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All Journal Perfecting a Video Game with Game Metrics Techno: Jurnal Penelitian Jurnal Teknologi Informasi dan Ilmu Komputer Info-Teknik KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jukung (Jurnal Teknik Lingkungan) JTERA (Jurnal Teknologi Rekayasa) ILKOM Jurnal Ilmiah JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Buletin Profesi Insinyur Jurnal Sains Komputer dan Teknologi Informasi Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) JUSTE (Journal of Science and Technology) Jurnal Jalan Jembatan
Yuslena Sari
Universitas Lambung Mangkurat
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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RANCANG BANGUN APLIKASI MONITORING TINGKAT KEHADIRAN PEGAWAI PADA BADAN PUSAT STATISTIK KOTA BANJARMASIN Husnul Khatimi; Muhammad Alkaff; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 1 No. 1 (2016)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (724.969 KB) | DOI: 10.20527/jtiulm.v1i1.5

Abstract

Tingkat kehadiran pegawai merupakan hal yang sangat penting pada instansi pemerintahan maupun swasta. Pada instansi yang menerapkan aturan absensi dengan jam datang dan jam pulang, akan menjadi sangat penting untuk memonitor secara personal maupun berkala tingkat kehadiran dalam bentuk jam kedatangan serta jam kepulangan pegawai. Perkembangan teknologi informasi sendiri telah memberikan kemudahan dalam proses absensi pegawai yaitu dengan teknologi fingerprint. Hal tersebut merupakan salah satu faktor ukuran kinerja pegawai yang bekerja pada instansi tersebut yang tentu saja pada akhirnya akan berpengaruh pada pemberian reward maupun punishment terhadap pegawai yang bersangkutan. Mesin absen sudah mengeluarkan output database Microsoft Access berupa jam datang dan jam pulang. Untuk dapat memonitor absensi pegawai, admin di BPS membuat program untuk mengkalkulasi jam datang, jam pulang, terlambat, dan pulang cepat. Namun pembuatan program tersebut masih belum selesai dan masih terdapatkekurangan. Maka untuk mengatasi hal tersebut perlu adanya tahap penyelesaian suatu program yang sudah ada, melengkapi kekurangan dan menambah fitur baru.
PREDIKSI KUALITAS HASIL HUTAN LAHAN BASAH MENGGUNAKAN BACKPROPAGATION Husnul Khatimi; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 1 No. 1 (2016)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1574.458 KB) | DOI: 10.20527/jtiulm.v1i1.6

Abstract

Many forests are wetlands plant palm or tribe (family) Arecaceae. One type is the coconut (Cocos nucifera) is often utilized all its parts including stem used for wood materials, the process of selecting coconut wood are used as ingredients of a product made by a grader trained by observing the wood directly without using tools (manual). The method of causing dependence expertise and experience in the selection of a grader coconut wood. With the limitations of a grader, then arises a problem when a large number of coconut wood objects tested manually exceeds the capacity of a grader. Therefore, the grouping of coconut wood needs to be made with intelligent systems that can overcome these problems. Determination of coconut wood can be automatically built using backpropagation method to identify the parameters of the determining characteristics of coconut wood obtained from coconut wood image of two-dimensional (2D). Determination of coconut wood characteristic parameters based on the extraction of texture features based on the image histogram 2D coconut wood. Features texture obtained from the histogram method is among others: the mean intensity, standard deviation, skewness, energy, entropy, and subtlety. This paper describes the determination of the quality of coconut timber using back propagation algorithm based on coconut wood texture 2D image.
SISTEM INFORMASI MANAJEMEN BERBASIS UML (STUDI KASUS PEMELIHARAAN TOILET PADA KAMPUS FAKULTAS TEKNIK UNIVERSITAS LAMBUNG MANGKURAT) Yuslena Sari; Irfan Prasetia
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 1 No. 2 (2016)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (857.649 KB) | DOI: 10.20527/jtiulm.v1i2.8

Abstract

This paper presents concept of a database system on a computer software systems. Requirements in analysis and design are a serious problem in developing a manual system into a computer software system that is fully automated. To link the two systems (manual and automatic), a modeling language Unified Modeling Language (UML) is now accepted as the de facto standard for the design and specification of object-oriented systems. In this study, ULM modeling language used to design a management information system (MIS) of Toilet Maintenance on the Faculty of Engineering, Lambung Mangkurat University using Access 2013. From this system, dean as admin of the system, can immediately know the damage or the need of maintenance in real time every day. Such information would greatly assist the management on making decision related to monitoring, maintenance and repair of toilet in the Faculty of Engineering, Lambung Mangkurat University. The final results is to keep the cleanliness and reliability of toilet in the Faculty of Engineering, Lambung Mangkurat University.
RANCANG BANGUN SISTEM INFORMASI MANAJEMEN KEPEGAWAIAN DI FAKULTAS TEKNIK UNIVERSITAS LAMBUNG MANGKURAT Maya Amalia; Muhammad Alkaff; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 1 No. 2 (2016)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (386.18 KB) | DOI: 10.20527/jtiulm.v1i2.10

Abstract

Implementation of management information sistems in state institutions or public organizations, will allow it to manage a variety of data needed to be valuable information for both internal organization and for those who are outside the organization. Faculty of Engineering, University Mangkurat in this case still has shortcomings in performing data collection associated with educators and education personnel, mainly deals with research and community service. The data collection process at the Faculty of Engineering, University Mangkurat still done manually and not computerized. The design and construction of a sistem of personnel information would be very helpful in speeding up the process of collection of data pertaining to educators and education personnel. Hopefully, by the information sistem, data educators and educational staff in the Faculty of Engineering, University of Mangkurat can be neatly arranged so as to facilitate the implementation of monitoring and evaluation in the field of personnel.
Prediksi Harga Emas Menggunakan Metode Neural Network Backropagation Algoritma Conjugate Gradient yuslena Sari
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 1 No. 2 (2017)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v1i2.21

Abstract

Artificial Neural Network Backpropagation is known as one of the most reliable methods of predicting. The algorithm used in this research is Conjugate Gradient algorithm, with gold data data of input data for training data. The price of gold becomes an issue in the market, as a precious metal that can be used for investment is very interesting to make a gold price prediction application. Gold prices continue to increase in the world market, making investors interested to invest in this precious metal. The application of gold price prediction will be very useful for investors of precious metals. Gold price data used in this research is daily data, taken 3 (three) last year and divided into test data and data testing. Test data is used to generate new weights for data testing. The parameters used in the measurement of evaluation of predicted results from Conjugate Gradient algorithm Artificial Neural Network Backpropagation method is Meant Square Error (MSE), where the result of MSE from this research is 0.0313651
Modelling and predicting wetland rice production using support vector regression Muhammad Alkaff; Husnul Khatimi; Wenny Puspita; Yuslena Sari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.10145

Abstract

Food security is still one of the main issues faced by Indonesia due to its large population. Rice as a staple food in Indonesia has experienced a decline in production caused by unpredictable climate change. In dealing with climate change, adaptation to fluctuating rice productivity must be made. This study aims to build a prediction model of wetland rice production on climate change in South Kalimantan Province which is one of the national rice granary province and the number one rice producer in Kalimantan Island. This study uses monthly climatic data from Syamsudin Noor Meteorological Station and quarterly wetland rice production data from Central Bureau of Statistics of South Kalimantan. In this research, Support Vector Regression (SVR) method is used to model the effect of climate change on wetland rice production in South Kalimantan. The model is then used to predict the amount of wetland rice production in South Kalimantan. The results showed that the prediction model with the RBF kernel with the parameter of C=1.0, epsilon=0.002 and gamma=0.2 produces good results with the RMSE value of 0.1392.
PSO optimization on backpropagation for fish catch production prediction Yuslena Sari; Eka Setya Wijaya; Andreyan Rizky Baskara; Rico Silas Dwi Kasanda
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14826

Abstract

Global climate change is an issue that is enough to grab the attention of the world community. This is mainly because of the impact it has on human life. The impact that is felt also occurs in waters on the South Kalimantan region. This is of course can disrupt the productivity of fish in the marine waters of South Kalimantan. This study aims to make fish catch production prediction models based on climate change in the South Kalimantan Province because the amount of productivity of marine fish has fluctuated. This study uses climate data as input and fish production as output which is divided into two, namely training and testing data. Then the prediction is conducted using Backpropagation method combined with Particle Swarm Optimization method. The results of the study produced a prediction model with RMSE of 0.0909 with a combination of parameters used, namely, C1: 2, C2: 2, w: 0.7, learning rate: 0.5, Momentum: 0.1, Particles: 5, and epoch: 500. While the model used when predicting testing data produces RMSE of 0.1448.
Vehicle detection using background subtraction and clustering algorithms Puguh Budi Prakoso; Yuslena Sari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.10144

Abstract

Traffic congestion has raised worldwide as a result of growing motorization, urbanization, and population. In fact, congestion reduces the efficiency of transportation infrastructure usage and increases travel time, air pollutions as well as fuel consumption. Then, Intelligent Transportation System (ITS) comes as a solution of this problem by implementing information technology and communications networks. One classical option of Intelligent Transportation Systems is video camera technology. Particularly, the video system has been applied to collect traffic data including vehicle detection and analysis. However, this application still has limitation when it has to deal with a complex traffic and environmental condition. Thus, the research proposes OTSU, FCM and K-means methods and their comparison in video image processing. OTSU is a classical algorithm used in image segmentation, which is able to cluster pixels into foreground and background. However, only FCM (Fuzzy C-Means) and K-means algorithms have been successfully applied to cluster pixels without supervision. Therefore, these methods seem to be more potential to generate the MSE values for defining a clearer threshold for background subtraction on a moving object with varying environmental conditions. Comparison of these methods is assessed from MSE and PSNR values. The best MSE result is demonstrated from K-means and a good PSNR is obtained from FCM. Thus, the application of the clustering algorithms in detection of moving objects in various condition is more promising.
Application of neural network method for road crack detection Yuslena Sari; Puguh Budi Prakoso; Andreyan Rizky Baskara
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14825

Abstract

The study presents a road pavement crack detection system by extracting picture features then classifying them based on image features. The applied feature extraction method is the gray level co-occurrence matrices (GLCM). This method employs two order measurements. The first order utilizes statistical calculations based on the pixel value of the original image alone, such as variance, and does not pay attention to the neighboring pixel relationship. In the second order, the relationship between the two pixel-pairs of the original image is taken into account. Inspired by the recent success in implementing Supervised Learning in computer vision, the applied method for classification is artificial neural network (ANN). Datasets, which are used for evaluation are collected from low-cost smart phones. The results show that feature extraction using GLCM can provide good accuracy that is equal to 90%.
Optimasi Penjadwalan Mata Kuliah Menggunakan Metode Algoritma Genetika dengan Teknik Tournament Selection Yuslena Sari; Muhammad Alkaff; Eka Setya Wijaya; Syarifah Soraya; Dany Primanita Kartikasari
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 1: Februari 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3621.855 KB) | DOI: 10.25126/jtiik.2019611262

Abstract

AbstrakBagi sebuah perguruan tinggi, penjadwalan perkuliahan merupakan suatu kegiatan yang sangat penting   untuk   dapat   terlaksananya   proses belajar mengajar   yang   baik.  Dimana   dalam   proses  belajar mengajar dapat dilakukan oleh semua pihak yang terkait, bukan hanya bagi dosen yang mengajar, tetapi juga bagi mahasiswa yang mengambil mata kuliah. Dalam penyusunan jadwal, ada beberapa variabel yang mempengaruhi yaitu: ruangan yang tersedia, jumlah mata kuliah yang diselenggarakan, waktu yang ada dan ketersediaan dosen yang mengajar. Oleh karena itu tujuan dari penelitian ini adalah merancang suatu sistem yang dapat membuat atau menyusun   jadwal    perkulihaan    secara  teroptimasi. Metode dalam proses pembuatan jadwal perkuliahan secara otomatis pada penelitian ini menggunakan metode algoritma genetika dengan teknik seleksi turnamen. hasil pengujian sistem dapat memberikan kemudahan dan kecepatan kepada user atau Program Studi Teknologi Informasi dalam proses pembuatan atau penyusunan jadwal untuk    perkuliahan,    yaitu hanya diperlukan waktu sekitar 14,7 menit dibandingkan dengan proses manual yang memerlukan waktu sekitar 2 (dua) hari.AbstractFor a college, the university course timetabling is is an activity that’s very important for the implementation of good teaching and learning process. In  teaching  and  learning  process  can be done    by    all    related    parties,   not    only    for Lecturers who teach, but also for students who take the course. In the preparation of the schedule, there are several variables that affect the: the available space, the number of courses held, the time available and the availability of lecturers  who  teach. Therefore, the  purpose  of this research is to design a system that can create or arrange optimization schedule optimally. Methods in the process of making university course   timetabling   automatically   in   this study using genetic algorithm method with tournament selection.
Co-Authors Ahmad Rivaldy Ahmad Shalludin Akhmad Rivaldy Andreyan Rizky Baskara Dany Primanita Kartikasari Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Eka Setya Wijaya Endi Gunawan Ferry Pratama Gusti Nizar Syafi'i Hani Pratiwi Husnul Khatimi Irfan Prasetia Johan Wahyudi Johan Wahyudi Mambang Maulidia Arafah Maya Amalia Muhammad Adetya Ashari Muhammad Alkaff Muhammad Alkaff Muhammad Alkaff Muhammad Andri Firdaus Muhammad Arif Rahman Muhammad Faidhorrahman Muhammad Syauqi Al Fath Muti`a Maulida Novitasari Novitasari Nurul Fathanah Mustamin Puguh Budi Prakoso Puguh Budi Prakoso Puja Darmawan Rakhmadhany Primananda Rama Aria Megantara Ricardus Anggi Pramunendar Rico Silas Dwi Kasanda Subhan Panji Cipta Syarifah Soraya Wenny Puspita