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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Pseudocode JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research ADI Journal on Recent Innovation (AJRI) Cyber Security dan Forensik Digital (CSFD) IJIIS: International Journal of Informatics and Information Systems ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Cyber and IT Service Management (IJCITSM) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Journal of Digital Market and Digital Currency Journal of Current Research in Blockchain International Journal Research on Metaverse
Husni Teja Sukmana
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Other

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Game Theoretical-Based Logistics Costs Analysis: A Review Husni Teja Sukmana; Andree Emmanuel Widjaja; Hery Juan Situmorang
International Transactions on Artificial Intelligence Vol. 1 No. 1 (2022): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i1.166

Abstract

As the range and complexity of outsourced services for logistics increase, Logistics has evolved into a distinct commercial service. The question of how to fairly charge logistics services has grown urgent. In this study, we conduct a comprehensive evaluation of the academic research on the cost of logistics services employing bibliometric and analyzing the content methodologies, with a focus on the application of game theory. Using three criteria logistics situations, game models, and influencing factors, we contrast and evaluate the research. This research examines the important stakeholders and research situations in logistics pricing examine the most suitable and often utilized game models, as well as highlights the primary elements determining logistics pricing. To close the gaps in our current understanding, we offer potential study directions. The present level of evidence-based study in the area of price for logistics is thoroughly reviewed in this work, this contributes to the creation of new models. From a pricing perspective, the results of this investigation are helpful in the advancement of logistics services, as a result, logistical activities will be more economical as well as environmentally sustainable.
Keamanan Jaringan Wi-Fi Terhadap Serangan Packet Sniffing Menggunakan Firewall Rule (Studi Kasus : Pt. Akurat.Co) Arini, Arini; Luthfi Arsalan, Muhammad; Teja Sukmana, Husni
Cyber Security dan Forensik Digital Vol. 6 No. 2 (2023): Edisi Bulan November tahun 2023
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2023.6.2.4075

Abstract

Wifi sangat rentan terhadap berbagai ancaman serangan seperti packet sniffing, sistem keamanan dan identifikasi yang baik diperlukan untuk mencegah serangan oleh oknum yang tidak bertanggung jawab. PT Akurat.co merupakan perusahaan media berita yang bergerak dibidang teknologi informasi yang berpotensi terjadi permasalahan keamanan jaringan karena terdapat port-port terbuka dan pengimplementasian topologi jaringan yang tidak aman. Untuk mengatasi masalah tersebut terdapat beberapa cara, berupa pencegahan dan pendeteksian. Salah satu bentuk pencegahan adalah firewall rule fitur yang terdapat di Mikrotik Router OS berfungsi sebagai pemberi akses paket koneksi. Metode simulasi menjadi dasar pada penelitian ini untuk mensimulasikan kejadian serangan pada wifi. Dengan adanya proses pengujian untuk sistem keamanan jaringan wifi yang berupa usaha penyusupan dengan percoban serangan arp spoofing untuk mencari username dan password dan percobaan scanning port untuk mencari port yang terbuka dan percobaan serangan ddos attack untuk mengirimkan paket ke target dan mengimplementasikan firewall rule terhadap serangan yang telah dilakukan. Firewall rule berhasil melakukan action drop terhadap seranga arp spoofing sehingga serangan tersebut dapat diproteksi, action tartip berhasil mengecoh port yang tebuka adalah port tipuan dan berhasil melakukan drop terhadap pengiriman paket yang banyak. Sehingga sistem keamanan jaringan terjaga dengan aman, dan setiap aktivitas peretasan berhasil di cegah oleh firewall rule mikrotik. Kata kunci: keamanan jaringan, wireless fidelity, packet sniffing, firewall rule mikrotik router os. ------------------------------------------------------------------------- Wifi is very vulnerable to various threats, such as packet sniffing. Good security and identification systems are needed to prevent attacks by irresponsible people. PT Akurat.co is a news media company operating in the field of information technology that has potential network security problems due to the existence of open ports and the implementation of an unsafe network topology. There are several ways to deal with the problem: prevention and detection. One form of precaution is the firewall rule feature that is present in Mikrotik Router OS and serves as the access provider for the connection package. The simulation method forms the basis for this research to simulate attacks on WiFi. With the testing process for the wifi network security system, there is an intrusion attempt with an arp spoofing attack attempt to find a username and password, a port scanning experiment to find an open port, and an attempt at a DDoS attack to send a package to the target. Implement a firewall rule against an attack that has been carried out. The firewall rule successfully performed an action drop against an arp spoofing attack so that the attack can be protected. The action tartip successfully blocked the port that was opened as a fraudulent port and successfully executed an action drop against the delivery of many packages. So the network security system is awake safely, and any hacking activity is successfully prevented by a Mikrotik firewall rule. Keywords: Network security, wireless fidelity, packet sniffing, firewall rule mikrotik router os.
Predicting Airline Passenger Satisfaction with Classification Algorithms Hayadi, B.Herawan; Kim, Jin-Mook; Hulliyah, Khodijah; Sukmana, Husni Teja
International Journal of Informatics and Information Systems Vol 4, No 1: March 2021
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i1.80

Abstract

Airline businesses around the world have been destroyed by Covid-19 as most international air travel has been banned. Almost all airlines around the world suffer losses, due to being prohibited from carrying out aviation transportation activities which are their biggest source of income. In fact, several airlines such as Thai Airways have filed for bankruptcy. Nonetheless, after the storm ends, demand for air travel is expected to spike as people return for holidays abroad. The research is aimed at analyzing the competition in the aviation industry and what factors are the keys to its success. This study uses several classification models such as KNN, Logistic Regression, Gaussian NB, Decision Trees and Random Forest which will later be compared. The results of this study get the Random Forest Algorithm using a threshold of 0.7 to get an accuracy of 99% and an important factor in getting customer satisfaction is the Inflight Wi-Fi Service.
The Success Factors of E-Philanthropy are Determined Based on Perceived Trust, Perceived Usefulness, Subjective Norms, Enjoyment and Religiosity: A Case Study on a Charity Site Sukmana, Husni Teja; Nanang, Herlino; Agustin, Fenty Eka Muzayyana; Aristoi, Zidny Fiqha; Azizah, Khansa
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.310

Abstract

The rapid development of information technology and social media has significantly influenced people's behaviors and preferences in various activities, including philanthropy. Traditionally, philanthropic activities necessitated direct interpersonal interactions. However, the advent of ephilanthropy has enabled more practical and accessible ways to engage in charitable activities anytime and anywhere using electronic technology. This study examines the perceived role of e-philanthropy users in Indonesia and their intention to make actual donations through crowdfunding for humanitarian purposes. The research integrates the Technology Acceptance Model (TAM) and the IS success model, supplemented by additional variables like trust, usefulness, subjective norms, and religiosity. Data were collected from 231 respondents across Indonesia using online questionnaires and analyzed using the PLS-SEM method. The findings indicate significant relationships between perceived quality and trust (t-value = 7.156, path coefficient = 0.681), trust and perceived usefulness (t-value = 31.724, path coefficient = 0.886), and religiosity and intention to use (t-value = 3.206, path coefficient = 0.360). However, perceived enjoyment (t-value = 1.100, path coefficient = 0.140), subjective norms (t-value = 1.448, path coefficient = 0.162), and perceived trust (t-value = 1.023, path coefficient = 0.128) did not significantly influence the intention to use e-philanthropy platforms. These insights can inform strategies to enhance user participation and trust in e-philanthropy initiatives in Indonesia.
Comparative Analysis of SVM and RF Algorithms for Tsunami Prediction: A Performance Evaluation Study Sukmana, Husni Teja; Durachman, Yusuf; Amri, Amri; Supardi, Supardi
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.159

Abstract

This study explores the use of machine learning algorithms, specifically SVM and RF, for predicting tsunamis, a crucial aspect of disaster management. The research utilized earthquake data from 2001 to 2023, evaluating these models based on accuracy, precision, recall, F1-score, and ROC AUC, emphasizing features like magnitude, depth, and alert levels. The SVM model demonstrated an accuracy of 65.61%, precision of 70.59%, recall of 19.67%, F1-score of 30.77%, and ROC AUC of 62.15%. In comparison, the RF model showed an accuracy of 61.15%, precision of 50.00%, higher recall of 36.07%, F1-score of 41.90%, and ROC AUC of 63.84%. These results highlight the distinct strengths of each model: SVM's precision makes it suitable for minimizing false positives, while RF's higher recall indicates its effectiveness in detecting actual tsunamis. The findings underscore the significance of selecting the appropriate model for tsunami prediction based on specific disaster management needs and the inherent trade-offs in model selection. The research concludes that SVM and RF models provide valuable yet distinct contributions to tsunami prediction. Their application should be customized to disaster management requirements, balancing accuracy and operational efficiency. This study contributes to disaster risk management and opens avenues for further research in enhancing the accuracy and reliability of machine learning in natural disaster prediction and response systems.
Survey Opinion using Sentiment Analysis Hariguna, Taqwa; Sukmana, Husni Teja; Kim, Jong Il
Journal of Applied Data Sciences Vol 1, No 1: SEPTEMBER 2020
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v1i1.10

Abstract

Sentiment analysis or opinion mining is a computational study of the opinions, judgments, attitudes, and emotions of a person towards an entity, individual, issue, event, topic, and attributes. This task is very challenging technically but very useful in practice. For example, a business always wants to seek opinion about its products and services from the public or the consumers. Additionally, potential consumers want to learn what users think they have when using a service or purchasing a product. To get public opinion on food habits, ad strategies, political trends, social issues and business policy, this is a very critical factor. This paper will explain a survey of key sentiment-extraction approaches.
Implementasi Pembelajaran Jarak Jauh di Fakultas Sains dan Teknologi Pasca Covid-19 Sukmana, Husni Teja; Rozy, Nurul Faizah; Eiji, Arta
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 2 No 2 (2024): Maret
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v2i2.487

Abstract

Pandemi Covid-19 yang melanda dunia telah mengakibatkan transformasi mendalam dalam sektor pendidikan, mendorong pertumbuhan pembelajaran jarak jauh sebagai alternatif penting saat pembelajaran tatap muka terhambat. Meskipun menawarkan fleksibilitas, transisi ke pembelajaran daring memerlukan adaptasi yang bertahap. Kendala yang dihadapi siswa, seperti koneksi internet yang tidak stabil dan dukungan finansial, menyoroti kebutuhan akan aksesibilitas teknologi yang lebih baik. Strategi pembelajaran yang berpusat pada siswa, melalui integrasi Teknologi Informasi dan Komunikasi (TIK) serta teknik pembelajaran aktif, dapat meningkatkan keterlibatan dan hasil pembelajaran. Penelitian ini mengevaluasi berbagai aspek pembelajaran jarak jauh, termasuk proses pembelajaran, sarana-prasarana, dan aspek psikologis siswa di Fakultas Sains dan Teknologi (FST). Tujuan penelitian adalah memberikan gambaran menyeluruh, mengevaluasi dampak, dan menyusun rekomendasi. Metodologi penelitian menggunakan pendekatan survei dengan 500 responden mahasiswa FST melalui kuesioner elektronik. Analisis data dilakukan dengan metode statistik deskriptif. Temuan penelitian menunjukkan preferensi terhadap model pembelajaran hibrid yang menggabungkan pembelajaran di kelas dan daring dan menegaskan pentingnya perencanaan yang matang serta dukungan infrastruktur untuk menjaga kualitas pendidikan di era pasca-Covid-19. Penelitian ini memberikan pemahaman yang mendalam tentang implementasi pembelajaran jarak jauh di FST, menyoroti tantangan yang dihadapi serta rekomendasi untuk perbaikan dan pengembangan ke depannya.
Transformer Architectures for Automated Brain Stroke Screening from MRI Images Abstract Sukmana, Husni Teja; Hasibuan, Zainal Arifin; Rahman, Abdul Wahab Abdul; Bayuaji, Luhur; Masruroh, Siti Ummi
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.736

Abstract

Early and accurate detection of stroke is critical for timely medical intervention and improved patient outcomes. This study explores the application of deep learning models, particularly the Vision Transformer (ViT), for the automated classification of brain stroke from medical images. A curated dataset of brain scans was used to train and evaluate the ViT model, which was benchmarked against a widely used convolutional neural network (CNN), ResNet18. Both models were trained using transfer learning techniques under identical preprocessing and training configurations to ensure fair comparison. The results indicate that the ViT model significantly outperforms ResNet18 in terms of validation accuracy, class-wise precision, and recall, achieving a peak accuracy of 99.60%. Visual analyses, including confusion matrices and sample prediction comparisons, reveal that ViT is more robust in detecting subtle stroke patterns. However, ViT requires more computational resources, which may limit its deployment in real-time or low-resource settings. These findings suggest that transformer-based architectures are highly effective for medical image classification tasks, particularly in stroke diagnosis, and offer a viable alternative to traditional CNN-based approaches.
A Comparative Study of Naive Bayes, SVM, and Decision Tree Algorithms for Diabetes Detection Based on Health Datasets Nurwicaksana, Satria; Oh, Lee Kyung; Sukmana, Husni Teja
International Journal of Informatics and Information Systems Vol 7, No 4: December 2024
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v7i4.230

Abstract

Diabetes is a chronic, progressive condition whose global prevalence continues to rise, creating substantial public health and economic burdens. Early diagnosis and timely intervention are critical to preventing severe complications and improving long-term patient outcomes. In recent years, artificial intelligence (AI) particularly machine learning (ML) has emerged as a powerful tool in medical diagnostics, offering capabilities in automated pattern recognition and disease classification. This study aims to evaluate and compare the predictive performance of three supervised ML algorithms such as Naïve Bayes, Support Vector Machine (SVM), and Decision Tree for classifying and predicting diabetes based on two primary physiological indicators: glucose level and blood pressure. The dataset employed was sourced from Kaggle, comprising 995 patient records containing relevant clinical attributes. The research methodology involved several stages, including data preprocessing to ensure quality and consistency, data partitioning into training and testing subsets using an 80:20 split ratio, model training, and performance evaluation. Each algorithm’s effectiveness was measured using accuracy, precision, recall, and F1-score metrics. The experimental findings demonstrate that the Decision Tree algorithm achieved the highest classification accuracy (94.47%), outperforming SVM and Naïve Bayes, both of which recorded 92.96% accuracy. Moreover, the Decision Tree exhibited balanced precision and recall values, underscoring its robustness in identifying both diabetic and non-diabetic cases with minimal misclassification. These outcomes indicate that the Decision Tree model provides an optimal balance between predictive accuracy and interpretability, making it particularly suitable for clinical decision-support applications.
Modern Technology Advances with Benefits for Humanity to Demonstrate Design with Conventional Sources Islamic Lestari Santoso, Nuke Puji; Dudhat, Amitkumar; Teja Sukmana, Husni; Mardiansyah, Aditya; Hardini, Marviola
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 1 No. 1 (2021): April
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (983.056 KB) | DOI: 10.34306/ijcitsm.v1i1.8

Abstract

There is an urgent interest among Muslims to participate in broader religious thought activities regarding the nature of modern technology in response to the refutation presented by the ideals of current technology. The impact and use on understanding modern technology cannot be limited. It is so much more pervasive because it conditions ideas, creates our goals and desires. In order to measure modern technology from within the framework of Islamic ethics and design the Islamic paradigm, this is very important by looking at psychological, spiritual, social, moral and circles of the latest postmodernist technology. For holistic insight and moral enhancement of technology, fortitude and practical appropriateness to respond to the latest (contemporary) incident produced due to technology that is holy and ethical poor. Maqashid al-syar'ah hold a useful asset. Muslims should review their traditional notions of Advantage (maṣlaḥah) along with take advantage of these fundamental religious ethics. The design of technological development is beneficial for mankind, because modern technology is infused through It is having a plan all by itself regarding good activities. The intense problem of the Islamic background is which kind of human needs (maṣlaḥah) intense a religion legal discussion can deal with the set of technological values. Muslim jurists, when assessing modern technology, often make use of expressions that describe the optimistic predictions of technology when it comes to human success. This resulted in most of them interpreting human benefit (maṣlaḥah) in terms of technology and issuing fatwas. This makes them be given a particularistic technique to the effect of cutting-edge generation with out considering the effect that current era would possibly have on Muslim life. In this article, it is argued that the contextual-important philosophy of contemporary-day era describes one of the preconditions for outlining what constitutes a reputable human interest (maṣlaḥah). This may be accomplished whilst on the identical time increasing the scope of Islamic Goals (maqashid al-syar'ah) to consist of critical lectures. It links the dual hermeneutic action between the Islamic (time) conception of human goodness (maṣlaḥah) and the axiological contextual perception of the problem during the model of technological development.
Co-Authors A'ang Subiyakto Abd. Rahman Ahlan Abdul Rahman Ahlan Aditya Mardiansyah Agung Yudo Ardianto Agustinus Purna Irawan Alamsyah, Aryajaya Amitkumar Dudhat Amri Amri Arini Arini Aristoi, Zidny Fiqha Azizah, Khansa B. Herawan Hayadi Chung-Wen Hung Dewi Khairani Diana Putri Lazirkha Dudhat, Amitkumar Eiji, Arta Febrian Wahyu Ramadhan Fenty Eka Muzayyana Agustin Henderi . Henry, Amir Acalapati Herlino Nanang Hery Juan Situmorang I Ketut Gunawan Isyak Meirobie Khairani, Dewi Khodijah Hulliyah Khodijah Hulliyah Kim, Jin-Mook Kim, Jong Il Lee Kyung Oh Lee Kyung Oh Lestari Santoso, Nuke Puji Luh Kesuma Wardhani Luhur Bayuaji, Luhur Luthfi Arsalan, Muhammad Mardiansyah, Aditya Marviola Hardini Mira Kartiwi Muhtadibillah, Achmad Nandaputra, Riandi Nuke Puji Lestari Santoso Nur Febriana Widiyanti Nurwicaksana, Satria Oh, Lee Kyung Rahman, Abdul Wahab Abdul Ramadhan, Febrian Wahyu Rayi Pradono Iswara Rohadi Rohadi Rozy, Nurul Faizah Saepul Aripiyanto Shafiera, Eghar Siti Atinah Siti Ummi Masruroh Supardi Supardi Taqwa Hariguna Taqwa Hariguna Widiyanti, Nur Febriana Widjaja, Andree E. Yusuf Abdurachman Zainal Arifin Hasibuan