Judul: Pengembangan Algoritme Battery-Recharge Scheduling untuk Swarm-UAV pada Skenario Persistent Monitoring dalam Indoor Farming
Abstrak: Sektor pertanian di Indonesia saat ini tengah mengalami perkembangan menuju smart farming 4.0. Salah satu konsep smart farming adalah indoor farming. Persistent monitoring pada indoor farming sangat penting dilakukan untuk menjaga lingkungan yang aman sebagai tempat pertumbuhan tanaman. Pada umumnya, berbagai sensor statis digunakan untuk menjamin persistent monitoring pada indoor farming. Namun, sensor statis dapat mengalami kerusakan dan perbaikannya memerlukan waktu. Hal ini akan mengganggu proses persistent monitoring. Pada penelitian ini, swarm-UAV Crazyflie digunakan untuk menggantikan sensor-sensor statis yang rusak, sementara sensor-sensor tersebut diperbaiki. Penelitian ini bertujuan untuk mengembangkan algoritme Ant Colony Optimization (ACO) dan Cloud-Based Drone Navigation (CBDN) dalam melakukan penjadwalan pengisian daya pada Crazyflie agar dapat menggantikan sensor rusak untuk sementara waktu. Hasilnya, algoritme hasil modifikasi yang diusulkan dapat mengalokasikan Crazyflie ke wilayah task tertentu dan melakukan battery-recharge scheduling dengan meminimumkan total travel time., The agricultural sector in Indonesia is currently going towards smart farming 4.0. One of the smart farming concepts is indoor farming. Persistent monitoring in indoor farming is very important to maintain a safe environment as a place for plants to grow. In general, various static sensors are used to guarantee persistent monitoring in indoor farming. However, the static sensors can be broken and to repair it will take time. This will interfere with the persistent monitoring process. In this study, Crazyflie swarm-UAV is used to replace the broken static sensors, while the sensors were repaired. This study aims to develop Ant Colony Optimization (ACO) and Cloud-Based Drone Navigation (CBDN) algorithms to perform charging scheduling task on Crazyflie in order to temporarily replace the broken sensors. As a result, the proposed modified algorithm can allocate the Crazyflie to certain task areas and perform battery-recharge scheduling by minimizing the total travel time.
Keyword: ACO, CBDN, penjadwalan pengisian daya, persistent monitoring

Judul: Crazyswarm and Lighthouse Positioning System Configuration to Support Multi-UAV Algorithm Implementation
Abstrak: Sistem multi-UAV saat ini banyak digunakan dalam berbagai bidang, termasuk pertanian. Salah satu algoritma terpenting untuk mengimplementasikan sistem multi-UAV adalah algoritma koordinasi dan algoritma pengalokasian tugas (task allocation). Sebelum algoritma-algoritma tersebut dapat diimplementasikan, sistem multi-UAV perlu dikonfigurasi terlebih dahulu agar UAV dapat berkoordinasi satu sama lainnya dan juga dengan central station yang mengendalikannya. Penelitian ini bertujuan untuk mengonfigurasi sistem Multi-UAV Crazyflie dan perangkat lunak Crazyswarm dalam lingkungan laboratorium. Setelah sistem Multi-UAV berhasil dikonfigurasi, sistem tersebut diuji dengan algoritma modifikasi Ant Colony Optimization (ACO) dan K-Means. Pengujian dilakukan dengan menerbangkan swarm Crazyflie ke posisi yang diperoleh oleh algoritma berdasarkan skenario yang telah ditentukan. Setelah mencapai posisi yang ditentukan, masing-masing Crazyflie akan terbang hover selama 5 detik di atas target. Posisi nyata Crazyflie ketika terbang hover ini kemudian dibandingkan dengan posisi luaran algoritma. Saat pengujiannya, Crazyswarm tidak bisa mendapatkan seluruh data posisi Crazyflie jika hanya menggunakan satu buah Crazyradio. Oleh karena itu, tiga buah Crazyradio serta tiga channel komunikasi berbeda digunakan supaya Crazyswarm dapat mengambil data posisi seluruh Crazyflie. Hasil pengujian menunjukkan bahwa nilai rata-rata error posisi UAV adalah -0.084 ± 0.033 cm untuk sumbu X, -0.251 ± 0.2 cm untuk sumbu Y, dan 0.01 ± 0.09 cm untuk sumbu Z., Multi-UAV systems are now widely used in various fields, including agriculture. One of the most important algorithms for implementing multi-UAV systems is the coordination and task allocation algorithms. Before these algorithms can be implemented, multi-UAV system needs to be configured in order to coordinate with each other and also with the central station that controls the system. This research aims to configure the Crazyflie Multi-UAV system and Crazyswarm software in a laboratory environment. After the Multi-UAV system was successfully configured, it is then tested with a modified Ant Colony Optimization (ACO) and K-Means algorithm. The testing was conducted by flying the Crazyflie swarm to the position obtained by the algorithm based on a predefined scenario. After reaching the specified position, each Crazyflie will hover for 5 seconds above the target. The real position of the Crazyflie when hovering is then compared with the algorithm's output position. While testing, Crazyswarm could not obtain all Crazyflie position data when using only one Crazyradio. Therefore, three Crazyradio and three different communication channels were used in order for Crazyswarm to retrieve the position data of all Crazyflies. The test result shows that the average value of UAV position error is -0.084 ± 0.033 cm for X axis, -0.251 ± 0.2 cm for Y axis, and 0.01 ± 0.09 cm for Z axis.
Keyword: ACO, configuration, Crazyflie, Crazyswarm, multi-UAV

Judul: Penggunaan Teorema Homeomorphy 2-Manifold dan Teorema Euler Poincare pada Torus 𝑇�� dan Simplicial Complex 𝐾��
Abstrak: Two dimensional topological spaces are said to be homeomorphic if they have the same topological invariant, where one of topological invariant used is an Euler characteristic. Homeomorphy 2-Manifold’s Theorem and Euler Poincare’s Theorem are used to distinguish two topological spaces. Homeomorphy 2-Manifold’s Theorem uses Euler characteristic to identify two dimensional topological spaces. Euler Poincare’s Theorem is an alternative way to find Euler characteristic with Betti number, which is topological invariant as well. The objective of this paper is to investigate the homeomorphism of torus 𝑇����� and simplicial complex 𝐾�����. Topological space torus and simplicial complex 𝐾����� have the same Euler characteristic, which is two. Based on Homeomorphy 2-Manifold’s Theorem topological space torus 𝑇����� and simplicial complex 𝐾����� is homeomorphic.
Keyword: simplicial, torus, Euler, homeomorphism, topology