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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan)
Marwanto Rahmatuloh
Universitas Logistik dan Bisnis Internasional
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Implementasi Algoritma FIFO (First In First Out) Pada Sistem Pergudangan Di Bagian Furniture Production Muhammad Ruslan Maulani; Supriady; Marwanto Rahmatuloh; Indah Triapriliani; Hafidzul Fauzan
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 9 No. 2 (2023)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol9.iss2.2023.1011

Abstract

CV Manis Maqbul Jaya is a Specialist Interior Design company, Furniture Production, Contractor Consultant and Kitchen Set Design. In the warehousing process carried out by CV Manis Maqbul Jaya, they still use the manual method, namely the process of goods entering the warehouse and the process of goods leaving the warehouse by recording using a book. Warehousing is used for the storage of goods, namely raw materials and finished goods (Production). The recording of manual inventory updates causes the accumulation of transaction data for incoming and outgoing goods, due to delays in delivering information from store clerks and production officers to warehouse officers or vice versa. so that the process of releasing goods is carried out not based on storage or expiration dates, resulting in damaged or expired old goods. These problems can be overcome by creating a warehousing application using the FIFO (First in First Out) method, where the first item that enters means that the item is the first one out. The warehouse application is software that functions to record and monitor all activities of goods leaving the warehouse and entering the warehouse in real-time. This application is made on a web-based basis to assist the process of recording inventory updates, accurate goods data can be used as an evaluation of incoming goods as an inventory report, thus facilitating the process of running calculations in inventory recording by paying attention to the quality of wood and the expiration of goods used in the warehousing process.
PENERAPAN KONSEP BIG DATA UNTUK OPTIMALISASI MANAJEMEN ASET DI PT POS INDONESIA Muhammad Ruslan Maulani; Iwan Setiawan; Marwanto Rahmatuloh
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 10 No. 2 (2024)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol10.iss2.2024.1528

Abstract

This research aims to apply the Big Data concept in order to optimize asset management at PT Pos Indonesia. PT Pos Indonesia needs to adopt Big Data technology to collect, manage, and analyze data generated by various sources. The research method used in this study is Scrum, a software development framework that focuses on flexibility and team collaboration. This research involves several stages. First, a needs analysis and identification of assets that need to be optimized were conducted. Next, data was collected from various sources such as asset management systems. The collected data is then processed and stored in a suitable Big Data infrastructure. Next, using the Scrum method, the research team and stakeholders were involved in the process of developing a Big Data solution. Short sprints were conducted to implement and test various components of the system, such as the data collection platform, analysis algorithms, and visualization of results. Regular iterations allowed for continuous adjustments and improvements according to feedback provided by the team and stakeholders. The result of this research is a prototype application and the application of the Big Data concept implemented in the asset management application at PT Pos Indonesia. By optimizing the use of data, PT Pos Indonesia can increase operational efficiency, improve decision making based on more accurate data analysis.
GENETIC ALGORITHM-BASED HYPERPARAMETER OPTIMIZATION IN DEEP LEARNING FOR HIGH-ACCURACY LOGISTICS EXPENDITURE CLASSIFICATION Marwanto Rahmatuloh; Supriady Supriady; Rukmi Juwita
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.7840

Abstract

Traditional reactive logistics auditing often fails to detect hidden operational inefficiencies, particularly in transaction data with imbalanced class distributions. This study aims to analyze the effect of Genetic Algorithm (GA)-based hyperparameter optimization on the performance of deep learning models for logistics expenditure efficiency classification and to compare its performance with baseline Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) models. This study used a real-world logistics transaction dataset, with the Cost per Kilogram metric employed as the basis for classification labeling. The research stages included data collection, preprocessing and feature engineering, data balancing using the Synthetic Minority Over-sampling Technique (SMOTE), development of ANN and CNN models, ANN hyperparameter optimization using GA, and comparative evaluation based on accuracy, precision, and recall. The results showed that the baseline ANN and CNN models obtained a recall of 0.00 in detecting inefficient transactions, whereas the GA-optimized ANN achieved an accuracy of 91% and a perfect recall of 1.00. These findings indicate that GA-based hyperparameter optimization improves the model's ability to detect inefficient transactions and reduces diagnostic blind spots in imbalanced logistics financial data. This study contributes a high-accuracy classification approach that can support proactive financial monitoring and automated auditing in the logistics sector.
Co-Authors Hafidzul Fauzan Indah Triapriliani Iwan Setiawan Muhammad Ruslan Maulani Rukmi Juwita Supriady Supriady Supriady