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All Journal Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik
Indi Febriana Suhriani
Universitas Gadjah Mada
Computer Science & IT

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SISTEM IDENTIFIKASI PERSEBARAN PECEMARAN AIR OLEH LIMBAH DI INDONESIA MENGGUNAKAN AVERAGE LINKAGE DAN K-MEAN CLUSTER LALU MUTAWALLI; Mohammad Taufan Asri Zaen; Indi Febriana Suhriani
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 1 No. 2 (2018): MISI Juni 2018
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v1i2.47

Abstract

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.
IMPLEMENTASI SPARQL DENGAN FRAMEWORK JENA FUSEKI UNTUK MELAKUKAN PENCARIAN PENGETAHUAN PADA MODEL ONTOLOGI JALUR KLINIS TATA LAKSANA PERAWATAN PENYAKIT KATARAK Lalu Mutawalli; Indi Febriana Suhriani; Supardianto Supardianto
Jurnal Informatika dan Rekayasa Elektronik Vol. 1 No. 2 (2018): JIRE Nopember 2018
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v1i2.66

Abstract

Abstract The prevalence of cataracts in Indonesia is very high, this can affect the quality of life, productivity and social aspects will cause the nation's economy to be in a low-level position. Cataract problems certainly need to be considered more, however, on the other hand, the lack of experts (doctors) is an obstacle especially outside the city. Uneven distribution of experts will complicate the conditions for solving problems. With these conditions, a semantic-based information technology approach is needed regarding the treatment of patients with cataracts. Semantic information can provide knowledge to non-physician health workers, this will certainly facilitate the process of prevention and prevention of cataracts. In this research, knowledge is modeled using the ontology concept. We have built an ontology model that can be used as a guide to the management of cataract disease. To extract the built-in ontology model, simple protocol and RDF Language (SPARQL) are used as query languages. Apache Jena Fuseki is used to simplify the process of evaluating knowledge.
Co-Authors Lalu Mutawalli Mohammad Taufan Asri Zaen Supardianto Supadianto