in future research to add a more precise process and be able to produce less storage capacity. Keyword: Comparison Multi-resolution GIS approach © This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

GIS-based measurements can combine vector and raster data to produce thematic data obtained from remote sensing data. The data used in this study uses data on land use in the city of Pekanbaru. After the data is obtained, the pixel calculation process is carried out using three methods: the cell center method, the maximum area, and the maximum combined area. This data describes information with multiple raster data resolutions and then interprets the level of distortion in the data. The research findings found that in the process of raster data from 8 different resolution levels for the 5x5 meter category, it is able to provide results that are closest to the area of vector data, where PL 1 code produces 404229 pixels, PL 2 code ranges from 225717 pixels, PL 3 code ranges from 160323 pixels, code PL 4 ranges from 92268 pixels, PL 5 code reaches 73384 pixels, PL 6 code reaches 57237 pixels, and PL 7 code reaches 48315 pixels. Meanwhile, of the 3 methods that were compared to determine distortion with vector data, the cell center approach was the closest to raster data by calculation through eight levels of raster resolution compared to the other two methods. In choosing the right pixel resolution for further use in mathematical modeling, it is necessary to pay attention to the level of resolution by generalizing the resolution of satellite imagery data so that the data can have the same resolution. The weakness of the three methods lies in increasing the resolution the greater it will make the data coarser. This research is expected to be used as a consideration in future research to add a more precise process and be able to produce less storage capacity.