Implementasi algoritma Autoregressive Moving Average dalam megukur kejadian kriminalitas berdasarkan data media online

Pebbi Pratama Putra S, Rsyidah siregar, Arief Budiman

Abstract


Criminal acts are increasing day by day and have significant social effects. Online information media is a daily source of information that contains articles on criminal acts that can be read by citizens or the public in Indonesia. Several online information media portals such as okezone.com, Tribunnews.com, kompas.com and detik.com have become the most frequently accessed online information media. The problem in this study will be to find out the criminal rate based on the data from the crawling of news media online media that has been obtained with the crawling technique, the results of the crawling will be analyzed using the Autoregressive Moving Average algorithm so that the crime rate is known based on the data of online media media. The purpose of this study is to measure the crime rate based on news articles published in online information media in Indonesia so that it can be known and compared to police data obtained from the Central Statistics Agency. In achieving this goal, the crawled data in the form of criminal category data will be used to predict the criminal rate.

Keywords


Prediction;criminal;algorithm

Full Text:

PDF

References


Aini, N., Sinurat, S., & Hutabarat, S. A. (2018). Penerapan Metode Simple Moving Average Untuk Memprediksi Hasil Laba Laundry Karpet Pada Cv. Homecare. Jurikom (Jurnal Riset Komputer), 5(2), 167–175.

Damayanti, F. N., Piarsa, I. N., & Sukarsa, I. M. (2016). Sistem Informasi Geografis Pemetaan Persebaran Kriminalitas Di Kota Denpasar. Merpati, 4(1), 22–32. Https://Doi.Org/10.24843/Jim

Dulkiah, M., & Nurjanah. (2018). Pengaruh Kemiskinan Terhadap Tingkat Tindak Kriminalitas Di Kota Bandung. Jurnal Ilmu Sosial Dan Ilmu Politik, 8(2), 57.

Pratibha, Gahalot, A., Uprant, Dhiman, S., & Chouhan, L. (2020). Crime Prediction And Analysis. 2nd International Conference On Data, Engineering And Applications, Idea 2020. Https://Doi.Org/10.1109/Idea49133.2020.9170731

Putra, R. S. (2016). Kriminalitas Di Kalangan Remaja (Studi Terhadap Remaja Pelaku Pencabulan Di Lembaga Pemasyarakatan Anak Kelas Ii B Pekanbaru). Jurnal Ilmu Komunikasi, 3(2), 1–15. Https://Media.Neliti.Com/Media/Publications/127491-Id-Pengaruh-Bauran-Promosi-Terhadap-Minat-B.Pdf

Taram, Nyoman Gde. (2019). Pengelompokan Tingkat Kriminalitas Dengan Metode Agglomerative Dan K-Means Serta Peubah Pencirinya. E-Jurnal Matematika, 8(2), 102. Https://Doi.Org/10.24843/Mtk.2019.V08.I02.P241

Ainun Faulina, N. (2020). Perbandingan Metode Arimax Dan Varimax Untuk Peramalan Jumlah Penumpang Kereta Api Menurut Wilayah. Muhammadiyah University, Semarang.

Annur, H. (2018). Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes. Ilkom Jurnal Ilmiah, 10(2), 160–165.

Arief, S., Imam, S., & Laela, N. (2019). Mekanisme Pembuatan Flowchart Penerimaan Pinjaman (Angsuran) Pada (Bumdes) Di Desa Pomahan Kecamatan Pulung Kabupaten Ponorogo. Jurnal Abdikarya: Jurnal Karya Pengabdian Dosen Dan Mahasiswa, 3(3).

Budi, S. (2017). Text Mining Untuk Analisis Sentimen Review Film Menggunakan Algoritma K-Means. Techno. Com, 16(1), 1–8.

Dewi, S. N., Cholissodin, I., & Santoso, E. (2018). Prediksi Jumlah Kriminalitas Menggunakan Metode Extreme Learning Machine ( Studi Kasus Di Kabupaten Probolinggo ). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer (J-Ptiik) Universitas Brawijaya, 2(11), 4687–4693.

Ensmenger, N. (2016). Information & Culture, 51(3), 321–351.




DOI: https://doi.org/10.30865/komik.v6i1.5785

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Pebbi Pratama Putra S, Rsyidah siregar, Arief Budiman

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.


KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)
P3M STMIK Budi Darma
Sekretariat Jln. Sisingamangaraja No. 338 Telp 061-7875998
email: komik@univ-bd.ac.id, komik.budidarma@gmail.com

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.