Jurnal SINTA 2
Prediksi Distribusi Air PDAM Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Di PDAM Kota Malang
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 3 No. 2 (2016) · pp. 83–87
- ISSN
- 2528-6579, 2355-7699
- Published
- 2016-06-20
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakDistribusi air PDAM merupakan nilai volume air yang disalurkan ke pelanggan PDAM. Faktor yang mempengaruhi distribusi air PDAM diantanya adalah jumlah kehilangan air dan jumlah air yang terjual. Paper ini mengimplementasikan jaringan syaraf tiruan backpropagation untuk memprediksi jumlah dari distribusi air perbulan berdasarkan jumlah kehilangan air dan jumlah air yang terjual. Pada tahap pelatihan dilakukan pengujian untuk mendapatkan iterasi, learning rate, data latih dan data uji, jumlah node pada lapisan tersembunyi, dan minimum error yang optimal. Hasil pelatihan didapatkan iterasi optimal sebanyak 2000, learning rate yang optimal 0.1, data latih dan data uji yang optimal sebanyak 80 untuk data latih dan 11 untuk data uji, jumlah node pada lapisan tersembunyi sebanyak 5, sedangkan minimum error adalah 0.00001. Dari hasil pengujian menggunakan parameter optimal tersebut didapatkan akurasi terbaik sebesar 97,99%.Kata kunci: prediksi, distribusi air, PDAM, backpropagation, jumlah kehilangan air, jumlah air terjualAbstractPDAM water distribution is the value of the volume of water delivered to the customer taps. Factors affecting the distribution of water are amount of water loss and amount of water sold. This paper implements of the use of backpropagation neural network to predict the amount of water distribution per month based on mentioned factors above. The learning phase is done to get the optimum number of iterations, learning rate, training data and test data, hidden node, and minimum error. The testing result shows the optimum number of iteration is 2,000, the optimum value of learning rate is 0.1, the optimum training data and test data as much as 80 for training data and 11 for the test data, the number of hidden node is 5, whereas the minimum error obtained is 0.00001. The results of testing by using these optimum parameter give the best accuracy of 97.99%.Keywords: prediction, water distribution, PDAM, backpropagation, water loss, water sold
Collaboration network of the authors
32 authors · 92 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- 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 |
|---|---|---|
| Imam Cholissodin | University of Brawijaya | 4 |
| Anang Hanafi | University of Brawijaya | 2 |
| Indriati Indriati | University of Brawijaya | 2 |
| Dany Primanita Kartikasari | University of Brawijaya | 1 |
| Yusi Tyroni Mursityo | University of Brawijaya | 1 |
| Nurul Hidayat | University of Brawijaya | 1 |
| Sutrisno . | Affiliation unknown | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Lailil Muflikhah | University of Brawijaya | 1 |
| Muhammad Syafiq | University of Brawijaya | 1 |
| Achmad Jafar Al Kadafi | University of Brawijaya | 1 |
| Rizka Husnun Zakiyyah | University of Brawijaya | 1 |
| Wanda Athira Luqyana | University of Brawijaya | 1 |
| Dhimas Anjar Prabowo | University of Brawijaya | 1 |
| Muhammad Fhadli | University of Brawijaya | 1 |
| Aryeswara Sunaryo | University of Brawijaya | 1 |
| M Fahrul Alam Yuniarsa | University of Brawijaya | 1 |
| Arrofi Reza Satria | University of Brawijaya | 1 |
| Luqman Hakim H | University of Brawijaya | 1 |
| Andri Santoso | University of Brawijaya | 1 |
| Nadia Artha Dewi | University of Brawijaya | 1 |
| Yoke Kusuma Arbawa | University of Brawijaya | 1 |
| Bayu Rahayudi | University of Brawijaya | 1 |
| Novanto Yudistira | University of Brawijaya | 1 |
| Nurfatima Selle | University of Brawijaya | 1 |
| Rizal Setya Perdana | University of Brawijaya | 1 |
| Firman Afrialdy | Affiliation unknown | 1 |
| Firman Afrialdy | Affiliation unknown | 1 |
| Candra Dewi | Affiliation unknown | 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.