Jurnal SINTA 1
Aturan Asosiasi Dengan Standar Storet Pada Model Prediksi Parameter Pendukung Uji Kualitas Air Baku
Journal of Information Systems Engineering and Business Intelligence · Vol. 1 No. 1 (2015) · pp. 1–8
- ISSN
- 2443-2555, 2598-6333
- Published
- 2015-06-25
- Publisher
- Universitas Airlangga
- Language
- eng
Abstract
Abstrak”Uji laboratorium tentang kualitas air baku pada penyediaan dan pengolahan air bersih memperhatikan parameter air terkait faktor fisika, kimia dan biologi. Analisis kualitas air di laboratorium membutuhkan waktu. Usulan sistem akan mempercepat waktu dengan menganalisis catatan dataparameter air yang ada dalam rekam data PDAM. Aturan asosiasi pada sistem digunakan untuk melihat hubungan antara parameter air yang didahului praproses dengan mengubah data numerik ke data kategorikal berdasarkan standar STOrage and RETrievalData Warehouse (STORET).Selanjutnya model prediksi parameter air yang dihasilkan dari data belajar akan diserderhanakan terlebih dahulu sebelum validasi model dengan data uji. Pengujian model menggunakan data belajar menunjukkan rata-rata akurasi 70% dengan minimal support-confidence 30% data. Hasil model hubungan parameter air menggunakan rekam data PDAM dapat menjadi pendukung kebijakan di daerah tersebut dalam penyediaan dan pengolahan air bersih sebelum dilakukan uji kualitas laboratorium. Tanpa ada uji laboratorium beberapa nilai parameter faktor kimia tidak dapat diketahui. Meskipun demikian aturan yang dihasilkan sistem usulan tanpa uji laboratorium dapat memberikan akurasi 80%-95% dengan asumsi missing valuesnilai faktor kimiasetelah dicek manual dari narasumber pemilik data. Data uji coba menggunakan dataset kecil untuk mempermudah cek manual. Kata Kunci” prediksi kualitas air, aturan asosiasi, storetAbstrak”Raw Water (Air Baku) laboratory analysis is testing physical, chemical and bacteriological characteristicsof water to ensure that water supply is clean, safe and ready for drinking water quality. Analyzing raw water quality in laboratorium needs more time. The proposed system could shorten the laboratory processing time by analyzing daily water production log. Association ruleinthe proposed system was used to generate relation model of water characteristicsfrom the data log provided by local government owned water utilities (PDAM, Perusahaan Daerah Air Minum). The data was transformed first from numerical data into categorical data using STOrage and RETrieval Data Warehouse (STORET)standard.Generated model needs to be simplified because some prediction rules could have the same interpretation. The generated parameter prediction modelwas sufficient to be used as the supporting data for any local policy made related to water supply and sanitationwithout additional costs from standard lab testing of water quality. Some water quality values of chemical characteristics need lab testing. Given the missing values of several chemical characteristics, the generated parameter prediction model still could give better accuracy of 80%-95%. Since PDAM staffmanually validated the generated model, the experiments used small data set. Keywords” water quality prediction, association rule, storet
Collaboration network of the authors
40 authors · 101 co-authorship links · 7 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Institut Teknologi Sepuluh Nopember
- Islamic University of Indonesia
- Universitas Muhammadiyah Malang
- University of Brawijaya
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Chastine Fatichah | Institut Teknologi Sepuluh Nopember | 9 |
| Agus Zainal Arifin | Institut Teknologi Sepuluh Nopember | 7 |
| Agus Budi Raharjo | Institut Teknologi Sepuluh Nopember | 4 |
| Apriantoni Apriantoni | Institut Teknologi Sepuluh Nopember | 3 |
| Nanik Suciati | Institut Teknologi Sepuluh Nopember | 3 |
| Rizka Wakhidatus Sholikah | Institut Teknologi Sepuluh Nopember | 2 |
| Yudhi Purwananto | Institut Teknologi Sepuluh Nopember | 2 |
| Fahrur Rozi | Institut Teknologi Sepuluh Nopember | 2 |
| Narandha Arya Ranggianto | Institut Teknologi Sepuluh Nopember | 2 |
| Hilya Tsaniya | Institut Teknologi Sepuluh Nopember | 2 |
| Abid Famasya Abdillah | Institut Teknologi Sepuluh Nopember | 2 |
| Safitri Juanita | Institut Teknologi Sepuluh Nopember | 2 |
| Gulpi Qorik Oktagalu Pratamasunu | Affiliation unknown | 2 |
| Khoirul Umam | Institut Teknologi Sepuluh Nopember | 1 |
| Fidi Wincoko Putro | Institut Teknologi Sepuluh Nopember | 1 |
| Khadijah Fahmi Hayati Holle | Institut Teknologi Sepuluh Nopember | 1 |
| Arif Fadllullah | Institut Teknologi Sepuluh Nopember | 1 |
| Dasrit Debora Kamudi | Institut Teknologi Sepuluh Nopember | 1 |
| Muhamad Nasir | Institut Teknologi Sepuluh Nopember | 1 |
| Dhian Kartika | Affiliation unknown | 1 |
| Umi Laili Yuhana | Institut Teknologi Sepuluh Nopember | 1 |
| Daniel Siahaan | Institut Teknologi Sepuluh Nopember | 1 |
| Dian Saputra | Affiliation unknown | 1 |
| Esti Yuniar | Affiliation unknown | 1 |
| Febriliyan Samopa | Institut Teknologi Sepuluh Nopember | 1 |
| Ade Afrian | Affiliation unknown | 1 |
| Yos Nugroho | Affiliation unknown | 1 |
| Putu Utami Andarini S. | Affiliation unknown | 1 |
| Indra Lukmana | Affiliation unknown | 1 |
| Daniel Swanjaya | Affiliation unknown | 1 |
| Arrie Kurniawardhani | Islamic University of Indonesia | 1 |
| Nur Hayatin | Universitas Muhammadiyah Malang | 1 |
| Rizal Setya Perdana | University of Brawijaya | 1 |
| Anny Yuniarti | Institut Teknologi Sepuluh Nopember | 1 |
| Dini Adni Navastara | Institut Teknologi Sepuluh Nopember | 1 |
| Arya Yudhi Wijaya | Institut Teknologi Sepuluh Nopember | 1 |
| Tsabbit Aqdami Mukhtar | Institut Teknologi Sepuluh Nopember | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.