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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) JOMLAI: Journal of Machine Learning and Artificial Intelligence
Irawan Irawan
STIKOM Tunas Bangsa, Pematangsiantar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Analisa Datamining dengan Metode Klasifikasi C4.5 Sebagai Faktor Penyebab Tanah Longsor Afrialita Widiastari; Solikhun Solikhun; Irawan Irawan
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Landslides are geological events where soil movement occurs such as falling rocks or large lumps on the ground. Landslides often occur when it rains, although not always. In addition, landslides generally occur in areas with steep slopes. With the C4.5 method it can be used to classify data that has numeric and categorical attributes. The results of the classification process in the form of rules can be used to predict the value of the discrete type attribute from a new record. Data obtained from the National Disaster Management Agency regarding the factors causing landslides can produce an accuracy value of 77.78%, meaning that the resulting rules or rules are close to 100%, it can be concluded that to classify the factors causing landslides using C4.5 by looking at the node the highest is slope. To find out these factors can provide input to the Disaster Management Agency to be more concerned with the factors that caused the landslides
Penerapan Data Mining Dalam Mengelompokkan Calon Penerima Beasiswa Dengan Menggunakan Algoritma K-Means Nur Afriani Manihuruk; Muhammad Zarlis; Eka Irawan; Heru Satria Tambunan; Irawan Irawan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 4, No 1 (2020): The Liberty of Thinking and Innovation
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v4i1.2575

Abstract

Penelitian ini bertujuan untuk mencari pengelompokkan data yang ada pada siswa yang berhak menerima beasiswa. Penyaluran beasiswa yang berasal dari keluarga yang kurang mampu harus dapat melalui seleksi yang melibatkan kriteria-kriteria tertentu. Kriteria tersebut seperti kondisi rumah, nilai raport, status rumah. Algoritma K-Means dapat membantu untuk mengklasifikasi siswa-siswi yang sangat layak untuk berupa mendapatkan bantuan berupa beasiswa. Adapun tujuan yang ada pada penelitian ini adalah menentukan clustering penerima beasiswa sehingga dapat memberikan rekomendasi yang layak, layak dengan pertimbangan dan kurang layak untuk menerima beasiswa dengan 4 kriteria. Data set yang digunakan sebanyak 128 siswa yang berasal dari sekolah SMP Muhammadiyah 54 Kerasaan. Data-data tersebut dapat dihitung dengan menggunakan algoritma K-Means dan pengujian dapat dilakukan melalui aplikasi RapidMiner 5.3. Metode K-Means berusaha mengelompokkan data yang ada kedalam beberapa kelompok, dimana data dalam satu kelompok mempunyai karakteristik yang sama satu sama lainnya dan mempunyai karakteristik yang berbeda dengan data yang ada didalam kelompok yang lain. Hasil penelitian diperoleh C1:73Item, C2:30Item, C3:25Item. Dari hasil analisis diharapkan dapat membantu pemahaman siswa yang berhak menerima beasiswa. Kata kunci: Data Mining, Metode K-Means, Pengelompokkan Penerima Beasiswa
Implementation of the Weighted Moving Average Method for Forecasting the Production of Manila Duck meat in Indonesia Diana Pratiwi; Riki Winanjaya; Irawan Irawan
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 3 (2022): September
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (723.134 KB) | DOI: 10.55123/jomlai.v1i3.916

Abstract

Manila duck is a waterfowl originating from South America, through the Philippines this type of duck entered Indonesia and has a large distribution in various regions of Indonesia the production on manila duck meat and from 2019-2020 has decreased due to the covid-19 pandemic which resulted in economic difficulties. And the lack of demand from restaurants and households so that the amount of production decrease. However, in 2020-2021 production will increase due to the relaxation from the previous pandemic and the demand and marketing has increased to that the number of production has increased from the previous year. The Weighted Moving Average method is a method used to determine the latest trend with a moving average value. The purpose of this study was to analyses the amount of production of manila duck meat in solving the problem. The result obtained with the smallest error percentage are at F128 in the province of North Maluku with MAPE value of 0,003 or equal to 0,3% with a bias of -0,25, MAD 0,25, MSE 0,06, with a forecasting value of 83,29 which is close to the original data, namely 83,04 so that the forecast value for 2022 is 83,24 tons.
Co-Authors Afrialita Widiastari Diana Pratiwi Eka Irawan Heru Satria Tambunan Muhammad Zarlis Nur Afriani Manihuruk Solikhun Solikhun Winanjaya, Riki