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"Saat ini populasi di dunia hampir mencapai 7,6 milliar dengan pertumbuhan 1,1% per tahun, yang berarti 83 juta orang bertambah setiap tahunnya. Seiring dengan pertumbuhan populasi, pangsa pasar akan Internet of Things (IoT) juga meningkat secara eksponensial yang membuat kompetisi di bidang IoT semakin besar selaras dengan pertumbuhan trafik data yang mengakibatkan terjadinya krisis spektrum frekuensi radio. Saat ini teknologi LPWAN telah diimplementasikan oleh perusahaan utilitas nasional yaitu PLN dengan smart meternya yang membantu perusahaan tersebut memotong biaya operasional dan menjaga kualitas layanan kepada masyarakat. Namun saat ini regulasi atas teknologi LPWAN belum ada terutama pada alokasi spektrum frekuensi, standar perangkat teknologi LPWAN dan bisnis modelnya. Penulisan ini dimaksudkan untuk mencari alternativealternatif yang terbaik untuk teknologi LPWAN dengan stakeholder terkait dan melakukan analisis biaya hak penggunaan spectrum frekuensi radio yang sesuai untuk implementasi LPWAN.

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Currently the world's population is nearly about 7.6 billion with a growth of 1.1% per year, which means that 83 million people are growing annually. As the population grows, the market share of Internet of Things (IoT) also increases exponentially which makes the IoT competition bigger in line with data traffic growth resulting in a radio frequency spectrum crises. Currently LPWAN technology has been implemented by the national utility company that is PLN with its smart meter that helps the company cut operating costs and maintain the quality of service to the community. However, the current regulation of LPWAN technology does not exist, especially in the allocation of frequency spectrum, LPWAN technology device standard and business model. This writing is intended to find the best alternatives for LPWAN technology with relevant stakeholders and to analyze the right cost of using the appropriate radio frequency spectrum for LPWAN implementation."

"Kemudahan manusia dalam mengakses informasi kapan dan dimana saja adalah tujuan diciptakannya Internet of Things (IoT). Banyak teknologi yang dapat menyokong implementasi IoT berjalan mulus, salah satunya Low Power Wide Area Network (LPWAN). Bertujuan mengirim informasi dalam jarak jauh dan konsumsi energi rendah, LPWAN didukung oleh teknologi physical layer sebagai platform modulasi radio untuk Internet of Things contohnya seperti LoRa. Berbagai data yang diterima oleh sensor node, maka diperlukan sebuah protokol penjadwalan sebelum melakukan transmisi ke base station atau sink node. Dalam riset ini, model penjadwalan yang akan digunakan adalah First Come First Served pada Cluster Head (CH-FCFS) dengan desain topologi jaringan star of stars. Model diimplementasikan ke dalam dua jaringan dengan 25 sensor nodes dan 1 cluster head; 50 sensor nodes dan 2 cluster head. Pengujian sistem model ini menggunakan simulator CupCarbon U-One 4.2. Hasil analisa jaringan pertama dan kedua memiliki keberhasilan pengiriman data sebesar 100% hingga ke sink node. Konsumsi energi 5 tahun untuk sensor node, cluster head S100, dan cluster head S200 adalah 22.732,2 Joule, 1.121.280 Joule, dan 1.121.280 Joule. Konsumsi energi 10 tahun untuk sensor node, cluster head S100, dan cluster head S200 adalah 45.464,4 Joule, 2.242.560 Joule, dan 2.242.560 Joule. Pengaruh dari penggunaan model scheduling dan penyesuaian penggunaan sensor berbasis baterai dijelaskan lebih rinci sesuai komunikasi model konsumsi energi pada simulasi.

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The ease with which humans access information anytime and anywhere is the purpose of the creation of the Internet of Things (IoT). Many technologies can support the implementation of IoT running smoothly, one of which is the Low Power Wide Area Network (LPWAN). Aiming at sending information over long distances and low energy consumption, LPWAN is supported by physical layer technology as a radio modulation platform for the Internet of Things for example like LoRa. Various data received by the sensor node, it requires a scheduling protocol before transmitting to the base station or sink node. In this research, the scheduling model that will be used is First Come First Served on Cluster Head (CH-FCFS) with a star of stars network topology design. The model is implemented in two networks with 25 sensor nodes and 1 cluster head; 50 sensor nodes and 2 cluster heads. The system testing of this model uses the CupCarbon U-One 4.2 simulator. The results of the first and second network analysis have the success of sending data by 100% to the sink node. The 5 year energy consumption for sensor nodes, S100 cluster head, and S200 cluster head are 22,732.2 Joules, 1,121,280 Joules, and 1,121,280 Joules. The 10 year energy consumption for sensor nodes, S100 cluster head, and S200 cluster head is 45,464.4 Joules, 2,242,560 Joules, and 2,242,560 Joules. The impact of the use of a scheduling model and adjustments to the use of battery based sensors are explained in more detail according to the communication model of energy consumption in simulations."

"Teknologi Internet of Things (IoT) memiliki potensi untuk merevolusi berbagai industri, termasuk pemantauan kualitas air. Penelitian ini mengusulkan sebuah sistem pemantauan kualitas air berbasis IoT menggunakan teknologi Low-Power Wide Area Network (LPWAN). Sistem tersebut terdiri dari perangkat IoT yang dilengkapi dengan sensor untuk mengukur berbagai parameter kualitas air, seperti pH, suhu, dan kekeruhan. Data yang terkumpul dikirimkan ke server pusat menggunakan teknologi LoRaWAN, yang memungkinkan komunikasi jarak jauh dengan konsumsi daya rendah. Data kemudian dianalisis dan diproses untuk memberikan informasi real-time tentang kualitas air kepada pemangku kepentingan. Sistem yang diajukan memberikan solusi efektif dan efisien untuk pemantauan kualitas air di daerah yang masih sulit terjangkau sinyal internet, di mana sistem pemantauan konvensional mungkin kurang efektif apabila dilakukan karena infrastruktur yang terbatas.

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The Internet of Things (IoT) technology has the potential to revolutionize various industries, including water quality monitoring. This research proposes an IoT-based water quality monitoring system using Low-Power Wide Area Network (LPWAN) technology. The system consists of IoT devices equipped with sensors to measure various water quality parameters, such as pH, temperature, and turbidity. The collected data is sent to the central server using LoRaWAN technology, which allows for long-range communication with low power consumption. The data is then analyzed and processed to provide real-time information on water quality to stakeholders. The proposed system provides an effective and efficient solution for water quality monitoring in remote areas with limited internet access, where conventional monitoring systems may be less effective due to limited infrastructure."

"Pencemaran udara merupakan masuknya polutan ke lingkungan yang menyebabkan efek negatif terhadap lingkungan seperti menurunkan tingkat kesehatan manusia dan organisme lain. Polusi udara terdiri dari dua jenis polutan yang berbentuk partikel dan gas dimana partikel berisikan PM2.5&PM10, sedangkan gas bersisikan Karbon Monoksida (CO), Nitrogen Dioksida (NO2), Sulfur Dioksida (SO2), dan Ozon (O3). Oleh karena itu, dibutuhkan suatu sistem yang dapat memantau tingkat polusi udara untuk mengetahui kualitas udara. Dengan menggunakan sistem berbasis Internet of Things (IoT), monitoring polusi udara dapat dilakukan secara real-time. Sistem IoT yang digunakan adalah berbasis Low Power Wide Area Network (LPWAN) yang cenderung baik untuk pemantauan polusi udara karena memiliki karakteristik konsumsi daya yang sedikit dan jarak jangkauan yang cukup luas. Parameter yang diukur pada penelitian ini adalah partikel PM2.5 & PM10 yang didasarkan oleh Air Quality Index (AQI).

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Air pollution is the entry of pollutants into the environment that causes negative effects on the environment, such as reducing the health levels of humans and other organisms. Air pollution consists of two types of pollutants in the form of particles and gases. Particles include PM2.5 and PM10, while gases include Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), and Ozone (O3). Therefore, a system is needed to monitor air pollution levels to determine air quality. By using an Internet of Things (IoT) based system, air pollution monitoring can be done in real-time. The IoT system used is based on Low Power Wide Area Network (LPWAN), which is well-suited for air pollution monitoring due to its low power consumption and wide coverage range. The parameters measured in this research are PM2.5 and PM10 particles, based on the Air Quality Index (AQI)."

"Saat mengalami kejadian yang sangat terdesak, pastinya akan berfikir untuk meminta pertolongan dan berusaha secepat mungkin agar cepat ditangani oleh pihak keamanan tanpa harus datang untuk melaporkan kejadian tersebut. Seiring teknologi, telah mendorong munculnya sebuah teknologi komunikasi nirkabel yaitu Low Power Wide Area Network (LPWAN) yang memiliki cakupan area yang luas, namun menggunakan daya yang relatif rendah dengan daya tahan baterai yang tinggi, Mekanisme kerjanya adalah panic button mengirimkan data (longitude dan latitude) ke gateway dengan menggunakan protokol komunikasi LoRa. Paket yang diterima dari end device kemudian diteruskan oleh gateway ke network server yang sudah terintegrasi langsung dengan application server. Selanjutnya data ditampilkan dalam sebuah peta pada web. Penelitian ini menerapkan sistem LoRaWAN karena sistem dapat mengirim data ke perangkat lain yang sudah terhubung ke cloud melalui perantara gateway. Pengujian kali ini dibagi menjadi dua yaitu uji sistem dan uji QoS. Untuk pengujian sistem akan diperhatikan apakah panic button-nya berfungsi dengan baik atau tidak. Untuk pengujian QoS, parameter yang diuji adalah Packet Delivery Ratio (PDR), Packet Loss, Signal Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), dan delay. Parameter tersebut diuji terhadap 6 jarak yang berbeda yaitu 100m, 200m, 300m, 1.2km, 1.6km, dan 2km dari gateway NLOS. Untuk pengujian 100m, 200m, 300m gateway terletak pada satu BTS referensi yaitu STO Kranggan, yang keseluruhan PDRnya adalah 100%, sehingga packet loss-nya 0%. Hal ini dikarenakan semua nilai RSSI-nya masih di atas -120dBm. Semakin jauh jarak yang ditempuh mengakibatkan nilai Path Loss (PL) akan semakin besar, berhubungan dengan RSSI yang semakin berkurang karena RSSI menjadi faktor penentu pengiriman data. Pada jarak 1.2km hasil PDR yang diperoleh adalah 100%, dengan packet loss sebesar 0%, nilai SNR rata-rata -0,523dB, nilai rata-rata RSSI -102dBm, dan delaynya 0,011123s. Nilai PDR pada 1,6km adalah 99,5% dengan packet loss sebesar 0,5 %, nilai SNR rata-rata -2,63941dB, nilai rata-rata RSSI sebesar -106,004dBm, nilai delay yang diperoleh sebesar 0,01127detik. Pada jarak 2km adalah 92,5%, packet loss sebesar 7,5%, nilai rata-rata SNR -10,86dB, nilai rata-rata RSSI -110,628571dBm, nilai delay paling besar yaitu 0,013078s. Sehingga semakin jauh jarak yang ditempuh, nilai packet loss dan delay semakin naik, sedangkan nilai PDR, SNR, RSSI semakin turun. Untuk gateway yang menjadi referensinya terdapat di STO Pasar Minggu, namun kenyataan adalah daerah tersebut juga mendapat cakupan dari gateway BTS lain, sehingga walaupun jaraknya lebih dekat, RSSI dan SNRnya menjadi lebih rendah, sebagai contoh nilai minimal SNR dan RSSI pada percobaan 1 jarak 1.2 km lebih kecil dibandingkan dengan percobaan 1 pada jarak 1.6km dan 2km.

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When experiencing a very urgent event, surely you will think to ask for help and try as fast as possible so that quickly handled by the security forces without having to come to report the incident. Along with technology, it has encouraged the emergence of a wireless communication technology namely Low Power Wide Area Network (LPWAN) which has a wide area coverage, but uses relatively low power with high battery life, its mechanism of action is a panic button sending data (longitude and latitude ) to the gateway using the LoRa communication protocol. Packets received from the end device are then forwarded by the gateway to the network server that is integrated directly with the application server. Then the data is displayed in a map on the web. This study applies the LoRaWAN system because the system can send data to other devices that are already connected to the cloud through an intermediary gateway. This time the test was divided into two namely the system test and QoS test. For testing the system will be considered whether the panic button is functioning properly or not. For QoS testing, the parameters tested are Packet Delivery Ratio (PDR), Packet Loss, Signal Noise Ratio (SNR), Received Signal Strength Indicator (RSSI), and delay. These parameters were tested against 6 different distances namely 100m, 200m, 300m, 1.2km, 1.6km, and 2km from the NLOS gateway. For testing 100m, 200m, 300m gateways are located in one reference base station, namely STO Kranggan, the overall PDR is 100%, so the packet loss is 0%. This is because all RSSI values are still above -120dBm. The farther the distance travelled causes the value of Path Loss (PL) will be greater, related to the decreasing RSSI because RSSI is a determining factor for data transmission. At a distance of 1.2km the PDR results obtained are 100%, with a packet loss of 0%, an average SNR value of -0.523dB, an average RSSI value of -102dBm, and a delay of 0.011123s. The PDR value at 1.6km is 99.5% with a packet loss of 0.5%, the average SNR value is -2.63941dB, the average RSSI value is -106,004dBm, the delay value obtained is 0.01127 seconds. At a distance of 2km is 92.5%, packet loss of 7.5%, the average value of SNR is -10.86dB, the average RSSI value is -110.628571dBm, the highest delay value is 0.013078s. So the farther the distance travelled, the value of packet loss and delay increases, while the value of PDR, SNR, RSSI decreases. For gateways that are referenced in the Pasar Minggu STO, the reality is that the area also receives coverage from other BTS gateways, so that even though the distances are closer, the RSSI and SNR are lower, for example the minimum SNR and RSSI values in trial 1 are 1.2 km smaller than experiment 1 at a distance of 1.6km and 2km."

"ABSTRAKInternet of Things devices that send small amounts of data do not need high bit rates as it is the range that is more crucial for them. The use of popular, unlicensed 2.4 GHz and 5 GHz bands is fairly legally enforced transmission power above power limits cannot be increased. In addition, waves of this length are very diffiult to propagate under field conditions e.g. in urban areas. The market response to these needs are the LPWAN Low Power WAN type networks, whose main features are far reaching wireless coverage and low power measurement end nodes that can be battery powered for months. One of the promising LPWAN technologies is the LoRaWAN, which uses a publicly available 868 MHz band in Europe and has a range of up to 20 km. This article presents how the LoRaWAN network works and describes the installation of the research and measurement infrastructure in this technology which was built in the Gdańsk area using the Academic Computer Center TASK network infrastructure. The methodology and results of the qualitative and performance studies of the constructed network with the use of unmanned aircraft equipped with measuring devices for remote collection of environmental data are also presented. The LoRaWAN TASK has been designed to support the development of other research projects as an access infrastructure for a variety of devices. Registered users can attach their own devices that send specific metrics that are then collected in a cloud based database, analyzed and visualized."