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Sistem Penyewaan Kontainer Pada Pt. Putra Guna Jaya Mulia Jakarta Munthe, Era Sari
JIK: Jurnal Ilmu Komputer Vol 7, No 2 (2011)
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/komp.v7i2.472

Penelitian ini dilakukan agar dapat mengetahui bagaimana sistem penyewaan kontainer pada PT. PUTRA GUNA JAYA MULIA Jakarta dengan menggunakan metode penelitian pertama yaitu metode lapangan, yang artinya penulis langsung melakukan pengumpulan data melalui wawancara dan pengamatan langsung, yang bertujuan untuk mendapat informasi yang akurat, kedua menggunakan metode kepustakaan dimana data dan informasi yang dibutuhkan penulis diperoleh dari buku dan sumber bacaan. Diharapkan dengan adanya perancangan aplikasi yang sederhana ini aktivitas pada perusahaan dalam sistem penyewaan kontainer dapat menjadi lebih mudah dalam pelaksanaan dan aktivitasnya.Kata kunci: sistem, sewa, kontainer

Perancangan Sistem Informasi Penggajian Pt Kinglab Indonesia Munthe, Era Sari
JIK: Jurnal Ilmu Komputer Vol 8, No 2 (2012)
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/komp.v8i2.485

Dalam penulisan ini penulis melakukan penelitian secara langsung pada PT Kinglab Indonesia.Dengan metode observasi dan wawancara secara langsung dengan Manajer Keuangan guna untuk mengetahui proses penggajian agar data yang didapat lebih cepat dan akurat.Diharapkan dengan adanya pembuatan aplikasi penggajian ini dapat mengolah penggajian pada PT Kinglab Indonesia dan akan lebih mudah, akurat, efisien dan efektif dalam pemprosesannya.Kata kunci: perancangan sistem, sistem informasi, penggajian

Analysis of Goods Stock Using the Apriori Algorithm to Aid Goods Purchase Decision Making Azis, Nur; Sucipto, Purwo Agus; Herwanto, Agus; Munthe, Era Sari; Irwanto, Dola
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 1 (2024): Articles Research Volume 8 Issue 1, January 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.13335

After the covid-19 pandemic outbreak and the high uncertainty index during the covid-19 pandemic. The business world is experiencing a huge impact in addition to the sluggish interest of buyers is also limited in its movement. On this occasion, the researcher intends to provide an overview that can help business people, especially in purchasing goods that are useful for filling the stock of goods in the warehouse. To get maximum results and minimum error rate. Researchers use the Apriori Algorithm in analyzing stock items and use the Tanagra version 1.4 application. Research data used the sales history of the past 1 year here the data used is between May 2022 and April 2023. With a total itemset of 375. But after applying the Golden Rule (threshold), there are only 10 products with sales reaching 1623 items. This research produces a final ordered association based on the minimum support and minimum confidence that has been determined, namely 12 rules with a combination of 2 itemsets with a confidence value of 100%.

The Role of ChatGPT in Business Information Systems to Support Strategic Decision Making in Medium-Scale Enterprises Diantoro, Karno; Munthe, Era Sari; Herwanto, Agus; Mubarak, Roy; Istianingsih, Nanik
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13673

Medium-scale companies often operate in dynamic and competitive business environments. Faced with market changes and new opportunities, timely and accurate strategic decisions are key to maintaining and enhancing the competitiveness of the company. This research aims to examine the role of ChatGPT in business information systems to support strategic decision-making in medium-scale enterprises. The research method employed is a literature review with a qualitative approach and descriptive analysis. Descriptive analysis will be used to present information from systematically selected articles from Google Scholar within the timeframe of 2014-2024. The study results indicate that in the continuously evolving digital era, medium-scale companies increasingly rely on technology to address increasingly complex business challenges. One innovation playing a significant role in today's business landscape is the presence of ChatGPT. As an artificial intelligence model capable of understanding and generating text naturally, ChatGPT has a significant impact on business information systems and supports strategic decision-making in these companies.

Cloud-Native Transformations: Microservices, Kubernetes, and Security Frameworks in Practice Munthe, Era Sari
Digitus : Journal of Computer Science Applications Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i2.880

Cloud-native application development is reshaping how modern organizations build, deploy, and manage software. This narrative review aims to synthesize recent literature on the adoption of cloud-native paradigms, particularly focusing on microservices architecture, containerization, orchestration tools, security frameworks, and AI-driven resource management. Using Scopus, IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar as primary databases, the review applies Boolean keyword combinations to identify relevant peer-reviewed publications. Studies were selected based on their alignment with defined inclusion criteria, emphasizing empirical insights on cloud-native technologies. The findings reveal that microservices enhance system scalability and business agility, while containerization offers portability and efficient resource utilization. Orchestration tools, especially Kubernetes, enable automated deployment and management across complex environments. Security integration through DevSecOps and Policy-as-Code frameworks strengthens defense mechanisms against cyber threats. Furthermore, AI-supported orchestration improves efficiency in resource allocation and system responsiveness. The discussion underscores the necessity of systemic support, including organizational policies, talent development, and cross-functional collaboration, in ensuring successful adoption. This review concludes that cloud-native success demands more than technical innovation; it requires strategic alignment between technology, human capital, and governance. Policymakers and organizational leaders must invest in comprehensive frameworks that support security, adaptability, and continuous learning. Future studies should expand the scope by evaluating cloud-native transformations across industries and developing scalable best practices for AI integration and policy deployment.

Generalizable and Energy Efficient Deep Reinforcement Learning for Urban Delivery Robot Navigation Samroh; Munthe, Era Sari
Digitus : Journal of Computer Science Applications Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i2.954

The increasing demand for contactless urban logistics has driven the integration of autonomous delivery robots into real world operations. This study investigates the application of Deep Reinforcement Learning (DRL) to enhance robot navigation in complex urban environments, focusing on three advanced models: MODSRL, SOAR RL, and NavDP. MODSRL employs a multi objective framework to balance safety, efficiency, and success rate. SOAR RL is designed to handle high obstacle densities using anticipatory decision making. NavDP addresses the sim to real gap through domain adaptation and few shot learning. The models were trained and evaluated in simulation environments (CARLA, nuScenes, Argoverse) and validated using real world deployment data. Evaluation metrics included success rate, collision frequency, and energy efficiency. MODSRL achieved a 91.3% success rate with only 4.2% collision, outperforming baseline methods. SOAR RL showed robust performance in obstacle rich scenarios but highlighted a safety efficiency trade off. NavDP improved real world success rates from 50% to 80% with minimal adaptation data, demonstrating the feasibility of sim to real transfer. The results confirm the effectiveness of DRL in advancing autonomous delivery navigation. Integrating domain generalization, hybrid learning, and real time adaptation strategies will be essential to support large scale urban deployment. Future research should prioritize explainability, continual learning, and user centric navigation policies.

Balancing Performance, Cost, and Sustainability in Software Engineering Munthe, Era Sari; Marthalia, Lia
Digitus : Journal of Computer Science Applications Vol. 3 No. 3 (2025): July 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v3i3.1075

The environmental impact of Information and Communication Technology (ICT) has become a global concern, especially with the increasing energy consumption of data centers, artificial intelligence, and software systems. This narrative review explores how green computing and sustainable software engineering practices can address these environmental challenges. Using a systematic search across Scopus, IEEE Xplore, Web of Science, and Google Scholar, the review identifies best practices in integrating sustainability across the software lifecycle. Key findings reveal that energy-efficient coding, optimized database systems, and green AI strategies can significantly reduce energy use and carbon emissions. Cloud and serverless architectures offer additional sustainability potential when paired with proper energy monitoring tools. The review also highlights how educational reforms and organizational governance play essential roles in promoting eco-conscious practices. However, challenges persist. These include limited awareness among practitioners, lack of standardized metrics for software sustainability, and weak cross-disciplinary collaboration. Regional disparities also influence adoption, with Europe leading due to stronger policy frameworks, while Asia and North America show mixed trends. This study concludes that integrating sustainability into software engineering requires both technical innovations and systemic reforms. Future research should focus on empirical validation of sustainability frameworks, development of standard evaluation metrics, and promotion of interdisciplinary approaches. Sustainable ICT practices are not only an environmental necessity but also a strategic imperative for the future of digital innovation.

Internet of Things-Based Home Trash Capacity Tracking System with Instant Notifications Munthe, Era Sari; Diantoro, Karno; Herwanto, Agus
Digitus : Journal of Computer Science Applications Vol. 2 No. 3 (2024): July 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i3.257

Garbage created from routine household activities is collected and stored in household garbage cans. Location This garbage makes rubbish collection easier to live in and helps to maintain a clean household environment. Household garbage cans are often designed to fit specific demands and feature a tight-fitting cover to keep sickness and animals out and to minimize unwanted odors. The layout To stop the spread of bacteria or fungus, something must be easy to clean. Lack of technology to monitor garbage bin fullness and inability to precisely monitor fill capacity, which can lead to trash overflow, offensive odors, and animal nuisances. Thus, volume sensorization techniques and Internet of Things (IoT) technologies are the answers to this challenge. To enable real-time waste capacity volume monitoring and to give users level information about trash charging through the Blynk platform, the system will deliver When the garbage can is full, an alarm sensor-equipped warning will ring. The Arduino IDE and the C programming language are the software used. The findings of the study demonstrate that the garbage can capacity monitoring system The information about waste filling levels that are provided in real-time by this IoT-based system is effective. By using this approach, homeowners can easily keep a clean and healthy home environment by knowing when it's time to remove the trash.

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