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All Journal Journal of System and Computer Engineering Indonesian Journal of Intellectual Publication (IJI Publication) Madani: Multidisciplinary Scientific Journal Sentra Dedikasi: Jurnal Pengabdian Masyarakat Indonesian Journal of Intellectual Publication (IJI Publication)
Rimalia, Watty
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Journal : Madani: Multidisciplinary Scientific Journal

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Implementasi Algoritma Machine Learning untuk Forecasting Demand Pada Usaha Kerupuk Sehat Krusawi Wijaya, Neti Septi; Usman, Syahrul; Iskandar, Imran; Rimalia, Watty; Syam, Rahmat Fuady
Madani: Jurnal Ilmiah Multidisiplin Vol 4, No 1 (2026): February 2026
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18358038

Abstract

The rapid development of information technology has encouraged business actors to utilize data analysis to improve efficiency and competitiveness, one of which is through demand forecasting. This study aims to implement machine learning algorithms to forecast product demand in the Krusawi Healthy Crackers business. The method employed is Prophet, which was selected due to its capability to handle time series data with nonlinear trends and seasonal patterns. The data used consist of historical daily sales data from April to July 2024, which were subsequently aggregated into weekly data. The research stages include data collection, data preprocessing (data aggregation, handling missing values, and Box-Cox transformation), Prophet model design with logistic growth and custom bi-monthly seasonality, model training, and performance evaluation. The results indicate that the Prophet model provides excellent forecasting performance, achieving a Mean Absolute Percentage Error (MAPE) of 6.57% or an accuracy level of 93.43%. The model successfully captures trend and seasonal patterns in Krusawi product sales. Therefore, the implementation of machine learning algorithms using the Prophet method proves to be a reliable solution for supporting production planning and inventory management in the Krusawi healthy crackers business, and has the potential to improve operational efficiency and business decision-making.
Implementasi Aplikasi Monitoring Suhu dan PH Air Akuarium Berbasis IoT Menggunakan ESP32 Nurfajry, Muh. Awal; Leonard, Benny; Iskandar, Imran; Rimalia, Watty; Suwardoyo, Untung
Madani: Jurnal Ilmiah Multidisiplin Vol 4, No 1 (2026): February 2026
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18358467

Abstract

Water quality is an important factor in maintaining the health and survival of ornamental fish in an aquarium. The main parameters that affect water quality are temperature and acidity level (pH). Manual monitoring of these parameters has limitations; therefore, a monitoring system capable of operating in real time and continuously is required. This study aims to design and implement an Internet of Things (IoT)–based aquarium water temperature and pH monitoring application using an ESP32 microcontroller. The system utilizes a DS18B20 temperature sensor and a pH sensor to measure aquarium water conditions, after which the collected data are transmitted to a Firebase database and displayed on a web-based monitoring dashboard in real time. The research methodology includes system design, hardware and software implementation, and system functionality testing. The results show that the developed system is able to monitor aquarium water temperature and pH accurately and in real time, thereby facilitating users in monitoring water quality. With the implementation of this system, aquarium management is expected to become more effective and to optimally support fish health.
Co-Authors Fadliana, Nurul Herianto, Dedy Iriany, Rosary Iskandar, Imran Jeffry Jeffry Leonard, Benny Nur Hamdani Nur Nurfajry, Muh. Awal Nurul Ahyana Panggabean, Benny Leonard Panggabean, Benny Leonard Enrico Syahrul Usman Syam, Rahmat Fuady Tenriana, Nuzul Untung Suwardoyo Wijaya, Neti Septi