Pengelompokkan Tingkat Kriminalitas di Indonesia Menggunakan Algoritma Average Linkage

Crime needs to be analyzed and grouped so that the act does not cause harm either ecologically or psychologically. The statistical method that can be used to classify crime is the Average Linkage Algorithm. The study aims to group and analyze the characteristics of criminal cases in Indonesia. From the results of the analysis, 3 clusters were formed based on the average of each cluster. Cluster 1 consists of Aceh, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Kep. Bangka Belitung, Kep. Riau, West Java, Central Java, DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, Maluku, North Maluku and Papua. Cluster 2 consists of North Sumatra while Cluster 3 consists of Metro Jaya. The grouping results are the basis of the government, apparatus, and the community in implementing the handling of criminal acts that occur in each cluster area so that prevention can minimize the losses caused by these crimes.

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SISTEM IDENTIFIKASI PERSEBARAN PECEMARAN AIR OLEH LIMBAH DI INDONESIA MENGGUNAKAN AVERAGE LINKAGE DAN K-MEAN CLUSTER

Jurnal Manajemen Informatika dan Sistem Informasi ◽

10.36595/misi.v1i2.47 ◽

2018 ◽

Vol 1 (2) ◽

pp. 36

Author(s):

LALU MUTAWALLI ◽

Mohammad Taufan Asri Zaen ◽

Indi Febriana Suhriani

Keyword(s):

Water Contamination ◽

Population Distribution ◽

West Kalimantan ◽

The Third ◽

Central Java ◽

East Kalimantan ◽

North Sulawesi ◽

South Sulawesi ◽

Average Linkage ◽

West Sumatra

Water contamination is a problem that is always difficult to resolved. One of the main sources that causes water contamination is waste caused by human activities. The needed for a system that can analyze the data of water contamination sources. The main cause of water contamination that became variables in this study are family, factory and other waste. The method of Cluster and Average Linkage is used to analyze hierarchical data. The results of Cluster analysis hierarchically divided into three provincial groups based on the population distribution of waste. The first group is the Province of Nanggroe Aceh Darussalam, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung, DKI Jakarta, DI Yogyakarta, East Java, Banten, Bali, NTB, NTT, East Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku, West Papua and Papua. The second group consists of West Java and Central Java. In the third group occupied by West Kalimantan, Central Kalimantan and South Kalimantan. The source of water contamination, namely family waste, dominates the second group or it can be said that the province classified as the second group is dominated by family waste. The source of factory waste water contamination that dominates in the third group or it can be said that the provinces classified in the third group are dominated by factory waste as one of the most important sources of water contamination. The first group consisted of 28 members or 28 provinces, the second group had 2 members, while the third group consisted of 3 members. The first group has a source of water contamination, the most important of which is based on the indicators that are seen to be stable for the three indicators. The main source of water contamination based on the three indicators studied for the second group is dominated by family waste and other wastes. Whereas for the third group is dominated by factory waste.

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PEMANFAATAN DATAMINING PADA PENGELOMPOKAN PROVINSI TERHADAP PENCEMARAN LINGKUNGAN HIDUP

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v3i1.1675 ◽

2019 ◽

Vol 3 (1) ◽

Author(s):

Mawaddah Anjelita ◽

Agus Perdana Windarto ◽

Dedy Hartama

Keyword(s):

Water Pollution ◽

Clustering Algorithm ◽

High Water ◽

West Kalimantan ◽

Central Java ◽

East Kalimantan ◽

North Sulawesi ◽

West Sumatra ◽

The Government ◽

The Many

This research aims to provide input for the government so that it can immediately tackle water pollution given the many adverse effects that lurk in various aspects of life. The method used in this study researchers used the method of K-means clustering datamining algorithm. The data used in this study are the number of villages according to the type of environmental pollution in 2018 which consists of 34 provinces in Indonesia obtained through the official website of the Directorate of Statistics Indonesia. The variable used is water pollution. The variable used is water pollution. Data is grouped into 2 clusters, namely provinces that have high levels of water pollution (C1) and provinces that have low levels of water pollution (C2). K-Means Clustering algorithm in this study produces 2 iterations, so the final result is: high water pollution (C1) in the provinces of North Sumatra, West Java, Central Java, East Java, for low level water pollution (C2) is in provinces of Aceh, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Kep.Bangka Belitung, Kep.Riau, DKI Jakarta, DI Yogyakarta, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku, West Papua, Papua.Keywords:Datamining, Clustering, K-means , Water pollution

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ANALISA METODE DATA MINING PADA PRODUKSI PERIKANAN LAUT YANG DIJUAL DI TEMPAT PERIKANAN IKAN (TPI)

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v3i1.1671 ◽

2019 ◽

Vol 3 (1) ◽

Author(s):

Hanifah Urbach Sari ◽

Agus Perdana Windarto ◽

Dedy Hartama

Keyword(s):

West Kalimantan ◽

Central Java ◽

North Sulawesi ◽

South Sulawesi ◽

Catchment Areas ◽

West Sumatra ◽

The Government ◽

High Level ◽

Water Catchment ◽

North Sumatra

The purpose of this research is that the results of the utilization of fish resources in producing marine fisheries by fishermen can be good using the K-Means clustring method. Data was obtained from the Central Statistics Agency (BPS) and assisted using RapidMiner software. Data used from 2013-2017 consisted of 21 Provinces. With these data can be obtained data with high-level clusters (C1), namely Central Java with production 587002.8 and low-level clusters (C2) provinces of Aceh, North Sumatra, West Sumatra, Bengkulu, Lampung, Bangka Belitung Islands, DKI Jakarta, West Java , DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, West Kalimantan, Central Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi and Gorontalo with a production of 20302.28. This can be input to the government for provinces that have low water catchment areas to be of more concern based on the cluster that has been done.Keywords: K-Means, Sea Fish Production, Clustering, Territory

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PENERAPAN ALGORITMA K-MEANS UNTUK PENGELOMPOKAN DAERAH RAWAN BENCANA DI INDONESIA

INTERNAL (Information System Journal) ◽

10.32627/internal.v1i2.42 ◽

2019 ◽

Vol 1 (2) ◽

pp. 1-10

Author(s):

Amril Mutoi Siregar

Keyword(s):

Natural Disasters ◽

Accurate Data ◽

Disaster Victims ◽

Central Java ◽

North Sulawesi ◽

Natural Beauty ◽

Or Groups ◽

Disaster Data ◽

The Government ◽

Almost All

Indonesia is a country located in the equator, which has beautiful natural. It has a mountainous constellation, beaches and wider oceans than land, so that Indonesia has extraordinary natural beauty assets compared to other countries. Behind the beauty of natural it turns out that it has many potential natural disasters in almost all provinces in Indonesia, in the form of landslides, earthquakes, tsunamis, Mount Meletus and others. The problem is that the government must have accurate data to deal with disasters throughout the province, where disaster data can be in categories or groups of regions into very vulnerable, medium, and low disaster areas. It is often found when a disaster occurs, many found that the distribution of long-term assistance because the stock for disaster-prone areas is not well available. In the study, it will be proposed to group disaster-prone areas throughout the province in Indonesia using the k-means algorithm. The expected results can group all regions that are very prone to disasters. Thus, the results can be Province West java, central java very vulnerable categories, provinces Aceh, North Sumatera, West Sumatera, east Java and North Sulawesi in the medium category, provinces Bengkulu, Lampung, Riau Island, Babel, DIY, Bali, West Kalimantan, North Kalimantan, Central Sulawesi, West Sulawesi, Maluku, North Maluku, Papua, west Papua including of rare categories. With the results obtained in this study, the government can map disaster-prone areas as well as prepare emergency response assistance quickly. In order to reduce the death toll and it is important to improve the services of disaster victims. With accurate data can provide prompt and appropriate assistance for victims of natural disasters.

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Analisis Algoritma Datamining pada Kasus Daerah Pelaku Kejahatan Pencurian Berdasarkan Provinsi

J-SAKTI (Jurnal Sains Komputer dan Informatika) ◽

10.30645/j-sakti.v4i1.189 ◽

2020 ◽

Vol 4 (1) ◽

pp. 77

Author(s):

Rinawati R ◽

Erene Gernaria Sihombing ◽

Linda Sari Dewi ◽

Ester Arisawati

Keyword(s):

Crime Rate ◽

West Java ◽

Central Java ◽

South Sulawesi ◽

West Sumatra ◽

The Government ◽

North Sumatra ◽

Very High ◽

Central Statistics

Theft is a behavior that causes harm to victims who are targeted and can cause victims. The level of theft behavior is increasing in each region due to the increasing number of unemployment and lazy nature of work that makes a person commit theft to make ends meet. The purpose of this study was to analyze using the technique of datamining in the area of perpetrators of theft crimes by province. The technique used is clustering with the K-means method. Data sourced from the Indonesian Central Statistics Agency with the url address: https://www.bps.go.id/. The results of the study using this technique are clustered in areas in Indonesia which have the highest crime theft rates. From the results of the study using the K-means technique, that there are 17 provinces out of 34 provinces that have the highest crime theft (C1) areas, namely: Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Lampung, DKI Jakarta, West Java, Central Java, East Java, Banten, West Nusa Tenggara, East Nusa Tenggara, South Kalimantan, South Sulawesi, Papua. The results of the study are expected to be information for the government in conducting policies to reduce the crime crime rate in Indonesia which is very high (50%).

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Direct and Indirect Effect of Macro Economic Factors in the West of Indonesia

Golden Ratio of Social Science and Education ◽

10.52970/grsse.v1i1.107 ◽

2020 ◽

Vol 1 (1) ◽

pp. 13-24

Author(s):

Nurhidayati Islamiah ◽

R. Rahmatia ◽

Hamid Paddu ◽

Muhammad Yusri Zamhuri

Keyword(s):

Economic Growth ◽

Government Spending ◽

Structural Equation ◽

Equation Model ◽

Research Approach ◽

The West ◽

Central Java ◽

New Findings ◽

West Sumatra ◽

The Government

This study aims to examine the effect of investment, expenditure on unemployment, income inequality, and economic growth in the west of part of Indonesia. The research approach is quantitative with structural equation model as a statistical approach. The number of provinces taken in the west of region as many as 18 provinces consisting of Nanggroe Aceh Darussalam, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung, Riau Islands, DKI Jakarta, West Java, Central Java and East Java, Yogyakarta, Banten, West Kalimantan and Central Kalimantan. Result of this study indicates that economic growth has a similar effect produced by investment on the unemployment rate in the west of Indonesia. Investments made by the government are significantly negative, most of which are centered on supporting welfare and developing the human index. There are new findings in the study, namely the different effects caused by government spending on reducing the unemployment ratio. In the west of Indonesia area, this does not show a significant impact whether tested between government spending on unemployment rates or economic growth in east or west of Indonesia. This means that government spending still needs to be converted into various work programs to absorb labor permanently.

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Perdagangan Antarpulau Komoditas Cabai di Indonesia: Dinamika Produksi dan Stabilitas Harga

Analisis Kebijakan Pertanian ◽

10.21082/akp.v16n2.2018.111-129 ◽

2018 ◽

Vol 16 (2) ◽

pp. 111 ◽

Cited By ~ 2

Author(s):

Herman Supriadi ◽

Wahyuning Kusuma Sejati

Keyword(s):

Descriptive Analysis ◽

Distribution Patterns ◽

Price Transmission ◽

Production Costs ◽

Management Tool ◽

Selling Price ◽

West Java ◽

Central Java ◽

West Sumatra ◽

The Government

The Study of Inter-island Trade (PAP) of chilli commodities is carried out with the aim of analyzing trade performance, as well as formulating policy alternatives that support the development of chili commodities. The study was conducted in 2016 in Central Java, West Java and West Sumatra. The analytical method used is quantitative descriptive analysis related toPAP distribution patterns, policies on regulation, marketing networks and price transmission elasticity. The results showed that chilli production increased sharply in the province of West Java, while in Central Java, West Sumatra, Lampung and other provinces relatively slow increases due to disease problems and limited land. The stabilization of red chili production on the islands of Java and West Sumatra greatly determines price stability in other regions. Chili production in West Sumatra still does not meet demand, where the distribution of chili from DIY and Central Java to West Sumatra Province tends to increase more than the out-flow of chili from the province. The government has attempted to stabilize the price of red chili, maintain a balance between the regions of surplus and deficit, and minimize the price disparity between regions, but so far it has not been successful due to the constraints of low production so that demand is not met and high transportation costs. The development of an agribusiness station (STA) such as in West Java has not been effective in accommodating and marketing the results of farmers because marketing has been controlled by large traders who are capable of PAP.In general, several factors that make low prices and price fluctuations at the farm level are caused by the varying quality of products produced by farmers, increased production costs, information that is not symmetrical and low bargaining power by marketers. Java island because prices in Java determine prices in other regions, especially in Java, Sumatra and Kalimantan. Vertical coordination and marketing contracts can be used as a risk management tool for income and prices because there are provisions on the selling price for farmers AbstrakStudi Perdagangan Antar Pulau (PAP) komoditas cabai dilakukan dengan tujuan untuk menganalisis kinerja perdagangan, serta merumuskan alternatif kebijakan yang mendukung pengembangan komoditas cabai. Penelitian dilakukan pada tahun 2016 di Jawa Tengah, Jawa Barat dan Sumatera Barat. Metode analisis yang digunakan adalah analisis deskriptif kuantitatif terkait pola distribusi PAP, kebijakan terhadap regulasi, jaringan pemasaran, dan elastisitas transmisi harga. Hasil penelitian menunjukkan produksi cabai meningkat secara tajam di Provinsi Jawa Barat, sedangkan di Jawa Tengah, Sumatera Barat, Lampung, dan provinsi lainnya relatif lambat kenaikannya karena masalah penyakit dan keterbatasan lahan. Stabilisasi produksi cabai merah di pulau Jawa dan Sumatera Barat sangat menentukan stabilitas harga di wilayah lain. Produksi cabai di Sumatera Barat masih belum memenuhi permintaan, dimana Arus distribusi cabai dari DIY dan Jawa Tengah ke Provinsi Sumatera Barat cenderung meningkat lebih banyak dari pada yang keluar provinsi. Pemerintah telah berupaya untuk stabilisasi harga cabai merah, menjaga keseimbangan antara daerah surplus dan defisit, serta memperkecil disparitas harga antar daerah, akan tetapi sejauh ini belum berhasil karena kendala rendahnya produksi sehingga permintaan kurang terpenuhi dan tingginya biaya transportasi pengangkutan. Pembangunan stasiun agribisnis (STA) seperti di Jawa Barat belum efektif menampung dan memasarkan hasil petani karena pemasaran sudah dikuasai oleh pedagang besar yang berkemampuan melakukan PAP. Secara umum beberapa faktor yang menjadikan rendahnya harga dan fluktuasi harga di tingkat petani disebabkan oleh beragamnya kuallitas produk yang dihasilkan oleh petani, meningkatnya biaya produksi, informasi yang tidak simetri dan rendahnya daya tawar oleh pelaku pemasaran. Perlu upaya peningkatan dan stabilisasi produksi cabai merah di pulau Jawa karena harga di Jawa sangat menentukan harga di wilayah lain, terutama di wilayah Jawa, Sumatera dan Kalimantan. Koordinasi vertikal dan kontrak pemasaran dapat digunakan sebagai alat manajemen risiko pendapatan dan harga karena ada ketentuan harga jual bagi petani.

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Peran Sekolah dan Masyarakat dalam Pelaksanaan Program Bantuan Operasional Sekolah

Jurnal Aspirasi ◽

10.46807/aspirasi.v10i1.1228 ◽

2019 ◽

Vol 10 (1) ◽

pp. 49-60

Author(s):

Yulia Indahri

Keyword(s):

Compulsory Education ◽

Field Studies ◽

City Governments ◽

West Kalimantan ◽

The Public ◽

North Sulawesi ◽

The World Bank ◽

Poor Families ◽

The Government ◽

The Ideal

School Operational Grant (BOS) is a program that absorbs large enough funds and received directly by beneficiaries, schools. The BOS program began on July 2005 in order to accelerate 9-year compulsory education, reduce dropout rates, and assist students from poor families to continue schooling. However, there was also an indication that the government wanted to invite stakeholders, namely schools and the committee, to actively involve in the implementation of the program. Although the funds received by students through their school have not reached the ideal, at least the minimum service requirement can be met. This paper uses literature studies and field studies in three provinces in Indonesia, namely Aceh, West Kalimantan, and North Sulawesi for comparison. Literature studies among which are based on the study and research conducted on the BOS Program by third parties such as SMERU and the World Bank. While field studies were conducted in order to understand problems on the implementation of BOS Program especially on stakeholders’ participation. As conclusion, it is seen that the addition of budget allocations should continue to pay more attention to suggestions from provincial/district/city governments, as well as from the community. Community participation, especially when it comes to funding, should not be unsupervised. There must be certainty of transparency and accountability of the use of funds that are constantly being reported to the public and not of a coercive nature.AbtrakBantuan Operasional Sekolah (BOS) merupakan program yang menyerap dana cukup besar dan langsung diterima oleh penerima bantuan, yaitu sekolah. Program BOS mulai dilaksanakan pada Juli 2005 dalam rangka percepatan Wajib Belajar 9 Tahun, menekan angka putus sekolah, dan membantu siswa dari keluarga miskin untuk dapat terus sekolah. Akan tetapi, ada keinginan dari pemerintah agar pemangku kepentingan, yakni sekolah dan komite sekolah, mau terlibat aktif dalam pelaksanaan program. Walaupun dana yang diterima oleh siswa melalui sekolah belum mencapai angka ideal, paling tidak kebutuhan standar pelayanan minimal dapat terpenuhi. Tulisan ini menggunakan studi pustaka dan studi lapangan di tiga provinsi di Indonesia, yaitu Aceh, Kalimantan Barat, dan Sulawesi Utara untuk perbandingan. Studi pustaka di antaranya adalah kajian dan penelitian yang dilakukan mengenai Program BOS oleh lembaga penelitian SMERU dan juga Bank Dunia. Studi di lapangan dilakukan untuk melihat kendala yang ditemui di lapangan dalam pelaksanaan Program BOS terutama dalam kaitannya dengan peran serta pemangku kepentingan. Dapat disimpulkan bahwa penambahan alokasi anggaran perlu terus mendengarkan masukan dari pemerintah provinsi/kabupaten/kota, dan juga dari masyarakat. Partisipasi masyarakat, terutama jika menyangkut pendanaan, tidak berarti tanpa pengawasan. Harus ada kepastian transparansi dan akuntabilitas dari pemanfaatan dana yang tetap dilaporkan ke masyarakat dan tidak bersifat memaksa.

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Karakteristik Mutu Minyak Pala Berdasarkan Peralatan Distilasi Drum Bekas dan Distilasi Stainless (Studi Kasus di Kabupaten Aceh Selatan)

Rona Teknik Pertanian ◽

10.17969/rtp.v10i2.8491 ◽

2017 ◽

Vol 10 (2) ◽

pp. 35-44

Author(s):

Mustafril Mustafril

Keyword(s):

Specific Gravity ◽

Coming Out ◽

Optical Rotation ◽

Oil Quality ◽

Oil Production ◽

Refraction Index ◽

North Sulawesi ◽

West Sumatra ◽

The Government

Quality Characteristics of Nutmeg Oil Between Used Barrels Distillation and Stainless Distillation (A Case Study in Aceh Selatan Regency)ABSTRACT. The Province of Aceh is the center of nutmeg oil production in Indonesia, which is about 70%-75% of the nutmeg oil production in Indonesia, is produced in the districts of South Aceh and Southwest Aceh. The rest is coming from the provinces of West Sumatra and West Java. Meanwhile, the nutmeg harvested in Maluku, North Maluku, North Sulawesi, and West Papua is not processed for its essential oil, but merely exported as spices. It is estimated that in 2017 the production of nutmeg oil will reach about 350-400 tones. The government has put a standard for nutmeg oil based on SNI 06-2388-2006. Therefore, taking this standard as consideration, a study on the characteristics of nutmeg oil quality in South Aceh was carried with 14 distillers as the sample. The tested nutmeg oil was taken from the distillers, both stainless distillation drum and used drum. The characteristics of nutmeg oil coming out of the used drum is from colorless to pale yellowish one, has nutmeg scent, specific gravity: 0,884 - 0,960, rafractive index: 1,481-1,500, optical rotation: (+)6,20o - (+)19,30o and rest of evaporation is between 5,70% - 28,15%. On the other hand, the characteristic of nutmeg oil taking from stainless distiller is colorless, has nutmeg scent, specific gravity: 0,861 - 0,892 refractive index: 1,472 - 1,484, optical rotation: (+)10,83o- (+)18,00o, and rest of evaporation is 0,50% - 4,80%. Most of nutmeg oil processed by used drum did not meet the SNI standard, whereas few of nutmeg oil distilled in stainless and semi stainless drum has met the SNI standard of nutmeg oil.Correlation of specific gravity and refraction index of nutmeg oil for stainless distillation is refraction index (Y) = 0,3151X + 1,2014, where R2 = 0,8403; whereas for used barrels distillation is refraction index (Y) = 0,28X + 1,2334, where R2 = 0,9637.Correlation of Optical Rotation for stainless distillation is Optical Rotation (Y) = -223,02X + 209,81, where R2 = 0,9645;conversely, forused barrels distillation Optical Rotation (Y) = -155,01X + 156,2, where R2 = 0,9348.Correlation of refraction index with Optical Rotation for nutmeg oil distilled with stainless distillation is Optical Rotation (Y) = -610,36X + 915,96, where R2 = 0,8536; contrarily for distillation with used barrels Optical Rotation (Y) = -545,71X + 827,26, where R2 = 0,9427.

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Identifikasi Molekuler Hawar Daun Bakteri (Xanthomonas oryzae pv. oryzae) dan Uji Patogenisitasnya pada Galur-galur Padi Isogenik

Jurnal AgroBiogen ◽

10.21082/jbio.v9n2.2013.p49-57 ◽

2016 ◽

Vol 9 (2) ◽

pp. 49 ◽

Cited By ~ 2

Author(s):

Tasliah Tasliah ◽

Mahrup Mahrup ◽

Joko Prasetiyono

Keyword(s):

Molecular Biology ◽

Molecular Analysis ◽

Xanthomonas Oryzae ◽

Specific Primers ◽

West Kalimantan ◽

Central Java ◽

South Sulawesi ◽

Pcr Product ◽

West Sumatra ◽

Pathogenicity Tests

Identification of Xanthomonas oryzae pv. oryzae (Xoo) based on molecular analysis has been introduced just few years ago. This method used some specific primers for Xoo and can be done quickly. The purposes of this research were to identify isolate Xoo originated from five locations in Indonesia and to determine the level of pathogenicity of these bacteria. Studies were conducted in the greenhouse and the Molecular Biology Laboratory of ICABIOGRAD, from 2011 to 2012. Bacterial isolates were taken from five regions in Indonesia, namely: West Sumatra, West Java, Central Java, South Sulawesi, and West Kalimantan. The specific primers of Xoo were Xoo2967, Xoo80, and Xoo. Results showed that 216 isolates could be grown to form yellow colored colonies, which belongs to a criterian for Xoo. Molecular analysis demonstrated that 189 isolates were Xoo and 27 isolates were not. Amplification of DNA of the isolates resulted a 337 bp PCR product for primer Xoo2976, 700 bp for primer Xoo80 and 534 bp for primer Xoo. Pathogenicity tests of the Xoo isolates showed xa5, Xa7, and Xa21 resistance genes were still effective againts BLB pathogens originated from those five regions, with percentage of resistance were 93.57, 77.49, and 85.37%, respectively.

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