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All Journal ComEngApp : Computer Engineering and Applications 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 KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIN (Jurnal Online Informatika) Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komputasi Sebatik Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Informatika dan Rekayasa Elektronik Jurnal Mnemonic Bubungan Tinggi: Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Teknik Informatika (JUTIF) Journal of Data Science and Software Engineering Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics

Rudy Herteno

Unknown Affiliation

Author-ID : 2667170

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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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.

PENGARUH SOFTWARE METRIK PADA KINERJA KLASIFIKASI CACAT SOFTWARE DENGAN ANN Achmad Zainudin Nur; Mohammad Reza Faisal; Friska Abadi; Irwan Budiman; Rudy Herteno
Journal of Data Science and Software Engineering Vol 1 No 01 (2020)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

Software Defect Prediction has an important role in quality software. This study uses 12 D datasets from NASA MDP which then features a selection of metrics categories software. Feature selection is performed to find out metrics software which are influential in predicting defects software. After the feature selection of the metric software category, classification will be performed using the algorithm Artificial Neural Network and validated with 5-Fold Cross Validation. Then conducted an evaluation with Area Under Curve (AUC), From datasets D” 12 NASA MDP that were evaluated with AUC, PC4, PC1 and PC3 datasets obtained the best AUC performance values. Each value is 0.915, 0.828, and 0.826 using the algorithm Artificial Neural Network.

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.

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (257.976 KB)

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.

Optimasi Bobot Weighted Moving Average Dengan Particle Swarm Optimization Dalam Peramalan Tingkat Produksi Karet Dendy Fadhel Adhipratama Dendy; Irwan Budiman; Fatma Indriani; Radityo Adi Nugroho; Rudy Herteno
Journal of Data Science and Software Engineering Vol 2 No 03 (2021)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Rubber is a mainstay commodity in the country, in 2014 Indonesia ranked second as the largest natural rubber producing country in the world. However, rubber production in Indonesia experiences uncertain ups and downs so it is necessary to predict it in order to benefit small farmers and the state. Weighted Moving Average ( WMA) is a method for predicting time series data. However, the parameters on the WMA need to be optimized in order to get optimal weight results on the WMA and get accurate results. Algorithm Particle Swarm Optimization implemented to determine the weight value of the method Weighted Moving Average more optimal. PSO-WMA and WMA were carried out on three weights, namely from weighting 3 4 and 5 on rubber production data. So that the results of this study are WMA with 3 weights get 81% accuracy, 4 weight 80.5% and 5 weight 80.3%. And for PSO-WMA, the accuracy at weighting 3 is 81.4%, weighting 4 is 80.9% and for weighting 5 it is 81.6%. The test results of this study have the effect of the weight value on WMA in increasing the accuracy results.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN POHON UNTUK RESTORASI LAHAN BEKAS KEBAKARAN DENGAN METODE ANALYTIC HIERARCHY PROCESS (AHP) DAN SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE EXPLOITING RANKS (SMARTER) Muhammad Denny Ersyadi Rahman; Muliadi; Rudy Herteno; Dwi Kartini; Friska Abadi
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 (449.162 KB)

Utilization or use of forest and land areas that are not in accordance with conservation principles can cause critical land to occur. Critical land is land inside or outside the forest area that has been damaged, so that it can cause loss or decrease in its function. The lack of knowledge of some people on critical land and the selection of inappropriate plant types sometimes makes the condition of burnt land increasingly become one of the obstacles for the Forest and Land Rehabilitation Program (RHL). Statistical data analysis can be used in the data processing process to become valuable information for the system. Applying statistical analysis methods in making decisions in selecting statistical data that has several criteria. This research is focused on the application of the Analytical Hierarchy Process (AHP) method to see a comparison of criteria. The SMARTER (Simple Multi Attribute Rating Technique Exploiting Rank) method is very suitable to be used to overcome the many alternatives that will be given to different soil samples later. In short, each final weight that affects the alternative is calculated with the results of the alternative assessment, so that the utility value of each alternative is obtained. From the research of the Analytical Hierarchy Process (AHP) and Simple Multi Attribute Rating Technique Exploiting Rank (SMARTER) method, the results of the Balangeran vegetation are obtained as the main recommendation with the greatest utility value, namely 1.321668.

COMPARATIVE ANALYSIS OF FUZZY TIME SERIES METHOD WITH FUZZY TIME SERIES MARKOV CHAIN ON RAINFALL FORECAST IN SOUTH KALIMANTAN M Kevin Warendra; Irwan Budiman; Rudy Herteno; Dodon Turianto Nugrahadi; Friska Abadi
Journal of Data Science and Software Engineering Vol 3 No 01 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Abstract Time series data (TS) is a type of data that is collected according to the order of time within a certain time span. Time Series data analysis is one of the statistical procedures applied to predict the probability structure of future conditions for decision making. FTS (FTS) is a data forecasting method that uses fuzzy principles as its basis. Forecasting systems with FTS capture patterns from past data and then use them to project future data. FTS Markov Chain is a new concept that was first proposed by Tsaur, in his research to analyze the accuracy of the prediction of the Taiwan currency exchange rate with the US dollar. In his research, Tsaur combines the FTS method with Markov Chain, The merger aims to obtain the greatest probability using a transition probability matrix. The results obtained from this research are tests with the best number of presentation values from FTS Markov Chain with FTS, resulting in different accuracy values depending on the two methods. The best accuracy performance is obtained by the Markov Chain FTS method with an error value of 1.6% and an accuracy value of 98.4% and for FTS with an error value of 7.4% and an accuracy value of 92.6%. produce different accuracy values depending on the two methods. The best accuracy performance is obtained by the Markov Chain FTS method with an error value of 1.6% and an accuracy value of 98.4% and for FTS with an error value of 7.4% and an accuracy value of 92.6%. produce different accuracy values depending on the two methods. The best accuracy performance is obtained by the Markov Chain FTS method with an error value of 1.6% and an accuracy value of 98.4% and for FTS with an error value of 7.4% and an accuracy value of 92.6%.

SISTEM PEMANTAUAN LOKASI PEGAWAI ULM BERBASIS PRESENSI BERGERAK Ahmad Juhdi; Radityo Adi Nugroho; Friska Abadi; Andi Farmadi; Rudy Herteno
Journal of Data Science and Software Engineering Vol 3 No 02 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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ULM attendance is usually done in each faculty using a fingerprint-based attendance machine. However, fingerprint-based presence during the pandemic is very dangerous due to the COVID-19 outbreak which allows the spread of the virus to be transmitted through finger intermediaries who use the presence machine simultaneously. As well as the existence of a letter prohibiting going home issued by the MENPENRB regarding "Restrictions on traveling activities outside the region or homecoming activities or leave for ASN in an effort to prevent the spread of Covid-18". In this study, we use a smartphone-based electronic system to overcome fingerprint-based attendance problems so that we can get an increase in terms of costs, and minimize the spread of the COVID-19 outbreak. By knowing the level of profit achieved through investment in the application development that the researcher has proposed, it is necessary to conduct a feasibility study (Feasibility Analysis) as a tool in drawing conclusions about what will be done electronically, a comparison will be made against the implementation of attendance in the previous year. The operational costs required are Rp. 27,665,070, while the costs incurred for application development are Rp. 1,613,666, it can be seen that there is an implementation cost savings of Rp. 26,051,404, when operational cost savings are included in the economic feasibility study, the Return on Investment (ROI) and Break-Event Point (BEP) values since the first year the application was implemented showed a positive value. Until the fourth year, ROI and BEP entered the feasible criteria so that from an Economic Feasibility perspective it can be seen that the application is economically feasible. And the application that is made is able to provide convenience in using the application as evidenced by validity and reliability tests.

PENERAPAN METODE FUZZY NEUTROSOPHIC SOFT SETS UNTUK PREDIKSI STATUS PENGAWASAN COVID-19 Lisnawati; Andi Farmadi; Dwi Kartini; Mohammad Reza Faisal; Rudy Herteno
Journal of Data Science and Software Engineering Vol 3 No 03 (2022)
Publisher : Fakultas MIPA Universitas Lambung Mangkurat

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Coronavirus Disease 2019 (COVID-19) is a new type of disease that has never been previously identified in humans and has been declared a pandemic. The diagnosis of the disease is complicated by the variety of symptoms and imaging findings and the severity of the disease at the time of presentation. Fuzzy Neutrosophic Soft Sets are able to handle many types of uncertainty data such as ambiguity, inaccuracy, ambiguity, and inconsistency. Therefore, Fuzzy Neutrosophic Soft Sets can be applied to overcome the uncertainty of symptoms in COVID-19 surveillance. This research was conducted by collecting and presenting the respondent's Neutrosophic value and Neutrosophic value as a knowledge base, then performed Fuzzy Neutrosophic Soft Sets operations (composition, complement, value function, and score function) to obtain the monitoring status of the predicted results. Furthermore, the monitoring status of the predicted results is compared with the actual monitoring status of the respondents to obtain the accuracy level of Fuzzy Neutrosophic Soft Sets. Based on testing of 12 respondents, with 7 respondents as training data and 5 respondents as testing data, the accuracy of the Fuzzy Neutrosophic Soft Sets method in the diagnosis of COVID-19 surveillance status was 80%.

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (675.556 KB)

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).

Co-Authors Abdullayev, Vugar Achmad Zainudin Nur Adawiyah, Laila Adela Putri Ariyanti Aflaha, Rahmina Ulfah Ahmad Juhdi Ahmad Rusadi Akhtar, Zarif Bin Al Ghifari, Muhammad Akmal Al Habesyah, Noor Zalekha Alfando, Muhammad Alvin Andi - Farmadi Andi Farmadi Andi Farmadi Andi Farmadi Angga Maulana Akbar Antoh, Soterio Arifin Hidayat Aryanti, Agustia Kuspita Athavale, Vijay Anant Azizah, Azkiya Nur Azizah, Siti Roziana Bahriddin Abapihi Dendy Fadhel Adhipratama Dendy Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini, Dwi Emma Andini Faisal, M. Reza Fatma Indriani Fauzan Luthfi, Achmad Favorisen R. Lumbanraja Fayyadh, Muhammad Naufaldi Febrian, Muhamad Michael Friska Abadi Ghinaya, Helma Hartati Hartati Hermiati, Arya Syifa Huynh, Phuoc-Hai Irwan Budiman Irwan Budiman Itqan Mazdadi, Muhammad Junaidi, Ridha Fahmi Lilies Handayani Lisnawati M Kevin Warendra Mariana Dewi Miftahul Muhaemen Muflih Ihza Rifatama Muhammad Alkaff Muhammad Anshari Muhammad Azmi Adhani Muhammad Denny Ersyadi Rahman Muhammad Itqan Mazdadi Muhammad Noor Muhammad Reza Faisal, Muhammad Reza Muhammad Rizky Mubarok Muhammad Sholih Afif Muhammad Syahriani Noor Basya Basya Muliadi Muliadi MULIADI -, MULIADI Muliadi Muliadi Muliadi Muliadi Muliadi Muliadi Nabella, Putri Nafis Satul Khasanah Ngo, Luu Duc Noor Hidayah Noryasminda Nur Hidayatullah, Wildan Nurdiansyah Nurdiansyah Nursyifa Azizah Oni Soesanto Pratama, Muhammad Yoga Adha Putri Nabella Putri, Nitami Lestari Radityo Adi Nugroho Rahmad Ubaidillah Rahmat Ramadhani Raidra Zeniananto Ramadhan, As`'ary Reza Faisal, Mohammad Rizky Ananda, Muhammad Rozaq, Hasri Akbar Awal Saputro, Setyo Wahyu Saragih, Triando Hamonangan Setyo Wahyu Saputro Siti Aisyah Solechah Suci Permata Sari Suryadi, Mulia Kevin Tri Mulyani Ulya, Azizatul Vina Maulida, Vina Wahyu Ramadansyah Wahyu Saputro, Setyo Zaini Abdan Zamzam, Yra Fatria

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