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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JURIKOM (Jurnal Riset Komputer)
Eddy Bambang Soewono
Politeknik Negeri Bandung, Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Model ARIMA Terbaik Prediksi Latitude dan Longitude Kegiatan Kapal Imigran Ilegal Eddy Bambang Soewono; Maisevli Harika; Cahya Ramadhan; Muhammad Reyhan Soeharto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3301

Abstract

The migration of a person to another country without following the law is illegal immigration. Many problems are caused by this activity, ranging from population problems to increased crime. Predicting the emergence of ships carrying illegal immigrants can assist border patrols in planning patrols to planning defense equipment. Time series forecasting to predict the latitude and longitude of boats carrying illegal immigrants is the Autoregressive Integrated Moving Average (ARIMA) model. The case studies for this research are the Straits of Malacca and the Riau Islands. The prediction range is from one to four weeks to find the model with the smallest error. The ARIMA model for one-week prediction distance succeeded in obtaining the smallest RMSE. However, the smallest RMSE result (0.28730) was obtained for a four-week prediction distance with ARIMA model parameters (4,0,2) for longitude prediction. Meanwhile, the prediction of latitude. The best model is ARIMA (4,0,1), with an RMSE of 0.11457. For latitude and longitude predictions in the Riau Islands, the best models are ARIMA (3,0,0) with RMSE of 0.009074 and ARIMA (2,0,0) with RMSE 0.045815. Based on this study, the ARIMA model is suitable for predicting latitude and longitude data with a short prediction distance (one week)
Simulasi Reinforcement Learning untuk Kecerdasan Buatan pada Exergame Penurun Berat Badan Sofy Fitriani; Siti Dwi Setiarini; Eddy Bambang Soewono
JURIKOM (Jurnal Riset Komputer) Vol 9, No 1 (2022): Februari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i1.3875

Abstract

The pandemic of Coronavirus Disease 2019 (Covid-19) is still sweeping the globe. This is alarming, and it has a negative impact on physical activity outside the home. Weight gain is one of the issues that has arisen. Artificial intelligence simulation research is proposed for physical activity to help lose weight for it to be something fun with all its limitations. This simulation is going to be included in the game. This study focused on the physical activity carried out based on the results of artificial intelligence calculations to lose weight before being applied to the game. The approach is quantitative. To begin, conduct a literature review to determine the topic, machine learning methods, and calorie calculations for weight loss. Additionally, using reinforcement learning, a model for calculating the need is created for a caloric deficit. The waterfall method is used to model the calculation, which is then simulated in the system. The final stage is model validation, which involves utilizing the functionality correctness in accordance with system requirements. It produces 100 percent correct output based on the list of requirements, according to the tests that have been conducted.
Co-Authors Cahya Ramadhan Maisevli Harika Muhammad Reyhan Soeharto Siti Dwi Setiarini Sofy Fitriani