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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Techno: Jurnal Penelitian Jurnal Teknologi Informasi dan Ilmu Komputer Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Journal of Information Systems Engineering and Business Intelligence Info-Teknik KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jukung (Jurnal Teknik Lingkungan) JTERA (Jurnal Teknologi Rekayasa) Jurnal Komtika (Komputasi dan Informatika) ILKOM Jurnal Ilmiah Astonjadro Jurnal Ilmu Komputer dan Bisnis 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) Journal of Advanced Health Informatics Research Jurnal Jalan Jembatan INSTALL: Information System and Technology Journal Jurnal Komtika (Komputasi dan Informatika)
Yuslena Sari, Yuslena
Dosen Program Studi Teknologi Informasi Fakultas Teknik Universitas Lambung Mangkurat, Indonesia
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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MIXTURE FEATURE EXTRACTION BASED ON LOCAL BINARY PATTERN AND GREY-LEVEL CO-OCCURRENCE MATRIX TECHNIQUES FOR MOUTH EXPRESSION RECOGNITION Ricardus Anggi Pramunendar; Dwi Puji Prabowo; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 7 No. 2 (2022)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v7i2.145

Abstract

Some academics struggle to recognize facial emotions based on pattern recognition. In general, this recognition utilizes all facial features. However, this study was limited to identifying facial emotions in a single facial region. In this study, lips, one of the facial features that can reveal a person's expression, are utilized. Using a combination of local binary pattern feature extraction (LBP) and grey level co-occurrence matrix (GLCM) methods and a multiclass support vector machine classification approach for feature extraction in facial images. The concept begins with image segmentation to create an image of a mouth. Experiments were also conducted for various tests, and the outcomes of these experiments revealed a recognition performance of up to 95%. This result was obtained through experiments in which 10% to 40% of the data were evaluated. These findings are beneficial and can be applied to expression recognition in online learning media to monitor the audience's condition directly.
DIABETES MELLITUS ATTRIBUTE CLASSIFICATION USING THE NAIVE BAYES ALGORITHM BASED ON FORWARD SELECTION Dwi Puji Prabowo; Rama Aria Megantara; Ricardus Anggi Pramunendar; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 7 No. 2 (2022)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v7i2.146

Abstract

Diabetes Mellitus is a chronic condition that frequently results in death. Almost every nation has experienced and contributed to this rise in mortality. Consequently, several researchers are motivated to determine this disease's source and prevent the increase in mortality rates. The research was conducted in the field of informatics in partnership with health professionals to determine the causes of this condition. Many informatics researchers employ machine learning techniques to aid in analyzing existing data. This study suggests feature selection based on forward selection and the naive Bayes classification approach to determine this disease's primary aetiology. The results demonstrate that our proposed strategy can increase the classification accuracy of patients. The performance outcomes improved by 169%. According to this theory, it is also known that the primary cause of this disease is its dependence on body mass index and age. Therefore, additional research must explore these two variables' impact on various other disorders.
Penerapan Logika Fuzzy Tsukamoto Untuk Pemantauan Kestabilan Suhu Menggunakan Sensor DS18B2 Pada Styrofoam Box Pengemasan Ikan Eka Setya Wijaya; Yuslena Sari; Andreyan Rizky Baskara; Ahmad Rivaldy
JUSTE (Journal of Science and Technology) Vol. 2 No. 1 (2021): JUSTE
Publisher : LLDIKTI WIlayah XII Ambon

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1826.596 KB) | DOI: 10.51135/justevol2issue1page59-77

Abstract

Menjaga kestabilan suhu dalam distribusi ikan segar merupakan bagian penting dari rantai pasokan industri perikanan. Penelitian ini bertujuan untuk menganalisis penerapan Logika Fuzzy Tsukamo dalam menjaga kestabilan suhu pada proses pengemasan ikan sampai pada penyaluran dan distribusi. Pembahasan difokuskan pada penggunaan sensor DS18B2 untuk pembacaan perubahan suhu yang terjadi dalam styrofoam box penyimpanan ikan secara tradisional di pelabuhan PPI (Pelelangan Pembongkaran Ikan) Batulicin Simpang Empat Kalimantan Selatan. Penelitian ini menggunakan teknik observasi lapangan dan uji akurasi data yang dihasilkan dari sensor. Pada proses pengemasan dan distribusi ikan secara tradisional umumnya menggunakan es balok yang hanya dapat mempertahankan suhu rendah dalam waktu tidak terlalu lama. Suhu ideal dari dalam styrofoam box tempat pengemasan ikan adalah 10˚C yang diukur dengan menggunakan alat pengukur suhu / termometer ruangan biasa. Pemantauan suhu pada saat perjalanan sangat tidak efektif, karena dilakukan dengan membongkar muatan dan mengecek box satu persatu secara manual. Dengan menggunakan sensor suhu DS18B2 dan pen-erapan logika fuzzy Tsukamoto dapat dibuat sebuah sarana sederhana yang memanfaatkan lampu LED sebagai notifikasi terhadap terjadinya perubahan suhu di dalam box pengemasan ikan secara real time, sehingga kestabilan suhu dapat dija-ga dan proses distribusi atau pengantaran ikan menjadi lebih efektif.
DESIGN OF AN INVENTORY INFORMATION SYSTEM FOR LABORATORY SUPPLIES Noor Razikin; Yuslena Sari; Erika Maulidiya
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 8 No. 1 (2023)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v8i1.159

Abstract

Data is inaccurate because it does not have a relevant data repository, data can be lost or damaged, inefficient data search and technicians cannot know for sure the amount of stock available. Based on some of the research above, the inventory information system for Laboratory goods in the Information Technology Study Program will be designed and built based on a website using the Laravel framework. The system development method used is the Incremental model. Incremental models are the result of a combination of elements from the waterfall model that are applied repeatedly, or it can be called a combination of the waterfall model and the Prototype Model. During testing, many errors were found in the system. Testing was carried out 4 times with a total of 164 test cases. In the first test, 98 bugs were found which were then reported to the programmer to be fixed. In the second test, 40 errors were found, in the third test, 19 errors were found, and in the last test conducted by the examiner, 0 bugs were found. The design of the Laboratory Goods Inventory Information System (SIMBA) begins with analyzing the weaknesses of the old system using the PIECES method. Then proceed with conducting a system requirements analysis and system feasibility analysis. After the analysis phase, it is continued with the design stage which begins with the UML design method.
Internet of Things untuk Sistem Pemantauan Kualitas Air pada Kolam Ikan Lele pada Pembudidaya TDR Sultan Adam Banjarmasin Yuslena Sari; Eka Setya Wijaya; Andreyan Rizky Baskara; Muhammad Syauqi Al Fath; Muhammad Andri Firdaus
Jurnal Pengabdian ILUNG (Inovasi Lahan Basah Unggul) Vol 3, No 1 (2023)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ilung.v3i1.9772

Abstract

TDR Catfish Farmer Sultan Adam Banjarmasin is a home industry (IRT) engaged in the business of catfish farming located on Jl. Sultan Adam No.17 RT.22, Surgi Mufti, North Banjarmasin. In the management of catfish farming, water quality is an important factor in the success of cultivation where poor water quality can cause fish to be more susceptible to disease. Apart from these needs, the TDR of Sultan Adam Catfish Farmers actually has problems in the process of monitoring pond water quality conditions which are currently carried out manually and periodically by breeders. This process is considered ineffective because it is difficult to determine water quality from the physical condition of the water which changes rapidly due to weather or fish feed residue. The solution offered to solve this problem is to develop a tool that can monitor temperature conditions and the acidity of catfish pond water automatically and in real time. This innovation was developed by utilizing the Internet of Things (IoT) through the use of the DS18B20 temperature sensor and SS15 pH sensor on the ESP32 WROOM-32D microcontroller. The results of system testing from fuzzy logic calculations at the output of the microcontroller and Matlab and the suitability of expert information in determining pool water quality obtained an average error value of 0.46%. Based on these results, it can be concluded that the IoT-based water quality monitoring system in determining water quality is suitable for direct use.
PENERAPAN ACTIVE CONTOUR MODEL PADA PENGOLAHAN CITRA UNTUK DETEKSI KERUSAKAN JALAN Yuslena Sari; Andreyan Rizky Baskara; Puguh Budi Prakoso; Muhammad Arif Rahman
Jurnal Jalan-Jembatan Vol 38 No 2 (2021)
Publisher : Direktorat Bina Teknik Jalan dan Jembatan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Road damage is a serious problem because it often occurs everywhere. Damage to the road surface, such as potholes, often disrupts land transportation, and can even cause accidents. With the automatic detection of road damage types, it can simplify the process of classifying the types of road damage by using images from the results of the classification system which can be used as supporting information in calculating road repairs. In this study, to identify road damage types by images, the active contour model segmentation technique is used based on the level set and then classified by the support vector machine method. Based on the test results, using 58 data sets with 12 types of road damage, the accuracy of this method is 87.93%.
Pemanfaatan Konfigurasi Layer Pada Metode CNN Untuk Peningkatan Kinerja Klasifikasi Penyakit Daun Tomat Sari, Yuslena; Firmansyah, Muhammad Ilham; Pramunendar, Ricardus Anggi
Jurnal Teknologi dan Sistem Komputer [IN PRESS] Volume 10, Issue 3, Year 2022 (July 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.13953

Abstract

Tomat adalah salah satu komoditas hortikultura dengan nilai ekonomi yang tinggi, tantang yang dihadapi oleh petani salah satunya dalah kerentanan penyakit tomat terhadap penyakit. Identifikasi secara visual pada daun sulit diuraikan dengan sekali pandang, sehingga menyebabkan asumsi yang tidak akurat tentang penyakit tersebut. Akibatnya, mekanisme pencegahan yang dilakukan petani menjadi tidak efektif dan berdampak merugikan. Penelitian ini mengusulkan identifikasi penyakit tomat secara automatis menggunakan metode Convolution Neural Network. Dalam makalah ini kami melakukan evaluasi pada metode CNN dengan arsitektur Alexnet dengan konfigurasi layer untuk mencari hasil kinerja terbaik dari penggunaan parameter tersebut pada architektur Alexnet. Pada penelitian ini juga melakukan analisis yang diperoleh dari hubungan antara parameter yang digunakan terhadap kinerja akurasi, dan analisis terhadap dampak penggunaan parameter dengan jumlah dataset daun tomat dari dataset PlantVillage.
Prediksi Harga Emas Menggunakan Metode Neural Network Backropagation Algoritma Conjugate Gradient Sari, yuslena
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
Challenges and Opportunities: Integration of Data Science in Cancer Research Through A Literature Review Approach Purwono, Purwono; Ariefah Khairina Islahati; Yuslena Sari; Dewi Astria Faroek; Muhammad Baballe Ahmad
Journal of Advanced Health Informatics Research Vol. 1 No. 3 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jahir.v1i3.167

Abstract

Several research articles in this journal relate to various aspects of cancer, such as treatment, patient outcomes, caregiver responsibilities, and the use of AI and liquid biopsy in cancer research. Covers a wide range of topics, including valuable insights into the latest developments in cancer research as well as potential future opportunities and issues. Several articles discuss the impact of non-coding RNA on gastric cancer, machine learning decision support systems for cancer survival factors, economic impact of cancer mortality, nausea in children diagnosed with cancer, protein-RNA variations in cancer clinical analysis, integration and proteomic data analysis in the context of cancer genomics, personalized cancer medicine, mass spectrometry-based clinical proteomics, cancer proteogenomics, subtype-based This journal provides an in-depth overview of various aspects of current cancer research and future research prospects
EFFECTIVENESS OF APPLYING BIM BASED COST ESTIMATION IN DEVELOPMENT OF THE SYAMSUDIN NOOR AIRPORT PROJECT BANJARMASIN Khatimi, Husnul; Fardian, Muhammad Reza; Sari, Yuslena
ASTONJADRO Vol. 10 No. 1 (2021): ASTONJADRO
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/astonjadro.v10i1.4200

Abstract

Development of The Syamsudin Noor Airport Project in Banjarmasin is one of the largest projects in Banjarmasin, South Kalimantan. This project applied BIM-based cost estimation on a steel roof structure. However, the cost estimation for this steel roof structure is applied conventionally. The BIM-based cost estimation could have been applied in collaborating a building information becomes unity in one model. This research will raise the issue of applying BIM-based cost estimation at The Syamsudin Noor Airport Project to find out the effectiveness calculation of cost estimation conventionally and BIM-based cost estimation. The report result by 3D modeling of Tekla is quantity take-offs using as a data for processing the cost analysis conventionally. Whereas the 3D model made by Tekla will be exported to Revit through the interoperability of IFC or application of extention of Tekla warehouse that is "Export to Revit Geometry” for the processing the BIM-based cost estimation analysis. The unit price for the cost calculation is acquired by list price (AHSP or subcontractor value). The result of these both cost calculation, there are large enough difference in cost of these both calculations. Difference of conventional calculations and BIM-based cost estimation using Revit worth Rp 3,690,741,474 - Rp 5,047,206,780 with a percentage of 14% - 20%. Cause of these large enough differences in cost due to the model exported is only 90% succeeded. It happened due to difference thing in the mapping of object profile and difference in shape BREP geometry conditions.
Co-Authors Adla, Musyfia Ahmad Rivaldy Ahmad Shalludin Akhmad Rivaldy Andreyan Rizky Baskara Ariefah Khairina Islahati ARIF RAHMAN, MUHAMMAD Bambang Lareno, Bambang Bayu Nugraha Chastine Fatichah Dany Primanita Kartikasari Darmawan, Puja Dewi Astria Faroek Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Endi Gunawan Fardian, Muhammad Reza Ferry Pratama Finki Dona Marleny Firmansyah, Muhammad Ilham Gusti Nizar Syafi'i Halimah Halimah Hani Pratiwi Husnul Khatimi Irfan Prasetia Johan Wahyudi Johan Wahyudi Mambang Maulidia Arafah Maulidiya, Erika Maya Amalia Meila Izzana, Meila Muhammad Adetya Ashari Muhammad Alkaff Muhammad Andri Firdaus Muhammad Arif Rahman Muhammad Baballe Ahmad Muhammad Faidhorrahman Muhammad Syauqi Al Fath Mutia Maulida Muti`a Maulida Nanik Suciati Noor Razikin Novitasari Novitasari Novitasari Novitasari Nurul Fathanah Mustamin Nurul Qamaria Prakoso, Puguh Budi Prastya, Septyan Eka Pratiwi, Hani Puguh Budi Prakoso Puguh Budi Prakoso Purwono, Purwono Rahman, Muhammad Arif Rakhmadhany Primananda, Rakhmadhany Rama Aria Megantara Ricardus A P, Ricardus A Ricardus Anggi Pramunendar Rico Silas Dwi Kasanda Royani, Noorhanida Rudy Ansari Rusiana, Novi Subhan Panji Cipta Syarifah Soraya Wenny Puspita Wijaya, Eka Setya