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All Journal Teika METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Digit : Digital of Information Technology Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI
Lena Magdalena
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Journal : METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi

 1 
SISTEM PENUNJANG KEPUTUSAN DALAM PENENTUAN RUTE DAN KAPASITAS MUATAN DISTRIBUSI DENGAN MENGGUNAKAN METODE SAVING MATRIX DAN NEAREST NEIGHBOAR PADA CV BINTANG BERKAH CIREBON ., Nico Firmansyah; Lena Magdalena; Mesi Febima
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3271

Abstract

This research creates and designs a Decision Support System (SPK) for CV Bintang Berkah by combining the Saving Matrix and Nearest Neighbor methods to optimize the route and capacity of the distribution load. CV Bintang Berkah faces challenges in managing distribution costs and load capacity, which affects operational efficiency. The Saving Matrix method helps in determining distribution routes with distance and cost savings, while the Nearest Neighbor method optimizes the order of visits based on the closest distance. The implementation of this system is expected to reduce transportation costs, increase distribution efficiency, and improve service quality. This system uses PHP and MySQL, focusing on the Cirebon City and Regency areas. The results show that applying this method significantly reduces the distance and cost of distribution and increases efficiency in the distribution process. With this system, CV Bintang Berkah is expected to overcome distribution challenges better, save costs, and increase the company's profitability.
SISTEM INFORMASI FORECASTING DATA PENJUALAN KENDARAAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING (STUDI KASUS: PT. SENDANG SUMBER ARUM VIAR MOTOR CIREBON) Lestari, Lina; Lena Magdalena; Mesi Febima
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3283

Abstract

Limited Liability Companies (PT) are found in almost all regions in Indonesia, one of which is PT.  Sendang Sumber Arum 'VIAR Motor which provides sales of Karya 3-wheeled motorcycle units, e-motorcycles, razors, Cross Adventure, vintech, and e-bikes. E-bikes are the best-selling vehicles for each period, especially the UNO3 type. The problem faced by this company is the imbalance in sales figures which causes damage to the e-bike batteries that are sold over a long period of time and requires forecasting. The Single Exponential Smoothing method is the right forecasting method used to predict demand for goods that change very quickly, which aims to determine the estimated availability of vehicle units that must be held in the future, based on previous sales data. In determining the error value in forecasting, the author uses the Mean Square Error (MSE) which is based on the alpha value. This forecasting is implemented into an information system that produces a forecast for the UNO3 type e-bike with the smallest Mean Square Error (MSE) value obtained with an alpha of 0.3, namely with a value of 167.294. This proves the best forecast for predicting the quantity of UNO3-type e-bike stock units at PT. Sendang Sumber Arum ‘VIAR Motor’ Cirebon for the period of June 2024 using alpha 0.3. So the forecast value of UNO3 type e-bike unit sales for June 2024 in the 11-month forecast period with alpha 0.3 is 24.89 or around 25 units with actual data.
IMPLEMENTASI K-MEANS RFM DAN HOLT-WINTERS EXPONENTIAL SMOOTHING ADDITIVE DALAM SISTEM BUSINESS INTELLIGENCE UNTUK STRATEGI PENGELOLAAN PELANGGAN PADA PERUSAHAAN TRANSPORTASI.: Pembuatan Dashboard BI Segmentasi pelanggan dan peramalan Jumlah pelanggan menggunakan Tools Tableau menggunakan metode Kmeans RFM dan Holtwinters Exponential Smoothing Priandini, Belfania; Marsani Asfi; Lena Magdalena
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 11 No. 2 (2025): Volume 11 Nomor 2 Tahun 2025
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v11i2.4511

Abstract

The growth of customer data in the transportation industry drives the need for analytical systems capable of segmenting customers objectively and strategically. This study aims to apply the K-Means Clustering method based on the Recency, Frequency, and Monetary (RFM) model for customer segmentation and utilize the Holt-Winters Exponential Smoothing Additive method to forecast passenger numbers. The dataset comprises 10,440 customer transactions from PT XYZ during the 2022–2024 period. RFM values were calculated, normalized, and processed using the K-Means algorithm to produce three customer clusters: Loyal, Regular, and Passive. Subsequently, the Holt-Winters method was employed to forecast passenger numbers, achieving the smallest Mean Absolute Percentage Error (MAPE) of 6.88%, indicating a high level of accuracy. The results were visualized through an interactive dashboard using Tableau, enabling management to make data-driven decisions. This research demonstrates that integrating segmentation and forecasting methods into a Business Intelligence system can enhance the effectiveness of marketing strategies and the operational efficiency of the company.
Co-Authors ., Nico Firmansyah Abdul Rachman adminDewi Yenny Sitanggang Ayuni Alfiani Nurkholifah Chaerul Anwar Deny Martha Edwin Sulistio Limas Efriza Yunardi Eunike Surya Mosory Fahrudin, Rifqi Hamdani . Ida Wati Kusnadi Kusnad Kusnadi Kusnadi Lia dahlia Lina Lestari, Lina Lisa Natalia Marsani Asfi Mesi Febima Muhammad Hatta Muhammad Hatta Muhammad Ricky Umar Natalia Gunawan, Trivena Petrus Sokibi Priandini, Belfania Ridho Taufiq Subagio Triana Ramadani