Fitriatien, Sri Rahmawati (2015) Aplikasi jaringan syaraf tiruan Kohonen Self Organizing Maps dan Learning Vector Quantization pada data kualitas air kali Surabaya. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kali Surabaya adalah sumber air baku yang digunakan masyarakat Surabaya untuk memenuhi kebutuhan sehari-hari. Kondisi air permukaan Kali Surabaya mengalami penurunan kualitas air yang dirasakan semakin hari semakin meningkat akibat sebagian besar limbah cair hasil dari kegiatan manusia dibuang ke saluran yang bermuara di Kali Surabaya. Limbah tersebut berasal dari permukiman, industri, pertanian, peternakan dan lain-lain. Indikator kimia pencemaran air limbah cair yang digunakan yaitu BOD, COD dan DO. Tujuan dari penelitian tesis ini adalah melakukan pengelompokan seluruh titik pantau kualitas air Kali Surabaya dengan jumlah cluster yang terbentuk dimulai dari 2 hingga 4 cluster berdasarkan kategori pembagian status mutu air. Dari pengelompokan titik pantau ini kemudian dilakukan penetapan status mutu kualitas air selama 14 periode dimulai dari bulan Januari 2010 hingga Juni 2013. Jaringan syaraf tiruan merupakan sistem pemroses informasi seperti pemroses pada otak manusia. Jaringan syaraf tiruan telah banyak digunakan dalam banyak aplikasi, salah satunya adalah clustering. Dalam tesis ini, metode Kohonen Self Organizing Maps dan Learning Vector Quantization digunakan untuk menyelesaikan masalah clustering titik pantau kualitas air Kali Surabaya pada setiap waktu pantau. Untuk penentuan cluster terbaik menggunakan Davies- Bouldin Index (DBI) sebagai validasi cluster. Penentuan status mutu air Kali Surabaya di setiap titik pantau dilakukan dengan metode Indeks Pencemaran yang divalidasi dengan uji distribusi normal. Dari implementasi dan uji coba program dapat diperoleh simpulan bahwa algoritma Kohonen-SOM dan LVQ dapat mengenali pola dan mampu mencocokan anggota kelompok titik pantau dengan parameter learning rate minimal 0,000001 diperoleh nilai mean square error pada jaringan LVQ lebih kecil dibandingkan dengan jaringan Kohonen-SOM. Berdasarkan Indeks Pencemaran, status mutu air Kali Surabaya pada Januari 2010-Juni 2013 berada pada status mutu air Tercemar Ringan. ============================================================================================================== Surabaya’s river is primary water source needed for Surabaya’s people for their daily demand. Meanwhile, the quality for water of Surabaya’s river is more decreased from day to day because the most liquid waste of human activities are thrown into canal to Surabaya’s river. The waste are from the settlement, industry, agriculture, animal husbandry, etc. Chemical indicator of liquid waste pollution that is BOD, COD and DO. The purposes of this research are to cluster all observation points of the quality of water in Surabaya’s river with the cluster number started from 2 clusters to 4 clusters. Based on this cluster result of observation points, it is then fixed the quality of water for 14 period started from January 2010 to June 2013. Artificial neural networks are information processing systems such as processing in the human brain. Artificial neural networks have been widely used in many applications, one of which is clustering. In this thesis, the method of Kohonen Self Organizing Maps and Learning Vector Quantization clustering is used to solve the problems of water quality monitoring points Surabaya at any time to monitor. To determine the best cluster using the Davies-Bouldin Index (DBI) as the cluster validation. Determination of the status of water quality at any point Surabaya monitoring was conducted by the Pollution Index test is validated by the normal distribution. From implementation and test programs can be concluded that the algorithm-SOM Kohonen and LVQ can recognize patterns and able to match the group members monitoring points with a minimal learning rate parameter value 0.000001 mean square error values obtained in LVQ network is smaller than the Kohonen -SOM. Based on the Pollution Index, the water quality status Kali Surabaya in January 2010-June 2013 are in the floaty polluted water quality status.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMa 006.3 Sri a |
| Uncontrolled Keywords: | Kohonen self organizing maps; Learning vector quantization; Status mutu air; Indeks pencemaran |
| Subjects: | Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) |
| Divisions: | Faculty of Mathematics and Science > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | - Taufiq Rahmanu |
| Date Deposited: | 04 Jul 2019 02:23 |
| Last Modified: | 04 Jul 2019 02:23 |
| URI: | https://repository.its.ac.id/id/eprint/63459 |
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