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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer Telematika JUITA : Jurnal Informatika Jurnal Fisika FLUX KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Informatika dan Rekayasa Elektronik Jurnal Pengabdian UNDIKMA Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) Journal of Data Science and Software Engineering Jurnal Informatika Polinema (JIP) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Muhammad Itqan Mazdadi
Universitas Lambung Mangkurat
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Journal : Journal of Data Science and Software Engineering

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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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.136 KB) | DOI: 10.20527/jdsse.v1i01.4

Abstract

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
PERFORMANCE ANALYSIS OF CLASSIFIER ON FACEBOOK DATA USING UNIGRAM & BIGRAM COMBINATIONS Yudha Sulistiyo Wibowo; Mohammad Reza Faisal; Ahmad Rusadi; Dodon T Nugrahadi; Muhammad Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 1 No 02 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Penelitian ini pada analisis sentimen menggunakan metode random forest sebagai klasifikasi. TF-IDF adalah fitur berbobot dan fitur kombinasi dari N-Grams adalah unigram dan bigram sebagai kata fitur. Dalam penelitian ini TF-IDF digunakan untuk fitur ekstraksi, tes ini menggunakan data Komentar Facebook tentang Berita Olahraga. Dalam studi ini, dataset digunakan sebanyak 1000 data terbagi menjadi 2, yaitu data pengujian dan pelatihan data. Mencapai kinerja akurasi tinggi hasil dalam fitur unigram dengan akurasi 83,67% dari 2757 fitur, Bigram menghasilkan 58% dengan fitur sebanyak 8457.
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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Abstract

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
GRU, AdaGrad, RMSprop, Adam Implementasi Metode Gate Recurrent Unit (GRU) dan Metode Optimasi Adam Untuk Prediksi Harga Saham Muhammad Mada; Andi Farmadi; Irwan Budiman; Mohammad Reza Faisal; Muhammad Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 2 No 01 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

In terms of their potential, stocks are one of the most profitable investment options today. If done well and right, stocks can be a very profitable investment. However, volatile stock prices make it necessary to predict stock prices to make a profit. Gated Recurrent Unit (GRU) is a method for predicting time series data such as stock prices. The Optimization method is needed to get accurate prediction results. The weight renewal optimization method such as Adam is implemented to obtain the best weight in the Gated Recurrent Unit (GRU) and to find out the best loss function value generated by the Adam optimization method. The GRU-Adam implementation is carried out on two stock data, namely ICBP and YULE. The results of this research are that the ICBP data yields the respective loss function values, namely train loss 0.0016 and validation loss 0.0007. Whereas the YULE data resulted in a train loss value of 0.0051 and a validation loss of 0.0031. The MAPE generated in the ICBP stock data is 0.97%. While the YULE data is 3.00%.
IDENTIFIKASI PESAN SAKSI MATA PADA BENCANA KEBAKARAN HUTAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Rinaldi; Mohammad Reza Faisal; Muhammad Itqan Mazdadi; Radityo Adi Nugroho; Friska Abadi
Journal of Data Science and Software Engineering Vol 2 No 02 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.011 KB)

Abstract

Social media, one of which is Twitter, is a medium for disseminating information that is growing rapidly at this time. The advantage of Twitter which has such a huge impact is its speed in spreading news and information that is happening. One of the information that is often reported through social media is information about natural disasters. Therefore, a lot of research on sensor social networks has been carried out by researchers using data from social media with the aim of obtaining valid data for the disaster emergency response process. In this study, the classification of eye witness messages for forest fires was carried out using Convolutional Neural Network and feature extraction Word2Vec with dimensions of 100. Twitter data used amounted to 3000 data and divided into 3 classes, namely eyewitnesses, non-eyewitnesses, and unknowns. The research was conducted to determine the accuracy performance obtained from testing using several types of configurations hyperparameter. Based on the results of the tests carried out, the best accuracy value was 81.97%.
PENGARUH RESOLUSI CITRA DALAM MENDETEKSI RAMBU LALU LINTAS SIRKULER MENGGUNAKAN HOUGH CIRCLE TRANSFORM Zaini Abdan; Andi Farmadi; Rudy Herteno; Radityo Adi Nugroho; Muhammad Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 2 No 02 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

The traffic signs have several shapes, one of which is circular. Hough Circle Transform is a function that detects a circular in an image based on the gradient. This function also needs some parameters, one of which is the image resolution. The traffic signs in the frame will have varying sizes. If after cropping, it will produce images with varying resolution sizes. Therefore, resizing image resolution is required so that all image data have the exact image resolution. Image resolutions to be tested are 25 × 25 pixels, 50 × 50 pixels, 75 × 75 pixels, 100 × 100 pixels, 125 × 125 pixels, 150 × 150 pixels, 175 × 175 pixels, and 200 × 200 pixels. This research proves that the image resolution in shape detection using Hough Circle Transform affects the shape detection accuracy. The data used are No Stopping signs and No Parking signs for True detection test, whereas Other Dangers signs and Pedestrian Crossing signs for False detection test. The highest accuracy was generated at a resolution of 75 × 75 pixels.
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

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Abstract

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 METODE TEMPLATE MATCHING TERHADAP PENGENALAN CITRA PLAT NOMOR KENDARAAN BERMOTOR Ahmad Shofi Khairian; Irwan Budiman; Muhammad Itqan Mazdadi; Andi Farmadi; Dwi Kartini
Journal of Data Science and Software Engineering Vol 3 No 02 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Abstract The motorized vehicle number (TNKB) sign or commonly referred to as the police license plate is a plate made of aluminum that shows the sign of a motorized vehicle in Indonesia that has been registered with the Samsat Office. The motor vehicle number sign in the form of an aluminum plate consists of 2 (two) lines, the first line showing the area code (letters), police number (numbers), and the final code/series. This study uses 10 license plates of motorized vehicles as test data taken for each character and 3 data sets of letters AZ and numbers 0-9 number plates of motorized vehicles for each character as training data. The purpose of this study was to determine the level of accuracy of the method Template Matching on image recognition of motor vehicle numbers. The results of the implementation of the method Template Matching on the image recognition of motorized vehicle license plates is to produce an accuracy rate of 95.56%.
PREDIKSI DATA PENARIKAN UANG TUNAI DI MESIN ATM MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) Fitrinadi; Irwan Budiman; Andi Farmadi; Dodon Turianto Nugrahadi; Muhammad Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 3 No 02 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract

Abstract Data mining is a series of processes to explore the added value of knowledge that has been unknown from a data set. Many algorithms can be used in solving a problem related to prediction or forecasting a new data value for the future based on pre-existing data. Sarima model is a model in time series analysis. The performance of the Seasonal Autoregressive Integrated Moving Average (SARIMA) method produces a suitable or good model used to predict cash withdrawal data at ATM machines. The data used in the study is a dataset of ATM transactions originating from Finhacks. The result of error using MAPE (Mean Absolute Percenttage Error) on the predicted result of cash withdrawal data at atm machines is K1 16.75%, K2 18.09%, K3 7.85%, K4 5.67%, and K5 11.80%. So it can be concluded that the data matches using the SARIMA model that has been selected because the MAPE value is smaller than 20%.
FORECASTING DENGAN MENGGUNAKAN METODE FUZZY LOGIC RELATIONSHIP GROUP PADA DATA PEMBUATAN PASPOR KANTOR IMIGRASI Aidil Akbar; Andi Farmadi; Muliadi; Dwi Kartini; Muhammad Itqan Mazdadi
Journal of Data Science and Software Engineering Vol 3 No 02 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (753.228 KB)

Abstract

Stationarity is a term used to describe the pattern of trend in time series data. In time series data, this term known as stationary and non-stationary. Non-stationary data is a data that has an unstable pattern of increase and decrease. This condition makes forecasting more difficult. Fuzzy Time Series is one of many forecasting methods that can be used. In this algorithm, adding order is an option that can be used to increase the accuracy of the method. Application up to order three are carried out to determine the effect of addition order to the resulted accuracy value. Experiment is done by applying the used method to the data which is divided into several amounts of data. From the experiment, the average accuracy value of the three Order of Fuzzy Logic Relationship Groups (FLRG) Order-1, Order-2, and Order-3 are 84.06719%, 85.77546%, 92.01034%. FLRG Order-3 has the largest accuracy value while the smallest accuracy value is owned by FLRG Order-1. From this, it is proven that the addition of order able to reduce the error in accuracy value while forecasting using non-stationary data but the accuracy produced by different amounts of data are erratically increasing and decreasing. the experiment concluded that the order, the amount of data, and the data pattern are factors that affect the accuracy result.
Co-Authors AA Sudharmawan, AA Abdilah, Muhammad Fariz Fata Abdullayev, Vugar Ade Agung Harnawan, Ade Agung Adela Putri Ariyanti Afifa, Ridha Ahdyani, Annisa Salsabila Ahmad Rusadi Ahmad Rusadi Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Shofi Khairian Ahmad Tajali Aidil Akbar Al Ghifari, Muhammad Akmal Alamudin, Muhammad Faiq Amalia, Raisa Andi - Farmadi Andi Farmadi Andi Farmadi Anna Khumaira Sari Anshory, Muhammad Naufal Ansyari, Muhammad Ridho Antoh, Soterio Ardiansyah Sukma Wijaya Athavale, Vijay Anant Athavale, Vijay Annant budiman, irwan Buih, Putri Helena Junjung Deni Sutaji Dina Arifah Djordi Hadibaya Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini Dwi Kartini, Dwi Dzira Naufia Jawza Erdi, Muhammad Faisal, Mohammad Reza Fathmah, Siti Fatma Indriani Fayyadh, Muhammad Naufaldi Fitriani, Karlina Elreine Fitrinadi Friska Abadi Haekal, Muhammad Hafizah, Rini Helma Herlinda Herteno, Rudi Indriani, Fatma Irwan Budiman Irwan Budiman Irwan Budiman Irwan Budiman M. Apriannur M. Khairul Rezki Mafazy, Muhammad Meftah Muflih Ihza Rifatama Muhamad Fawwaz Akbar Muhamad Ihsanul Qamil Muhammad Khairin Nahwan Muhammad Mada Muhammad Mirza Hafiz Yudianto Muhammad Mursyidan Amini Muhammad Reza Faisal, Muhammad Reza Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Nabella, Putri Normaidah, Normaidah Nugraha, Muhammad Amir Nursyifa Azizah P., Chandrasekaran Patrick Ringkuangan Prastya, Septyan Eka Putri Nabella Radityo Adi Nugroho Rahmah, Indah Noor Rahmat Hidayat Rahmat Ramadhani Rahmat Ramadhani Rahmawati, Nanda Hesti Ramadhani, Muhammad Irfan Ramadhani, Rahmat Ratnapuri, Prima Happy Riadi, Agus Teguh Rifki Izdihar Oktvian Abas Pullah Rifki Rinaldi Rozaq, Hasri Akbar Awal Rudy Herteno Saputra, Adryan Maulana Saputro, Setyo Wahyu Saragih, Triando Hamonangan Satrio Yudho Prakoso Setyo Wahyu Saputro Shalehah Syahputra, Muhammad Reza Tajali, Ahmad Totok Wianto Wahyu Dwi Styadi Wijaya Kusuma, Arizha Yanche Kurniawan Mangalik YILDIZ, Oktay Yoga Pambudi Yudha Sulistiyo Wibowo Zaini Abdan