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All Journal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika JISA (Jurnal Informatika dan Sains)
Irawan, Lukman
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science

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ANALISA PREDIKSI EFEK KERUSAKAN GEMPA DARI MAGNITUDO (SKALA RICHTER) DENGAN METODE ALGORITMA ID3 MENGGUNAKAN APLIKASI DATA MINING ORANGE Irawan, Lukman; Hasibuan, Liyando Hermawan; Fauzi, Fauzi
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 14 No. 2 (2020): Jurnal Teknologi Informasi Jurnal Keilmuan dan Aplikasi Bidang Teknik Informat
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v14i2.1079

Abstract

Earthquakes are relatively common natural disasters in Indonesia, mainly due to the interaction of tectonic plates. In this study the seismic energy recorded on the seismograph was measured on the Richter Scale (SR). The dataset collected during Semester 1 of 2019 from the Meteorology and Geophysics, Climatology Agency (BMKG) noted that there were many seismic energy vibrations occurring from small to large around Indonesia. Furthermore, for the attributes of the dataset that have been collected include Date / Time, Longitude, Latitude, Depth (Km), Magnitude (SR), Range of depth (Km) and the effect of earthquake damage selected as the class of the dataset collected, in this study the authors used the method classification with ID3 algorithm to produce effective prediction data for the benefit of earthquake early warning in the Indonesian archipelago.
PREDICTION OF INCOMING ORDERS USING THE LONG SHORT-TERM MEMORY METHOD AT PT. XYZ Irawan, Lukman; Fauzi, Fauzi; Andwiyan, Denny
JISA(Jurnal Informatika dan Sains) Vol 4, No 1 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i1.902

Abstract

Currently the need for domestic packaging paper continues to increase, driven by the level of consumer awareness about sustainable packaging. PT XYZ is a local company engaged in the Corrugated Cardboard Box (KKG) industry. So far, the problems in fulfilling incoming orders every month are not optimal with an average of about 30% inaccuracy. This is because the orders that enter cannot be predicted. As an effort to win market competition in packaging paper, PT. XYZ must improve the fulfillment of incoming orders by predicting incoming orders using the Long Short-Term Memory (LSTM) method. The aim of this research is to provide a predictive model for incoming orders in accordance with the needs of order fulfillment to be applied to production planning. So that order fulfillment can be on time. The method used in predicting incoming orders is the Long Short-Term Memory (LSTM) method using weighting evaluations with the lowest Root Mean Squared Error (RMSE) and Augmented Dickey-Fuller test (ADF). The test results of the LSTM method with parameter sizes of Batch: 1 Epochs: 5000 Neurons: 1 show that the RMSE for MDM products is 8.767582 and 0.287924, LNR products are 10.623984 and 0.466621, WTP products are 1.636849 and 0.361515 lower than the size of the fit parameters for other LSTM models, and the ADF Statistic value for MDM products -6.137597, LNR -6.753697, WTP -4.872927
Co-Authors Andwiyan, Denny Fauzi Fauzi Hasibuan, Liyando Hermawan