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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
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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Rancang Bangun Aplikasi E-Commerce Produk Desa Binaan Fakultas Teknik ULM Kecamatan Cempaka Banjarbaru Yuslena Sari; Husnul Khatimi; Muhammad Alkaff; Andreyan Rizky Baskara; Muti’a Maulida; Halimah Halimah; Nurul Qamaria
Buletin Profesi Insinyur Vol 2, No 2 (2019): Buletin Profesi Insinyur (Juli-Desember)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/bpi.v2i2.45

Abstract

Desa Cempaka yang terletak di Banjarbaru Kalimantan Selatan merupakan desa pengrajin sasirangan dan produk-produk kerajinan lainnya. Banyak masyarakat yang berdatangan kesana untuk membeli kain sasirangan maupun produk buatan tangan lainnya karena dikenal dengan kualitasnya yang bagus. Tetapi dalam pengelolaan jual beli di Desa Cempaka, pembeli harus datang langsung ke tempat untuk melihat barang dan melakukan proses transaksi jual beli. Hal ini akan memakan waktu untuk pembeli dan bisa menyebabkan kurangnya minat pembeli untuk kerajinan di Desa Cempaka Banjarbaru. Dengan berkembangnya teknologi informasi saat ini banyak aplikasi yang membuat Online Shop untuk lebih mudah melakukan jual – beli dan menghemat waktu tanpa datang langsung ke toko yang kita inginkan. Perkembangan bisnis menggunakan Online Shop pun semakin meningkat seiring dengan banyaknya masyarakat yang menggunakan internet. Untuk itu kami membuat aplikasi Online Shop untuk memfasilitasi kerajinan yang ada di Desa Cempaka Banjarbaru. Penelitian ini mengaplikasikan metode waterfall dalam pengembangan sistemnya. Metode waterfall dipilih karena system ini akan berkelanjutan seiring dengan perkembangan bisnis di Desa Cempaka Banjarbaru. Tujuan dari penelitian adalah untuk mempermudah masyarakat yang ingin membeli produk kerajinan di desa cempaka sehingga dapat meningkatkan penjualan produk kerajinan dari Desa Cempaka.Kata kunci : online shop, waterfall, bisnis, Cempaka
Rancang Bangun Sistem Informasi Pelatihan dan Penelitian pada Badan Kependudukan Keluarga Berencana Nasional (BKKBN) Kalimantan Selatan Yuslena Sari
Buletin Profesi Insinyur Vol 3, No 2 (2020): Buletin Profesi Insinyur (Juli-Desember)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/bpi.v3i2.66

Abstract

Deputi Latbang Badan Kependudukan Keluarga Berencana Nasional (BKKBN) Kalimantan Selatan setiap tahunnya melaksanankan banyak pelatihan dan program penelitian dengan total biaya yang besar. Secara manual, administrasi kegiatan-kegiatan tersebut sangat sulit. Strategi mempermudah proses tersebut adalah dengan membuat sistem informasi berbentuk website. Perancangan sistem informasi pelatihan dan penelitian pada deputi Latbang BKKBN Kalimantan Selatan menggunakan metode perancangan berbasis Unified Modelling Language (UML) yaitu diagram usecase. Tujuannyauntuk manajemen data dan menghemat biaya operasional. Proses testing sistem informasi pelatihan dan penelitian BKKBNN Kalimantan Selatan menggunakan black-box dan usability. Hasil dari Pengujian sistem menggunakan black-box berhasil 100% dan untuk hasil usability mendapat nilai 3,905 dari rentang nilai 1 (sangat sulit) – 5 (sangat mudah). Sistem informasi ini telah diimplementasikan dan dapat mengatasi kendala proses manajemen data, efisiensi waktu dan menghemat biaya operasional proses pelatihan dan penelitian pada Deputi Latbang BKKBN Kalimantan Selatan. Kata kunci: BKKBN, sistem informasi, UML, black-box, usability
Penerapan Metode K-Means Berbasis Jarak untuk Deteksi Kendaraan Bergerak Yuslena Sari; Andreyan Rizky Baskara; Puguh Budi Prakoso
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 4: Agustus 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022945768

Abstract

Deteksi kendaraan bergerak adalah salah satu elemen penting dalam aplikasi Intelligent Transport System (ITS). Deteksi kendaraan bergerak juga merupakan bagian dari pendeteksian benda bergerak. Metode K-Means berhasil diterapkan pada piksel cluster yang tidak diawasi untuk mendeteksi objek bergerak. Secara umum, K-Means adalah algoritma heuristik yang mempartisi kumpulan data menjadi K cluster dengan meminimalkan jumlah kuadrat jarak di setiap cluster. Dalam makalah ini, algoritma K-Means menerapkan jarak Euclidean, jarak Manhattan, jarak Canberra, jarak Chebyshev dan jarak Braycurtis. Penelitian ini bertujuan untuk membandingkan dan mengevaluasi implementasi jarak tersebut pada algoritma clustering K-Means. Perbandingan dilakukan dengan basis K-Means yang dinilai dengan berbagai parameter evaluasi yaitu MSE, PSNR, SSIM dan PCQI. Hasilnya menunjukkan bahwa jarak Manhattan memberikan nilai MSE = 1.328 , PSNR = 21.14, SSIM = 0.83 dan PCQI = 0.79 terbaik dibandingkan dengan jarak lainnya. Sedangkan untuk waktu pemrosesan data memperlihatkan bahwa jarak Braycurtis memiliki keunggulan lebih yaitu 0.3 detik. AbstractDetection moving vehicles is one of important elements in the applications of Intelligent Transport System (ITS). Detection moving vehicles is also part of the detection of moving objects. K-Means method has been successfully applied to unsupervised cluster pixels for the detection of moving objects. In general, K-Means is a heuristic algorithm that partitioned the data set into K clusters by minimizing the number of squared distances in each cluster. In this paper, the K-Means algorithm applies Euclidean distance, Manhattan distance, Canberra distance, Chebyshev distance and Braycurtis distance. The aim of this study is to compare and evaluate the implementation of these distances in the K-Means clustering algorithm. The comparison is done with the basis of K-Means assessed with various evaluation paramaters, namely MSE, PSNR, SSIM and PCQI. The results exhibit that the Manhattan distance delivers the best MSE = 1.328 , PSNR = 21.14, SSIM = 0.83 and PCQI = 0.79 values compared to other distances. Whereas for data processing time exposes that the Braycurtis distance has more advantages 
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.
Perbandingan Metode Pembobotan Tf-Rf Dan Tf-Idf Dikombinasikan Dengan Weighted Tree Similarity Untuk Sistem Rekomendasi Buku Yuslena Sari; Andreyan RIzky Baskara; Puguh Budi Prakoso; Noorhanida Royani
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022935709

Abstract

Unit Pusat Terpadu Perpustakaan merupakan perpustakaan pusat yang ada di Universitas Lambung Mangkurat. Perpustakaan ini mempunyai sistem pencarian buku namun sistem tersebut belum adanya fitur rekomendasi buku sehingga anggota menjadi kesulitan dalam melakukan pencarian buku yang sesuai dengan keinginan anggota. Oleh karena itu, dengan adanya rekomendasi buku atau saran buku yang lain dapat menjadi alternatif untuk membantu anggota dalam melakukan pencarian buku yang sesuai. Dalam penelitian ini menggunakan perbandingan pembobotan kata TF-IDF dan TF-RF dengan weighted tree similarity sebagai pengukur kemiripan diantara beberapa data dengan parameter tree yang sudah ditentukan dan dilakukan perbandingan perhitungan dengan menghitung tf-idf dengan tf-rf menggunakan perhitungan excel mendapatkan nilai yang berbeda antara tf-idf dengan tf-rf, pembobotan tf-idf dapat mengukur kemiripan antara dokumen dan kata kunci buku yang paling mirip dengan buku yang dianggap paling relevan. Sehingga anggota memasukan kata kunci kemudian akan menemukan kemiripan buku dari kata kunci yang dimasukan sebelumnya namun untuk pembobotan tf-rf memberikan kata kunci dari setiap kategori. Hasil perbandingan yang di dapat yaitu 96% untuk tf-idf dan 98% untuk tf-rf. Sistem ini menggunakan bahasa pemrograman python dengan web framework django. AbstractThe Central Integrated Library Unit is the central library at Lambung Mangkurat University. This library has a book search system but the system does not have a book recommendation feature so that members find it difficult to search for books that match the wishes of members. Therefore, the existence of book recommendations or other book suggestions can be an alternative to assist members in searching for suiTabel books. In this study using a comparison of the weighting of the words TF-IDF and TF-RF with weighted tree similarity as a measure of the similarity between several data and a comparison of calculations is carried out by calculating tf-idf with tf-rf using excel calculations to get different values between tf-idf and tf -rf, tf-idf weighting can measure the similarity between documents and keywords of the book that is most similar to the book that is considered the most relevant. So that members enter keywords and then find the similarity of books from the keywords entered previously but for weighting tf-rf provides keywords from each category. The comparison results obtained are 76% for tf-idf and 80% for tf-rf. This system uses the python programming language with the django web framework.
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%.
Co-Authors 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 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 Musyfia Adla Mutia Maulida Muti`a Maulida Nanik Suciati Noor Razikin Noorhanida Royani Novitasari Novitasari Novitasari Novitasari Nurul Fathanah Mustamin Nurul Qamaria Prakoso, Puguh Budi Pratiwi, Hani Puguh Budi Prakoso Puguh Budi Prakoso Puja Darmawan Purwono, Purwono Rahman, Muhammad Arif Rakhmadhany Primananda Rama Aria Megantara Ricardus A P, Ricardus A Ricardus Anggi Pramunendar Rico Silas Dwi Kasanda Rudy Ansari Rusiana, Novi Septyan Eka Prastya Subhan Panji Cipta Syarifah Soraya Wenny Puspita Wijaya, Eka Setya