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Abu Khalid Rivai
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Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Materials Science & Nanotechnology Physics

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Pengaruh Penggunaan Teknik Blending Dan Kompaksi Terhadap Morfologi Komposit Polimer UHMWPE-Na2B4O7.5H2O Sebagai Bahan Perisai Radiasi Neutron Termal Winda Surya Bery; Dian Fitriyani; Elvaswer Elvaswer; Enny Zavianti; Mardiyanto Mardiyanto; Abu Khalid Rivai; Sulistioso Giat Sukaryo
Jurnal Ilmu Fisika (JIF) Vol 8 No 2 (2016): September 2016
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jif.8.2.98-103.2016

Abstract

Telah dilakukan pembuatan dan karakterisasi komposit polimer UHMWPE dengan filler Na2B4O7.5H2O sebagai bahan perisai radiasi neutron termal.  Pembuatan bahan dilakukan dengan menggabungkan UHMWPE dan Na2B4O7.5H2O menggunakan metode blending untuk menghasilkan komposit yang homogen, dan proses kompaksi untuk meminimalkan jarak antar partikel penyusun bahan.  Persentase penambahan Na2B4O7.5H2O yang digunakan bervariasi dari 0% hingga 52%. Bahan dasar dan filler di-blending pada suhu 165°C selama 15 menit, selanjutnya dikompaksi dengan pembebanan 10 ton.  Hasil analisis EDS menunjukkan persentase massa filler di permukaan bahan meningkat dengan penambahan Na2B4O7.5H2O hingga konsentrasi 40% dan menurun di 52%.  Hasil karakterisasi SEM menunjukkan persentase filler optimum pada 40%.  Dengan demikian metode blending dan kompaksi sesuai digunakan untuk mencampurkan UHMWPE dan Na2B4O7.5H2O menjadi bahan perisai neutron termal dengan perbandingan komposisi (60:40)%. Kata kunci :  Perisai radiasi, neutron termal, UHMWPE, Na2B4O7.5H2O, filler, blending, kompaksi 
Karakterisasi Bahan Perisai Radiasi Neutron Ultra High Molecular Weight Polyethyene Dengan Filler Gd2O3 Menggunakan Teknik Radiografi Neutron Enny Zarvianti; Dian Fitriyani; Elvaswer Elvaswer; Winda Surya Bery; Abu Khalid Rivai; Mardiyanto Mardiyanto; Sulistioso G.S
Jurnal Ilmu Fisika Vol 9 No 1 (2017): March 2017
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jif.9.1.1-6.2017

Abstract

Radiasi merupakan pancaran energi melalui suatu materi atau ruang dalam bentuk energi, panas, partikel atau gelombang yang dapat diserap oleh bahan lain. Beberapa radiasi dapat mengionisasi bahan yang dilaluinya salah satunya radiasi neutron karena memiliki daya tembus yang tinggi sehingga sangat diperlukan perisai radiasi. Adapun kriteria dari perisai radiasi neutron harus memiliki kandungan hidrogen yang tinggi, memiliki nilai tampang lintang yang baik dan tidak bersifat korosi. Bahan UHMWPE (Ultra High Molecular Weight Polyethyene) memiliki kandungan hidrogen yang tinggi dan tidak mudah korosi dan bahan Gadolinium oxide (Gd2O3) sangat baik menyerap neutron karena mempunyai tampang lintang serapan neutron yang tinggi. Berdasarkan hal tersebut maka dibuat komposit UHMWPE-Gd2O3 dengan tujuan dapat meningkatkan nilai serapan neutron sehingga dalam aplikasinya bisa lebih efektif untuk memperlambat bahkan menahan radiasi neutron. Telah dilakukan karakterisasi bahan perisai radiasi neutron yang dibuat sendiri dengan teknik radiografi neutron. Bahan perisai radiasi dibuat dengan bahan utama UHMWPE dan penambahan filler Gadolinium Oxide (Gd2O3) dengan kompoisisi 70% : 30% massa menggunakan metode blending dan kompaksi. Bahan dibuat dengan ketebalan yang bervariasi dari 0,5 cm hingga 2 cm. Hasil karakterisasi XRD menunjukkan tidak terbentuk senyawa kimia antara kedua bahan dan karakterisasi menggunakan SEM terlihat hasil distribusi unsur yang terkandung dalam filler Gd2O3 merata pada bahan dasar polimer. Pengujian serapan neutron menggunakan teknik radiografi neutron dengan metode film. Dengan penambahan variasi ketebalan meningkatkan daya serap bahan dari 58,78% menjadi 67,89% dan nilai koefisien atenuasi diperoleh sebesar 1,025.Kata kunci: perisai radiasi, UHMWPE,Gd2O3, radiografi neutron, daya serap dan koefisien  atenuasi.
Analisis Transaksi Pembayaran Tiket Kereta Api (KAI) Dengan Pembayaran Via Bank Menggunakan Metode K-Nearest Neighbors Dan Naïve Bayes Studi kasus PT XYZ Rizki Agustian; Murni Handayani; Abu Khalid Rivai
Jurnal Ilmu Komputer Vol 3 No 1 (2025): Jurnal Ilmu Komputer (Edisi Juli 2025)
Publisher : Universitas Pamulang

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Abstract

In the digital era, train ticket payment patterns are increasingly complex with the increasing use of bank payment methods. PT XYZ, as a train ticket service provider, faces challenges in understanding customer behavior based on available transaction data. The main problem in this study is how to effectively group customer data based on their transaction characteristics to support service improvement and marketing strategies. This study implements two data mining classification algorithms, namely K-Nearest Neighbors (KNN) and Naïve Bayes, to analyze train ticket payment transaction patterns. Processing is carried out through the RapidMiner application, with an approach based on historical transaction data collected and processed using Microsoft Excel. The research methodology includes the stages of data collection, preprocessing, classification modeling, and model performance evaluation based on accuracy, precision, and recall metrics. The results show that the Naïve Bayes algorithm has superior performance compared to KNN, with an accuracy of 99.10%, a precision of 99.07%, and a recall of 99.14%. This indicates that Naïve Bayes is more effective in classifying customer transaction data. Companies can implement the Naïve Bayes algorithm in internal analytics systems to support data-driven decision-making, particularly in marketing strategies and customer service personalization
Systematic Literature Review : Tren Perkembangan Model dan Algoritma Analisis Video Kerumunan-Padat Fristiyanto, Doni; Abu Khalid Rivai
Jurnal Ilmu Komputer Vol 3 No 1 (2025): Jurnal Ilmu Komputer (Edisi Juli 2025)
Publisher : Universitas Pamulang

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Abstract

Dense-crowd video analysis is a branch of computer vision that has various important applications in public safety, emergency management, urban planning, pedestrian traffic engineering, and crowd management at large events, such as religious activities, music concerts, and sports matches. This study presents a Systematic Literature Review (SLR) of 30 scientific publications published between 2010 and 2025. The main objective of this review is to identify the latest research trends, classification of algorithms used, application domains, and the main challenges still faced in crowd video analysis. The results of this SLR show that deep learning-based approaches, such as Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Transformer, still dominate various applications, especially in anomaly detection which aims to recognize suspicious behavior in dense crowds. This technology has significant potential for preventing  dangerous events such as riots, mass panic, or accidents. In addition, trends in the integration of new technologies are also found, such as the use of hybrid algorithms that combine several approaches, federated learning for distributed model training, and the use of multimodal data and drones to improve monitoring effectiveness. However, many challenges remain, such as limited representative datasets, decreased accuracy under extreme conditions, computational limitations for real-time applications, and issues of privacy and model interpretability. Therefore, the results of this SLR are expected to make a strategic contribution to the development of more sophisticated, adaptive, and relevant crowd analytics systems.
Co-Authors Dian Fitriyani Elvaswer Elvaswer Enny Zarvianti Enny Zavianti Fristiyanto, Doni Mardiyanto Mardiyanto Murni Handayani Rizki Agustian Sulistioso G.S Sulistioso Giat Sukaryo Winda Surya Bery