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All Journal Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Information System Journal (INFOS) Advance Sustainable Science, Engineering and Technology (ASSET)
Vikky Aprelia Windarni
universitas amikom yogyakarta
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Mathematics

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The Determination of Village Area in Semarang Regency Using The Circle Method Vikky Aprelia Windarni; Adi Setiawan
Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Vol 6, No 1 (2021)
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jm.v6i1.1876

Abstract

This research conducted a calculation of all villages area (253 villages) which located in Semarang regency. The data obtained is based on the data from GADM and Google earth by using the coordinate points (latitude and longitude). The research stage used were (1) finding the coordinate of villages boundaries in Semarang regency based on the data from GADM and Google Earth, (2) calculating the village area using two methods (Karney polygon method and circle method) and (3) analyzing the comparison of villages area based on each district and the reference area from Central Statistics Agency (BPS). The purpose of this research is the researchers would like to find out whether or not the Karney polygon method can be used to calculate the area of 253 villages in Semarang regency. From this research, it obtains the percentage difference with the lowest and highest percentage based on the data from GADM and Google Earth. The lowest percentage uses the Karney polygon method (GADM) of 7.63% and the highest percentage is 66.5%. The lowest percentage uses the circle method (GADM) is 14.39% and the highest percentage is 74.79%. The lowest percentage uses the Karney polygon method (Google Earth) is 7.63% and the highest percentage is 66%. The lowest percentage uses the circle method (Google Earth) is 15.87% and the highest percentage is 234%. MdAPE results for the data based on GADM using the Karney polygon method has the percentage of 18.73% and 35.19% by using the circle method. Based on Google Earth using the Karney polygon method, it has the percentage of 18.48% and 33.93% by using the circle method. It can be concluded that the Karney polygon method can be used to calculate the area of 253 villages in 19 districts in Semarang regency based on the data from GADM and Google Earth
Rain Prediction Using Rule-Based Machine Learning Approach Muchamad Taufiq Anwar; Saptono Nugrohadi; Vita Tantriyati; Vikky Aprelia Windarni
Advance Sustainable Science, Engineering and Technology (ASSET) Vol 2, No 1 (2020)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v2i1.6019

Abstract

Rain prediction is an important topic that continues to gain attention throughout the world. The rain has a big impact on various aspects of human life both socially and economically, for example in agriculture, health, transportation, etc. Rain also affects natural disasters such as landslides and floods. The various impact of rain on human life prompts us to build a model to understand and predict rain to provide early warning in various fields/needs such as agriculture, transportation, etc. This research aims to build a rain prediction model using a rule-based Machine Learning approach by utilizing historical meteorological data. The experiment using the J48 method resulted in up to 77.8% accuracy in the training model and gave accurate prediction results of 86% when tested against actual weather data in 2020.
DETEKSI WEBSITE PHISHING MENGGUNAKAN TEKNIK FILTER PADA MODEL MACHINE LEARNING Vikky Aprelia Windarni; Anggit Ferdita Nugraha; Surya Tri Atmaja Ramadhani; Dewi Anisa Istiqomah; Fiyas Mahananing Puri; Adi Setiawan
Information System Journal Vol. 6 No. 01 (2023): Information System Journal (INFOS)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/infosjournal.2023v6i01.1268

Abstract

Phishing merupakan bentuk serangan pada dunia maya yang cukup popular, dimana pengguna dibuat untukmengunjungi situs web yang tidak sah. Pengguna ditipu untuk mengungkapkan informasi pribadinya sepertiusername, password, informasi kartu kredit dan sebagainya. Maraknya phishing membuat kerugian dalam halprivacy, bahkan terjadi penyalahgunaan data yang menyebabkan kerugian finansial. Tujuan dari penelitian iniadalah peneliti ingin menggunakan machine learning dengan memanfaatkan fitur filter yang ada didalamnya yaitupearson correlation dan menerapkan 3 metode Naïve Bayes, Decision Tree dan Random Forest untuk menentukanmetode yang paling efektif dalam mendeteksi web phishing. Terdapat 4 alur penelitian yang digunakan olehpeneliti, yaitu (1) Tahap persiapan, (2) Metode yang digunakan, (3) Analisa, dan (4) Evaluasi. Dari hasil penelitianini didapatkan bahwa penerapan metode Naïve Bayes memiliki nilai akurasi sebesar 60,4%, metode Decision Treememiliki nilai akurasi 94,4% dan metode Random Forest memiliki akurasi sebesar 96,3%. Sehingga dapatdisimpulkan bahwa metode yang paling efektif untuk mendeteksi web phishing adalah menggunakan RandomForest karena memiliki tingkat akurasi sebesar 96.3%. Pada penelitian selanjutnya dapat dilakukan pada kasusyang sama dengan menggunakan algoritma yang berbeda.
Co-Authors Adi Setiawan Anwar, Muchamad Taufiq Dewi Anisa Istiqomah Fiyas Mahananing Puri Nugraha, Anggit Ferdita Saptono Nugrohadi Surya Tri Atmaja Ramadhani Vita Tantriyati