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All Journal Journal of Innovation and Future Technology (IFTECH)
Dadang Amiruddin
Universitas Bina Bangsa
Computer Science & IT Education Electrical & Electronics Engineering Engineering Library & Information Science

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RANCANG BANGUN SISTEM INFORMASI PERMINTAAN LAYANAN DALAM LINGKUP DEPARTEMEN IT DI PT CONCORD CONSULTING INDONESIA Irma Yunita Ruhiawati; Dadang Amiruddin; Yul Hendra; Ely Nuryani; Nanang Wahyudi
Journal of Innovation And Future Technology Vol. 8 No. 1 (2026): Vol 8 No 1 (Februari 2026): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v8i1.4522

Abstract

In the digital era, information technology plays a vital role in supporting business operations. Effective IT service management is essential for improving work efficiency and employee productivity. PT Concord Consulting Indonesia, an information technology consulting firm, faces challenges in managing internal IT service requests, which are still handled manually through emails, instant messaging applications, and direct communication. This unstructured process leads to several issues, such as difficulties in tracking request statuses, lack of systematic documentation, absence of clear prioritization mechanisms, and unclear task distribution. This study aims to design and develop a web-based information system for managing IT service requests to support a more organized, well-documented, and transparent process. The implementation of this system is expected to accelerate service resolution, enhance operational efficiency, and improve coordination among teams within the IT Department.
TRANSFORMASI DATA TRANSAKSI KE DERET WAKTU DAN EVALUASI MODEL PERAMALAN PERMINTAAN PADA MARKETPLACE PLAZA BANTEN Widyawati Widyawati; Dadang Amiruddin
Journal of Innovation And Future Technology Vol. 8 No. 1 (2026): Vol 8 No 1 (Februari 2026): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v8i1.4550

Abstract

Plaza Banten, an MSME marketplace in Banten Province, generates ordering and sales transaction data that can be leveraged to support operational decisions, particularly inventory planning and promotional timing. However, decision-making is often reactive because demand forecasting has not been systematically developed from historical transactions. This study proposes an end-to-end pipeline that transforms Plaza Banten transaction records into daily demand time-series data at the product-category (Group) level, following data preparation and modeling stages in a data mining framework. The study uses transaction data from January to December 2024 and is positioned as a continuation of a previous Market Basket Analysis (MBA) study, which indicated that high transaction volumes were dominated by packaged rice products (e.g., rice boxes and chicken rice packages), motivating a forecasting follow-up for high-demand categories with recurring purchase patterns. The preprocessing stage includes data cleaning, validation of quantity and unit price, feature construction (quantity and revenue), daily demand aggregation by category, and completion of missing calendar dates to form continuous time series. For modeling, this study compares baseline forecasting methods (Naïve and 7-day Moving Average) against an Exponential Smoothing (Holt–Winters/ETS) model that accounts for trend and weekly seasonality. Model performance is evaluated using MAE, RMSE, and MAPE to ensure measurable selection of the best approach. The forecasting results are then interpreted as operational insights to estimate demand levels per category and support inventory planning and promotional prioritization based on predicted demand trends.
Co-Authors Ely Nuryani Nanang Wahyudi Ruhiawati, Irma Yunita Widyawati Widyawati Yul Hendra