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All Journal NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Informatika dan Komputer JITCoS : Journal of Information Technology and Computer System
Dafa Ikhwanu Shafa
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Computer Science & IT Control & Systems Engineering Social Sciences

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Pembuatan Rumah Burung Hantu sebagai Upaya Pengendalian Hama Tikus Ramah Lingkungan dan Mengurangi Ketergantungan Pestisida Kimia di Desa Pematang Kasih Ariqah Luthfiyah; Aprilia Putri Silaen; Cut Latifah Putri; Dafa Ikhwanu Shafa; Khairunnisa Khairunnisa
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): November: NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v5i4.6864

Abstract

The Community Service Program (KKN) in Pematang Kasih Village, Pantai Cermin District, focused on the construction of owl houses (RUBUHA) as an environmentally friendly effort to control rice field rats. The background to this activity was the high level of rat infestation that was detrimental to local farmers' rice harvests and the excessive use of chemical pesticides, which had the potential to negatively impact human health and ecosystem balance. The research method used was descriptive qualitative, with data collection techniques through direct observation in agricultural fields, interviews with farmer groups, and documentation of the owl house construction process. The results showed that the village community responded positively to this program because the use of owls as natural predators was proven to be more effective in controlling the rat pest population while reducing dependence on chemical pesticides. In addition, this program also increased public awareness of the importance of ecologically based pest control and preserving biodiversity. With the owl houses built around rice fields, it is hoped that a sustainable agricultural pattern can be created that supports the welfare of farmers while preserving the environment.
A Discrete-Event and Monte Carlo-Based Simulation Model for Multi-Server Call Center Queueing Systems Nur Bainatun Nisa; Dafa Ikhwanu Shafa; Muhammad Yusuf Azmi; Parinduri, Armayanti Akhiriyah
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Volume 1 Number 2, December 2025
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.35

Abstract

This study presents the implementation and performance evaluation of a multi-server queueing system model for call center operations using discrete-event simulation combined with Monte Carlo analysis. The objective is to analyze system performance under varying numbers of service agents to identify the optimal configuration that balances service efficiency and customer satisfaction. The model assumes that customer arrivals follow a Poisson distribution, while service times are exponentially distributed to represent realistic call handling behavior. Simulation experiments were conducted over eight-hour operational periods with server counts ranging from one to eight, each replicated 500 times for statistical robustness. Performance indicators such as average waiting time, server utilization, and Service Level Agreement (SLA) compliance were analyzed to measure system efficiency. Results show that increasing the number of servers significantly reduces average waiting time and enhances service level compliance. Configurations with five or more servers achieved average waiting times close to zero and over 99% compliance with the SLA, while maintaining moderate server utilization levels between 70% and 80%. These findings demonstrate that integrating discrete-event simulation with Monte Carlo methods provides an effective and reliable framework for evaluating service system performance, optimizing resource allocation, and supporting decision-making in call center management.
Classification of Organic and Non-Organic Waste Using Convolutional Neural Network (CNN) Muhammad Farhan; Mhd Farhan Aditiya; Dafa Ikhwanu Shafa; Supiyandi; Aidil Halim Lubis
Jurnal Ilmiah Informatika dan Komputer Vol. 2 No. 2 (2025): Desember 2025
Publisher : CV.RIZANIA MEDIA PRATAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69533/xbpg4s54

Abstract

The increase in waste volume in Indonesia, which reached emergency levels in 2024, requires technological solutions that can assist in the sorting process quickly and accurately. Previous research on CNN-based waste classification generally focused on recyclable waste categories with many classes and used structured datasets, which did not adequately represent real-world waste conditions, especially organic waste, which has more varied shapes and conditions. Based on this gap, this study proposes a Convolutional Neural Network (CNN) model for classifying two main categories—organic and inorganic—using 25,077 images and direct testing on field samples. The model was trained using the Adam optimizer and categorical crossentropy loss. The results show high accuracy for inorganic waste (96%), but lower accuracy for organic waste (62%) due to the complexity of texture and natural damage. This study contributes to the field of informatics through the application of more applicable and realistic deep learning for automatic waste sorting systems, as well as opening up opportunities for the development of model architectures that are more adaptive to waste conditions in the actual environment.
Co-Authors Aidil Halim Lubis Aprilia Putri Silaen Ariqah Luthfiyah Cut Latifah Putri Khairunnisa Khairunnisa Mhd Farhan Aditiya Muhammad Farhan Muhammad Yusuf Azmi Nur Bainatun Nisa Parinduri, Armayanti Akhiriyah Supiyandi Supiyandi