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Tundo
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Prediksi Produksi Sablon di Perusahaan Tomoinc dengan Perbandingan Metode Single Moving Average dan Single Exponential Smoothing Galih Satria Yacob; Tundo; Dadang Iskandar Mulyana; Sri Lestari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3018

Abstract

A common problem faced by companies is predicting future production of goods based on previously recorded data. The company produces only according to orders, conducting production processes solely based on consumer demand. Any excess production is stored as stock to meet sudden consumer demands. These predictions significantly influence management decisions regarding the quantity of goods that must be prepared, considering factors like general business and economic conditions, competitors' actions, government policies, market trends, product life cycles, styles and fashions, changes in consumer demand, and technological innovations. This research aims to identify and analyze screen printing production predictions using the Moving Average and Exponential Smoothing methods. The more data used for comparison, the more accurate the prediction results. The research successfully developed a screen printing production prediction system, facilitating easier determination of future production quantities.
Perancangan UI/UX untuk Optimalisasi Booking Online dalam meningkatkan Potensi Wisata Daerah Leuwi Asih Humam Mu'asyir; Tundo; Husain Rahmani; Muhammad Derry Oktaviandi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3794

Abstract

UI/ UX Design for development of online booking technology and digital tour guides in the Leuwi Asih tourist area aims to increase regional tourism potential through web-based services. This system is designed to make it easy for tourists to make reservations and get information related to tourist destinations efficiently. This research uses a qualitative method by collecting data through direct interviews with local residents and local tourism business owners. The result of this research is a website that functions as a platform to facilitate the management of tourist reservations and provide digital tourist information. Thus, this system is able to support the development of local tourism and improve the tourist experience significantly.
Penerapan Data Mining Menggunakan Algoritma Single Moving Average pada Penjualan Mobil Honda Tundo; Marcia Rizky Hamdala; Andi Saidah; Muhammad Nurdin
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3847

Abstract

Data mining is a branch of artificial intelligence that is used to find patterns and information hidden in data. One of the common algorithms used in data mining is the Single Moving Average (SMA). The SMA algorithm can be used to analyze and predict trend data, such as sales, stocks, production, and so on. In this study, SMA will be used to provide forecasts on Honda car sales and find hidden patterns in them with the aim of finding out the dominant patterns in Honda car sales and preparing for all possible risks that will be obtained due to this forecasting system. The data used in this study is Honda car sales data from official Honda dealers, where data was collected as much as 90 data as a dataset, and 8 data as data to be tested from 2017 to 2023. The results of the study show that the SMA algorithm can be used to analyze Honda car sales data where the right order in this case is order 2 with a value obtained above 90% based on the results of calculations from MAPE and MSE. These results can be used by the Honda company to improve sales strategies and improve product quality in terms of inventory management.
Penerapan Prediksi untuk Klasifikasi Penerima Beasiswa Berprestasi pada SMK Islam Pemalang Berdasarkan Algoritma K-Nearest Neighbor Agung Yuliyanto Nugroho; Tundo; Riolandi Akbar
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3848

Abstract

This research aims to help Pemalang Islamic SMK in identifying outstanding students and predicting potential scholarship recipients, by utilizing the algorithm, K-Nearest Neighbor (K-NN) in determining students who have the potential to receive scholarships. This research used 100 student data involving attributes such as report card grades, academic achievement, parental responsibilities, parental salary, and participation in organizations. Meanwhile, the testing process is carried out by adding 6 data on potential scholarship recipients to be predicted. The data is then processed and normalized before being applied to the K-NN algorithm. The K-NN steps involve determining the K parameter (number of nearest neighbors), calculating the Euclidean distance, sorting the distance results, and selecting the majority category as a prediction for the new object class. The research results show that the application of the K-NN algorithm with K=3 is successful in providing predictions of outstanding students by considering relevant attributes. This process is carried out with the help of JAVA programming to calculate and analyze data. The research conclusion shows that the K-NN algorithm can be used as an effective prediction tool for classification to determine students who excel and are worthy of receiving scholarships. This research contributes to increasing efficiency and accuracy in the selection of outstanding scholarship recipients in the school environment with an accuracy of 83.33%.
Co-Authors Agung Yuliyanto Nugroho Dadang Iskandar Mulyana` Galih Satria Yacob Humam Mu'asyir Husain Rahmani Marcia Rizky Hamdala Muhammad Derry Oktaviandi Muhammad Nurdin Riolandi Akbar Saidah, Andi SRI LESTARI