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All Journal Foristek ScientiCO : Computer Science and Informatics Journal Indonesian Journal of Electrical Engineering and Computer Science
Indrajaya, Muhammad Aristo
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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RANCANG BANGUN E-SUPPLY CHAIN MANAGEMENT SYSTEM PADA BRIGHT GAS PERTAMINA MENGGUNAKAN METODE DISTRIBUTION REQUIREMENT PLANNING (DRP) Ngemba, Hajra Rasmita; Syahrullah, Syahrullah; Indrajaya, Muhammad Aristo; Hendra, Syaiful; Lakatjinda, Adiatma
ScientiCO : Computer Science and Informatics Journal Vol 4, No 2 (2021): Scientico : November
Publisher : Fakultas Teknik, Universitas Tadulako

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

Abstract

Proper handling of problems is needed to support distribution activities. E-SCM or Electronic Supply Chain Management is a collaborative use of technology and strategic management to improve speed, performance, real-time monitoring of business processes aimed at integrating combined productive capacity and other resources in a supplier network system (Supply Chain System) through technology. Internet. The development of this system uses an extreme programming model by building Android-based applications that can only be run on mobile devices using at least the Android 5.0 Lollipop operating system. System testing will be tested with Blackbox and User Acceptance. The results of this study are the distribution system design with DRP can minimize the number of orders because the number of orders is optimal so that orders do not need to be made every week.
Classification of weather conditions based on automatic weather station data using a multi-layer perceptron neural network Indrajaya, Muhammad Aristo; Sollu, Tan Suryani; Subito, Mery; Rahman, Yuli Asmi; Saputra, Erwin Ardias
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp540-550

Abstract

Weather is one of the important elements that greatly determines human activities, especially those related to economic factors. Therefore, understanding weather conditions using weather parameters as a reference is important for human life, so a method is needed to classify weather according to its category so that the information produced can be used for various needs. Determining weather conditions in an area will not run well without a reliable method that can analyze existing weather parameters. Therefore, in this study, the weather condition classification process was carried out using the multilayer perceptron algorithm, a type of neural network (NN) algorithm. All data analyzed were weather parameter data collected by mini weather stations placed on land. The weather parameters used were temperature, humidity, air pressure, wind speed, dew point, wind chill, daily rainfall, solar radiation, and UV index. This study was conducted in Palu city, Central Sulawesi Province, Indonesia. The classification process carried out by the multilayer perceptron algorithm was carried out on the Altair AI Studio application and produced an accuracy value of 93.87%, recall of 92.33%, and precision of 91.29%.
LINE TRACER PENYORTIR BARANG DENGAN QR CODE SEBAGAI PENGENALAN POSISI TARGET Putra, Wisnu Rahmat Dwi; Fauzi, Rizana; Ardias, Erwin; Subito, Mery; Indrajaya, Muhammad Aristo; Rahman, Yuli Asmi
Foristek Vol. 15 No. 1 (2025): Foristek
Publisher : Foristek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54757/fs.v15i1.752

Abstract

Robotic-based sorting systems offer an innovative solution to enhance efficiency and accuracy in the logistics industry. This research aims to design and implement a robotic system capable of automatically sorting goods by integrating barcode scanning technology and line tracer navigation. The system is built using an Arduino Mega 2560 as the main controller and is equipped with Stepper motors, DC motors, mecanum wheels, a GM65 barcode scanner, and various supporting actuators.Experimental results show that the GM65 sensor can optimally read barcodes at distances ranging from 15 to 55 cm. The servo motor demonstrates an accuracy rate of over 98%, while the Stepper motor performs optimally at a minimum voltage of 9.0 V. Additionally, line sensor calibration yields a threshold range between 528 and 573, ensuring accurate line detection. The system also exhibits stable movement with consistent speed and minimal travel time variation, indicating efficient operational performance.By integrating these technologies, the developed robotic sorter system significantly improves productivity, accuracy, and reliability in automated goods sorting processes. The implementation of this system is expected to support automation in the logistics sector and provide a practical solution to distribution management challenges in the era of Industry 4.0.
Co-Authors Ardias, Erwin Erwin Ardias Saputra Hajra Rasmita Ngemba Lakatjinda, Adiatma Mery Subito Putra, Wisnu Rahmat Dwi Rizana Fauzi, Rizana Syahrullah Syahrullah Syaiful Hendra Tan Suryani Sollu Yuli Asmi Rahman