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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Komputasi Sebatik Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Journal of Data Science and Software Engineering Jurnal Informatika Polinema (JIP) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics

Andi Farmadi

Universitas Lambung Mangkurat

Author-ID : 3166642

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Materials Science & Nanotechnology

Published : 61 Documents Claim Missing Document

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IMPLEMENTASI TRANSFER LEARNING CONVOLUTIONAL NEURAL NETWORK UNTUK DETEKSI LUBANG JALAN PADA VIDEO DRONE Miftahul Muhaemen; Mohammad Reza Faisal; Dodon Turianto Nugrahadi; Andi Farmadi; Rudy Herteno
Journal of Data Science and Software Engineering Vol 1 No 01 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Pothole is one of the problems that can cause harm to a person or a lot of people and can even cost lives. So a lot of research has been done to detect potholes, especially image-based. This research uses Unmanned Aerial Vehicle (UAV) to get aerial video dataset and train Convolutional Neural Network (CNN) with the dataset. However, instead of doing learning from the beginning, transfer learning can be used to train CNN to recognize the object of a pothole and measure the value of its performance and what the optimal frame rate is. Then the results of this study indicate that the CNN model, ssd_resnet_50_fpn_coco gets an average performance value of 48.90 mAP. And the optimal frame rate with the average highest performance value at a frame rate of 30FPS with a value of 49.43 mAP, followed by 1FPS with a value of 48.36 mAP . Keywords: Performance, Transfer Learning, Convolutional Neural Network, Pothole Detection, Aerial Video.

IMPLEMENTASI ALGORITMA ENKRIPSI RSA PADA APLIKASI INSTANT MESSAGING Ardiansyah Sukma Wijaya; Dodon T. Nugrahadi; Muhammad Itqan Mazdadi; Andi Farmadi; Ahmad Rusadi
Journal of Data Science and Software Engineering Vol 1 No 01 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

At this time the use of instant messaging applications is increasingly used compared to the use of SMS or other media because of its use which is more practical and faster. From the other side, the message information sent certainly requires confidentiality so that the message is not spread and known by others. For this reason mechanisms are needed, one of which is encryption to maintain message security. This research will implement the RSA (Rivest Shamir Adleman) encryption algorithm in the instant messaging application. This study uses a key length scenario of RSA 1024, 2048, 4096, and 6144 bits and a message length of 125, 250, 500, and 1000 characters implemented on 3 different devices. The results of testing on time and speed are the shorter the key used, the process will be shorter and faster. Keywords : RSA, Processing Time, Processing Speed

SENSITIVITY TEST FUZZY TOPSIS AND FUZZY TOPSIS ROC METHODS FOR THE SELECTION OF THE SASIRANGAN BANJAR FABRIC MOTIFS Nafis Satul Khasanah; Andi Farmadi; Dodon Turianto Nugrahadi; Muliadi; Rudy Herteno
Journal of Data Science and Software Engineering Vol 1 No 01 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Decision making is one of problem that we often find in society, as well as choosing the fabric of the motif of Sasirangan Banjar that currently there are many kinds of it. So, to find out the ideal solution need the various of considerations that will make hesitation. And it will influence in time of accuracy of decision-making. Multi Atribut Decision Making (MADM) is a part of decision-making with various criteria that have a weight. The objective is to find out and ideal solution that can be optimal in implementation. The used Fuzzy TOPSIS and Fuzzy TOPSIS ROC methods an important to make an assesment with a simple system and calculation of priority weights to produces various motives. The result of two methods that have been test sensitivity are the best decision with the result 7,16% for weight Rank Order Centroid (ROC) and 0,6% for weight TOPSIS. So, Fuzzy TOPSIS ROC is better in values weight because it has a higher sensitivity than the Fuzzy TOPSIS.

Penerapan Long Short Term Memory RNN untuk Prediksi Transaksi Penjualan Minimarket Patrick Ringkuangan; Fatma Indriani; Muhammad Itqan Mazdadi; Irwan Budiman; Andi Farmadi
Journal of Data Science and Software Engineering Vol 1 No 02 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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This study aims to determine whether it can build a prediction of sales of goods at the Lapan-Lapan Mart by using the Long Short Term Memory Recurrent Neural Network method that can be used to predict the sale of goods. In this study, the data was taken from the Lapan-Lapan Mart, together with data on 10 different items sold every day. The data is then compiled for the level of sales to be weekly and a total of 52 data is obtained for each item so that the total data is amounted to 520. To get the weight in the LSTM calculation, there are two processes, namely forward and backward . the weight will be used to make predictions using the basic formula of the LSTM.Based on the research that has been done, it is known that the highest accuracy of using MAD (Mean Absolute Deviation) is 91 gr (11.61803507) indomie goods and 1.8kg of lemon daia (2.077000464) for the lowest MAD

IMPLEMENTASI METODE CONVOLUTIONAL NEURAL NETWORK UNTUK PREDIKSI HARGA SAHAM LQ45 Aris Pratama; Dwi Kartini; Akhmad Yusuf; Andi Farmadi; Irwan Budiman
Journal of Data Science and Software Engineering Vol 1 No 02 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (195.714 KB)

Stock are securities of ownership of a company. Investments in the stock market on average can produce a return rate of 10-30% per year, this amount is about two to three times higher than the rate of return on deposits or savings in banks which are only 5-10 % every year. One problem is the stock price is fluctuating or changing due to certain factors. This study compares several window size data with different amounts of data, aiming to find window size data with a more accurate amount of data for stock price predictions. Convolutional neural network algorithm with window size data of 7 days, 14 days, 21 days and 28 days in the amount of data 1 year and 2 years for stock price predictions. The results of this study are the convolutional neural network algorithm with a data window size of 7 days at the amount of data 2 years is more accurate than the window size data and the amount of other data. Because the smallest error result is 0.000201587.

IMPLEMENTASI ALGORITMA GENETIKA DENGAN TEKNIK SELEKSI TOURNAMENT UNTUK PENYUSUNAN JADWAL KULIAH Faisal Murtadho; Andi Farmadi; Dodon Turianto Nugrahadi; Irwan Budiman; Dwi Kartini
Journal of Data Science and Software Engineering Vol 2 No 01 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Genetic Algorithms can help human work, one of which is compiling course schedules. Preparation of course schedules, if done manually, will take a long time because you have to make a schedule where there are no schedule conflicts between one course and another. Therefore, this study will implement a Genetic Algorithm for the preparation of course schedules, so that it will speed up the preparation of course schedules compared to manual scheduling. In this study, the Genetic Algorithm with Tournament Selection was carried out with the input of control parameters, namely Population Size = 10, Crossover Rate (CR) = 0.75, and Mutation Rate (MR) = 0.01. In this study, the Genetic Algorithm has succeeded in obtaining the desired solution, namely scheduling courses where there are no schedule conflicts between one course and another. This search process took 88 generations to find the best solution.

HYPERPARAMETER TUNING METHOD OF EXTREME LEARNING MACHINE (ELM) USING GRIDSEARCHCV IN CLASSIFICATION OF PNEUMONIA IN TODDLERS Pirjatullah; Dwi Kartini; Dodon Turianto Nugrahadi; Muliadi; Andi Farmadi
Journal of Data Science and Software Engineering Vol 2 No 03 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.07 KB)

Pneumonia is a disease that is susceptible to attack toddlers. According to data from the Ministry of Health, the cause of under-five mortality due to pneumonia is number 2 of all under-five deaths. The dataset used is pneumonia disease data at the MTBS Health Center of East Martapura Health Center. The classification method in this study uses the Extreme Learning Machine (ELM) method. The classification process starts from SMOTE upsampling to balance the class, then parameter tunning is performed using GridsearchCV on the hidden layer neurons, then classification is carried out using the ELM method using the Triangular Basis activation function by comparing the test datasets 90:10, 80:20, 70:30, 60:40 and 50:50. This study provides the best performance results with an accuracy of 86.36%, the ratio of training and test data is 90:10 and 3 neurons hidden layer.

ANALISIS SOFTWARE DEFINED NETWORK (SDN) MENGGUNAKAN OPENDAYLIGHT CONTROLLER DENGAN ANOVA REPEATED MEASURES Rifki Izdihar Oktvian Abas Pullah Rifki; Dodon T. Nugrahadi; M. Itqan Mazdadi; Andi Farmadi; Ahmad Rusadi
Journal of Data Science and Software Engineering Vol 3 No 01 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (429.266 KB)

Abstract The rapid development of technology today makes the technology around us also become more advanced and continues to grow, this has an impact on the development of the internet network. Technology such as Software Defined Network (SDN) is needed because it results in improved performance in network management, control and data handling that allows it to be managed centrally and more easily by network administrators by separating the control plane and data plane. In this study, an analysis of the SDN architecture was carried out using the Opendaylight controller based on the parameters of throughput, delay and jitter which then can be seen how the performance of the SDN architecture in a topology by increasing the number of nodes. The throughput test shows that the custom topology has a significant increase in value and has a better average throughput value among other topologies. While in the delay and jitter test, the custom topology has a better average value even though it has an insignificant increase in the delay and jitter value when there is an increase in the number of nodes.

Implementasi Algoritma Convolutional Neural Network (CNN) Untuk Klasifikasi Gambar X-Ray Penyakit Covid-19 dan Pneumonia Fitria Agustina fitria; Andi Farmadi; Dwi Kartini; Dodon Turianto Nugrahadi; Ando Hamonangan Saragih
Journal of Data Science and Software Engineering Vol 3 No 01 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstrak Pneumonia caused by the corona virus is different from ordinary pneumonia. One way to find out which pneumonia is caused by the corona virus is to do an X-ray. The disadvantage of this examination is that it requires a radiologist and the analysis time is relatively long. Therefore, to overcome this problem, deep learning methods can be used by implementing the Convolutional Neural Network (CNN) Algorithm method for X-ray image classification. The implementation of the Convolutional Neural Network (CNN) Algorithm is done by using training data of 4800 images which are trained using batch size values of 16, 32, and 64. The train process with batch size values of 16, 32 and 64 produces an average accuracy of 90%, 91% and 92%, while the loss values are 0.22, 0.16 and 0.25. From this process it was found that batch 64 was the best loss and accuracy result for training data. The test data with batch values of 16, 32, and 64 resulted in an accuracy of 76%, 82% and 76%, while the loss values were 0.79, 0.53 and 0.63. The results of this manual testing of 30 photos contained 7 images that are not recognized by the model because of the images look similar to each other with an accuracy of 76%. From this process it was found that batch 32 was the best loss and accuracy result for testing data.

Text Mining Untuk Mengklasifikasi Judul Berita Online Studi Kasus Radar Banjarmasin Menggunakan Metode TF-IDF dan K-NN Salsabila Anjani; Andi Farmadi; Dwi Kartini; Irwan Budiman; Mohammad Reza Faisal
Journal of Data Science and Software Engineering Vol 3 No 01 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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ABSTRACT The news media that used to be commonly used were newspapers. However, with the development of the times, the news media is now entering the digital era. Many online news media spread on the internet. The sophistication of the internet makes it easier for readers to choose which news they want to read. Unlike newspapers, online news media have categories where readers can choose. In general, the categorization of a news in online media is determined by the editor. Given the number of news published in a day, of course, makes the editor's job difficult. A category in the news is usually not appropriate because usually the headline is made as attractive as possible to attract the interest of the reader. So there are times when the news title does not match the category that has been entered by the editor. The use of the K-Nearest Neighbor (K-NN) method can be used in determining the categorization of a news. By using a case study of the online media Radar Banjarmasin, a research was conducted to find out how well the Canberra and Euclidean classification methods were using news headline data for categorization. The results obtained in this study are the better classification method is Euclidean and with an accuracy value of 65.00%. Improvements that should be made for further research is to use other methods for comparison.

Co-Authors Abdilah, Muhammad Fariz Fata Abdullayev, Vugar Achmad Rizal Ahdyani, Annisa Salsabila Ahmad Bahroini Ahmad Faris Asy’arie Ahmad Juhdi Ahmad Rusadi Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Tajali Akhmad Yusuf Ando Hamonangan Saragih Ardiansyah Sukma Wijaya Arif, Nuuruddin Hamid Arifin Hidayat Aris Pratama Azizah, Siti Roziana Bachtiar, Adam Mukharil Bahriddin Abapihi Deni Sutaji Dita Amara Djordi Hadibaya Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini Dwi Kartini, Dwi Dzira Naufia Jawza Efendi Mohtar Erdi, Muhammad Evi Nadya Prisilla Faisal Murtadho Fathul Hadi Fatma Indriani Fayyadh, Muhammad Naufaldi Fitria Agustina fitria Friska Abadi Ghinaya, Helma Gita Malinda Heru Candra Kartika Heru Kartika Chandra I Gusti Ngurah Antaryama Irwan Budiman Irwan Budiman Jumadi Mabe Parenreng Junaidi, Ridha Fahmi Keswani, Ryan Rhiveldi Khairunnisa Khairunnisa Lisnawati M. Apriannur Miftahul Muhaemen Muhammad Alkaff Muhammad Halim Muhammad Itqan Mazdadi Muhammad Khairin Nahwan Muhammad Nadim Mubaarok Muhammad Reza Faisal, Muhammad Reza Muhammad Ridha Maulidi Muhammad Rusli Muliadi Muliadi Muliadi Muliadi Aziz Muliadi Muliadi Muliadi Muliadi muliadi muliadi Musyaffa, Muhammad Hafizh Mutiara Ayu Banjarsari Nafis Satul Khasanah Ngo, Luu Duc Noryasminda Nugraha, Muhammad Amir Nugrahadi, Dodon Nurcahyati, Ica Nurlatifah Amini P., Chandrasekaran Patrick Ringkuangan Pirjatullah Pirjatullah Pirjatullah Radityo Adi Nugroho Raidra Zeniananto Ramadhan, As`'ary Rifki Izdihar Oktvian Abas Pullah Rifki Rizki, M. Alfi Rozaq, Hasri Akbar Awal Rudy Herteno Rusdiani, Husna Salsabila Anjani Saputro, Setyo Wahyu Saragih, Triando Hamonangan Sa’diah, Halimatus Setyo Wahyu Saputro Shalehah Suci Permata Sari Syahputra, Muhammad Reza Tajali, Ahmad Ulya, Azizatul Umar Ali Ahmad Wijaya Kusuma, Arizha Winda Agustina YILDIZ, Oktay

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