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"Traditional laboratories are being complemented by virtual and remote laboratories. Students attend traditional laboratories in class and after hours perform experiments remotely, often from their home. There have been several remote laboratories that have been developed for a range of disciplines. This paper propose a remote laboratory for teaching FPGA and HDL at low cost. The remote laboratory is made of one server and multiple remote hardware sets. Each remote hardware set consists of one control board and at least one FPGA board. The Altera Development and Education (DE) Board is based on the Cyclone II ZC20 FPGA and is physically connected to the control broad. Both boards communicate with a computer server. The control board relays the FPGA inputs/outputs to the server, which in tums sends the status of the outputs to the client over the lnternet to visually display the results. Students use a computer client to perform experiments remotely on the F PGA. This architecture is designed to have high scalability and low data bit rate communication link with the average client requiring only a data rate of 450B/s. A FPGA board is planned to be used as a traditional laboratory during day and reassemble with a control board and a serverto become a remote laboratory at night."

"Pencemaran udara sebagai dampak dari pertumbuhan industri dan aktivitas manusia telah menjadi perhatian global. Salah satu kategori polutan udara yang berbahaya bagi kesehatan manusia adalah particulate matter (PM) 2.5. Laporan IQAir mencatat rata-rata konsentrasi PM2.5 di Indonesia per tahun 2022 sekitar 30,4 mikrogram per meter kubik, atau enam kali lipat lebih besar dari standar aman WHO. Dalam menanggapi kompleksitas masalah ini, penelitian ini merancang sistem deteksi dini dan monitoring polutan PM2.5 berbasis komunikasi LoRa 920 MHz dan Internet-of-Things (IoT) dengan sensor low-cost DSM501A. Penggunaan komunikasi LoRa, dengan menggunakan modul LoRa RFM95 pada frekuensi 920 MHz, menawarkan jangkauan transmisi atau coverage yang luas. Hasil deteksi partikel particulate matter divisualisasikan dalam bentuk laman web berbasis React Vite, Tailwind CSS, dan Node.js. Pengujian QoS komunikasi LoRa dilakukan dengan memprediksi path loss dan RSSI dengan pendekatan Okumura-Hata, serta mengukur nilai aktual SNR, RSSI, dan PDR, pada 10 titik pengujian di kawasan Universitas Indonesia. Hasil pengujian menunjukkan transmisi sinyal LoRa berhasil terkirim pada 8 dari 10 titik pengujian, dengan rentang jarak dari 8 m hingga 362.43 m, dengan nilai RSSI yang variatif pada rentang -85.87 dBm hingga -111.27 dBm, nilai SNR pada rentang 8.30 dB hingga -8.83 dB, serta PDR% pada rentang 100 % hingga 12.5 %, yang menunjukkan bahwa variabel LoRa seperti spreading factor, bandwidth, dan frekuensi, maupun variabel lingkungan, seperti jarak, area lintasan propagasi, dan vegetasi sangat mempengaruhi QoS transmisi sinyal LoRa di kawasan urban. Sementara itu, pada periode 14 hari pengumpulan data, total rata-rata polutan PM2.5 berdasarkan kategori waktu adalah pada tanggal 4 Juni 2024, yakni 149.42 mikrogram per meter kubik. Berdasarkan total rata-rata PM2.5 harian, indeks tertinggi terdapat pada hari Rabu, 5 Juni 2024, yakni 113.35 mikrogram per meter kubik. Rata-rata tertinggi indeks PM2.5 berdasarkan kategori waktu selama 14 hari pengumpulan data adalah pada siang hari.

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Air pollution, as a consequence of industrial growth and human activities, has become a global concern. One of the categories of air pollutants that poses a significant threat to human health is particulate matter (PM) 2.5. The IQAir report recorded an average PM2.5 concentration in Indonesia in 2022 of approximately 30.4 micrograms per cubic meter, which is six times higher than the WHO's safe standard. In response to this complex issue, this study designs an early detection and monitoring system for PM2.5 pollutants based on 920 MHz LoRa communication and the Internet of Things (IoT) using the low-cost DSM501A sensor. The use of LoRa communication, utilizing the LoRa RFM95 module at a 920 MHz frequency, offers a wide transmission range or coverage. The detected particulate matter data is visualized in the form of a web page based on React Vite, Tailwind CSS, and Node.js. The QoS testing of LoRa communication is conducted by predicting path loss and RSSI using the Okumura-Hata model and measuring actual values of SNR, RSSI, and PDR at 10 test points within the University of Indonesia area. The test results indicate that LoRa signal transmission successfully reached 8 out of 10 test points, with distances ranging from 8 m to 362.43 m, with varying RSSI values between -85.87 dBm and -111.27 dBm, SNR values between 8.30 dB and -8.83 dB, and PDR% ranging from 100% to 12.5%, showing that LoRa variables such as spreading factor, bandwidth, and frequency, as well as environmental variables like distance, propagation path area, and vegetation, significantly affect the QoS of LoRa signal transmission in urban areas. Meanwhile, during the 14-day data collection period, the total average PM2.5 pollutants by time category was on June 4, 2024, at 149.42 micrograms per cubic meter. Based on the total daily average PM2.5, the highest index was on Wednesday, June 5, 2024, at 113.35 micrograms per cubic meter. The highest average PM2.5 index by time category during the 14-day data collection period was during the daytime."

"This book about modeling of environment in terms of physical environment related parameters and measuring similar parameters by means of multispectral remote sensing, primarily by means of passive microwave remote sensing technology. Another new step is in the development and utilization of a multilevel approach which includes remote sensing of the land and water parameters like soil moisture, depth to water table, biomass of vegetation, temperature and salinity of water, in situ measurements of similar parameters and incorporation of GIS and data sets into the models of typical environments. "

"Skripsi ini membahas tentang pengujian kapabilitas mesin deteksi dari IDS yang dikembangkan oleh ID-SIRTII, yaitu Mata Garuda dengan menggunakan framework Pytbull dan hasilnya akan dibandingkan dengan IDS lain yang sudah banyak didistribusikan di masyarakat dan bersifat open source, yaitu Snort dan Suricata. Pada skripsi ini akan dijelaskan mengenai konsep dasar dari IDS, berbagai macam bentuk serangan yang dapat menyerang jaringan, pengujian serangan pada Mata Garuda, Snort, dan Suricata, serta analisis hasil pengujian pada ketiga IDS tersebut. Hasil pengujian menggunakan Pytbull yang dilakukan memberikan hasil bahwa akurasi deteksi Mata Garuda dan Snort secara keseluruhan (86.95%) lebih baik dibandingkan dengan Suricata (78.26%), namun dalam perbandingan ketepatan pendeteksian Suricata masih lebih unggul (73.91%) dibandingkan dengan Mata Garuda dan Snort (63.04%). Sedangkan dalam penggunaan resource CPU dan memori, Suricata lebih unggul dalam lingkungan multi core (40.67% pada core1 dan 5.39% pada core2, memori 919,917 bytes) daripada Mata Garuda (52.81% pada core1 dan 0.68% pada core2, memori 1,192,627 bytes) dan Snort (52.84% pada core1 dan 0.62% pada core2, memori 1,166,965 bytes).

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This research is concerned about the capability of detection engine from the IDS that developed by ID-SIRTII, called Mata Garuda using Pytbull framework and compared the result with the other well-known open source IDS, Snort and Suricata. This research will explain about the basic concept of IDS, some example of network attacks, penetration test to Mata Garuda, Snort, and Suricata, as well as the analysis about the result of the test from the three IDS.

The result of the test using Pytbull shows that the detection accuracy of Mata Garuda and Snort overall (86.95%) is better than Suricata (78.26%), but in the comparison of full detection ratio, Suricata (73.91%) is better than Mata Garuda and Snort (63.04%). In the comparison of CPU and memory usage, Suricata is better in multi core environment (40.67% on core1 and 5.39% on core2, memory 919,917 bytes) than Mata Garuda (52.81% on core1 and 0.68% on core2, memory 1,192,627 bytes) and Snort (52.84% on core1 and 0.62% on core2, memory 1,166,965 bytes)."

"The interaction of the solar and heat radiation with the atmosphere and surface is the subject of the book. The book contains the description of 17 computer studying programs supporting different topics of courses."

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Pertambangan menjadi sektor penting yang berperan dalam mendukung pembangunan dan perekonomian Indonesia. Salah satu perusahaan tambang terbesar di dunia adalah PT Freeport Indonesia yang terletak di Kabupaten Mimika, Papua. Dalam operasi pertambangannya, PT Freeport Indonesia menghadapi sejumlah masalah lingkungan, salah satunya adalah perubahan lahan bervegetasi menjadi lahan tandus yang minim vegetasi. Kerusakan lingkungan hidup yang terjadi akibat aktivitas pertambangan dapat dipulihkan melalui kegiatan reklamasi. Reklamasi lahan di wilayah pertambangan memerlukan waktu dalam jangka panjang untuk mencapai struktur dan fungsi ekosistem yang berkembang, stabil, dan matang sehingga diperlukan monitoring perubahan kondisi tutupan vegetasi di lahan bekas tambang menggunakan teknologi yang efektif dan efisien, yaitu penginderaan jauh. Dalam penelitian ini, citra penginderaan jauh yang digunakan adalah citra Sentinel-2 yang dikumpulkan dari tahun 2016 hingga 2023 untuk mendapatkan distribusi nilai indeks tutupan vegetasi (NDVI) dan tingkat kehijauan vegetasi di Area Reklamasi Grasberg. Variabel yang digunakan untuk menganalisis perubahan tutupan vegetasi selama proses revegetasi di Area Reklamasi Grasberg adalah indeks vegetasi (NDVI), jenis vegetasi, tahun reklamasi, ketinggian, kemiringan lereng, dan arah lereng. Penelitian ini menunjukkan bahwa semakin bertambah waktu reklamasi, maka semakin bertambah luas area yang tertutupi vegetasi dengan tingkat kehijauan sedang dan tinggi yang ditunjukkan dari hasil regresi linier yang bernilai posistif. Perubahan tutupan vegetasi di Area Reklamasi Grasberg menunjukkan tren peningkatan tutupan vegetasi seluas 379,66 hektar atau 98,71% dari total luas area reklamasi dan sisanya mengalami tren penurunan berdasarkan hasil analisis tren Sen’s Slope+Mann Kendall. Perubahan tutupan vegetasi di Area Reklamasi Grasberg tidak dipengaruhi oleh jenis vegetasi karena karakteristik vegetasi di area tersebut cenderung sama. Sedangkan perubahan tutupan vegetasi di Area Reklamasi Grasberg berdasarkan hasil uji korelasi dipengaruhi oleh faktor kondisi topografi. Ketinggian wilayah tidak menunjukkan pengaruh yang kuat terhadap tutupan vegetasi tetapi kemiringan lereng yang curam akan memicu terjadinya tingkat kehijauan tutupan vegetasi yang rendah dan sebaliknya. Sedangkan vegetasi yang berada di lereng yang menghadap ke arah timur memiliki tingkat kehijauan yang tinggi karena mendapatkan penyinaran matahari yang cukup. Pemantauan perubahan tutupan vegetasi di area reklamasi bekas tambang sangat bermanfaat untuk kebijakan pengelolaan lahan di area pertambangan dan perencanaan reklamasi.

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Mining is an important sector that plays a role in supporting Indonesia's development and economy. One of the largest mining companies in the world is PT Freeport Indonesia, located in Mimika Regency, Papua. In its mining operations, PT Freeport Indonesia faces a number of environmental problems, one of which is the change of vegetated land into barren land with minimal vegetation. Environmental damage caused by mining activities can be restored through reclamation activities. Land reclamation in mining areas takes a long time to achieve a developed, stable and mature ecosystem structure and function so that it is necessary to monitor changes in vegetation cover conditions in post-mining land using effective and efficient technology, namely remote sensing. In this research, the remote sensing images used were Sentinel-2 images collected from 2016 to 2023 to obtain the distribution of vegetation cover index (NDVI) and vegetation greenness in the Grasberg Reclamation Area. The variables used to analyze changes in vegetation cover during the revegetation process in the Grasberg Reclamation Area are vegetation cover index (NDVI), vegetation type, reclamation year, elevation, slope, and slope direction. This study shows that as the reclamation time increases, the area covered by vegetation with medium and high greenness levels increases, as shown by the positive linear regression results. Changes in vegetation cover in the Grasberg Reclamation Area show an increasing trend covering 379.66 hectares or 98.71% of the total reclamation area and the others show a decreasing trend based on the results of Sen's Slope+Mann Kendall trend analysis. Changes in vegetation cover in the Grasberg Reclamation Area are not influenced by vegetation type because the characteristics of vegetation in the area tend to be the same. Meanwhile, changes in vegetation cover in the Grasberg Reclamation Area based on the results of the correlation test are influenced by topographic conditions. The elevation of the area does not show a strong influence on vegetation cover but steep slopes will trigger a low level of vegetation cover greenness and vice versa. The vegetation on the east-facing slope has a high level of greenery because it gets enough sunlight. Monitoring changes in vegetation cover in ex-mining reclamation areas is very useful for land management policies in mining areas and reclamation planning."

"The book focuses on the different aspects of sensing technology, i.e. high reliability, adaptability, recalibration, information processing, data fusion, validation and integration of novel and high performance sensors specifically aims to monitor agricultural and environmental parameters. "