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All Journal Jurnal Vokasi Indonesia Jurnal Ekonomi Manajemen Sistem Informasi JSSM Jurnal Vokasi Indonesia Journal of Indonesian Tourism and Policy Studies
Yulius Eka Agung Seputra
Vocational Education Program, Universitas Indonesia, Indonesia
Arts Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Public Health Social Sciences Other

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HEAT TREATMENT OF ALUMINIUM MATRIX COMPOSITE (AMC) REINFORCEMENT ORGANOCLAY FOR AUTOMOTIVE APPLICATION Yulius Eka Agung
Jurnal Vokasi Indonesia Vol 5, No 2 (2017): July - December
Publisher : Program Pendidikan Vokasi Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (239.193 KB) | DOI: 10.7454/jvi.v5i2.88

Abstract

Aluminum Matrix Composites (AMC) reinforced montmorillonite (MMT) was performed using cationic surfactant , Artificial Aging and stir casting method. The content of MMT as a filler is 3%wt. Characterization were performed using Xray Difractometer, ultrasonic testing, SEM, and Hardness Vickers. The results show increase in crystallographic parameter, decrease in density, shiffting in XRD pattern and increase in hardness.Keywords: metal, composite, matrix, aluminum, AMC, MMC, organoclay, heat treatment MMT, artificial aging,stir casting, automotive
Prediksi Pergerakan Harga Bitcoin menggunakan Algoritma Genetika Yulius Eka Agung Seputra
Journal of Social Sustainability Management Vol. 3 No. 2 (2023): APRIL 2023
Publisher : Journal of Social Sustainability Management

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Abstract

Prediksi pergerakan harga bitcoin merupakan tantangan yang sering dihadapi oleh investor dan pedagang kripto. Salah satu cara untuk memprediksi harga bitcoin adalah dengan menggunakan algoritma genetika. Artikel ini membahas tentang pengembangan model prediksi pergerakan harga bitcoin menggunakan algoritma genetika untuk rentang waktu tahun 2015-2022. Metode pemodelan algoritma genetika digunakan dengan memilih parameter yang tepat, fungsi fitness yang akurat, teknik pemilihan orang tua dan crossover yang efektif, serta metode mutasi yang sesuai. Hasil dari pengembangan model ini kemudian dievaluasi dan diuji dengan membandingkan hasil prediksi dengan data aktual. Berdasarkan hasil evaluasi, model prediksi pergerakan harga bitcoin menggunakan algoritma genetika dapat memberikan hasil yang cukup akurat. Pada tahun 2015-2018, model prediksi menunjukkan tren naik pada harga bitcoin, kemudian mengalami penurunan pada tahun 2018-2019. Selanjutnya, pada tahun 2020-2022, model prediksi menunjukkan tren naik kembali pada harga bitcoin. Penggunaan algoritma genetika dalam prediksi harga bitcoin dapat membantu mengurangi kesalahan manusia dalam proses pengambilan keputusan dan meningkatkan efisiensi proses. Namun, penggunaannya harus dilakukan dengan hati-hati dan selalu diimbangi dengan pengetahuan dan pengalaman yang memadai dalam investasi.
UJIAN ON LINE DALAM E-LEARNING: PERBANDINGAN UJIANONLINE (COMPUTER BASED) TERHADAP UJIAN TRADISIONAL (PAPER BASED) Yuliyanto, Heri; Wahyuni, Titis; Seputra, Yulius Eka Agung
Jurnal Vokasi Indonesia Vol. 4, No. 2
Publisher : UI Scholars Hub

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Abstract

Spreading the uneven quality education in Indonesia is a national educational problems to be solved. Implementation of quality education largely implemented in Java, in the case of Indonesian citizens spread all over Indonesia, from Sabang to Merauke. All citizens of the Indondesia want to receive a quality education that is easily accessible at reasonable costs. One solution that can be used to solve the problem is e-learning. However, many factors must be considered in the process of long-distance pembejaran known as elearning, one of which is the process of evaluating learning outcomes. This article discusses the process of evaluation of learning outcomes by studying literature several articles published between the years 2007 - 2015 with a focus on expert opinion to the statement "whether the test on line (computer-based) may replace the exam traditional (paper-based)" through the presentation of the pros and cons exam on line. From this study it was found that there are opportunities to replace paper-based exams to computer-based test with due regard to the technical elements such as security, ease of use and ability of computer users base. However, such reimbursement can not be applied to all conditions and the need to pay attention to the learning objectives that have been set. Therefore, further research is needed to develop a model to evaluate student achievement by combining the concept of competency-based assessment cubic online (Cubiks Online Asesessment) by combining multiple information security concepts.
Heat Treatment of Aluminium Matrix Composite (AMC) Reinforcement Organoclay for Automotive Application Seputra, Yulius Eka Agung; B, Chanra J. Soegijono.
Jurnal Vokasi Indonesia Vol. 5, No. 2
Publisher : UI Scholars Hub

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Abstract

Aluminum Matrix Composites (AMC) reinforced montmorillonite (MMT) was performed using cationic surfactant , Artificial Aging and stir casting method. The content of MMT as a filler is 3%wt. Characterization were performed using Xray Difractometer, ultrasonic testing, SEM, and Hardness Vickers. The results show increase in crystallographic parameter, decrease in density, shiffting in XRD pattern and increase in hardness.
ANALISIS TREN SAHAM CFD, FOREX DAN KRIPTO MENGGUNAKAN PENDEKATAN FUZZY Saputra, Yulius Eka Agung
Jurnal Vokasi Indonesia Vol. 11, No. 1
Publisher : UI Scholars Hub

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Abstract

Penelitian ini bertujuan untuk menemukan solusi untuk mengatasi ketidakpastian dalam menentukan waktu yang tepat untuk bertransaksi dan berinvestasi dalam produk derivatif perdagangan valas. Metode yang digunakan adalah dengan menguji beberapa indikator teknikal, seperti Ichimoku, KSA, Fuzzy Logic, dan Expert Advisors, pada semua pasangan yang diuji berdasarkan sesi (Jepang, London, AS). Hasilnya menunjukkan bahwa penggunaan kombinasi indikator teknikal ini dapat memberikan keuntungan maksimum dan kerugian tertunda minimum untuk semua pasangan yang diuji, sehingga dapat membantu para pedagang untuk menentukan kondisi yang tepat untuk berdagang dan berinvestasi yang diperkuat dengan nilai Mean Square Error (MSE) sebesar 5% dan Mean Absolute Percentage Error (MAPE) sebesar 1,5%. Penelitian ini memberikan solusi untuk mengurangi risiko dan meningkatkan potensi keuntungan bagi pedagang produk derivatif valuta asing
ANALISIS PERTUKARAN MATA UANG ASING MENGGUNAKAN FOURIER TRANSFORM DAN ANT COLONY OPTIMATION (ACO) 1990 - 2022 Seputra, Yulius Eka Agung
Jurnal Vokasi Indonesia Vol. 11, No. 2
Publisher : UI Scholars Hub

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Abstract

Tujuan dari penelitian ini adalah untuk menganalisis pasar valuta asing (Forex) menggunakan teknik Transformasi Fourier dan Ant Colony Optimization (ACO) untuk mengatasi permasalahan sering kalahnya tader dalam memprediksi mata uang . Dengan menggunakan metode komputasi ini, penelitian ini bertujuan untuk meningkatkan akurasi analisis pasar Forex dan memberikan wawasan berharga bagi para trader dan investor. Penelitian ini menggunakan Transformasi Fourier untuk menganalisis data deret waktu harga Forex. Teknik ini membantu mengidentifikasi komponen frekuensi dominan dan pola-pola mendasar dalam data. Selain itu Ant Colony Optimization (ACO) , yang terinspirasi dari perilaku koloni semut, digunakan untuk memprediksi pergerakan harga Forex di masa depan yang tidak dapat dilakukan hanya menggunakan metode statistic seperti Mean Square Error dan Mean Absolute Percent Error. ACO adalah algoritma heuristik yang mengoptimalkan pencarian solusi optimal dalam ruang masalah yang kompleks yang meniru kecerdasan semut dalam mencari makanan yang letaknya tidak diketahui. Hasil penelitian ini menunjukkan bahwa Transformasi Fourier efektif dalam menangkap pola dan tren dalam data harga Forex. Dengan menganalisis komponen frekuensi, penelitian ini mengungkap wawasan berharga tentang dinamika pasar. Selain itu, integrasi ACO dengan analisis Fourier memungkinkan prediksi akurat terhadap pergerakan harga Forex dengan Mean Square Error (MSE) sebesar 2,35% dan Mean Absolute Percentile Error (MAPE) sebesar 3,17%. Kombinasi dari teknik-teknik ini meningkatkan akurasi analisis pasar dan membantu para trader dan investor dalam membuat keputusan yang terinformasi. Penelitian ini memberikan kontribusi pada literatur yang ada dengan menggabungkan teknik Transformasi Fourier dan ACO untuk menganalisis pasar Forex. Penerapan Transformasi Fourier memberikan pemahaman yang lebih mendalam tentang pola dan tren mendasar, sementara ACO menawarkan pendekatan baru dalam prediksi harga. Integrasi dari metode-metode ini menyajikan kontribusi unik pada bidang analisis pasar Forex.
Smart Tourism Using Cryptocurrency Based on Fuzzy Logic Seputra, Yulius Eka Agung
Journal of Indonesian Tourism and Policy Studies Vol. 8, No. 1
Publisher : UI Scholars Hub

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Abstract

Smart tourism is a rapidly emerging field that combines innovative technologies and tourism practices to enhance the overall travel experience. This journal article investigates the integration of cryptocurrency based on fuzzy logic in the context of smart tourism. The study aims to explore the potential benefits and challenges associated with using cryptocurrency as a payment method and decision-making tool in the tourism industry. By applying fuzzy logic principles, this research examines how cryptocurrency can enhance transaction security, improve financial transparency, and facilitate personalized travel recommendations. The study analyzes the implications of incorporating cryptocurrency based on fuzzy logic in smart tourism, including its impact on transaction efficiency, customer satisfaction, and sustainability. The findings of this study indicate that integrating cryptocurrency based on fuzzy logic has the potential to revolutionize the tourism industry by providing efficient and secure transactions, enabling personalized and tailored travel experiences, and promoting sustainable tourism practices. The results contribute to the existing body of knowledge on smart tourism and offer insights into the practical implications and future directions for implementing cryptocurrency in the tourism sector. This research provides valuable insights for industry stakeholders, policymakers, and researchers interested in the applications of cryptocurrency in the tourism domain. The study also highlights the need for further exploration and testing of this technology in real-world tourism scenarios to fully understand its potential benefits and address any associated challenges. Overall, the integration of cryptocurrency based on fuzzy logic presents an exciting opportunity to enhance the efficiency, security, and personalization of smart tourism experiences, contributing to the growth and advancement of the tourism industry
Deep Learning and Neuro Evolution Method for Enhancing Productivity Analysis in Indonesia's Automotive Industry Yulius Eka Agung Seputra
Jurnal Ekonomi Manajemen Sistem Informasi Vol. 7 No. 3 (2026): Jurnal Ekonomi Manajemen Sistem Informasi (Januari - Februari 2026)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jemsi.v7i3.7201

Abstract

This study explores the application of  Deep Learning and Neuro Evolution to enhance productivity analysis in Indonesia's automotive industry. Deep Learning and Neuro Evolution an advanced AI method, is employed due to its superior capability in automating the selection, optimization, and tuning of machine learning models, making it the most suitable approach compared to other AI methods developed worldwide. By leveraging Deep Learning and Neuro Evolution, we aim to identify and optimize the key factors affecting manufacturing productivity, including foreign direct investment, energy use, gross fixed capital formation, research and development expenditure, and total labor force. Using data spanning from 2003 - 2022, the automated approach facilitates the handling of complex and large datasets, ensuring a comprehensive analysis of how these variables impact value added per worker in the industry. The results indicate that Deep Learning and Neuro Evolution models outperform traditional methods, yielding a Mean Squared Error (MSE) of 0.012 and a Mean Absolute Percentage Error (MAPE) of 1.6 %. These findings provide actionable insights for policymakers and industry stakeholders to foster a more productive and competitive automotive sector in Indonesia.
Co-Authors B, Chanra J. Soegijono. Wahyuni, Titis Yuliyanto, Heri