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All Journal Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Buana Information Technology and Computer Sciences (BIT and CS) Scientific Student Journal for Information, Technology and Science
Nurhayati
Universitas Buana Perjuangan Karawang
Computer Science & IT

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Implementation of the Futsal Field Ordering Platform using the UCD Method Agustia Hananto; Muhamad Mammun; Nurhayati
Buana Information Technology and Computer Sciences (BIT and CS) Vol 1 No 1 (2020): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (409.731 KB) | DOI: 10.36805/bit-cs.v1i1.678

Abstract

The development of information technology is exploding. We cannot separate the need for information from the use and use of computers. With a computerized information system, the work done will be more effective and accurate. Karawang Futsal is a sports venue in the Karawang Regency. Using the futsal ordering system is still manual, the data input system which is still recording in the ledger, making reports is not accurate because of frequent miscalculations that result in making reports not on time because all processes are done. Therefore, with the existence of a computer system, all the needs for everything in the Karawang Regency Futsal will run.
Analisis Pola Pembelian Produk pada Toko Sembako Mamah Dedeh Menggunakan Algoritma FP-Growth Dina Aliya Sari; Adi Rizky Pratama; Nurhayati; Deden Wahiddin
Scientific Student Journal for Information, Technology and Science Vol. 7 No. 2 (2026): Scientific Student Journal for Information, Technology and Science
Publisher : Scientific Student Journal for Information, Technology and Science

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Abstract

Penelitian ini bertujuan menganalisis pola pembelian produk pada Toko Sembako Mamah Dedeh menggunakan algoritma Frequent Pattern Growth (FP-Growth). Data yang digunakan berupa transaksi penjualan selama tujuh bulan yang melalui tahap praproses, meliputi pembersihan data, penghapusan duplikasi, dan pengelompokan transaksi. Selanjutnya, analisis dilakukan melalui pembentukan FP-Tree, conditional pattern base, conditional FP-Tree, serta pembangkitan aturan asosiasi berdasarkan nilai minimum support dan confidence. Hasil penelitian menunjukkan adanya beberapa kombinasi produk yang memiliki nilai support dan confidence tinggi sehingga berpotensi dijadikan dasar dalam penyusunan strategi penempatan produk, paket penjualan, dan program promosi. Dengan demikian, algoritma FP-Growth terbukti efektif dalam mengidentifikasi pola pembelian konsumen serta mendukung pengambilan keputusan yang lebih tepat berdasarkan data transaksi.
Sistem Kotak Penggalangan Dana Otomatis Berbasis ESP32 dengan Klasifikasi Nominal Uang Kertas Menggunakan Metode Euclidean Distance Gilang Cantona; Deden Wahiddin; Nurhayati; Adi Rizky Pratama
Scientific Student Journal for Information, Technology and Science Vol. 7 No. 2 (2026): Scientific Student Journal for Information, Technology and Science
Publisher : Scientific Student Journal for Information, Technology and Science

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Abstract

Pengelolaan kotak penggalangan dana secara manual sering kali menimbulkan berbagai kendala, seperti keterlambatan pencatatan, risiko kesalahan, serta rendahnya transparansi dalam pelaporan. Penelitian ini bertujuan merancang sistem otomatis berbasis Internet of Things (IoT) menggunakan mikrokontroler ESP32 dan sensor warna TCS3200 untuk mengenali nominal uang kertas Rupiah. Metode Euclidean Distance digunakan untuk mengklasifikasikan nominal berdasarkan nilai ambang RGB dari masing-masing uang kertas yang telah dikalibrasi. Hasil klasifikasi kemudian dikirimkan secara real-time melalui bot Telegram beserta total saldo yang diperbarui secara otomatis. Sistem diuji pada tujuh nominal uang kertas, mulai dari Rp1.000 hingga Rp100.000, dan menunjukkan tingkat keberhasilan deteksi yang tinggi, terutama pada nominal besar. Hasil penelitian menunjukkan bahwa kombinasi sensor warna dan metode Euclidean Distance dapat menjadi solusi yang efektif untuk mengotomatisasi pencatatan donasi secara efisien dan transparan.
Analysis of English Score Data as an Indicator of Graduate Learning Outcomes Achievement Using a Data-Driven Approach Nurhayati; Hilda Tri Yulianti
Techno Xplore: Journal of Computer Science and Information Technology Vol. 11 No. 1 (2026): Techno Xplore: Jurnal Ilmu Komputer dan Teknologi Informasi
Publisher : Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/7ma3fh89

Abstract

This study investigates the utilization of English score data as an indicator of graduate learning outcomes achievement in Informatics Engineering programs through a data-driven approach. A dataset comprising 9894 student English Score records was analyzed using a combination of descriptive statistics, machine learning classification, clustering techniques, and deep learning models. The study aims to evaluate students’ English proficiency levels and explore the potential of artificial intelligence (AI) methods in supporting academic decision-making. The results reveal that the average English score (235.78) is significantly below the CPL threshold (≥260), with only 33.90% of students meeting the required standard, indicating a substantial gap in English proficiency achievement. Classification models demonstrate strong predictive capability in distinguishing student performance categories, while clustering analysis reveals distinct groupings of student proficiency levels. Furthermore, a 1D Convolutional Neural Network (CNN) model demonstrates the feasibility of deep learning approaches in modeling educational data. The findings highlight the importance of integrating AI-based analytics into academic evaluation systems to support Outcome-Based Education (OBE). This study contributes to the development of a data-driven framework for continuous quality improvement and provides insights for designing targeted interventions to enhance student competencies..
Co-Authors Adi Rizky Pratama Deden Wahiddin Dina Aliya Sari Gilang Cantona Hananto, Agustia Hilda Tri Yulianti Muhamad Mammun