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JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Published by Universitas Lambung Mangkurat
ISSN : 25275399     EISSN : 25282514     DOI : http://dx.doi.org/10.20527
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) is intended as a media for scientific studies on the results of research, thinking and analytical-critical studies regarding research in Systems Engineering, Informatics / Information Technology, Information Management and Information Systems. As part of the spirit of disseminating knowledge from the results of research and thought for service to the wider community and as a reference source for academics in the field of Technology and Information.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 1 (2016)" : 5 Documents clear
PENERAPAN ALGORITMA EVOLVING NEURAL NETWORK UNTUK PREDIKSI CURAH HUJAN Subhan Panji Cipta
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 (299.513 KB) | DOI: 10.20527/jtiulm.v1i1.2

Abstract

Weather and climate information have contributed as one consideration for decision makers. This arises because the information the weather / climate has economic value in a variety of activities , ranging from agriculture to flood control . From the data obtained implied that the current rainfall prediction not so accurate . Forecasts are often given to the public on a regular basis is the weather forecast , not the amount of rainfall. This study uses an algorithm Evolving Neural Network (ENN) as an approach to predict the rainfall , the data processing and calculations will use MatLab 2009b . The parameters used in this study is time , rainfall , humidity and temperature. The results also compared with the test results and predictions BPNN BMKG. From the results of research conducted from early stage to test and measurement , the application of this ENN has a rainfall prediction with accuracy better than the BPNN and prediction algorithms BMKG.
RANCANG BANGUN SISTEM INFORMASI PENJUALAN MEUBEL (STUDI KASUS: CV. FAJAR INDAH AMUNTAI) Windarsyah; Muhammad Alkaff
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 (890.07 KB) | DOI: 10.20527/jtiulm.v1i1.3

Abstract

One of the media information that is widely used by some companies today is desktop-based information systems where an application is expected to help facilitate in resolving a problem. Furniture Fajar Indah Amuntai in managing goods data, pricing and reporting the results of the transaction is still using paper media or notebook in storing such data, however, when there are changes in prices of goods then the data is written back in a new book, so the time and cost of wasted writing and buying new books. To identify the needs of the system in this study using data flow trending analysis. From the information obtained by the analysis conducted inputs, outputs and system processes that are expected, which is a facility operator to manipulate data, manipulate data items, records every sales transaction, it can display and print the report. With the analysis results can be obtained interface design is more user friendly and easy to use.
PREDIKSI KELULUSAN MAHASISWA DENGAN JARINGAN SYARAF TIRUAN Rudy Ansari
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 (596.389 KB) | DOI: 10.20527/jtiulm.v1i1.4

Abstract

Graduation became a benchmark in the policy making college management. Can estimate the graduation students annually is needed to be known by the university. Moreover, this paper attempts to apply neural network algorithms in predicting graduation, the selected method to be used is the method of propagation. This method is widely used in the researchers predict a problem. The sample data in the application of this algorithm is data the students began class of 2010 up to 2013. With the third generation output is passed late, fast and timely. From the results of the learning algorithm used obtained good accuracy results with the architecture of the pattern formed is 12-9-3.
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.

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