Post on 30-Nov-2021
Sistem Deteksi Bencana Banjir Menggunakan Algoritma Naïve Bayes dan
Modul Komunikasi NRF24L01 Berbasis IOT
Tugas Akhir
Diajukan Untuk Memenuhi
Persyaratan Guna Meraih Gelar Sarjana Strata I
Informatika Universitas Muhammadiyah Malang
Rizky Rahmad Andre Anang
( 201510370311179 )
Jaringan
PROGRAM STUDI INFORMATIKA
FAKULTAS TEKNIK
UNIVERSITAS MUHAMMADIYAH MALANG
2020
vii
KATA PENGANTAR
Segala puji bagi Allah SWT, yang telah memberi Rahmat serta Karunianya, sehingga
penulis dapat menyelesaikan skripsi yang berjudul:
“Sistem Deteksi Bencana Banjir Menggunakan Algoritma Naïve Bayes dan
Modul Komunikasi NRF24L01 Berbasis IOT”
Skripsi ini merupakan salah satu syarat studi yang harus ditempuh oleh seluruh
mahasiswa Universitas Muhammadiyah Malang, guna menyelesaikan akhir studi pada jenjang
program Strata 1.
Peneliti menyadari masih banyak kekurangan dan keterbatasan dalam penulisan tugas
akhir ini. Untuk itu, penulis sangat mengharapkan saran yang membangun agar tulisan ini dapat
berguna untuk perkembangan ilmu pengetahuan kedepan.
Malang, 7 Agustus 2020
Penulis
Rizky Rahmad Andre Anang
viii
DAFTAR ISI ABSTRAK…………………………………………………………………………………...iv
ABSTRACT…………………………………………………………………………………..v
BAB I PENDAHULUAN……………………………………………………………………...1
1.1 Latar Belakang ................................................................................................................. 1
1.2 Rumusan Masalah ............................................................................................................ 3
1.3 Tujuan Penelitian ............................................................................................................. 4
1.4 Batasan Masalah .............................................................................................................. 4
1.5 Sistematika Penulisan ...................................................................................................... 4
BAB II TINJAUAN PUSTAKA………………………………………………………………6
2.1 Penelitian Sebelumnya ..................................................................................................... 6
2.2 Sistem Deteksi Banjir ...................................................................................................... 6
2.3 Algoritma Naïve Bayes .................................................................................................... 7
2.4 Internet of Things ............................................................................................................. 8
2.5 Modul Komunikasi NRF24L01 ....................................................................................... 9
2.6 Arduinno Uno ................................................................................................................ 10
2.7 Sensor Ultrasonik ........................................................................................................... 10
2.8 Sensor Water flow .......................................................................................................... 11
2.9 Arduino IDE................................................................................................................... 12
2.10 Python .......................................................................................................................... 12
2.11 Sublime Text ................................................................................................................ 12
2.12 Xampp .......................................................................................................................... 13
2.13 MYSQL........................................................................................................................ 13
2.14 CodeIgniter .................................................................................................................. 13
2.15 Pengujian Sensor Ultrasonik ........................................................................................ 13
2.16 Packet loss ................................................................................................................... 14
2.17 Delay ............................................................................................................................ 14
2.18 Pengujian Accuracy, Recall, dan Precision ................................................................. 14
BAB III METODE PENELITIAN…………………………………………………………...16
3.1 Metodologi Penelitian .................................................................................................... 16
3.2 Identifikasi Masalah ...................................................................................................... 17
3.3 Analisis Sistem............................................................................................................... 17
3.4 Persiapan Data ............................................................................................................... 17
3.5 Perancangan Sistem Deteksi Banjir ............................................................................... 18
3.5.1 Perangkat keras ....................................................................................................... 18
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3.5.2 Perangakat Lunak.................................................................................................... 18
3.5.3 Arsitektur Sistem .................................................................................................... 19
3.5.4 Perancangan Perangkat Keras ................................................................................. 20
3.5.5 Perancangan Proses Pendeteksi Banjir .................................................................. 21
3.5.6 Algoritma Naïve Bayes untuk Klarifikasi Sistem Deteksi Banjir .......................... 25
3.6 Perancangan atau skenario pengujian ............................................................................ 28
3.6.1 Pengujian sistem ..................................................................................................... 28
3.6.2 Pengujian Sensor Ultrasonik ................................................................................... 28
3.6.3 Pengujian QoS( Quality of System )....................................................................... 28
3.6.4 Pengujian Accuracy, Recall, dan Precision ............................................................ 29
3.6.5 Perancangan Prototipe ........................................................................................... 29
3.6.6 Tampilan Antar Muka Web .................................................................................... 30
BAB IV HASIL DAN PEMBAHASAN……………………………………………………..31
4.1. Implementasi ................................................................................................................. 31
4.1.1 Sensor Node ............................................................................................................ 31
4.1.2 Sink Node................................................................................................................ 33
4.1.3 Server ...................................................................................................................... 35
4.1.4 Implementasi Algoritma Naïve Bayes .................................................................... 36
4.1.5 Antar Muka Web Untuk Monitoring Data .............................................................. 37
4.2 Pengujian........................................................................................................................ 38
4.2.1 Pengujian Sensor ultrasonik .................................................................................... 38
4.2.2 Pengujian Quality of Service ( QoS ) ...................................................................... 40
4.2.2.1 Pengujian Packet Loss ..................................................................................... 40
4.2.2.2 Pengujian Delay ............................................................................................... 41
4.2.3 Pengujian Algoritma Naïve Bayes .......................................................................... 42
BAB V PENUTUP….………………………………………………………………………..44
5.1 Kesimpulan .................................................................................................................... 44
5.2 Saran .............................................................................................................................. 44
DAFTAR PUSTAKA………………………………………………………………………...45
LAMPIRAN………………………………………………………………………………….48
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DAFTAR GAMBAR
Gambar 2.1 Sistem Pendeteksi Banjir Berbasis Sensor Ultrasonik Dan Mikrokontroler Dengan
Media Komunikasi Sms Gate Way [17] ............................................................................ 7
Gambar 2.2 Sistem Peringatan Dini Banjir Secara Real-Time Berbasis Web Menggunakan
Arduino dan Ethernet [15] ................................................................................................. 9
Gambar 2.3 Bentuk Fisik NRF24L01 ........................................................................................ 9
Gambar 2.4 Bentuk Fisik Arduino Uno ................................................................................... 10
Gambar 2.5 Bentuk Fisik Sensor Ultrasonik ........................................................................... 10
Gambar 2.6 Pemantulan Gelombang Ultrasonik ..................................................................... 11
Gambar 2.7 Bentuk Fisik Sensor Water Flow ......................................................................... 11
Gambar 3.1 Tahapan Metode Penelitian .................................................................................. 16
Gambar 3.2 Arsitektur Sistem Deteksi Banjir Menggnakan Algoritma Naïve Bayes dan Modul
Komunikasi NRF24L01 Berbasis IOT ............................................................................ 19
Gambar 3.3 Rangkain semua komponen mikrokontroller ....................................................... 20
Gambar 3.4 Penempatan Komponen Perangkat Keras Sistem Deteksi Banjir ........................ 21
Gambar 3.5 Proses pengambilan data dan pengiriman data pada sensor node ....................... 22
Gambar 3.7 Proses Server Mengolah Data pada Sistem Deteksi Banjir ................................. 24
Gambar 3.8 Alur Sistem Deteksi Bencana Banjir dengan Menggunakan Algoritma Naïve
Bayes ................................................................................................................................ 25
Gambar 3.9 Tahap Learning Algoritma Naïve Bayes ............................................................. 26
Gambar 3.10 Tahap Testing Algoritma Naïve Bayes .............................................................. 27
Gambar 3.11 Pengujian sensor Ultrasonik............................................................................... 28
Gambar 3.12 Perancangan Prototipe Sistem Deteksi Banjir ................................................... 29
Gambar 3.13 User Interface Web Sistem Deteksi banjir ......................................................... 30
Gambar 4.1 Perangkat Sensor Node ........................................................................................ 31
Gambar 4.2 Kode Program insiliasi port dan pin address pada sensor Ultrasonik, Sensor Water
Flow dan Modul Komunikasi NRF24L01 Transmitter ................................................... 32
Gambar 4.3 Kode Program Monitoring Data pada Sensor Node digunakan Sensor Ultrasonik
dan Sensor Water flow ..................................................................................................... 32
Gambar 4.4 Perangkat Arduino dan Modul Komunikasi NRF24L01 pada Sink Node ........... 33
Gambar 4.5 Kode Program library dan Inisialisasi port, pin dan alamat pada Modul
Komunikasi NRF24L01 Receiver.................................................................................... 34
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Gambar 4.6 Kode Program Sink Node Menerima Pangambilan Data Ketingian air dan Debit
Air Sensor Node ............................................................................................................... 34
Gambar 4.7 Perangakat Sink Node menerima data dari sensor Node Berupa data Tinggi Muka
Air dan Debit Air ............................................................................................................. 35
Gambar 4.8 Kode Program Menghubungkan Sink Node ke Database .................................... 35
Gambar 4.9 Data yang di Terima Sink Node dimasukan ke Database .................................... 36
Gambar 4.10 Database Sistem Deteksi Banjir ......................................................................... 36
Gambar 4.11 Tahap Modeling Dataset dari Jasa Tirta ............................................................ 37
Gambar 4.12 File Pickle Modeling Algoritma Naïve Bayes Untuk Pembantu Keputusan
Terjadinya Banjir di Sungai ............................................................................................ 37
Gambar 4.13 Tampilan Antar Muka Aplikasi Web Sistem Deteksi Banjir Menggunakan
Algoritma Naïve Bayes .................................................................................................... 38
Gambar 4.14 Grafik pengujian Sensor Ultrasonik ................................................................... 39
Gambar 4.15 Pengujian QoS Packet Loss ............................................................................... 40
Gambar 4.16 Pengujian QoS Delay ......................................................................................... 42
Gambar 4.17 hasil pengujian Algoritma Naïve Bayes ............................................................. 42
DAFTAR TABEL
Tabel 4.1 Tabel Pengujian Sensor Ultrasonik .......................................................................... 39
Tabel 4.2 Pengujian QoS Packet Loss pada NRF24L01 ......................................................... 40
Tabel 4.3 Pengujian QoS Delay pada NRF24L01 ................................................................... 41
45
DAFTAR PUSTAKA
[1] Scifo, F., & Setiyono, B. (2014). Monitoring Level Air dan Peringatan Dini Bahaya
Banjir Berbasis SMS.
[2] Ariyani, D. R., & Putri, R. E. (2017). Sistem Monitoring Banjir Pada Jalan
Menggunakan Aplikasi Mobile Dan Modul Wi-Fi, (November), 1–2.
[3] Abdullah, R. K., & Utami, E. (2018). Studi Komparasi Metode SVM dan Naive Bayes
pada Data Bencana Banjir di Indonesia pembaca ataupun peneliti bisa melihat pola
yang tersembunyi di Indonesia.
[4] Widiastuti, D., Informasi, J. S., & Gunadarma, U. (2007). Analisa Perbandingan
Algoritma Svm , Naive Bayes , Dan Decision Tree Dalam Mengklasifikasikan
Serangan ( Attacks ), 1–8.
[5] Aminah, S., Bandung, P. M., Sunarya, A. S., & Bandung, P. M. (2016). Perancangan
Sistem Peringatan Dini Tanah Longsor Berbasis Perubahan Resistivitas Tanah dengan
Menggunakan Arduino MEGA 2560 dan WeMos ESP8266 D1-MINI, (April 2018).
[6] Putra, R., . Z., Madona, E., & Nasution, A. (2018). Desain dan Implementasi Peringatan
Dini Banjir Menggunakan Data Mining dengan Wireless Sensor Network. Jurnal
Nasional Teknik Elektro, 5(2), 181. https://doi.org/10.25077/jnte.v5n2.261.2016
[7] Yuzria, H. O., Pesma, R. A., Dahlan, D., Harmadi, H., Shadri, M., & Wildian, W.
(2017). Rancang Bangun Sistem Peringatan Dini Banjir Menggunakan Telemetri
Nikabel Dengan Transceiver nRF24L01+. Jurnal Ilmu Fisika | Universitas Andalas,
9(1), 57–67. https://doi.org/10.25077/jif.9.1.57-67.2017
[8] Al-gaufiqy, M., Rasmana, S., & Puspasari, ira. (2017). Journal of Control and Network
Systems. Journal of Control and Network Systems, 6(1), 73–86. https://doi.org/1.
octavianus 2. jusak 3. anjik sukmaaji.
[9] Bangun, R., Deteksi, S., & Banjir, L. (2018). Lilian Efendi *, Wildian, 7(4), 328–333.
[10] Wulandari, R. (2018). Analisis Qos (Quality Of Service) Pada Jaringan Internet (Studi
Kasus : Upt Loka Uji Teknik Penambangan Jampang Kulon – Lipi). Jurnal Teknik
46
Informatika Dan Sistem Informasi, 2(2), 162–172.
https://doi.org/10.28932/jutisi.v2i2.454.
[11] Kurniawan, Y. I., Surakarta, U. M., & Bayes, N. (2018). Comparison of Naive Bayes
and C. 45 Algorithm in Data Mining, 5(4), 455–464. https://doi.org/10.25126/jtiik.
[12] Vafeiadis, T., Diamantaras, K. I., Sarigiannidis, G., & Chatzisavvas, K. C. (2015). A
comparison of machine learning techniques for customer churn prediction. Simulation
Modelling Practice and Theory. https://doi.org/10.1016/j.simpat.2015.03.003
[13] Wulandari, R. (2018). ANALISIS QoS (QUALITY OF SERVICE) PADA JARINGAN
INTERNET (STUDI KASUS : UPT LOKA UJI TEKNIK PENAMBANGAN
JAMPANG KULON – LIPI). Jurnal Teknik Informatika Dan Sistem Informasi, 2(2),
162–172. https://doi.org/10.28932/jutisi.v2i2.454
[14] Shorina, U. J., Primananda, R., & Maulana, R. (2018). Analisis Kinerja Pengiriman
Data Modul Transceiver NRF24l01, Xbee dan Wifi ESP8266 Pada Wireless Sensor
Network. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(4),
1510–1517.
[15] Satria, D., Yana, S., Munadi, R., & Syahreza, S. (2017). Peringatan Dini Banjir. Jurnal
Teknologi Informasi Dan Komunikasi, 1(1), 1–6.
[16] Sulistyowati, R., Sujono, H. A., Khamdi, A., Jurusan, M., Elektro, T., Industri, F. T.,
… Uckun, S. (2013). Sensor Validation using {Bayesian} Networks. Sistem Pendeteksi
Dini Banjir Menggunakan Sensor Kecepatan Air Dan Sensor Ketinggian Air Pada
Mikrokontroler Arduino, 2(1), 1–5. https://doi.org/10.1109/ISMAR.2009.5336489
[17] Informatika, J. T., & Informasi, F. T. (2015). Sistem Pendeteksi Banjir Berbasis Sensor
Ultrasonik Dan Mikrokontroler, 49–58.
[18] Liliana, D. Y. (2015). Pengembangan Aplikasi Pendeteksi Potensi Bencana Gunung
Berapi Menggunakan Pengklasifikasi Bayesian. Multinetics, 1(1), 15.
https://doi.org/10.32722/multinetics.vol1.no.1.2015.pp.15-18
47
[19] Shorina, U. J., Primananda, R., & Maulana, R. (2018). Analisis Kinerja Pengiriman
Data Modul Transceiver NRF24l01, Xbee dan Wifi ESP8266 Pada Wireless Sensor
Network. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(4), 1510–
1517.
[20] Sugiyanto, & annas marzuki, S. (2016). Perancangan Web sebagai Media Penjualan
Online, (September), 40–45.
[21] Iqbal Maulan Tanjung. (2011). Analisis Dan Perancangan Sistem Informasi Berbasis
Website Menggunakan Arsitektur Mvc Dengan Framework Codeigniter. Sekolah
Tinggi Manajemen Informatika Dan Komputer Amikom Yogyakarta.