Articles
<![CDATA[The Development of Prototype Data Delivery System Based on LoRa and Mesh Topology ]]>
<![CDATA[Dewa Gede Kesuma Yoga]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[I Putu Agus Eka Pratama]]>
<![CDATA[ Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 10 No 1 (2022): Vol. 10, No. 1, April 2022 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana ]]>
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DOI: 10.24843/JIM.2022.v10.i01.p05
<![CDATA[This study aimed to build a prototype development on a data transmission system using the LoRa communication protocol by applying a mesh topology in areas that difficult to reach by Wi-Fi or internet networks, the position of the first IoT devices has a role as a gateway between the IoT devices and a server. To connect the IoT devices with a server, the location of the IoT devices must be in a strategic location therefore it can connect to the internet network. Then the second IoT devices has a role as a gateway between the IoT devices. This study emphasizes the use of a WEB interface application on a computer or laptop used by the user to control and monitor the condition of an electronic device that has a considerable distance. This study used the NodeMCU ESP8266 microcontroller which is used on the first IoT devices, then this study also used the Arduino UNO microcontroller which is used on every IoT device which is intended to carry out the process of sending data between IoT devices. The used of the LoRa module in this study was used as a communication medium between IoT devices, and the use of the DS18B20 temperature sensor was used as a data transmission parameter. Based on the trials that have been carried out, the results of the prototype system work well according to the available features, but there is still one obstacle in this study where the IoT device in carrying out the data transmission process will be disrupted if there is another device that has a frequency that resembles the IoT device used. and there are obstacles in the form of buildings or dense trees, resulting in disturbances in sending data. This IoT device can still be used to send data even though there are obstacles as previously mentioned, provided that the distance does not exceed 500 meters. Keywords: Arduino Uno, IoT, NodeMCU]]>
<![CDATA[Design and Development of Android-Based Indoor Wi-Fi Site Survey Application ]]>
<![CDATA[Ida Bagus Kade Taruna]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[I Putu Agus Eka Pratama]]>
<![CDATA[ Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana ]]>
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DOI: 10.24843/JIM.2021.v09.i03.p08
<![CDATA[In the indoor wireless network technology, it is found that there are many disturbances such as interference with LOS (Line of Sight), improper access point position, and low signal strength. To overcome these disturbances, wireless network optimization can be done by conducting a survey or analysis of the coverage area and quality of service. This analysis can be done by using an application, however available applications are mostly desktop applications, which makes surveying the indoor wireless network less efficient. This study discusses the design and development of mobile applications that can be used to analyze Wi-Fi networks in an indoor environment which can provide information about the coverage area of ??a Wi-Fi network. The application development uses the PDR (Pedestrian Dead Reckoning) RSSI (Receive Signal Strength Indicator) classification method. Application testing was carried out using two different scenarios, where in the first scenario the Wi-Fi network source was placed in the living room area, while in the second scenario the Wi-Fi network source was placed in the bedroom area 2. The result of the test carried out is the application can provide information regarding the coverage area of the signal from the two positions of different Wi-Fi network sources in a heatmap format that can be easily understood and can be used to optimize Wi-Fi networks in the future. Keywords : Android Application, Wireless Network, Sensor, Network Survey]]>
<![CDATA[Rancang Bangun Game Sad Ripu Berbasis Mobile Platform Android ]]>
<![CDATA[Komang Arta Wibawa]]>;
<![CDATA[Putu Wira Buana]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>
<![CDATA[ Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 7, No. 3, Desember 2019 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana ]]>
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DOI: 10.24843/JIM.2019.v07.i03.p07
<![CDATA[Sad Ripu adalah salah satu bagian dari ajaran agama Hindu yang memiliki arti enam musuh di dalam diri manusia. Fakta bahwa beberapa materi pelajaran di Indonesia khususnya pelajaran agama Hindu hanya diajarkan pada satu jenjang pendidikan menjadikan beberapa materi pelajaran terlupakan seiring waktu. Pentingnya makna yang terkandung dalam materi Sad Ripu yaitu mengenai pengendalian diri serta melihat masalah sistem pendidikan terkait penyampaian materi pelajaran mendasari ide tentang pemanfaatan media baru untuk menyampaikan materi Sad Ripu dengan cara yang lebih menarik. Game Sad Ripu dibangun untuk platform mobile Android, bergenre Tactical RPG (Role Playing Game), serta menerapkan sistem pertarungan Player versus Non-Player Character (NPC). Hasil pengujian menunjukkan hasil yang positif terkait penyampaian materi Sad Ripu, dengan total persentase jawaban setuju dan sangat setuju 88.89% pada aspek cerita, 70.67% jawaban setuju dan sangat setuju pada aspek grafis, serta 82.32% jawaban setuju dan sangat setuju pada aspek fungsionalitas.Kata kunci: Game, Android, AI, Sad Ripu, Tactical Game]]>
<![CDATA[Implementasi Algoritma PRNG pada Aplikasi Port Knocking Sebagai Perlindungan Server ]]>
<![CDATA[Made Andika Verdiana]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[Anak Agung Ketut Agung Cahyawan Wiranatha]]>
<![CDATA[ Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana ]]>
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DOI: 10.24843/JIM.2020.v08.i03.p08
<![CDATA[Keamanan jaringan harus dipertimbangkan dan dilindungi dengan baik. Masalah yang terjadi jika keamanan jaringan tidak terlindungi akan menyebabkan kerusakan sistem server dan dapat terjadinya akses tidak sah pada sistem server. Penelitian ini bertujuan untuk melakukan proses autentikasi jaringan antara komputer klien dengan komputer server dalam memvalidasi klien yang akan terhubung dengan sistem server. Penelitian dilakukan dengan metode autentikasi port knocking yang telah diimplementasikan algoritma PRNG (pseudo random number generator) dengan acuan seed waktu sistem. Hasil dari penelitian ini yaitu autentikasi port knocking dilakukan menggunakan hasil random sequence port yang berbeda sesuai dengan waktu sistem saat random number dibangkitkan guna untuk memperkuat autentikasi dalam memvalidasi klien yang akan terhubung dengan sistem server.]]>
<![CDATA[Optimalisasi Formula Default Pada Amibroker Untuk Analisis Teknikal Pada Pasar Saham ]]>
<![CDATA[Ridho Hisbi Sulaiman]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[Anak Agung Ketut Agung Cahyawan Wiranatha]]>
<![CDATA[ Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020 ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana ]]>
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DOI: 10.24843/JIM.2020.v08.i03.p03
<![CDATA[Penelitian ini bertujuan mengoptimalisasi sebuah formula default pada Amibroker menggunakan Bahasa AFL dengan beberapa algoritma yang dirancang agar para trader di pasar saham dapat melakukan analisis teknikal dan mengetahui langkah apa yang dapat diambil selanjutnya pada pasar saham. Formula default yang sudah dioptimalisasi memberikan informasi berupa tampilan chart. Para pengguna formula default yang sudah dioptimalisasi dapat mengetahui tindakan selanjutnya yang dapat diperoleh diambil dengan melihat sinyal buyatau sell yang tampil pada chart. Hasil dari penelitian nantinya diharapkan formula default yang dioptimalisasi dapat menjalankan fungsi-fungsi sebagaimana mestinya. Kesimpulan yang dapat ditarik dari penelitian ini adalah hingga saat ini formula default pada Amibroker yang sudah dioptimalisasi sebelumnya telah dapat menampilkan chart yang dapat memberikan analisis teknikal bagi pengguna berupa kondisi buy atau sell yang ditandai dengan sinyal berupa panah, menampilkan area resistance dan area support untuk membatasi keuntungan dan kerugian yang dapat diperoleh dari saham yang dimiliki.]]>
<![CDATA[Efektivitas Sniffer Menggunakan Natural Language dalam Pembelajaran Lalu Lintas Jaringan Komputer ]]>
<![CDATA[Putu Adhika Dharmesta]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[I Made Sunia Raharja]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i3.1696
<![CDATA[Computer networks are currently very active in the development of technology that is around us. Seeing this, of course knowledge of the network will be needed if there is a problem on the network. Scapy is a Python module that allows for sending, sniffing and dissecting a packet on a network. This capability allows users to create an application that can dissect how the workings of a network packet. Researchers will create a protocol traffic learning application on a computer network using Scapy and natural language to convey the results of the ongoing sniffing process. The application uses natural language to convey the translation of the sniffing process. The translation result of the sniffing process by using the natural language of this application is expected to be effective and can facilitate and make users understand and learn about the work process of a network packet. To measure the effectiveness of the use of natural language for the translation of the sniffing process a questionnaire was distributed to students of the SMKN 1 Denpasar school majoring in Computer and Network Engineering. The results of the distribution of the questionnaire were then calculated using a Likert scale and then the results obtained that the original results of the sniffing process got a Likert scale value of 37%. While the results of sniffing that have been translated get a value of 73%. This shows respondent better understands the results that have been translated compared to the original results that have not been translated.]]>
<![CDATA[Komparasi Algoritma Pincer Search dan Algoritma FP-Growth ]]>
<![CDATA[Putu Ratih Wulandari]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[Ni Kadek Dwi Rusjayanthi]]>
<![CDATA[ Techno.Com Vol 21, No 2 (2022): Mei 2022 ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.33633/tc.v21i2.5803
<![CDATA[Jumlah pembelian barang setiap harinya berbeda-beda karena itu permasalahan kekurangan stock barang dapat terjadi dan mengakibatkan ketidakpuasan pelanggan dalam berbelanja karena tidak tersedianya produk yang diinginkan. Permasalahan kekurangan stock barang dapat diminimalisir dengan melakukan penelitian mengenai data mining asosiasi menggunakan data transaksi penjualan dari Toko X berdasarkan metode algoritma pincer search dan algoritma FP-Growth. Penelitian ini bertujuan untuk mendapatkan association rule dan jumlah kemunculan frequent item set dalam data transaksi melalui minimum support yang dimanfaatkan untuk mengatasi permasalahan kekurangan stock barang di Toko X serta melakukan komparasi algoritma pincer search dan algoritma FP-Growth terhadap waktu pemrosesan data, frequent item set, rule, confidence dan lift ratio dengan bahasa pemrograman Python. Komparasi algoritma pincer search dan algoritma FP-Growth terhadap frequent item set, rule, confidence dan lift ratio dengan bahasa pemrograman Python memperoleh hasil yang sama, tetapi waktu yang dibutuhkan dalam pemprosesan data berbeda yang disebabkan oleh minimum support, jumlah transaksi dan jumlah item serta alur proses data yang berbeda dari kedua metode.]]>
<![CDATA[Video Streaming Data Security Using AES-Rijndael Algorithm ]]>
<![CDATA[Zebedeus Cheyso]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[Gusti Made Arya Sasmita]]>
<![CDATA[ CESS (Journal of Computer Engineering, System and Science) Vol 7, No 2 (2022): July 2022 ]]>
Publisher : <![CDATA[Universitas Negeri Medan ]]>
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DOI: 10.24114/cess.v7i2.32989
<![CDATA[Keamanan merupakan salah satu aspek yang paling penting dalam jalannya proses pertukaran informasi di masa ini. tidak semua informasi yang dipertukarkan dapat diperbolehkan menjadi konsumsi publik apalagi jika jatuh ke tangan pihak yang tidak bertanggung jawab yang dapat mengubah, memanipulasi dan menyebarkan informasi tersebut tanpa izin. Salah satu bentuk informasi yang perlu dilakukan langkah pengamanan ialah data video streaming. Metode enkripsi adalah pilihan yang paling tepat untuk mengamankan kerahasiaan data tersebut. Enkripsi merupakan sebuah ilmu untuk mengkonversikan sebuah data menjadi bentuk yang tidak dapat dimengerti guna menyembunyikan informasi yang hanya dapat diakses oleh pihak yang berhak. Penelitian ini memanfaatkan algoritma enkripsi AES-Rijndael untuk mengamankan data dan informasi dari video streaming yang dilakukan antara client dan server dengan memanfaatkan protokol transmisi RTP dan RTSP dalam kontrol alur media, enkripsi AES-Rijndael akan digunakan untuk mengubah data dari format file video berekstensi Mjpeg. Algoritma AES-Rijndael mampu mengamankan data dan informasi video dengan baik, ketika client memasukan kunci dekripsi yang berbeda, frame video yang dikirimkan dari server tidak dapat didekripsi dan ditampilkan secara utuh. Pengujian hashing SHA-256 dilakukan pada 25 dan 50 frame dari video untuk mengecek keaslian data berjalan dengan baik tanpa ada perubahan pada data frame yang dikirimkan.]]>
<![CDATA[Classification of Public Figures Sentiment on Twitter using Big Data Technology ]]>
<![CDATA[Ayu Krisnasari Ni Komang]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>;
<![CDATA[I Made Sunia Raharja]]>
<![CDATA[ JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022 ]]>
Publisher : <![CDATA[Universitas Medan Area ]]>
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DOI: 10.31289/jite.v6i1.7329
<![CDATA[Public figures often receive widespread public attention because they can exert a meaningful influence. On Twitter, the users can freely express their opinion through tweets. There are about 456,000 tweets sent in a minute which with this large and diverse number will make Big Data. Big Data has valuable potential for better decision-making. This large amount of tweet data can yield valuable information through sentiment analysis. This study aims to conduct a sentiment classification of Indonesian public figures using Twitter's data. This study used 1,034,329 tweets collected from Twitter in the period November 2021 until March 2022. Tweet classification is done by building a classification model using the Bidirectional Long Short-Term Memory algorithm. Sentiment toward public figures in Indonesia is 45.98% negative sentiment, 28.04% positive sentiment, and 25.98% neutral sentiment resulting from this study. The highest positive sentiment is obtained by public figures when there is content or news that is relevant to the public figure, while the highest negative sentiment is obtained when there is content or news that contradicts the image of the public figure.]]>
<![CDATA[Analysis of Public Sentiment Towards Goverment Efforts to Break the Chain of Covid-19 Transmission in Indonesia Using CNN and Bidirectional LSTM ]]>
<![CDATA[Gusti Agung Mayun Kukuh Jaluwana]]>;
<![CDATA[Gusti Made Arya Sasmita]]>;
<![CDATA[I Made Agus Dwi Suarjaya]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v6i4.4055
<![CDATA[COVID-19 is a new disease that has a negatively impacts in Indonesia, so the government is taking several measures to suppress the spread of COVID-19, such as new normal, social distancing, health protocols fines, and COVID-19 vaccination. The government's handling efforts have reaped a variety of negative to positive responses from the public on social media, so this study aims to determine the effectiveness of the government's efforts by analyzing public sentiment using the Deep Learning method with 1,875 training datasets consisting of four types government efforts and taken from various media social. The use of Deep Learning begins with testing several Deep Learning architectures to determine the best architecture for predicting data. The architectures tested include CNN and Bi-LSTM, where from these tests, Bi-LSTM outperforms CNN with the best performance achieving the accuracy of 97.34% and 97.33% for precision, recall, and F1-score. The results of public sentiment analysis show that social distancing efforts are considered the most effective by obtaining the most positive sentiments by 33.93%, while the effort to health protocol fines is considered lacking because it obtains the most negative sentiment of 35.64%, so the government must continue to enforce social distancing and optimize other efforts that are still considered ineffective.]]>
