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All Journal JIK Jurnal Ilmu Komputer Majalah Ilmiah Matematika Komputer Nuansa Informatika Jurnal Teknologi Informatika dan Komputer Jurnal Pemberdayaan Komunitas MH Thamrin Jurnal Jaring SainTek International Journal of Business, Law, and Education Jurnal Ilmu Ekonomi Manajemen dan Akuntansi Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Jurnal Informatika Dan Tekonologi Komputer (JITEK) Indonesia Journal of Engineering and Education Technology (IJEET) Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Jurnal Informatika Dan Tekonologi Komputer
Yohanes Bowo Widodo
Universitas Mohammad Husni Thamrin
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Kecerdasan Buatan dalam Pendidikan: Meningkatkan Pembelajaran Personalisasi Widodo, Yohanes Bowo; Sibuea, Sondang; Narji, Mohammad
Jurnal Teknologi Informatika dan Komputer Vol. 10 No. 2 (2024): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i2.2324

Abstract

Penelitian ini mengkaji peran Kecerdasan Buatan (Artificial Intelligence) dalam pendidikan, khususnya dalam meningkatkan pembelajaran personalisasi. Pembelajaran personalisasi adalah pendekatan yang disesuArtificial Intelligencekan dengan kebutuhan, kecepatan, dan preferensi individu, memungkinkan siswa mendapatkan pengalaman belajar yang lebih efektif dan relevan. Melalui penerapan Artificial Intelligence, seperti sistem rekomendasi berbasis data, analisis prediktif, dan chatbot cerdas, proses pendidikan dapat dioptimalkan untuk memberikan dukungan yang lebih baik bagi siswa. Penelitian ini mengeksplorasi berbagai teknologi Artificial Intelligence yang digunakan dalam pendidikan, manfaatnya dalam mendukung gaya belajar individual, serta tantangan yang mungkin muncul dalam implementasinya, termasuk masalah privasi, bias algoritma, dan aksesibilitas teknologi. Hasil penelitian menunjukkan bahwa penerapan Artificial Intelligence dalam pendidikan dapat meningkatkan keterlibatan siswa, mempercepat proses pembelajaran, dan menyediakan umpan balik yang lebih tepat waktu. Meskipun demikian, regulasi dan kebijakan yang tepat dibutuhkan untuk memaksimalkan potensi Artificial Intelligence sekaligus meminimalkan risiko yang mungkin timbul. Penelitian ini akan mengeksplorasi bagaimana Artificial Intelligence dapat digunakan untuk menciptakan pengalaman belajar yang lebih personal bagi siswa. Dengan menggunakan algoritma pembelajaran mesin, sistem pendidikan dapat menganalisis gaya belajar individu dan menyesuaikan materi ajar sesuai dengan kebutuhan masing-masing siswa. Penelitian ini juga akan membahas tantangan etis dan privasi yang mungkin muncul dalam pengumpulan data siswa. Secara keseluruhan, penelitian ini menyimpulkan bahwa AI memiliki potensi besar untuk mengubah sistem pendidikan menjadi lebih adaptif dan personal. Namun, untuk memaksimalkan dampak positifnya, implementasi Artificial Intelligence dalam pendidikan harus diiringi dengan persiapan yang matang, termasuk pengembangan kebijakan, pelatihan guru, serta penyediaan infrastruktur dan akses yang merata.
Pengembangan Model Machine Learning untuk Rekomendasi Produk Berdasarkan Analisis Pola Pembelian Sibuea, Sondang; Widodo, Yohanes Bowo
Jurnal Teknologi Informatika dan Komputer Vol. 10 No. 2 (2024): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i2.2354

Abstract

Dalam era digital saat ini, sistem rekomendasi menjadi komponen penting dalam platform e-commerce untuk meningkatkan pengalaman pengguna dan penjualan. Penelitian ini bertujuan untuk mengembangkan model machine learning yang mampu merekomendasikan produk secara personalisasi berdasarkan analisis pola pembelian pengguna. Algoritma Collaborative Filtering dan Content-Based Filtering diterapkan dalam penelitian ini untuk mengidentifikasi preferensi pelanggan dan memberikan rekomendasi yang relevan. Dataset yang digunakan terdiri dari riwayat transaksi pengguna, informasi produk, serta atribut demografis pengguna. Model Collaborative Filtering menggunakan pendekatan berbasis pengguna dan produk untuk mengidentifikasi kemiripan antara pola pembelian, sedangkan model Content-Based Filtering menganalisis fitur produk untuk memberikan rekomendasi produk yang mirip dengan yang telah dibeli pengguna. Hasil dari kedua model ini dikombinasikan menggunakan teknik Hybrid Filtering untuk meningkatkan akurasi dan relevansi rekomendasi. Evaluasi model dilakukan dengan menggunakan metrik seperti precision, recall, Mean Average Precision (MAP), dan Mean Squared Error (MSE). Hasil eksperimen menunjukkan bahwa model hybrid mampu memberikan rekomendasi produk dengan tingkat akurasi yang lebih tinggi dibandingkan model individu. Model ini juga menunjukkan peningkatan dalam keterlibatan pengguna dan potensi peningkatan penjualan melalui rekomendasi yang lebih tepat sasaran. Penelitian ini menyimpulkan bahwa pengembangan sistem rekomendasi berbasis machine learning yang efektif dapat memberikan keuntungan kompetitif bagi platform e-commerce dengan meningkatkan kepuasan pengguna serta memperluas cakupan produk yang dipromosikan. Model ini juga dapat disesuaikan dengan kebutuhan pasar yang berbeda melalui penyesuaian parameter dan pengoptimalan berkelanjutan.
Artificial Intelligence for Unstructured Data Processing Widodo, Yohanes Bowo; Widyahastuti, Febrianti; Narji, Mohammad; Sibuea, Sondang
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 1 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i1.2542

Abstract

In the digital era, the volume of unstructured data such as text, images, audio, and video continues to increase exponentially. Processing unstructured data is a major challenge for various industries due to its high complexity and the difficulty of extracting relevant information. Artificial Intelligence (AI) has become an innovative solution in addressing this challenge through techniques such as Natural Language Processing (NLP), Computer Vision, and Machine Learning. This study aims to explore various AI methods used in processing unstructured data and examine their effectiveness in improving the efficiency and accuracy of data analysis. adopts a multidisciplinary approach that combines natural language processing (NLP), machine learning, and data analytics techniques to extract information from unstructured data, especially in the context of electronic medical records (EMR). This study will be conducted in several stages including data collection, data processing, model development, and evaluation of results. The results show that AI is not only able to automate the information extraction process but also improve the accuracy and speed of data analysis, which is very important in the context of decision making in the fields of healthcare, finance, and business. By using deep learning models and advanced algorithms, AI can identify patterns and relationships in complex data, thereby providing deeper insights for better decision making. The results of this study are expected to provide insight for developers and practitioners in optimizing the use of AI to manage unstructured data more effectively and efficiently.
YOLOv12 for Human Object Detection in Real-time Video Surveillance Systems Widodo, Yohanes Bowo; Sibuea, Sondang; Agustino, Rano
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2789

Abstract

This research discusses the application of the YOLO (You Only Look Once) model to detect human objects in real-time video surveillance systems. This model was developed in response to the increasing need for efficiency and accuracy in video surveillance analysis, particularly in identifying abnormal or malicious activities. The application of deep learning technology, especially the YOLO model, has been shown to provide better performance in object recognition compared to traditional methods, such as SVM and Haar-Cascade, which often experience limitations in terms of speed and accuracy. One significant contribution of the use of YOLO lies in its ability to detect objects simultaneously in high-speed video, which is crucial in surveillance contexts that require rapid response to incidents. The implementation of YOLO also promises better collaboration between edge and cloud computing, allowing video processing to be carried out closer to the data source, reducing latency and improving data security. With this approach, the system can generate relevant information for rapid decision-making, such as monitoring human behavior in public settings and detecting suspicious activity. The analysis of this study highlights the significant potential of YOLO in improving real-time video surveillance systems and demonstrates that more accurate object detection capabilities can improve overall public safety. Through this model, we hope to revolutionize surveillance practices, adapt to modern needs, and provide a solid foundation for further development in the field of video surveillance.
Stock Investment with Bollinger Band Indicator, Moving Average and Relative Strength Index of Three Big Capitalization Issuers of Telecommunication Infrastructure Ependi; Ningsih, Putu Tirta Sari; Gusvarizon, Muhammad; Widodo, Yohanes Bowo
Ilmu Ekonomi Manajemen dan Akuntansi Vol. 6 No. 1 (2025): Jurnal Ilmu Ekonomi Manajemen dan Akuntansi
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/ileka.v6i1.2587

Abstract

The purpose of the study is to determine the buying and selling prices of three Big Cavitalization Infrastructure Telecommunication issuers in the 2020-2023 period with the Bollinger Brand, Moving Average and Relative Strength Index indicators. Quantitative research with secondary data on the research population of three Big Cavitalization Infrastructure Telecommunication issuers using the Bollinger Bands indicator to determine the Buy signal can be seen when the Candle touches the lower band, while to determine the Sell signal can be seen when the Candle touches the upper band. From the results of the study, the total signal accuracy level was obtained as many as 53 (fifty-three) signals, consisting of 20 Buy and Sell signals with an accuracy level of 100%. Consisting of 40% correct signals and 60% incorrect signals at PT Telkom Indonesia (Persero) Tbk, 15 Buy and Sell signals with 100% accuracy rate consisting of 73.3% correct signals and 26.7% incorrect signals at PT Indosat Tbk, 18 Buy and Sell signals with 100% accuracy rate consisting of 33.3% correct signals and 66.7% incorrect signals at PT XL Axiata Tbk. The results of this study obtained a total Capital Gain of 148.85% and a total Capital Loss of -116.68%, consisting of 34.07% Capital Gain and -55.89% Capital Loss at PT Telkom Indonesia (Persero) Tbk, 69.2% Capital Gain and -18.89% Capital Loss at PT Indosat Tbk, 45.58% Capital Gain and -41.9% Capital Loss at PT XL Axiata Tbk. It can be seen that using the Bollinger Bands Indicator can provide quite good results compared to using the Moving Average and Relative Strength Index indicators.
Analisis Pendataan Berita Acara Temuan Selisih Berbasis Web pada PT Bank negara Indonesia, Tbk Yohanes Bowo Widodo; Kiki Kurniawan; Reni Febrianti
Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Vol. 1 No. 3 (2021): November : Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jaem.v1i3.34

Abstract

Bank Negara Indonesia is a state-owned company that operates as a financial institution that has been around for more than 70 years. However, in its development it turns out that Information Technology has not been applied by all parts of PT. Bank Negara Indonesia, Tbk. In processing the data on the minutes of discrepancy findings. PT. Bank Negara Indonesia, Tbk still uses manual bookkeeping to collect data on findings of discrepancies. So that there are often invalidities and discrepancies in the data collection of the minutes of discrepancies found. Therefore, it is very necessary to have a data collection system for the minutes of discrepancies found. Based on this, it is necessary to create an application system related to data collection of minutes of discrepancies found at PT. Bank Negara Indonesia, Tbk The method that will be used in making the application is using the SSAD method with the steps of Feasibility, Investigation of the Current Environment, Business System Options, Definition Requirements, Technical System Options, Logical Design and Physical Design. With this method, it is hoped that application programs can be created according to the company's needs. With the application of data collection on the minutes of discrepancies found at PT. Bank Negara Indonesia Tbk, the process of finding the difference becomes easier and the data stored is well maintained and can be easily searched.
ANALISIS PENGARUH NET PROFIT MARGIN DAN CURRENT RATIO TERHADAP DIVIDEND PAYOUT RATIO PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI PT. BURSA EFEK INDONESIA Putu Tirta Sari Ningsih; Muhammad Gusvarizon; Nur Fadilla; Yohanes Bowo Widodo
Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Vol. 1 No. 3 (2021): November : Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jaem.v1i3.74

Abstract

This study aims to determine: (1) The effect of Net Profit Margin on Dividend Payout Ratio in manufacturing companies at PT. Indonesia stock exchange. (2) Effect of Current Ratio on Dividend Payout Ratio in manufacturing companies at PT. Indonesia stock exchange. (3) Effect of Net Profit Margin and Current Ratio on Dividend Payout Ratio in manufacturing companies at PT. Indonesia stock exchange. The research method is descriptive quantitative. In this study, there are two independent variables, namely Net Profit Margin and Current Ratio and one dependent variable, namely the Dividend Payout Ratio. The sampling technique used purposive sampling with a sample of 12 manufacturing companies registered at PT. Indonesia stock exchange. Data analysis used multiple regression analysis. Based on the results of data analysis obtained: (1) There is a joint influence between Net Profit Margin and Current Ratio on the Dividend Payout Ratio. (2) There is a significant effect of Net Profit Margin on the Dividend Payout Ratio. (3) There is a significant effect of Current Ratio on Dividend Payout Ratio.
ANALISIS PELAKSANAAN PENGELOLAAN PEMUNGUTAN, PENYETORAN, DAN PELAPORAN PPN DAN PPh PASAL 22 WAJIB PUNGUT BUMN PADA PERUM PERUMNAS KANTOR PUSAT Gatot Hery Djatmika; Putu Tirta Sari Ningsih; Erent Dany Pratama; Yohanes Bowo Widodo
Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Vol. 1 No. 1 (2021): Maret : Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jaem.v1i1.82

Abstract

This study aims to determine the process of applying collection, depositing, reporting value added tax and income tax article 22 compulsory collection, and tax compliance Perum Perumnas. In this study the dependent variable used is PMK-136 /PMK.03 / 2012, PMK-37 / PMK.03 / 2015, and UU KUP No. 16 of 2009, while the independent variable in this study is the Obligatory Value Added Tax Collection, Article 22 Income Tax and Tax Compliance. This study uses descriptive qualitative research methods and the data used in the form of secondary data is a report on the Period of Value Added Tax Collection and Notification of Income Tax Article 22 during January to December 2018. The population in this study is Perumnas Corporation engaged in real estate owned by a State-Owned Enterprise. And using information from 3 people from Perum Perumnas to dig up information and data related to taxation at Perum Perumnas, using unstructured interviews, documentation, and literature studies. Data analysis techniques begin by revealing events or facts, circumstances, phenomena, variables and circumstances that occur when the study takes place by presenting what actuallyhappened. The results of this study indicate that in general the process of applying collection, depositing, reporting on Value Added Tax and Income Tax Article 22 Mandatory Collection is in accordance with PMK-136 / PMK.03 / 2012 and PMK-37 / PMK.03 / 2015, and can it was concluded that Perum Perumnas was obedient in carrying out its tax obligations in accordance with the general tax provisions Law No. 16 of 2009.
PENGARUH PENGETAHUAN PAJAK DAN TINGKAT PENGHASILAN TERHADAP KEPATUHAN WAJIB PAJAK DALAM MEMBAYAR PAJAK KENDARAAN BERMOTOR PADA KELURAHAN BEKASI JAYA Gatot Hery Djatmika; Budi Harsono; Rosidah Rosidah; Yohanes Bowo Widodo
Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis Vol. 1 No. 2 (2021): Juli: Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jaem.v1i2.84

Abstract

This study aims to examine and analyze the influence of tax knowledge and income levels on taxpayer compliance in paying motor vehicle taxes in the area of Bekasi Jaya, East Bekasi. The data was collected through questionnaires and conducted on 100 respondents residing in the area of Bekasi Jaya Urban Village, East Bekasi. Data analysis in this study using SPSS version 22. The analysis technique used is multiple regression analysis with the least squares equation and hypothesis test using t-statistics to test the partial regression coefficient with level of significance 5%. In addition, the validity test, reliability test, and classic assumption test include normality test, multicollinearity test, and heteroscedasticity test. The results showed that: (1) There is a positive and significant influence between tax knowledge with taxpayer compliance t value> t table (6,709> 1,66) and significance <0,05 (0,000 <0,05), Ho is rejected. (2) There is a significant positive influence between income level with taxpayer compliance, t count> t table (6,917>1,66) and significance <0,05 (0,000 <0,05), Ho is rejected. Based on the results of research are not found variables that deviate from the classical assumption, it shows that the available data have been qualified to use multiple linear regression equation model. From the results of research indicates that taxpayer compliance and income level have a positive effect on taxpayer compliance. The predictive ability of both variables on taxpayer compliance is 70.1%.
PERANCANGAN ROBOT PEMADAM API DENGAN PENGONTROLAN GERAK METODE PROPORTIONAL INTEGRAL DERIVATIVE (PID) MENGGUNAKAN SENSOR SONAR BERBASIS MIKROKONTROLLER Sondang Sibuea; Agung Rahmaddoni; Yohanes Bowo Widodo
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 1 No. 3 (2021): November : Jurnal Informatika dan Teknologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v1i3.83

Abstract

This research designs and implements a control algorithm on a wheeled wall follower robot that uses a PID controller (Proportional, Integral, Differential) as a navigation system for a wall follower fire fighting robot. The task of this robot is to walk along the walls of the area. The PID controller aims to smooth the movement of the robot when tracing the track space. With the help of the PID controller, the wall follower robot is able to navigate safely, smoothly, responsively and quickly. Fire fighting robots require a variety of sensors to run properly, one of which is using sonar sensors that are used for robot navigation. This sensor works based on the principle of wave reflection, where in this case the variable measured is the time of reflection since the wave was emitted. The sonar sensor detects an obstruction. The robot will turn and walk again without hitting obstacles or objects in the vicinity. To detect fire, fire sensor is used. This sensor also find hotspots by assessing the intensity of the light. Arduino ATMega328 microcontroller functions as a robot control. The output of the microcontroller will produce logic 1 to activate the motor driver to activate the right and left wheel motors. The DC motor is used as a driving force for the robot, and the battery here functions as a power supply for the robot. The result is, this robot can detect the fire point of the candle and extinguish the candle flame.
Co-Authors Achmad Rivaldi Ade Muhammad Ichsan Adrie Oktavio Agie Annan Agung Rahmaddoni Agus Wiyatno Ahmad Gunawan Ajeng Tias Endarti Akbar, Khoironi Fanana Amin Sakaria, Muhammad Andika Dirsa Andrian, Feri Anggraeini, Silvia Ayu Anindya, Aulia Arie Bayu Untoro Arie Bayu Untoro Aulia Anindya Budi Harsono Budi Harsono Dedi Setiadi Dedi Setiadi Ependi Erent Dany Pratama Erent Dany Pratama Febrianti Widyahastuti Febrianti, Reni Febrianto Febrianto Febrianto Febrianto, Febrianto Fenty Tristanti Julfia Fenty Tristanti Julfia Feri Andrian Fius Bryan Nigel M. Sinaga Gatot Hery Djatmika Gatot Hery Djatmika Gustiawan, Handa Gusvarizon, Muhammad Handa Gustiawan Handa Gustiawan Hasan Basri Ibrahim Aziz Indira Meilita Istifadah Istifadah Julfia, Fenty Tristanti Khaliq, Muhammad Nur Kiki Kurniawan Kiki Kurniawan Leo Faturahman Lily Nabilah Lingga Hanggada Adi Saputra Miftachul Amri Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro Mohammad Ikhsan Saputro, Mohammad Ikhsan Muhammad Amin Sakaria Muhammad Bahrul Lutfianto Muhammad Gusvarizon Muhammad Gusvarizon Muhammad Nur Khaliq Nadia Lutfiana Sari Narji, Mohammad Ni Desak Made Santi Dwyarthi Ningsih, Putu Tirta Sari Nur Asniati Djaali Nur Fadilla Nur Fadilla Purnomo Purnomo Putu Tirta Sari Ningsih Rahman, Taslim Idris Rano Agustino Reni Febrianti Reni Febrianti RIO ANDRIYAT KRISDIAWAN Rosidah Rosidah Rosidah Rosidah Sakaria, Muhammad Amin Silvia Ayu Anggraeini Simaibang, Frenta Helena Sinaga, Fius Bryan Nigel M. Sondang Sibuea Sondang Sibuea Sopian, Abu Sutanto Priyo Hastono Sutrisno Sutrisno Sutrisno, Sutrisno Taslim Idris Rahman Tata Sutabri Tri Octavianto Untoro, Arie Bayu Via Yustitia Vidi Lampah Widyahastuti, Febrianti Wiwit Wijayanti, Wiwit Yudhazaldi Nuki Putrasandi Yustinus Tri Handoyo