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Widodo, Agung Mulyo
Universitas Esa Unggul
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Enterprise Architecture Business Model Planning Using EAP Framework (Case Study: PT. Gempita Cahaya Makmur) Mutedi, Ahmad; Mulyo Widodo, Agung; Firmansyah, Gerry; Tjahjono, Budi
Asian Journal of Social and Humanities Vol. 3 No. 1 (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.v3i1.416

Abstract

The advancement of technology in a company has an impact on improving business quality. From this observation, architectural planning is a part that is used to build alignment between business strategy and information technology. Architecture within the business domain illustrates how a company conducts business activities and functions to achieve the company's goals. Therefore, the company's business model architecture depicts the current state of architecture by identifying business needs and activities. From this study, the business role of PT. GEMPITA CAHAYA MAKMUR, a company engaged in the procurement of goods and services, especially in the field of wholesale office stationery, printing, photocopier sales, and photocopier and laptop rentals, which has customers from medium-sized companies, large companies, both private and government. The use of the Enterprise Architecture Planning or EAP framework focuses on business architecture. The purpose of this research is expected to produce a blueprint proposal that will be beneficial for PT. GEMPITA CAHAYA MAKMUR to plan the business model architecture that will become the foundation for the design phase of application architecture.
Clustering of Child Stunting Data in Tangerang Regency Using Comparison of K-Means, Hierarchical Clustering and DBSCAN Methods Azzam Robbani, Muhammad; Firmansyah, Gerry; Mulyo Widodo, Agung; Tjahjono, Budi
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.v2i12.422

Abstract

This study aims to analyze stunting in children in Tangerang Regency using clustering methods such as k-means, Hierarchical Clustering with Agglomerative Nesting, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Stunting is a significant health issue affecting child growth due to chronic malnutrition and recurrent infections. The research revealed that k-means produced the best clustering results with a Silhouette Score of 0.52, indicating its effectiveness in categorizing children based on age, nutritional status, and stunting risk. The k-means method identified three clusters: Cluster 0 (ages 46-55 months, good nutrition, no stunting), Cluster 1 (ages 9-18 months, varied nutritional status, high stunting risk), and Cluster 2 (ages 27-36 months, good nutrition, no stunting). The study suggests preventive actions such as balanced nutrition education, regular health monitoring, complete immunizations, and physical activity, alongside curative measures like nutritional consultations and supplements. The findings provide a framework for targeted preventive and curative interventions, enabling Tangerang Regency's health department to effectively address and reduce stunting rates.
Peningkatan Pengetahuan Kader Posyandu tentang Perawatan Kehamilan dan Gizi-Hidrasi melalui Pelatihan dan Pemanfaatan Media Digital Kesehatan: indonesia Mulyani, Erry Yudhya; Nurhayati, Ety; Widodo, Agung Mulyo
Jurnal Abdimas Madani dan Lestari (JAMALI) Volume 07, Issue 02, September 2025
Publisher : UII

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/jamali.vol7.iss2.art20

Abstract

The prevalence of maternal mortality and KEK (Energy-Protein Deficiency) in South Tangerang in 2022 were 27.34% and 3.51%, respectively. These figures provide an illustration that although it decreased in 2022 and reached the target, it still requires attention considering the impact of mothers experiencing high-risk KEK on their fetuses. One effort that can be made is to provide pregnancy care training and nutrition-hydration education. This activity involved cadres of the RT002 Posyandu and PKK Serua Ciputat Tangerang Selatan mothers totaling 10 people. This activity was carried out for 3 months (November - January 2025). The form of activity was in the form of socialization, discussion group forums, and pregnancy care training including weight and height checks, blood pressure, and talk shows (T-1, T-2, T-10). Online socialization via Zoom for 120 minutes (45-minute lecture), Q&A discussion (60 minutes), discussion group forum (90 minutes) and training (90 minutes). The average age of cadres is 51-60 years (60.0%), D3/D4 education (60.0%), and works as a housewife (50.0%). This activity shows an increase in subject knowledge related to water needs, the role of vitamin D, understanding dehydration, T2 activities, T4 measurements, and the benefits of Fe tablets where previously less than 90.0%, to more than 90.0%. Therefore, it is necessary to carry out continuous training and practice to improve cadre skills in delivering health materials in the community.
Enhanced Dermatological Diagnosis: Autoimmune and Non-Autoimmune Skin Disease Classification Using MobileNet and ResNet Tyara Regina Nadya Putri; Widodo, Agung Mulyo
Infact: International Journal of Computers Vol. 9 No. 01 (2025): International Journal of Computers
Publisher : Universitas Kristen Immanuel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61179/infact.v9i01.711

Abstract

Autoimmune diseases arise when the immune system mistakenly attacks the body's healthy cells, causing a range of symptoms that can greatly affect a patient's quality of life. In Indonesia, these conditions present a significant public health concern. According to research by Ministry of Health Republic Indonesia in 2024, autoimmune lupus affects approximately 0.5% of the population, impacting over 1.3 million individuals. This study proposes a classification and detection model utilizing Convolutional Neural Networks (CNN) with transfer learning, incorporating MobileNetV2, MobileNetV3Small, MobileNetV3Large, ResNet50, ResNet101, and ResNet152 architectures. The model's performance is assessed using a confusion matrix, evaluating precision, recall, and F1-score, while computational efficiency is analyzed using a GPU T4. Experimental results demonstrate that ResNet152 achieved the highest accuracy at 92%. These findings emphasize the crucial role of selecting an optimal CNN architecture to enhance the accuracy of autoimmune and non-autoimmune skin disease classification and detection.
Audit Tata Kelola Teknologi Informasi Menggunakan Framework COBIT 2019 Pada Rumah Sakit Medika Dramaga Andriana, Dian; Firmansyah, Gerry; Tjahjono, Budi; Widodo, Agung Mulyo; 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.v4i8.4176

Abstract

Penelitian ini bertujuan untuk mengevaluasi tata kelola teknologi informasi (TI) di Rumah Sakit Medika Dramaga menggunakan kerangka kerja COBIT 2019. Hasil audit menunjukkan bahwa meskipun beberapa aspek tata kelola TI telah mencapai tingkat tertentu, masih terdapat kesenjangan antara kondisi saat ini dan harapan yang diinginkan. Pada domain APO12 (Pengelolaan Risiko), tingkat kemampuan mencapai 87% pada level 2 dan 73% pada level 3, namun tidak ada pencapaian pada level 4 dan 5. Sementara itu, pada domain APO13 (Pengelolaan Keamanan Informasi), tingkat kemampuan hanya mencapai 82% pada level 2 tanpa pencapaian pada level yang lebih tinggi. Kesenjangan ini menunjukkan bahwa pengelolaan risiko dan keamanan informasi masih memerlukan peningkatan signifikan untuk mencapai standar yang diharapkan. Berdasarkan temuan tersebut, penelitian ini memberikan beberapa rekomendasi, termasuk evaluasi kebijakan manajemen risiko, implementasi teknologi pendukung, pelatihan SDM, dan pengembangan strategi jangka panjang untuk meningkatkan tata kelola TI. Dengan menerapkan rekomendasi ini, diharapkan Rumah Sakit Medika Dramaga dapat meningkatkan keamanan dan keandalan sistem informasi serta meminimalkan risiko kebocoran data.
Evaluasi dan Optimasi Kinerja MySQL Master-Slave dengan Metode Kuantitatif pada Database Pemohon Tes Psikologi SIM PT XYZ pada POLDA METRO JAYA Haryoto, Iin Sahuri; Firmansyah, Gerry; Tjahjono, Budi; Widodo, Agung Mulyo; Akbar, Habibullah; Fatonah, Nenden Siti
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 9 (2025): : JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i9.4685

Abstract

The development of information technology and cloud computing has enabled organizations to manage large-scale data efficiently. PT XYZ, which is engaged in psychological testing for Driving Licenses (SIM), uses a web-based system with a MySQL database that has implemented master-slave replication. However, as the data volume increases to 4,000-5,000 entries per day, the system experiences performance constraints, especially in the speed of read and write queries. This study aims to optimize the performance of the MySQL database by adjusting the server configuration and specifications to improve system efficiency. The test results show that server specification settings, including processor speed, memory size, and replication configuration, play an important role in improving system performance. By adjusting the master and slave server configurations, the system shows a significant increase in database response time and operational efficiency. This optimization is expected to be a reference in the implementation and management of large-scale databases using MySQL replication.
Evaluation of Transfer Learning-Based Convolutional Neural Networks (InceptionV3 and MobileNetV2) for Facial Skin-Type Classification Muttaqin, Naufal Hafizh; Widodo, Agung Mulyo
Jurnal Ilmu Komputer dan Informatika Vol 5 No 1 (2025): JIKI - Juni 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jiki.264

Abstract

Manual classification of facial skin types often suffers from subjectivity and inconsistency due to reliance on human expertise. Accurate identification of skin types is crucial for selecting appropriate skincare solutions. This study evaluates the performance of two transfer-learning-based Convolutional Neural Networks (CNNs), InceptionV3 and MobileNetV2, for classifying facial skin types into four categories: normal, oily, dry, and acne-prone. A total of 1,733 facial images were collected from Kaggle and Roboflow and split into training, validation, and testing sets with a 70:20:10 ratio. Preprocessing involved normalization, augmentation, and resizing based on each model’s input size. Both models were fine-tuned and evaluated using accuracy, precision, recall, and F1-score metrics. InceptionV3 achieved the highest accuracy of 90.12% and a macro F1-score of 89.47%, particularly excelling in identifying normal and acne-prone skin. MobileNetV2 reached 81.15% accuracy and performed well on dry skin types. Confusion matrices and evaluation on new, unseen data confirmed the models’ generalization capabilities, though misclassifications still occurred among visually similar classes. These findings suggest that CNNs with transfer learning provide a robust foundation for developing AI-assisted facial skin-type classification systems, offering potential integration into dermatological applications.
Enterprise Architecture Design of Indonesian Engineers Association Using The Open Group Architecture Framework (TOGAF) Qiqi Asmara, Abdullah; Firmansyah, Gerry; Tjahjono, Budi; Mulyo Widodo, Agung; Yudha Putra Hadjarati, Panji Ramadhan
Devotion : Journal of Research and Community Service Vol. 5 No. 9 (2024): Devotion: Journal of Community Research
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/devotion.v5i9.7640

Abstract

The Indonesia Engineers Association has used Microsoft Dynamics Axapta (AX) enterprise resource planning (ERP) software as its operational support system. However, there are obstacles that are obstacles to completing business processes effectively by users, which have an impact on declining work performance and not achieving company targets. In addition, for the next 3 years, IT solutions are also needed to be able to support business development in the company. The implementation of Enterprise Architecture is expected to be the answer for the Indonesia Engineers Association in the next 3 years, so that the company can be more productive and develop as well as there is alignment between the business strategies owned by the company to optimize the use of information systems and information technology owned by the Indonesia Engineers Association. The basis for choosing using the TOGAF ADM method in designing Enterprise Architecture is that TOGAF ADM has a complete methodology, clear and structured stages, so that the design and specifications become easier and reduce the implementation risks faced by the Indonesia Engineers Association. This research is expected to provide insights for policymakers and enterprise architecture practitioners in selecting and implementing the framework that best suits the context and needs of their organizations. In addition, this study also provides recommendations to improve the efficiency and effectiveness of the implementation of enterprise architecture in the Indonesia Engineers Association.
Utilization of Query Expansion Using Data Mining Method In Analyzing Documents on The Irama Nusantara Website Aulia, Rizky; Widodo, Agung Mulyo
Jurnal Ekonomi Teknologi dan Bisnis (JETBIS) Vol. 3 No. 11 (2024): JETBIS : Journal Of Economich, Technology and Business
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/jetbis.v3i11.156

Abstract

In Indonesia, many local websites, such as Irama Nusantara, hold valuable information related to music and culture. Although rich in data, the utilization of this information is still limited. This research aims to utilize query expansion techniques through data mining methods in analyzing data from the Irama Nusantara website. Data was collected from the Irama Nusantara website through a crawling process, resulting in 5404 entries covering audio, images and text. The analysis was conducted using Natural Language Processing (NLP) techniques starting with the preprocessing stage. Next, the K-Means algorithm was applied for clustering, and the Term Frequency-Inverse Document Frequency (TF-IDF) method was used for term weighting. Classification models were built using Support Vector Machine (SVM) and Naive Bayes for comparison. The analysis shows that the use of query expansion significantly improves the accuracy of information retrieval on the Irama Nusantara website. The method evaluation showed that SVM gave better results in terms of accuracy and precision compared to Naive Bayes. In addition, Principal Component Analysis (PCA) shows that 70-95% of the variance in the data can be explained by the resulting principal components, which signifies the efficiency of the applied method. This research not only provides a deeper insight into the patterns and trends in the analyzed data, but also contributes to the development of information technology in the field of culture in Indonesia. This research successfully developed an effective analysis model to utilize data from the Irama Nusantara website.
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.
Co-Authors Achmad Fansuri Achmad Randhy Hans Adhi Fernandes Gamaliel Adilah Widiasti Agam Aprianto Ahmad Musnansyah Ahmad Mutedi Akbar, Habibullah Alexander Alexander, Alexander Alivia Yufitri Andriana, Dian Annazma Ghazalba Arif Pami Setiaji Arisandi Langgeng Tardiana Asmara, Qiqi Azzam Robbani, Muhammad Bayu Sulistiyanto Ipung Sutejo Binastya Anggara Sekti Budi Aribowo Budi Tjahjono Budi Tjahjono Budi Tjahyono Budi Tjahyono Budi Tjahyono Budilaksono, Sularso Cahya Darmarjati Catur Agus Sulistyo Deni Iskandar Deni Iskandar Desy Prastyani Doni Antoro Dulbahri Dulbahri Dwiaji, Lingga Dwiputra, Dedy Eko Prasetyo Endang Ruswanti Erry Yudhya Mulyani Ety Nurhayati Euis Heryati Fadlilatunnisa, Fanny Fatonah, Nenden Siti Fernandes Gamaliel, Adhi Fikri Saefullah Gerry Firmansyah Gerry Firmasyah Ghazalba, Annazma Gilang Romadhanu Tartila Gunawan, Sholeh Gusti Fachman Pramudi Hadi, Muhammad Abdullah Hani Dewi Ariessanti Hartono Hartono Haryoto, Iin Sahuri Hendaryatna Hendaryatna Hendry Gunawawan Heri Wijayanto I Gede Pasek Suta Wijaya Ichwani, Arief Ilham Banuaji Irawan, Bambang Ismiyati Meiharsiwi Iwan Setiawan Izhar Rahim Joniwan Joniwan Karisma Trinanda Putra kartini, kartini Kevin Valeri Khairurrahman, Rifqi Krisogonus Wiero Baba Kaju Kundang Karsono Juman Kundang Karsono Juman Kundang Karsono Juman Kus Hendrawan Muiz Lingga Dwiaji Lisdiana Lisdiana Lisdiana Lisdiana Lukman Cahyadi Made Aka Suardana Martin Saputra Massie, Julius Ivander Maulana, Syaban Meiharsiwi, Ismiyati Meria, Lista MF. Arrozi Adhikara Muhammad Azzam Robbani Muhammad Fajrul Aslim Muhammad Hadi Arfian Mutedi, Ahmad Muttaqin, Naufal Hafizh Nina Nurhasanah, Nina Nindyo Artha Dewantara Wardhana Nixon Erzed Nizirwan Anwar Nugraha, William Nurfilael, Gagas Nurfilae Panji Ramadhan Yudha Putra Hadjarati Pratama, Fajar Prayitno Purwano SK Rachman, Riyandi Patu Rahaman, Mosiur Randhy Hans, Achmad Restamauli br Nainggolan Rian Adi Pamungkas Ricky Salim Ricky Salim Rifqi Khairurrahman RILLA GANTINO Riris Septiana Sita Dewi Rizki Faro Khatiningsih Rizky Aulia Roesfiansjah Rasjidin Ryan Putra Laksana Sholeh Gunawan Simorangkir, Holder Suhendry, Mohammad Roffi Sunardi, Sunardi Syaban Maulana Syamsul Bahri Tyara Regina Nadya Putri Ulum, Muhamad Bahrul Ummanah Ummanah, Ummanah Vitri Tundjungsari Wahid Abdul Azis Wardhana, Nindyo Artha Dewantara Wibowo, Yudha Widiasti, Adilah William Nugraha Wisnujati, Andika Yanathifal Salsabila Anggraeni Yessy Oktafriani Yohanes Bagas Ari Widatama Yudha Putra Hadjarati, Panji Ramadhan Yulhendri Yulhendri