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All Journal Jurnal Media Infotama Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Informatika dan Teknik Elektro Terapan Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Riau Journal of Computer Science International Journal of Artificial Intelligence Research JIKO (Jurnal Informatika dan Komputer) INOVTEK Polbeng - Seri Informatika Pendas : Jurnah Ilmiah Pendidikan Dasar MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL PENDIDIKAN TAMBUSAI JOURNAL OF SCIENCE AND SOCIAL RESEARCH MIND (Multimedia Artificial Intelligent Networking Database) Journal JSAI (Journal Scientific and Applied Informatics) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) Indonesian Journal of Electrical Engineering and Computer Science IJIIS: International Journal of Informatics and Information Systems Journal of Computer System and Informatics (JoSYC) JINAV: Journal of Information and Visualization Journal of Applied Data Sciences JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Journal of Applied Computer Science and Technology (JACOST) Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Indonesian Journal of Economy, Business, Entrepreneuship and Finance (IJEBEF) International Journal for Applied Information Management Journal Corner of Education, Linguistics, and Literature JUSTIN (Jurnal Sistem dan Teknologi Informasi) ProBisnis : Jurnal Manajemen Edu Sociata : Jurnal Pendidikan Sosiologi JOURNAL OF ICT APLICATIONS AND SYSTEM Innovative: Journal Of Social Science Research Neraca Manajemen, Akuntansi, dan Ekonomi Cendikia Pendidikan Jurnal Media Akademik (JMA) Bhinneka Multidisiplin Journal Jurnal Manajemen Kewirausahaan dan Teknologi Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain
B. Herawan Hayadi
Universitas Bina Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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The Development of ITSM Research in Indonesia: A Systematic Literature Review Hayadi, B.Herawan; Sukmana, Husni Teja; Shafiera, Eghar; Kim, Jin-Mook
International Journal of Artificial Intelligence Research Vol 5, No 2 (2021): December 2021
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.666 KB) | DOI: 10.29099/ijair.v5i2.233

Abstract

IT Service Management (ITSM) is a framework used to support businesses by increasing IT service quality. Several studies have tried to examine the development of ITSM based on their respective interests. However, the development of ITSM in Indonesia has not been widely studied, such as the types of research that are most often investigated, what domains are often researched, the areas and types of companies being studied. The things above are the main objectives of this research. The method used in capturing data, screening, and analysis is the systematic literature review method. There are many findings obtained from this research. One of them is the domination of the service operation research area (45%) among other areas. Meanwhile, applied research had been researched quite consistently over the last five years. From these results,  it can be noticed that a deeper understanding of the synchronization between business and IT is needed. This is in accordance with the objectives of ITSM implementation so that future research is expected to provide balance in other areas, such as service strategy, design, transition, operation, and continuous service improvement.
Penerapan Algoritma Deep Learning Convolutional Neural Network Dalam Menentukan Kematangan Buah Jeruk Manis Berdasarkan Citra Red Green Blue (RGB) Yanto, Budi; Rouza, Erni; Fimawahib, Luth; Hayadi, B.Herawan; Pratama, Rinanda Rizki
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 1: Februari 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023105695

Abstract

Secara umum proses menentukan jeruk manis layak (bagus) dan tidak layak (busuk) masih banyak menggunakan cara manual. Cara manual dilakukan berdasarkan pengamatan visual secara langsung pada buah yang akan diamati. Pengamatan dengan cara ini memiliki beberapa kelemahan yaitu adanya keterbatasan visual manusia, di pengaruhi oleh kondisi psikis pengamatannya serta memakan waktu yang lama terutama bagi perkebunan besar. Untuk itu, diperlukan suatu algoritma untuk menentukan buah jeruk manis dengan sistem terkomputerisasi yang dibuat menggunakan algoritma Convolutional Neural Network (CNN) merupakan salah satu algoritma dari deep learning yang merupakan pengembangan dari Multilayer Percepton (MLP) yang mampu mengolah data dalam bentuk dua dimensi, misalnya gambar serta mampu melakukan klasifikasi pada citra dengan kelas–kelas yang lebih banyak atau besar. Sistem ini dirancang dan dibangun menggunakan bahasa pemrograman matlab versi R2018a, dengan 100 dataset gambar jeruk manis menunjukan tingkat akurasi sebesar 96% untuk training 92% untuk testing yang dinilai telah mampu melakukan klasifikasi kelayakan buah jeruk manis dengan sangat baik. Pada pengujian menggunakan data baru dari 10 citra jeruk manis dihasilkan 9 citra jeruk manis dengan nilai benar dan 1 citra jeruk manis dengan nilai salah. AbstractIn general, the process of determining appropriate (good) and unfit (rotten) sweet oranges still uses manual methods. The manual method is carried out based on direct visual observation of the fruit to be observed. Observations in this way have several weaknesses, namely the presence of human visual limitations, being influenced by the psychological condition of the observations and taking a long time, especially for large plantations. For this reason, an algorithm is needed to determine sweet oranges with a computerized system created using the Convolutional Neural Network (CNN) algorithm, which is one of the deep learning algorithms, which is the development of Multilayer Perceptron (MLP), which is able to process data in two-dimensional form, for example. Images as well as being able to classify images with more or larger classes. This system is designed and built using the Matlab programming language version R2018a, with 100 sweet orange image datasets showing an accuracy rate of 96% for training 92% for testing which is considered to have been able to classify the feasibility of sweet oranges very well. In testing using new data from 10 images of sweet oranges, 9 images of sweet oranges were generated with the correct value and 1 image of sweet oranges with a false value.
PERENCANAAN STRATEGIS MANAJEMEN KEUANGAN UNTUK SUKSES PENDIDIKAN DI SDN KAMPUNG BARU Rahmulyana, Anjar; Yusuf, Furtasan Ali; Hayadi, B. Herawan; Yustiva, Fitriyatul; Junaesih, R.; Raman, Raman
Indonesian Journal of Economy, Business, Entrepreneuship and Finance Vol. 4 No. 1 (2024): Indonesian Journal of Economy, Business, Entrepreneuship and Finance
Publisher : Yayasan Education and Social Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53067/ijebef.v4i1.135

Abstract

This research aims to explore the role of strategic planning in financial management to support educational success at the Kampung Baru State Elementary School (SDN). Through a qualitative approach involving in-depth interviews, participant observation, document analysis, and focus group discussions (FGD), this research highlights challenges, best practices, and recommendations for improving financial management in these schools. The research results reveal that SDN Kampung Baru faces significant challenges in managing limited financial resources, including a lack of funding and increasing operational costs. However, best practices such as careful budget management and active participation from stakeholders have been identified as important factors in improving the effectiveness of school financial management. Strategic recommendations resulting from this research include the development of a long-term financial strategic plan that involves participation from all relevant parties, increasing transparency and accountability in school financial management. This research also contributes to a better understanding of the importance of strategic planning in the context of school financial management and provides a foundation for further research in this area
Penggunaan Aplikasi Canva untuk Meningkatkan Motivasi Belajar Informatika Kelas XI MA Al-Khairiyah Pipitan Putri, Nova Amelia; Hayadi, B. Herawan; Irfan, Mursyid
Jurnal Pendidikan Tambusai Vol. 8 No. 3 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk mengetahui persepsi guru dan siswa terhadap penggunaan aplikasi Canva sebagai media pembelajaran Informatika di kelas XI MA Al-Khairiyah Pipitan. Penelitian ini menggunakan pendekatan kualitatif deskriptif. Teknik pengumpulan data yang digunakan adalah observasi, wawancara, dan dokumentasi. Data yang diperoleh kemudian dianalisis secara kualitatif melalui tahap reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa guru dan siswa memiliki persepsi positif terhadap penggunaan aplikasi Canva dalam pembelajaran Informatika. Aplikasi Canva dinilai dapat meningkatkan minat dan motivasi belajar siswa, serta mendukung terciptanya pembelajaran yang lebih menarik dan interaktif. Siswa merasa terbantu dalam membuat desain dan presentasi yang menarik, sementara guru menemukan aplikasi ini efektif untuk menyampaikan materi pelajaran Informatika. Meskipun demikian, terdapat beberapa kendala yang dihadapi, seperti keterbatasan fasilitas dan kemampuan siswa dalam mengoperasikan aplikasi Canva. Secara keseluruhan, penggunaan aplikasi Canva sebagai media pembelajaran Informatika dinilai efektif dan dapat diterapkan di MA Al-Khairiyah Pipitan. Penelitian ini memberikan implikasi praktis bagi guru untuk memanfaatkan teknologi digital dalam inovasi pembelajaran, serta memberikan wawasan bagi penelitian selanjutnya terkait pemanfaatan aplikasi Canva atau media pembelajaran berbasis teknologi lainnya.
Perancangan Sistem Berita Acara Perkuliahan Online Menggunakan Framework Laravel Wijaya, Rehan Surya; Hayadi, B Herawan; Pratama, Gelard Untirtha
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.20449

Abstract

Proses pencatatan Berita Acara Perkuliahan (BAP) di Fakultas Ilmu Komputer Universitas Bina Bangsa masih dilakukan secara manual menggunakan formulir kertas. Prosedur ini kerap menimbulkan keterlambatan, kehilangan data, serta menyulitkan rekapitulasi informasi akademik secara efisien. Penelitian ini bertujuan untuk merancang dan mengembangkan aplikasi Berita Acara Perkuliahan Online yang dapat mempercepat, mempermudah, serta mendigitalisasi proses pencatatan dan pengelolaan BAP. Metode yang digunakan adalah model Waterfall dengan tahapan analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan pemeliharaan. Data dikumpulkan melalui observasi dan wawancara. Sistem dirancang menggunakan UML dan dibangun menggunakan framework Laravel dengan arsitektur Model-View-Controller (MVC). Hasil penelitian menunjukkan bahwa aplikasi ini dapat mempercepat proses pengisian dan validasi BAP, mengurangi kesalahan pencatatan, serta memudahkan pencarian data berdasarkan periode. Sistem juga menyediakan fitur akses yang berbeda untuk dosen, admin, dan mahasiswa. Kesimpulan dari penelitian ini adalah bahwa aplikasi BAP Online berhasil menjadi solusi digital yang efektif dan efisien untuk mendukung administrasi akademik yang modern dan terstruktur.
PENDEKATAN MACHINE LEARNING MENGGUNAKAN ALGORITMA C4.5 BERBASIS PSO DALAM ANALISA PEMAHAMAN PEMROGRAMAN WEBSITE R.H. Zer, P.P.P.A.N.W Fikrul Ilmi; Hayadi, B. Herawan; Damanik, Abdi Rahim
Jurnal Informatika dan Teknik Elektro Terapan Vol. 10 No. 3 (2022)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v10i3.2700

Abstract

Bahasa Pemrograman merupakan notasi-notasi yang digunakan untuk menulis sebuah program di komputer. Berdasarkan tingkat populernya bahasa pemrograman PHP yang digunakan untuk membuat Website. Matakuliah pemrograman website menjadi tolak ukur mahasiswa dalam membuat website untuk digunakan pembuatan Tugas Akhir. Terdapat beberapa mahasiswa kesulitan dalam memahami pemrograman website yang mengakibatkan banyak mahasiswa yang mengalami kesulitan dalam membuat Tugas Akhir Variabel yang digunakan dalam penelitian ini adalah Kemudahan, Familiar, Cara Ajar Dosen, Spesifikasi Perangkat yang dibutuhkan, dan Bentuk Pemrograman. Tujuan dalan penelitian ini adalah untuk melakukan mengklasifikasi pemahaman mahasiswa terhadap pemrograman website menggunakan metode C4.5 berbasis PSO dengan data sebanyak 100 sampel di AMIK Tunas Bangsa Pematangsiantar. Penelitian ini menghasilkan nilai akurasi data sebesar 83,00% dengan variabel Kemudahan merupakan node tertinggi. Dengan hasil penelitian ini dapat memberikan keputusan yang akan diambil oleh pihak AMIK Tunas Bangsa mengatasi permasalahan tersebut.
STRATEGI KEUANGAN DALAM MENINGKATKAN KUALITAS MANAJEMEN KEUANGAN DI SMPN 3 CILEGON Halabi, Ahmad; Rahmulyana, Anjar; Hayadi, B. Herawan; Yusuf, Furtasan Ali
Bhinneka Multidisiplin Journal Vol. 1 No. 2 (2024): Bhinneka Multidisiplin Journal
Publisher : Yayasan Education and Social Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53067/bmj.v1i2.8

Abstract

This research aims to analyze and evaluate the financial strategies implemented in improving the quality of financial management at SMPN 3 Cilegon. Good quality financial management in schools is a crucial factor in supporting the achievement of educational goals and human resource development. The research method used is a qualitative approach. Data was collected through observation, interviews and analysis of documents related to school finances. This research will focus on identifying financial strategies that have been implemented, such as budget allocation, financial resource management, and financial performance evaluation. SWOT analysis will be used to evaluate strengths, weaknesses, opportunities and threats in implementing financial strategies at SMPN 3 Cilegon. It is hoped that the research results will provide a deeper understanding of the effectiveness of the financial strategies that have been implemented, as well as provide recommendations for improvements to improve financial management at SMPN 3 Cilegon. The implications of this research can be a basis for policy makers, school principals and related parties in designing strategic policies that are more effective in improving the quality of financial management in secondary level educational institutions
PERAN PENTING MANAJEMEN KEUANGAN DI SDN GEDONG DALEM 01 KOTA CILEGON UNTUK MENCAPAI KEUNGGULAN PENDIDIKAN Junaesih, R.; Yusuf, Furtasan Ali; Hayadi, B. Herawan; Rahmulyana, Anjar; Raman, Raman; Yustiva, Fitriyatul
Bhinneka Multidisiplin Journal Vol. 1 No. 2 (2024): Bhinneka Multidisiplin Journal
Publisher : Yayasan Education and Social Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53067/bmj.v1i2.9

Abstract

This research explores the important role of financial management in achieving educational excellence at SDN Gedong Dalem 01, Cilegon City. Using qualitative and quantitative approaches, this research analyzes school financial data and conducts in-depth interviews with key stakeholders to understand the impact of effective financial management on the quality of education. The research results show that transparency, efficiency and wise allocation of funds are important factors in improving the quality of education in these schools. These findings are consistent with previous research which confirms the importance of good financial management in achieving educational goals. Practical implications of this research include the need to expand managerial and financial capacity for school staff through training and technical support. This research makes a significant contribution in strengthening understanding of the relationship between school financial management and the achievement of educational excellence, as well as providing direction for concrete efforts to improve managerial and financial capabilities at the school level
Predicting Campaign ROI Using Decision Trees and Random Forests in Digital Marketing Hayadi, B Herawan; El Emary, Ibrahiem M. M.
Journal of Digital Market and Digital Currency Vol. 1 No. 1 (2024): Regular Issue June 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v1i1.5

Abstract

Digital marketing has become a cornerstone of modern business strategies, leveraging various channels and technologies to promote products and services. Measuring the Return on Investment (ROI) is crucial in evaluating the effectiveness of these marketing campaigns. This study aims to predict the ROI of digital marketing campaigns using two prominent machine learning algorithms: Decision Trees and Random Forests. The primary objective of this research is to compare the performance of Decision Trees and Random Forests in predicting the ROI of digital marketing campaigns. The study focuses on evaluating the accuracy, precision, and robustness of these models, and identifying the key features that influence ROI. The dataset used in this study comprises 200,000 rows and 16 columns, detailing various aspects of digital marketing campaigns, including campaign type, target audience, duration, and channels used. Initial Exploratory Data Analysis (EDA) identified no missing values or duplicates, ensuring a clean dataset for modeling. Data preprocessing involved feature engineering and encoding categorical variables. The models were trained and evaluated using an 80-20 split for training and testing, with cross-validation applied to ensure robustness. The Decision Tree model achieved a Mean Squared Error (MSE) of 1.0896, a Root Mean Squared Error (RMSE) of 1.0439, a Mean Absolute Error (MAE) of 0.8958, and an R2 value of -0.0781. In contrast, the Random Forest model showed superior performance with an MSE of 1.0143, an RMSE of 1.0071, an MAE of 0.8755, and an R2 value of -0.0035. Cross-validation for the Random Forest model yielded a CV MSE of 1.0035, a CV RMSE of 1.0018, and a CV R2 of -0.0039, reinforcing its robustness and accuracy. The Random Forest model's superior performance is attributed to its ability to handle complex interactions between features and its robustness against overfitting. Key predictors such as Conversion_Rate, Acquisition_Cost, and Engagement_Score were identified as significant factors influencing ROI. The study discusses the practical implications of these findings for optimizing digital marketing strategies, acknowledging the limitations of data quality and model assumptions, and suggesting directions for future research, including the integration of additional data sources and exploration of advanced machine learning techniques. This study highlights the potential of machine learning models, particularly Random Forests, in predicting the ROI of digital marketing campaigns. The findings provide valuable insights for marketers to enhance their strategies and optimize budget allocations, emphasizing the importance of predictive analytics in achieving marketing success. Future work should focus on improving model accuracy and exploring new techniques to further advance the field of marketing analytics.
Enhancing Security and Efficiency in Decentralized Smart Applications through Blockchain Machine Learning Integration Hayadi, B Herawan; El Emary, Ibrahiem M. M.
Journal of Current Research in Blockchain Vol. 1 No. 2 (2024): Regular Issue September
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v1i2.16

Abstract

This study investigates the integration of machine learning (ML) into blockchain-based smart applications, aiming to enhance security, efficiency, and scalability. The research contributes a novel framework that combines blockchain's decentralized ledger with privacy-preserving ML techniques, addressing key challenges in data integrity and computational efficiency. The primary objective is to evaluate the performance of this integration in a simulated smart grid environment, focusing on security, processing time, energy consumption, and scalability. Our findings reveal that the integrated system significantly improves security, achieving a 98% success rate in mitigating data breaches and reducing the impact of adversarial attacks by 90%. Computational efficiency is also enhanced, with the optimized blockchain-ML configuration reducing processing time by 33% and energy consumption by 20% compared to standard blockchain setups. However, scalability remains a challenge; the system demonstrates effective scalability up to 100 nodes, beyond which transaction processing time increases by 50%, indicating the need for further optimization. The results suggest that while the integration of ML and blockchain offers substantial improvements in security and efficiency, addressing scalability and environmental impact are critical for broader application. The novelty of this research lies in its dual focus on enhancing both security and efficiency within blockchain-ML systems, providing a foundation for future advancements in decentralized intelligent applications across industries. This work contributes to the field by offering empirical data that supports the viability of blockchain-ML integration and by highlighting the areas where further research is needed to realize its full potential.
Co-Authors -, Basorudin Abdi Rahim Damanik Adyanata Lubis agung setiawan Agus Perdana Windarto Agustina Akhmad Zulkifli Alvin, Muhammad Ambarsari, Yuke Aramiko Kayanie Nenden Atryana Arifin, Rita Wahyu Arman Basri Asep Supriyanto Asyahri Hadi Nasyuha Bachtiar, Marsellinus Bayu Kusuma Budi Yanto Budi Yanto, Budi Budiarto, Mukti Cindy Paramitha Dahliyusmanto, Dahliyusmanto Damanik, Abdi Rahim David Setaiwan Dede Nurhasanah Devi Delawati Didik Setiyadi Dwi ASTUTI Dwiastuti, Dwiastuti Edi Roseno Eko Priyanto El Emary, Ibrahiem M. M. Engkos Kosasih Enny Widawati Erna Armita, NST Erni Rouza, Erni fatimah Fatimah Franciska, Yuni Furtasan Ali Yusuf Halabi, Ahmad Handayani, Meli Hartono Hartono Hayatul Masquroh Henderi . Hendrawati, Tuti Heni Pujiastuti Herlina Latipa Sari Hermawansyah, Hermawansyah Husni Teja Sukmana I Gede Iwan Sudipa Ichsan Firmansyah Ihlas Ahmad Subarkah Ilham Arifin Irawati Irawati ISKANDAR JAKA KUSUMA Jaka Kusuma Jaka Tirta Samudra Jaka Tirta Samudra Jufri -, Jufri Jufri Jufri Juhriah Juhriah, Juhriah Junaesih, R. Karina Andriani Kasman Rukun Kelvin Leonardi Kohsasih Khodijah Hulliyah Kim, Jin-Mook Luth Fimawahib M Haidar Husein Mahdi, Ahmad Masquroh, Hayatul Muadifah, Muadifah muflihah muflihah Muhammad Sadikin Mulyadi, Dadi Mursyid Irfan Musadad Musadad Novendra Adisaputra Sinaga Ovi Sakti Cahyaningtyas P. Eko Prasetyo P.P.P.A.N.W Fikrul Ilmi R.H. Zer Padeli Padeli Pardede, Doughlas Prasiwiningrum, Elyandri Pratama, Gelard Untirtha Pratama, Rinanda Rizki Puji Sari Ramadhan Putri, Nova Amelia R.H. Zer, P.P.P.A.N.W Fikrul Ilmi Rahmulyana, Anjar Raman Raman Raman, Raman Riandini, Meisarah RIKA ROSNELLY Rika Rosnelly Rinanda Rizki Pratama Rindi Genesa Hatika Rizky Ema Wulansari Rohim, Rouf Rubianto Rudi Gunawan Saepudin Saepudin Safril Safril Sartika Mandasari Sepriyanti, Sepriyanti Shafiera, Eghar Siregar, Pariang Sonang Sofiana, Sofa sono, Aji Sudar Suheti, Suheti Suirat, Suirat Sumiyati SUMIYATI SUMIYATI Suwarni Suwarni Swastika, Rulin Tambunan, Fazli Nugraha Teddy Surya Gunawan Toyibah, Toyibah Tutut Herawan Uniba, Muadifah Utomo, Ahmar Dwi Wahdi, Adi Wanayumini Wijaya, Rehan Surya Wiwik Handayani Wiwik Novianawati Yuke Ambarsari Yuni Franciska Tarigan Yuningsih, Yuyun Yustiva, Fitriyatul Zakarias Situmorang