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All Journal JIK Jurnal Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Astonjadro CCIT (Creative Communication and Innovative Technology) Journal JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI International Journal Of Science, Technology & Management (IJSTM) IAIC Transactions on Sustainable Digital Innovation (ITSDI) Devotion: Journal of Research and Community Service Jurnal Impresi Indonesia Journal Of World Science Jurnal Locus Penelitian dan Pengabdian Jurnal Indonesia Sosial Teknologi Jurnal Indonesia Sosial Sains Eduvest - Journal of Universal Studies Asian Journal of Social and Humanities INOVTEK Polbeng - Seri Informatika
Firmansyah, Gerry
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3D GOVERNMENT ENTERPRISE ARCHITECTURE FRAMEWORK Firmansyah, Gerry
JIK: Jurnal Ilmu Komputer Vol 2, No 01 (2017): JIK : Jurnal Ilmu Komputer
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/komp.v2i1.2138

Abstract

AbstractBased on the research on the determinants of successful e-Government implementation that have been studied the results are very diverse, in the previous study using Principal Component Analysis found an inherent structure that became the main component of e-Government implementation, each component has a weight. When resource constraints (time, cost, sdm) then weights can help in determining the priorities of e-government implementation. Inherent structure combined with Generic Government Enterprise Architecture can form a new 3D Governance Enterprise Architecture (GEA) that becomes the reference of a country. This research performs GEA formation process by using inherent structure of e-government data. Keywords: e-government, e-government component, principal component analysis AbstrakBerdsarkan penelitian mengenai faktor penentu keberhasilan implementasi e-Government yang sudah dipelajari hasilnya sangat beragam, pada penelitian sebelumnya dengan menggunakan Principal Component Analysis ditemukan suatu inherent structureyang menjadi komponen utama dari implementasi e-Government, setiap komponen mempunyai bobot. Saat keterbatasan sumber daya (waktu, biaya, sdm) maka bobot dapat membantu dalam menentukan prioritas implementasi e-government. Inherent structure yang dikombinasikan dengan Generic Government Enterprise Architecture dapat membentuk suatu 3D Government Enterprise Architecture (GEA) baru yang menjadi acuan dari sebuah negara. Penelitian ini melakukan proses pembentukan GEA dengan menggunakan inherent structure dari data e-government. Kata Kunci:  e-government, e-government component, principal component analysis
ANALISA DAN PERANCANGAN ARSITEKTUR ENTERPRISE MENGGUNAKAN THE OPEN GROUP ARCHITECTURE FRAMEWORK (TOGAF) : STUDI KASUS KOPERASI SYARIAH BENTENG MIKRO INDONESIA (KOPSYAH BMI) Anwar Solihin, Muhamad; Firmansyah, Gerry; Kailani Ridwan, M; Supardi, Supardi; Irawan, Devi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 1 (2023): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i1.1523

Abstract

Pada era globalisasi pemanfaatan suatu teknologi informasi pada organisasi mulai dikembangkan dengan strategi yang beragam, hal ini diperlukan terlebih pada sebuah organisasi simpan pinjam pada koperasi dimana lanjunya perkebangan sistem atau teknologi informasi akan berpengaruh pada proses bisnis yang sedang berjalan. Koperasi Syariah Benteng Mikro Indonesia atau disingkat Kopsyah BMI adalah Koperasi Simpan Pinjam dan Pembiayaan Syariah yang merupakan Koperasi Besar Indonesia yang memiliki 77 kantor cabang. Begitupun dengan program kerja dalam divisi-divisi manajerial Kopsyah belum terintegrasi dan audit internal yang dilakukan oleh TIM Satuan Pengendali Internal (SPI) belum menggunakan aplikasi atau online, sehingga laporan audit internal harus di rekap dan ditulis dengan menggunakan aplikasi office sehingga membutuhkan waktu dan tidak dapat mengambil keputusan dengan cepat. Setiap kegiatan usaha atau bisnis pasti diperlukan perancangan arsitektur bisnis untuk memudahkan dalam pencapaian visi dan misi perusahaan. Enterprise Architecture (EA) adalah kumpulan dari metode, model, dan prinsip yang digunakan dalam membuat rancangan dan merealisasiskan teknologi informasi, proses bisnis, struktur organisasi, dan infrastrukturnya. Hasil Enterprise Architecture pada koperasi syariah BMI, terdapat beberapa usulan fase arsitektur visi untuk merubah struktur organisasi dari segi peran dan stakeholders. Sehingga harapannya dapat mempertanggungjawabkan tugasnya masing-masing dalam struktur organisasi untuk mencapai visi dan misi. Dapat juga memberikan dokumentasi setiap tahapan mulai dari data, aplikasi hingga proses bisnis di BMI Kopsyah baik dari segi Sistem informasi maupun teknologi informasi yang diusulkan oleh TOGAF untuk mencakup keseluruhan kegiatan di BMI Kopsyah.
Fraud Detection in Credit Card Transactions Using HDBSCAN, UMAP and SMOTE Methods Setiawan, Rudy; Tjahjono, Budi; Firmansyah, Gerry; Akbar, Habibullah
International Journal of Science, Technology & Management Vol. 4 No. 5 (2023): September 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i5.929

Abstract

Credit card abuse and fraud in credit card transactions pose a serious threat to financial companies and consumers. To overcome this problem, accurate and effective fraud detection is essential. In this study, we propose an approach that combines HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise), UMAP (Uniform Manifold Approximation and Projection), and SMOTE (Synthetic Minority Over-sampling Technique) methods to detect fraud in credit card transactions. The HDBSCAN method is used to group transactions based on their spatial density, allowing identification of suspicious groups of transactions. UMAP is used to reduce the dimension of transaction data, thus enabling better visualization and more efficient data analysis. In addition, we use SMOTE to overcome class imbalances, namely differences in the number of fraudulent and non-fraudulent transactions. In our experiments, we used. In this experiment, we used a dataset of credit card transactions that included both fraudulent and non-fraudulent transactions. The experimental results show that the proposed approach is able to detect fraud with high accuracy. The HDBSCAN method is able to effectively identify suspicious groups of transactions, while UMAP helps in better understanding and visualization of data. The use of SMOTE has successfully overcome class imbalances, resulting in more balanced fraud detection results between fraud and non-fraud. The results of this study show that the combination of HDBSCAN, UMAP, and SMOTE methods is effective in detecting fraud in credit card transactions. This approach can help financial companies identify suspicious transactions with high accuracy, reduce fraud losses, and improve the security of credit card transactions.
Optimization of Delay Using Killer Whale Algorithm (KWA) on NB-IoT Hadi, Muhammad Abdullah; Widodo, Agung Mulyo; Firmansyah, Gerry; Akbar, Habibullah
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12933

Abstract

Abstract: NB-IoT is designed to connect IoT devices with low-power, wide-area coverage and efficient costs. Ensuring optimal data transmission delay is a challenge in NB-IoT implementation. Inadequate coverage can hinder IoT adoption. Optimization balances energy saving and delay trade-off. The Killer Whale Algorithm (KWA) optimizes delay by adjusting repetition variables. KWA addresses dimensions, variable limits. Applying KWA in NB-IoT optimizes transmission, enhancing QoS. Optimizing delay involves reducing latency in uplink data transmission using repetition variables. This study applies KWA to optimize NB-IoT delay. Analysis in Table 4 shows non-linear repetition-distance correlation. Interestingly, delay outcomes exhibit a contrasting relationship. Still, delay remains advantageous, remaining under 1 second even at 10 km, specifically 9.2674 ms (0.0092674 seconds). This thesis aims to optimize delay in NB-IoT network transmission using the Killer Whale Algorithm (KWA), crucial for modern communication networks and IoT applications. Leveraging KWA, the research identifies solutions to reduce transmission delay, enhancing efficiency and meeting IoT communication demands for speed and timeliness
Comparative Analysis of Time Series Methods LSTM and ARIMA for Predicting Inventory Availability (Case Study: PT XYZ) Kartawijaya, Edi; Munawar, Munawar; Firmansyah, Gerry; Tjahjono, Budi
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 1 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v18i1.3443

Abstract

Product availability plays a crucial role in supply chain management, directly impacting all aspects of business operations, from production to distribution. This study analyzes the optimization of product availability at PT. XYZ, a frozen and chilled food trading company in Indonesia, focusing on four main commodities: beef, buffalo meat, chicken, and potatoes. Utilizing historical transaction data from 2020 to July 27, 2024, this research compares the performance of two forecasting models: ARIMA (AutoRegressive Integrated Moving Average) and Long Short-Term Memory (LSTM), in predicting product availability The traditional ARIMA model has proven effective in time series data analysis but has limitations in capturing complex patterns and non-linear fluctuations. LSTM, as a machine learning technique, demonstrates superiority in capturing long-term temporal relationships. This study finds that the LSTM model consistently outperforms ARIMA for beef, buffalo meat, and chicken categories, although there is a slight increase in error for the potatoes category. Model performance evaluation is conducted using metrics such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE). The results indicate that the LSTM model exhibits lower errors compared to ARIMA, proving its effectiveness in predicting dynamic demand patterns. With a better understanding of product availability, the company is expected to reduce operational costs, avoid losses, and enhance customer satisfaction through more efficient supply chain management. This research provides significant insights for PT. XYZ and similar industries in implementing more accurate forecasting methodologies
Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT) in the Indonesian Aviation Sector Dwiaji, Lingga; Widodo, Agung Mulyo; Firmansyah, Gerry; Tjahyono, Budi
Asian Journal of Social and Humanities Vol. 2 No. 6 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i6.261

Abstract

Cyber attacks are one of the genuine threats that have emerged due to the evolution of a more dynamic and complex global strategic environment. In Indonesia, several cyber attacks target various government infrastructure sectors. The National Cyber and Crypto Agency (BSSN) predicts Indonesia will face approximately 370.02 million cyber attacks in 2022. The majority of cyber attacks target the government administration sector. The National Cyber and Crypto Agency (BSSN) officially formed a Computer Security Incident Response Team (CSIRT) to tackle the rampant cybercrime cases. CSIRT is an organization or team that provides services and support to prevent, handle, and respond to computer security incidents. The current CSIRT does not have a data storage process and forensic preparation. CSIRT will repeat the procedure, and so on. This is a repeating procedure; the attack will occur once, and only a technical problem will arise. Therefore, the research entitled "Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT)" is expected to implement this Knowledge Management Strategy to manage existing knowledge so that it can make it easier for the CSIRT team to handle cyber attacks that occur.
Assessment of the level of student understanding in the distance learning process using Machine Learning Widiasti, Adilah; Widodo, Agung Mulyo; Firmansyah, Gerry; Tjahjono, Budi
Asian Journal of Social and Humanities Vol. 2 No. 6 (2024): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v2i6.272

Abstract

As technology develops, data mining technology is created which is used to analyse the level of understanding of students. This analysis is conducted to group students according to their ability to understand and master the subject matter. This research can provide guidance and insight for educators, as well as artificial intelligence, machine learning, association techniques, and classification techniques. Researchers and policymakers are working to optimise learning and improve the quality of student understanding. This study aims to analyse the level of student understanding in simple and structured terms. Using the Machine learning method to analyse the level of student understanding has the potential to impact the quality of education significantly. In addition, machine learning categories are qualified to be applied to the concept of data mining. The data mining techniques used are association and classification. Association techniques are used to determine the pattern of distance student learning. The following process of classification techniques is used to determine the variables to be used in this study using the Logistic Regression model where data that have been classified are grouped or clustered using the K-Means algorithm into three, namely the level of understanding is excellent, sound, and lacking, based on student activity, assignment scores, quiz scores, UTS scores, and UAS scores.
Analysis of The Maturity Level of Cyber Security in The Context of Personal Data Protection for MSMEs in Depok City Sulistyo, Catur Agus; Firmansyah, Gerry; Tjahjono, Budi; Widodo, Agung Mulyo
Eduvest - Journal of Universal Studies Vol. 5 No. 2 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i2.50822

Abstract

This research explores the cybersecurity maturity level in the context of personal data protection for Micro, Small, and Medium Enterprises (MSMEs) in Depok City, Indonesia. The increased use of digital technology by MSMEs has raised concerns about personal data security and the vulnerability to cyberattacks. This study aims to develop an assessment tool that MSMEs can use to evaluate their compliance with the Personal Data Protection (PDP) Law and measure their readiness to face cybersecurity challenges. Through a combination of qualitative and quantitative methods, the study analyzes MSMEs' preparedness for cybersecurity and compliance with the PDP Law. The results reveal that while 60.2% of MSMEs manage personal data, a significant 93.5% have not complied with the PDP Law, exposing them to potential financial losses and cyber risks. The research emphasizes the need for MSMEs to adopt a simple yet effective cybersecurity framework to ensure data protection and compliance.
Prototype Green Energy System for Real Estate Housing Development Based Internet of Everything Suhendar, Suhendar; Irawan, Bambang; Firmansyah, Gerry; Tjahjono, Budi; Erzed, Nixon; Rahaman, Mosiur
Eduvest - Journal of Universal Studies Vol. 5 No. 6 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i6.51212

Abstract

Climate change and the crisis of conventional energy resources are two interrelated global issues that severely impact environmental sustainability and economic development. Real estate development using renewable energy is carried out for various reasons involving environmental, economic, and social aspects. Internet of Everything (IoE) is a concept that expands the Internet of Things (IoT), including machine-to-machine, machine-to-person, and person-to-person communications with expanded digital features. The research method is quantitative, with numerical data that can be statistically measured in system performance. The research focuses on developing a prototype architecture of green energy for real estate development to maximize the efficiency of solar energy potential. The research's conclusion holds excellent promise for broader implementation. Solar energy's efficiency and potential can be maximized as a renewable energy source by utilizing the Internet of Everything (IoE) for real-time monitoring, control, and analysis. Additionally, this approach can offer valuable insights for decision-making in energy management going forward.
Prediksi Peringkat Akreditasi BAN PT Program Studi Sarjana Rumpun Ilmu Komputer Menggunakan Klasifikasi Machine Learning Aribowo, Budi; Tjahjono, Budi; Firmansyah, Gerry; Widodo, Agung Mulyo
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 10, No 2 (2025): Mei 2025
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v10i2.3089

Abstract

Accreditation ranking is one of the causes and indicators chosen by prospective students when choosing a study program in higher education. From the data collected, only 5% of study programs in the Computer Science group have a Superior accreditation rating and an A accreditation rating in LLDikti Region III Jakarta. So it is necessary to know the factors that influence the accreditation ranking. The machine learning methodology used in this approach is K-Nearest Neighbors (KNN) and from the data obtained there are 6 factors that can be strongly suspected to influence the study program accreditation value. The four machine learning models, namely KNN, Gaussian Naïve Bayes Decision Tree and Logistic Regression, it was found that the KNN machine learning model with 2 input variables had the highest AUC value, namely 84.38%. Meanwhile, from the model simulation run by KNN machine learning, 2 input variables can produce relatively accurate prediction results. And the results of cross validation with 10 folds support the selected machine learning with an accuracy level of 80%. In general, the KNN machine learning model with 2 input variables was able to predict the accreditation rating of Study Programs, especially from the Computer Science Cluster.Keywords – Accreditation, Area Under Curve (AUC), Department of School, Kfold Cross Validation, Machine Learning.
Co-Authors Akbar , Habibullah Akbar, Habibullah Alexander Alexander, Alexander Andriana, Dian Anwar Solihin, Muhamad Asianto, Andriyanti Aulia, Anisa Ayu Larasati Azizah, Anik Hanifa Azzam Robbani, Muhammad Budi Aribowo BUDI TJAHJONO Budi Tjahyono Dewi, Riris Septiana Sita Dodo, La Dwi Pamungkas, Eric Dwiaji, Lingga Dwiputra, Dedy Edi Kartawijaya Fathan Ali, Dudy Fatonah, Nenden Siti Fernandes Gamaliel, Adhi Ghazalba, Annazma Gunawan, Sholeh Hadi, Muhammad Abdullah Haryoto, Iin Sahuri Ipung Sutejo, Bayu Sulistiyanto Irawan, Devi Irsyadul Anam, Reza Kailani Ridwan, M Khairurrahman, Rifqi Lisdiana Lisdiana M Bahrul Ulum, M Bahrul Maulana, Syaban Meiharsiwi, Ismiyati Mulyo Widodo, Agung Munawar Munawar Muslih, Muhamad Mutedi, Ahmad Nasihin, Anwar Natadirja, Trenggana Nixon Erzed Nugraha, William Nugroho Budhisantosa Pamungkas, Ryan Tri Putra, Sipky Jaya Qiqi Asmara, Abdullah Rachman, Riyandi Patu Rahaman, Mosiur Ramadhan, Noval Rizky Randhy Hans, Achmad Riya Widayanti RR. Ella Evrita Hestiandari Rudy Setiawan Sakron, Narul Siti Fatomah, Nenden Sri Redjeki Sugiyanti, Sri Dewi Suhendar Suhendar, Suhendar Sulistyo, Catur Agus Supardi Supardi Supriyade, Supriyade Tardiana, Arisandi Langgeng Tartila, Gilang Romadhanu Wardhana, Nindyo Artha Dewantara Widiasti, Adilah Widodo, Agung Mulyo Widodo, Agung Mulyono Wijaya, Jacob S Yudha Putra Hadjarati, Panji Ramadhan