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All Journal Math Didactic: Jurnal Pendidikan Matematika PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer
Nurapriani, Nurapriani
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Computer Science & IT Mathematics

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Strengthening the ability of students to solve mathematical problems through classroom conduct wit autograph aided mathematics learning media Nurapriani, Nurapriani; Hasibuan, Lily Rohanita; Siregar, Sakinah Ubudiyah
Math Didactic: Jurnal Pendidikan Matematika Vol 10 No 1 (2024): Januari - April 2024
Publisher : Universitas PGRI Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33654/math.v10i1.2553

Abstract

Penelitian ini bertujuan untuk memperbaiki proses belajar dikelas sehingga berdampak pada peningkatan kemampuan pemecahan masalah matematika siswa. Penelitian ini berupa penelitian tindakan kelas yang dilakukan terhadap 25 siswa di kelas VIII MTs Syahru Thoyibbah Annafisah. Data yang diperoleh melalui proses observasi dan pemberian tes pemecahan masalah. Selanjutnya, data tersebut dianalisis melalui tiga tahap, yaitu: 1) reduksi data, 2) pemaparan data dan 3) menarik kesimpulan. Penelitian ini adalah penelitian deskriptif dengan pendekatan kualitatif. Selanjutnya, hasil penelitian ini memperlihatkan terjadinya peningkatan kemampuan pemecahan masalah matematika siswa baik pada indikator pemahaman masalah, perencanaan masalah, melaksanakan rencana dan menyimpulkan.
Penerapan Algoritma Apriori Dalam Menentukan Pola Pergerakan Kebutuhan Distribusi Pada PT. Satria Teknik Indonesia Yoviyardi, Rama; Lia Hananto, April; Nurapriani, Nurapriani; Huda, Huda
Jurnal PROCESSOR Vol 20 No 1 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.1.2207

Abstract

In an increasingly competitive business environment, companies are required to make more precise strategic decisions to enhance operational efficiency. The shift in customer demand trends has become a major challenge faced by PT Satria Teknik Indonesia, a goods distribution company. To address this challenge, the company can leverage transaction data to analyze customer purchasing patterns. By utilizing the results of this analysis, PT Satria Teknik Indonesia can improve the accuracy of customer demand predictions, accelerate data-driven decision-making, and optimize inventory management. One effective method for this analysis is the Apriori algorithm. The data used were obtained from the company's transaction recording system during the period from January 2023 to October 2024 and were analyzed to discover association rules in large datasets and identify relationships between products that are frequently purchased together. The results of this study reveal two items that are prioritized for ordering: Back Support and Safety Shoes Cheetah. If customers purchase Back Support, they are highly likely to also purchase Safety Shoes Cheetah, with a support value of 20.22% and a confidence level of 100%. Conversely, if customers purchase Safety Shoes Cheetah, they tend to also buy Back Support, with a support value of 20% and a confidence level of 94.74%. This study identifies a strong purchasing association pattern between Back Support products and Safety Shoes Cheetah, providing empirical evidence of the benefits of implementing data mining techniques to improve inventory management effectiveness and better respond to customer needs
Co-Authors April Lia Hananto Hasibuan, Lily Rohanita Huda Huda Siregar, Sakinah Ubudiyah Yoviyardi, Rama