Authors : Destarita Indah Permatasari

Volume/Issue : Volume 7 - 2022, Issue 3 - March

Google Scholar : http://tinyurl.com/54ph923b

Scribd : http://tinyurl.com/5ha57tr9

DOI : https://doi.org/10.5281/zenodo.10727133

Abstract : The SDG’s goals are served as the datas upper, which Carbon Emission Reduction. By some countries which are signed international agreement in Paris, they promising to push the percentage of cabron emission in their country. For Indonesia government announced that could be attained at 26 %. From the tables, we can conclude than the carbon emission reduction are fluctuated. With the range from - 195, 72% in 2015 at the bottom and 137, 41 % at the top in 2012. The most increasing percentage contributed in 2012 with 110 %, while at the other shide the sharply decreasing happener at 2015 by 55 %. The sources of carbon emission is divided by energy; industry, agriculture; waste, and forest. (Ministry of Forest, 2021). The minimum of percentages of green open spaces is 20 % in every sites while 10 % is the minimum percentages of grey open spaces. (Law 2007 about Spatial Planning). The period of observation are during 2010 – 2020, considering the datas availability. The scope of research is 34 provinces in Indonesia. We are already collected data for several variables which are predicted to be the causes of carbon emission. As follows : The percentage of national carbon emission nationally; The household consumption; The government spending; The human development index; The value of export; The value of import; The total population; The percentage of inflation; The number of electricity tower; and The number of electricity network. Consist of the step of analysis, the standar of taking the results : The Step of research concist of : grouping the datas gathered from National Stathystical Board from difeerent file into one file each variable; Clustering the region by my previous research related to existence of city flagship area to enlarge the management as greater area; Combine each variables into one sheet become 1 file; Making identification by setted that according the predicted columns based on the level of impact to carbon emission reduction reduction; High list every cell by certain coloured in order to make sure the differentiation by these three groups : below mean, mean, upper mean; The last step is give scores each each cell with this rule : 1 for below mean; 2 for mean; and 3 for upper mean, and make results regarding the analysis before. There are 6 cluster of region (sub island / islands) categorized as developed areas, while the other 7 classified as developing areas, and none of them is poverty areas. They are : Developed Areas (inflations minimum once in 10 years more than 10 %): cluster 1 ( Aceh – Sumatera Utara); cluster 2 (Sumatera Barat - Riau – Kepulauan Riau); cluster 3 (Jambi – Sumatera Selatan – Bengkulu – Kepulauan Bangka Belitung); cluster 4 ( Lampung – Banten); cluster 7 (Jawa Timur – Bali – Nusa Tenggara Barat – Nusa Tenggara Timur); dan cluster 10 ( Kalimantan Selatan – Kalimantan Timur- Kalimantan Utara); Developing Areas (inflations minimum once in 10 years less than 10 %): : Cluster 5 ( DKI Jarta – Jawa Barat); cluster 6 ( Jawa Tengah – DIY); cluster 8-9 (Kalimantan Barat – Kalimantan Tengah); cluster 11 (Sulawesi Utara- Gorontalo- Sulawesi Tenggara); cluster 12 ( Sulawesi Tengah – Sulawesi Selatan – Sulawesi Barat); dan cluster 13 ( Maluku- Maluku Utara-Papua Barat-Papua); Poverty areas (inflations minimum once in 10 years more than 5 %): none of 13 cclusters. The attainment of carbon emission targets during 2010-2020 are assumed impacted of the spaces both public and privates : Carbon emission : <0 %,0,01-100 %, and > 100,01 %; Household Consumption : 100.000.000-300.000.000; Government Spending : 188.000.000-44.000.000; IPM : 66 % - 72 %; Expor : 4.000-6.000; Impor : 4.000-6.000; Penduduk : >7.000.000; Inflation : <0, >5, >10; Towers : 1.000-2.000; Networks : 4.500 – 7.250. The enlargement and reducing stock of spaces are proposed by the achievement of green shading (upper mean) or yellow shading (below in between bottom and too mean) and pink shading (below mean). Level of wealth in green zone at Sumatera Utara, Banten, DKI Jakarta, Jawa Tengah, Jawa Timur; yellow zone at Aceh, Sumatera Barat, Riau, Kepulauan Riau, Sumatera Selatan, Lampung, Jawa Barat, Bali, Kalimantan Barat, Kalimantan Timur ; and pink zone at Jambi, Bengkulu, Kepulauan Bangka Belitung, DIY, Nusa Tenggara Barat, Nusa Tenggara Timur, Kalimantan Tengah, Kalimantan Selatan, Kalimantan Utara, Sulawesi Utara, Gorontalo, Sulawesi Tenggara, Sulawesi Tengah,Sulawesi Selatan, Sulawesi Barat, Maluku, Maluku Utara, Papua Barat, dan Papua. Govermenment Spending in green zone in Sumatera Utara, DKI Jakarta, Jawa Barat, Jawa Tengah, Jawa Timur, Sulawesi Selatan, Maluku Utara, dan Papua ; yellow zones in Aceh, Sumatera Barat, Riau, Sumatera Selatan, Lampung, DIY, Bali , Nusa Tenggara Timur, Nusa Tenggara Barat, Kalimantan Barat, Kalimantan Tengah, Kalimantan Selatan, Kalimantan Timur, Sulawesi Utara, Sulawesi Tenggara, Sulawesi Tengah and pink zones Kepulauan Riau, Jambi, Bengkulu, Kepulauan Bangka Belitung, Banten, Kalimantan Utara, Gorontalo, Sulawesi Barat, Maluku, Papua Barat,; The linkage between each variables as so the row of columns can be grouped as new policies for each provinces. For Green zone : reduce the housing estates, education spaces, industrial and trade centres, and office complex, enlarge the spaces for recreational, forest and wet lands, public infrastructures, green public free and rent areas; and grey private open spaces; For Yellow zone : maintain all area dan keep existance of the all function spaces; For the pink zone : reverse back from the point a.