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All Journal JIK Jurnal Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL TEKNOLOGI DAN OPEN SOURCE Astonjadro CCIT (Creative Communication and Innovative Technology) Journal JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences 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 International Journal of Islamic Education, Research and Multiculturalism (IJIERM) Jurnal Locus Penelitian dan Pengabdian Jurnal Indonesia Sosial Teknologi Jurnal Indonesia Sosial Sains Journal Research of Social Science, Economics, and Management Eduvest - Journal of Universal Studies Asian Journal of Social and Humanities INOVTEK Polbeng - Seri Informatika
Gerry Firmansyah
Universitas Esa Unggul
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Evaluating the Performance of Association Rules in Apriori and FP-Growth Algorithms: Market Basket Analysis to Discover Rules of Item Combinations Dwiputra, Dedy; Mulyo Widodo, Agung; Akbar, Habibullah; Firmansyah, Gerry
Journal of World Science Vol. 2 No. 8 (2023): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v2i8.403

Abstract

This study focuses on applying data mining techniques, especially association rules mining using the Apriori and FP-GROWTH algorithms, for market basket analysis on PT. XYZ is a pharmaceutical company in Indonesia. A quantitative methodology uses a dataset of 100,498 transactions originating from 432,356 rows of data covering July to December 2022 in the JABODETABEK area. Apriori and FP-GROWTH algorithms are applied for association rules mining. The results show that FP-GROWTH has the fastest execution time of 84,655 seconds. However, the memory usage for the Apriori algorithm is the lowest at 482.32 MiB, with increments of: 0.21 MiB. For the rules generated, the two algorithms, both Apriori and FP-GROWTH, produce the same number of rules and values of support, confidence, lift, Bi-Support, Bi-Confidence, and Bi-Lift. In conclusion, Apriori is recommended for sales datasets if memory usage and ease of implementation are important. However, if the speed of execution time and a large amount of data are considered, FP-GROWTH is a better choice because the execution time is faster for large amounts of data. However, the choice of algorithm depends on the specific analysis objectives, itemset size, data scale, and computational capabilities. Results from association rules mining provide evidence of product popularity, purchasing patterns, and opportunities for strategic marketing and inventory management. These findings can help PT. XYZ improves business efficiency, understands customer behavior, and increases profitability.
Analisis dan Design Knowledge Management System pada PT XYZ dengan Menggunakan Metode Tiwana Alexander, Alexander; Firmansyah, Gerry; Tjahjono, Budi; Mulyo Widodo, Agung; Akbar , Habibullah
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 8 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i8.4686

Abstract

Dalam dunia bisnis, keberlangsungan dan pertumbuhan suatu perusahaan sangat dipengaruhi oleh kualitas sumber daya manusia (SDM) atau karyawan yang dimiliki, karyawan yang kompeten dan memiliki wawasan pengetahuan yang luas dianggap sebagai aset penting yang dapat menjadi pembeda utama antara perusahaan dengan para pesaingnya. Maka dari itu, perusahaan biasanya berinisiatif untuk melakukan berbagai macam program pelatihan dan pengembangan yang bertujuan untuk meningkatkan kemampuan dan pengetahuan karyawannya secara berkelanjutan, hal lain yang dapat dilakukan oleh perusahaan adalah dengan mengelola pengetahuan dari karyawannya melalui sebuah tools yaitu Knowledge Management System (KMS). Sebagai perusahaan konsultan properti terkemuka dengan jaringan global yang luas, PT XYZ memiliki komitmen untuk dapat mengembangkan pengetahuan karyawannya, PT XYZ selalu berupaya untuk menciptakan lingkungan kerja yang mendukung pertumbuhan pengetahuan, terutama bagi karyawan di bidang Information and Technology (IT). Penelitian ini menggunakan metode Tiwana yang dilakukan hingga tahapan ke-6 dari 10 tahapan yang ada, dengan tujuan penelitian untuk menghasilkan blueprint sebagai landasan untuk merancang KMS yang sesuai dengan kebutuhan perusahaan. Adapun hasil dari penelitian ini adalah sebuah blueprint rancangan KMS.
Pengembangan Model IT Masterplan untuk Perguruan Tinggi: Studi Kasus Pada Universitas Bakrie dengan Pendekatan TOGAF Wijaya, Jacob S; Firmansyah, Gerry; Tjahjono, Budi; Akbar, Habibullah
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 11 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i11.4859

Abstract

Transformasi digital di perguruan tinggi menuntut perencanaan teknologi informasi yang strategis, terstruktur, dan berkelanjutan agar mampu mendukung efisiensi akademik dan administrasi. Penelitian ini bertujuan untuk menyusun IT Masterplan Universitas Bakrie sebagai kerangka strategis pengembangan sistem informasi dan transformasi digital universitas secara holistik. Metode penelitian menggunakan pendekatan kualitatif dengan kombinasi analisis dokumen, wawancara semi-terstruktur, dan survei di lingkungan Universitas Bakrie, termasuk Biro Rektorat, Direktorat TI, dan fakultas-fakultas. Analisis dilakukan dengan mengacu pada kerangka kerja Enterprise Architecture (EA) menggunakan TOGAF Architecture Development Method (ADM) serta analisis kesenjangan (gap analysis) antara kondisi eksisting dan target arsitektur yang diinginkan. Hasil penelitian menunjukkan bahwa kondisi sistem TI Universitas Bakrie masih terfragmentasi, dengan beberapa aplikasi tidak saling terintegrasi dan data yang tersebar. Rekomendasi utama berupa rancangan arsitektur target yang menerapkan model berbasis layanan (service-oriented architecture) dan integrasi melalui middleware untuk mendukung pertukaran data lintas unit secara real-time. Selain itu, disusun pula desain data warehouse terpusat serta mekanisme tata kelola data (data governance) untuk meningkatkan akurasi dan analitik lintas fungsi. Implementasi IT Masterplan ini diharapkan mampu meningkatkan efisiensi pengelolaan sumber daya TI, mengurangi redundansi sistem, memperkuat interoperabilitas aplikasi, serta mendorong kelincahan digital universitas dalam menghadapi era transformasi pendidikan tinggi.
Integration Of Garch Models And External Factors In Gold Price Volatility Prediction: Analysis And Comparison Of Garch-M Approach Tardiana, Arisandi Langgeng; Akbar, Habibullah; Firmansyah, Gerry; Widodo, Agung Mulyo
Eduvest - Journal of Universal Studies Vol. 4 No. 5 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i5.1195

Abstract

This study investigates the volatility of gold prices by applying the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and extending it with the GARCH-M model, incorporating the Federal Reserve's interest rate as an external variable. The GARCH(1,1) model revealed a positive average daily return for gold, with high sensitivity to recent price changes, indicated by the significant estimation of mu and a high alpha1 value. The persistence of past volatility on current volatility is reflected by a beta1 value close to one. In the GARCH-M model development, a significant negative relationship was found between the Federal Reserve's interest rates and gold returns, suggesting that an increase in the Federal Reserve's interest rates could potentially decrease gold returns. An increase in the Log Likelihood value and improvements in information criteria such as the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) indicate that the GARCH-M model provides a better fit than the GARCH(1,1) model that uses only gold price data. The study concludes that macroeconomic factors like the Federal Reserve's interest rates play a crucial role in influencing gold price volatility, and these findings can aid investors and portfolio managers in devising more effective risk management strategies. Additionally, the findings contribute to financial theory by highlighting the importance of multivariate models in the analysis of asset price volatility.
Churn Prediction Analysis Of Customer Ferry Operator "Batamfast" Using Machine Learn-Ing With Supervised Classification Model Pamungkas, Ryan Tri; Fatonah, Nenden Siti; Firmansyah, Gerry; Tjahjono, Budi
Eduvest - Journal of Universal Studies Vol. 5 No. 1 (2025): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i1.1669

Abstract

BatamFast is the first ferry operator in Batam and has been serving international routes to Singapore and Malaysia since 1985. Until 2010, BatamFast was the only ferry operator in Batam. However, since 2011, competitors such as Sindo Ferry, Horizon Ferry, and Majestic have emerged, increasing competition to four ferry operators in Batam by 2024. This study aims to measure the churn rate of BatamFast customers and identify the factors causing it using machine learning prediction models such as Random Forest, XGBoost, and Gradient Boosting. In addition to churn prediction, feature importance analysis was conducted to determine the significant features influencing customer decisions. The results indicate that XGBoost is the best model compared to Random Forest and Gradient Boosting. Key factors for churn are customer category, payment method, and booking mode. These findings are expected to help BatamFast reduce churn, improve customer satisfaction, and strengthen its competitive position in the international ferry market.
Product Recommendations Using Adjusted User-Based Collaborative Filtering on E-Commerce Platforms Tartila, Gilang Romadhanu; Akbar, Habibullah; Firmansyah, Gerry; Widodo, Agung Mulyo
Eduvest - Journal of Universal Studies Vol. 5 No. 1 (2025): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i1.50224

Abstract

Product recommendations on e-commerce platforms play a crucial role in supporting customers' purchasing decisions by leveraging user data to provide relevant product suggestions. With the increasing volume of e-commerce data, recommendation methods are needed that are not only accurate but also capable of being applied to diverse datasets. This research focuses on evaluating three product recommendation methods, namely User-Based Collaborative Filtering, Item-Based Collaborative Filtering, and Content-Based Filtering, using various datasets from the Kaggle platform, including transaction data and user reviews. The main problem identified is how to ensure that these three recommendation methods remain optimal despite using different datasets. Through an experimental approach, this research aims to implement and evaluate the performance of these recommendation methods. The results of this study are expected to demonstrate that one of the recommendation methods can work generally on various datasets, thereby making a significant contribution to the selection of the appropriate product recommendation method on e-commerce platforms.
Comparative Performance of Learning Methods In Stock Price Prediction Case Study: MNC Corporation Khairurrahman, Rifqi; Firmansyah, Gerry; Tjahjono, Budi; Mulyo Widodo, Agung
Asian Journal of Social and Humanities Vol. 2 No. 5 (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.v2i5.252

Abstract

Shares are a popular business investment, the development of information technology now allows everyone to buy and sell shares easily online, investment players, both retail and corporate, are trying to make predictions. The purpose of this study is to find out comparative performance of learning methods in stock price prediction. There are currently many research papers discussing stock predictions. using machine learning / deep learning / neural networks, in this research the author will compare several superior methods found in the latest paper findings, including CNN, RNN LSTM, MLP, GRU and their variants. From the 16 result relationships and patterns that occur in each variable and each variable is proven to show its respective role with its own weight, in general we will summarize the conclusions in chapter V below, but in each analysis there are secondary conclusions that we can get in detail. The variable that has the most significant effect on RMSE is variable B (repeatable data) compared to other variables because it has a difference in polarity that is so far between yes and no. The configuration of input timestep (history)=7 days and output timetep (prediction)=1 day is best for the average model in general.
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.
Evaluation of IT Service Level Infrastructure In Organizations Using ITIL (Information Technology Infrastructure Library) Version 3 Standardization Randhy Hans, Achmad; Firmansyah, Gerry; Tjahyono, Budi; Mulyo Widodo, Agung
Asian Journal of Social and Humanities Vol. 2 No. 12 (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.v2i12.393

Abstract

The rapid development of business and advancements in information technology today are highly significant, especially in supporting the progress of ongoing businesses. Many businesses, particularly startups, make information technology the backbone supporting every main business process to achieve their business goals. Startups that operate 24/7 require sufficiently robust information technology, which must always be ready to provide the needed services to support the business. IT service assessment is an activity commonly carried out within an organization to eval_uate the level of information system services it possesses. An assessment, particularly an IT service assessment, can be conducted independently if the organization has adequate tools and is equipped with the correct standards. The eval_uation of information system services can be carried out using various standards, such as ITIL. In this research, the researcher will conduct an assessment using ITIL standards in the form of a website, which can serve as a tool. This website assessment application focuses on the domains of Service Management and Service Delivery, with the expectation that the services provided by PT Loyal.id will improve further.
Co-Authors Achmad Randhy Hans Adhi Fernandes Gamaliel Adilah Widiasti Agung Mulyono Widodo Ahmad Mutedi Akbar, Habibullah Alandrian Surya Tantra Alexander Alexander, Alexander Alnino Dio Putera Amelia Sholikhaq Andriana, Dian Andrianto, Eko Andriyanti Asianto Andriyanti Asianto Anisa Aulia Annazma Ghazalba Anwar Solihin, Muhamad Ardiansyah, Miri Arif Pami Setiaji Asianto, Andriyanti Aulia, Anisa Aurel Elviolita Putri Ayu Larasati Azizah, Anik Hanifa Azzam Robbani, Muhammad Bayu Sulistiyanto Ipung Sutejo Bob Tjahjono Budi Aribowo Budi Tjahjono Budi Tjahyono Budi Tjahyono Budi Tjahyono Devi Irawan Dewi, Riris Septiana Sita Dodo, La Dudy Fathan Ali Dwi Nurmawaty Dwi Pamungkas, Eric Dwiaji, Lingga Dwiputra, Dedy Edi Kartawijaya Eric Dwi Pamungkas Farida Farida Fathan Ali, Dudy Fatonah, Nenden Siti Fernandes Gamaliel, Adhi Ghazalba, Annazma Gilang Banuaji Gunawan, Sholeh Gusti Fachman Pramudi Hadi, Muhammad Abdullah Haryoto, Iin Sahuri Hendaryatna Hendaryatna Husni Sastra Mihardja Husni Satra Mihardja Husni Satra Mihardja Intan Setya Palupi Ipung Sutejo, Bayu Sulistiyanto Irawan, Devi Irsyadul Anam, Reza Ismiyati Meiharsiwi Kailani Ridwan, M Khairurrahman, Rifqi La Dodo Lingga Dwiaji Lisdiana Lisdiana Lisdiana Lisdiana M Bahrul Ulum, M Bahrul Master Maruahal Sidabutar Maulana, Syaban Meiharsiwi, Ismiyati Muhammad Azzam Robbani Muhammad Fajrul Aslim Muhammad Kailani Ridwan Munawar Munawar Muslih, Muhamad Mutedi, Ahmad Narul Sakron Nasihin, Anwar Natadirja, Trenggana Nenden Siti Fatomah Nenden Siti Fatonah Nenden Siti Fatonah Nenden Siti Fatonah Nila Rusiardi Jayanti Nindyo Artha Dewantara Wardhana Nixon Erzed Nugraha, William Nugroho Budhisantosa Pamungkas, Ryan Tri Popong Setiawati Putra, Sipky Jaya Qiqi Asmara, Abdullah Rachman, Riyandi Patu Rahaman, Mosiur Ramadhan, Noval Rizky Randhy Hans, Achmad Reza Irsyadul Anam Rifqi Khairurrahman Riya Widayanti Riyan Asep Susanto Rizky Yananda RR. Ella Evrita Hestiandari Rudy Setiawan Sabri Alim Sakron, Narul Sandy, Raynaldi Sholeh Gunawan Sigit Purworaharjo Siti Fatomah, Nenden Sri Redjeki Sugiyanti, Sri Dewi Suhendar Suhendar, Suhendar Suhendry, Mohammad Roffi Sulistyo, Catur Agus Supardi Supardi Supriyade Supriyade Supriyade, Supriyade Syafika Zalfanissa Dila Tardiana, Arisandi Langgeng Tartila, Gilang Romadhanu Wardhana, Nindyo Artha Dewantara Wibowo, Yudha Widiasti, Adilah Widodo, Agung Mulyo Widodo, Agung Mulyono Wijaya, Jacob S William Nugraha Yessy Oktafriani Yudha Putra Hadjarati, Panji Ramadhan