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Journal of Data Science and Software Engineering
Published by Universitas Lambung Mangkurat
ISSN : 27755320     EISSN : 27755487     DOI : https://doi.org/10.20527/jdsse.v1i01.13
Core Subject : Science,
Computer Science & IT
Journal of Data Science and Software Engineering adalah jurnal yang dikelola oleh program studi Ilmu Komputer Universitas Lambung Mangkurat untuk mempublikasikan artikel ilmiah mahasiswa tugas akhir. Terbit tiga kali dalam setahun.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 46 Documents
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THE EFFECT THE EFFECT OF SPREADING FACTOR ON LORA TRANSMISSION Muhammad Khairin Nahwan; Dodon Turianto Nugrahadi; M. Itqan Mazdadi; Andi Farmadi; Friska Abadi
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (554.399 KB)

Abstract

The conditions of a different area can affect the transmission of data so that transmission is needed that is resistant to interference and in certain conditions a device that can monitor several places is needed at once. The concept of Wireless Sensor Network (WSN) is applied to meet these demands. This research is shown to determine the effect of Spreading Factor (SF) on Long Range (LORA) transmission on distance by analyzing Quality of Service (QOS). The test is divided into 2 conditions, namely: The Line of Sight (LOS) condition & Non-Line of Sight (NLOS) condition. The test results show that the maximum distance that the LoRa transmitter can reach is 1100m in LOS conditions while for NLOS conditions it can only reach a distance of 300m. The QOS parameters used to consist of Delay, Throughput, RSSI, & SNR. Spreading Factor (SF) affects Delay and Throughput, not RSSI and SNR. The best value of Delay (9.64 ms), Throughput (667.60 Bps), and RSSI ( -94.25 dBm) is at Spreading Factor (SF) 6 and SNR (5.23 dB) is Spreading Factor (SF) 8 and for the distance, the value of RSSI (-76.45 dBm) and SNR (5.23 dB) is at a distance of 10m. This applies in LOS and NLOS conditions.
Implementasi Implementasi Kinerja Transmisi Data Dengan Modul Komunikasi LoRa dan Protokol MQTT-SN Pada Gateway Untuk Mendukung Transmisi Data Sensor Kelembapan Tanah Djordi Hadibaya; Dodon Turianto Nugrahadi; M. Reza Faisal; Andi Farmadi; M. Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (325.963 KB)

Abstract

Wireless sensor network can help remote data transfer. Implementation of wireless sensor network in IoT system must be done with a good planning because IoT system typically have limited system resources. This limitation can affect performance of a wireless network sensor. The purpose of this study is to find out the effect of node range to the data transfer performance in terms of delay, throughput, RSSI, and SNR by using QOS (quality of service) analysis for LoRa and MQTT protocol. The results of LoRa’s protocol delay are between 2,82 ms to 37,27 ms. Throughput between 0,61 Kb/s to 24,29 Kb/s. SNR between 2,7 dBm to 8,34 dBm, and RSSI between -74,92 dBm to -122,36 dBm. On the other hand, the results of MQTT’s protocol delay are between 677,49 ms to 1182,69 ms. Throughput between 0,60 Kb/s to 1,12 Kb/s. SNR between 2,7 dBm to 8,34 dBm and RSSI between -74,92 dBm to -122,36 dBm.
Optimasi SVR dengan PSO untuk peramalan harga Cryptocurrency Arifin Hidayat; Andi Farmadi; Mohammad Reza Faisal; Dodon Turianto Nugrahadi; Rudy Herteno
Journal of Data Science and Software Engineering Vol 3 No 01 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Cryptocurrency is the nickname given to a system that uses Cryptography technology to securely transmit data and process digital currency exchanges in a dispersed manner. A Cryptocurrency is a form of risky investment, Cryptocurrency prices are very volatile (changing) making Cryptocurrency prices need to be predicted to make a profit. Support Vector Regression (SVR) is one method for predicting time series data such as Cryptocurrency prices. However, the SVR parameters need to be optimized to get accurate results. The Particle Swarm Optimization (PSO) algorithm is implemented to determine the effect on the optimization of SVR parameters. The implementation of SVR and SVR-PSO is carried out on Bitcoin and Shiba Inu Coin Cryptocurrency data. The result of this research is that the SVR algorithm has an accuracy of 13.19082% (Bitcoin) and 68.3221% (Shiba Inu Coin). The SVR-PSO algorithm obtained an accuracy of 96.92359% (BTC) and 94.74245% (SHIB).
IMPLEMENTASI PROTOKOL MQTT-SN PADA INTERNET GATEWAY DEVICE DENGAN PENGIRIMAN PAKET DATA UDP Wahyu Dwi Styadi; Dodon Turianto Nugrahadi; M. Itqan Mazdadi; Mohammad Reza Faisal; Friska Abadi
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (275.431 KB)

Abstract

Internet of Things (IoT) is one of the new trends in the world of technology that is likely to become a trend in the future, to be able to make this happen, communication protocols such as MQTT-SN are needed which is a variant of the MQTT protocol and the connection protocol that supports IoT is NB- IoT to support this. Unlike MQTT which uses TCP as its communication protocol, MQTT-SN uses UDP as its data communication protocol. The purpose of this study is to determine the results of Quality of Service on the value of delay and throughput at QoS levels 0, 1, and 2. There are 2 test scenarios, namely real-time test scenarios and phased test scenarios. The design of the instrument consists of sensor instruments, Raspberry Pi microcontrollers for internet gateway device, and NB-IoT modules to then be tested with scenarios to get test results. Based on the test results, the best QoS results for the delay parameter in the real-time scenario are QoS level 2 with a delay value of 1.602 seconds, while for the gradual scenario there is QoS 0 with a delay value of 1.622 seconds. Furthermore, the best QoS results for throughput parameters in real-time scenarios are found at QoS level 2 with a throughput value of 245.79 bits per second and in a phased scenario found at QoS level 1 with a throughput value of 286.42 bits per second.
IMPLEMENTATION OF LORA WITH TEMPERATURE SENSORS IN IRRIGATION AREA (CASE STUDY: MARTAPURA CITY) Muhammad Mirza Hafiz Yudianto; Dodon Turianto Nugrahadi; Dwi Kartini; M. Itqan Mazdadi; Friska Abadi
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.073 KB)

Abstract

This study applies to the concept of a Wireless Sensor Network (WSN) consisting of a transmitting instrument and a receiving instrument using Long Range (LoRa) data transmission with a frequency of 915 MHz and LoRa 920 MHz. The test is divided into 2 tropical weather conditions, namely when the weather is sunny and rainy. The test results show that the maximum distance that the LoRa transmitter can reach is 1 kilometer. The QoS (Quality of Service) parameters used to consist of Delay, Throughput, RSSI, & SNR. Based on the test results of the QoS parameters, both frequencies affect tropical weather conditions and increase as the distance of data collection increases. LoRa Frequency 915 MHz and Frequency 920 MHz have their respective differences and advantages, which are uncertain on weather conditions and data transmission distances.
Implementasi Metode Haralick dengan Random Forest Classifier untuk identifikasi Penyakit Kentang Pada Citra Daun Muhammad Syahriani Noor Basya Basya; Andi Farmadi; Dwi Kartini; Radityo Adi Nugroho; Rudy Herteno
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Potato plants are one of the most widely grown food crops in the highlands of Indonesia. Besides being used as food, potatoes are now known to be used to fight free radicals, control blood sugar, and nourish the digestive system. Therefore, potatoes have good prospects for development. In connection with efforts to develop potatoes in Indonesia, there are obstacles, namely the attack of potato plants by disease. As for the disease in potato plants, one of the characteristics of knowing it is on the leaves. To identify the leaf image, the texture feature is an important feature to recognize the leaf from an image. This is because there are differences in texture between normal and diseased leaves. To perform image processing through texture features, one method that can be used is haralick. In this study, a system was created to identify the types of diseases present in potato leaves using the Haralick method with the Random Forest Classifier. The image used is 300 data consisting of 3 classes, namely Late Blight, Early Blight, and Health. In this study, the testing was carried out by dividing the training and testing data with a percentage of 70:30, 80:20, and 90:10. The highest accuracy value in this study was obtained by using a combination of 80:20 split data, which was 0.88. The 70:30 data split gets an accuracy of 0.85 and the 90:10 data split gets an accuracy of 0.87.

Page 5 of 5 | Total Record : 46

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