Jurnal Teknologi Informasi dan Terapan (J-TIT)
Jurnal Teknologi Informasi dan Terapan (J-TIT) | ISSN:2354-838X (cetak) | ISSN:2580-2291 (online) adalah media publikasi ilmiah di bidang Teknologi Informasi Terapan yang terbit secara periodik dua kali dalam setahun setiap bulan Januari dan Juli. J-TIT dipublikasikan melalui media cetak maupun elektronik (website). J-TIT pertama kali terbit pada Januari 2014. J-TIT di publikasikan oleh Jurusan Teknologi Informasi dan Terapan Politeknik Negeri Jember. Lingkup J-TIT mencakup bidang teknologi informasi dan terapan.
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<![CDATA[Sistem Informasi Diagnosis Ikterus Neonatorum Menggunakan Logika Fuzzy ]]>
<![CDATA[Jazil Ramadhanty]]>;
<![CDATA[Trismayanti Dwi Puspitasari]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v8i2.187
<![CDATA[Angka Kematian Bayi (AKB) di Indonesia masih tergolong cukup tinggi dibandingkan negara – negara Asia Tenggara. Hal tersebut perlu mendapatkan perhatian karena suatu negara dapat dinilai tingkat kesehatannya dari AKB. Salah satu penyebab AKB yang masih tinggi yaitu penyakit kuning pada bayi (Ikterus Neonatorum). Bayi dapat mengalami ikterus fisiologis (normal) maupun patologis (parah) bergantung dari gejala yang ditimbulkan. Dari kedua jenis ikterus tersebut sulit membedakan antara ikterus normal dan parah tanpa melakukan pemeriksaan lebih lanjut sehingga sebagian besar masyarakat salah dalam melakukan penanganan awal. Berdasarkan permasalahan tersebut, penulis akan membuat sistem informasi untuk diagnosis Ikterus Neonatorum. Dengan sistem tersebut, masyarakat mendapatkan edukasi mengenai ikterus neonatorum dan dapat mengetahui tingkat keparahan yang diderita oleh bayi. Sistem juga memberikan alternatif solusi yang dapat dilakukan saat bayi mengalami ikterus sesuai dengan tingkat keparahan. Penulis menggunakan logika fuzzy dengan metode sugeno untuk membantu melakukan diagnosis. Hasil yang ditampilkan yaitu berupa prosentase tingkat keparahan ikterus neonatorum. Setelah melakukan pengujian blackbox didapatkan hasil bahwa sistem sudah dapat bejalan sesuai dengan skenario yang diharapkan. Untuk pengujian UAT (User Acceptance Testing) didapatkan hasil sebesar 77,86 % yang dapat diartikan bahwa sistem sudah bisa diterima dengan baik oleh pengguna.]]>
<![CDATA[Sistem Peramalan Waktu Masak Fisiologis Benih Padi Menggunakan Double Exponential Smoothing ]]>
<![CDATA[Najmi Nurus Shofi]]>;
<![CDATA[Aji Seto Arifianto]]>;
<![CDATA[Mochamat Bintoro]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.196
<![CDATA[The success of the rice harvest is influenced by various factors, one of which is the selection of quality seeds. Good rice seeds are those obtained during physiological maturity where the moisture content in the seeds is not too low/high. The physiological cooking time of rice seeds can be done by calculating heat accumulation and testing germination. Heat accumulation is the total heat energy from solar radiation received by rice plants, this value can be calculated by recording the maximum, minimum, and humidity temperature data continuously for 90-120 days. Meanwhile, post-harvest laboratory tests were carried out for germination. Temperature and humidity data that were stored and processed quickly of course could be predicted the physiological ripening time of seeds better. Therefore in this article, a web-based forecasting system with the double exponential smoothing method was developed and supported by a graphical display of the data development. This research was conducted on 3 rice varieties namely IR64, Sinta Nur, and Ciherang. The yield that could be conveyed for the IR64 variety reached 85% germination with heat accumulation of 1147 and 105 DAS. The Sinta Nur variety had 92% germination and 86% Ciherang variety with heat accumulation of 1266 at 115 DAS. In this forecasting process, the MAPE value is 0.205 with alpha 0.9 and beta 0.1.]]>
<![CDATA[Klasifikasi Citra Rimpang Menggunakan Support Vector Machine dan K-Nearest Neighbor ]]>
<![CDATA[Saniyatul Mawaddah]]>;
<![CDATA[Mohammad Robihul Mufid]]>;
<![CDATA[Darmawan Aditama]]>;
<![CDATA[Nurul Islamiya]]>;
<![CDATA[Trisyayekti Wulandari]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.250
<![CDATA[Abstract— Rhizome is part of the plant that has many benefits. Some types of rhizomes that are often found are ginger, turmeric and galangal. But in reality, for the three types of rhizomes, there are still many that cannot be recognized. This is because some types of rhizomes do have properties and textures. This research proposes a rhizome recognition system with the classification of SVM (Support Vector Machine) and KNN (K-Neirest Neighbor). SVM searches for the best hyperplane by maximizing the distance between classes. KNN classifies objects based on the learning data that is the most distant from the object. The types of rhizomes used in this research data collection are the three types of rhizomes mentioned above. Meanwhile, the number of images in this study consisted of 150 training images and 30 testing images. The test is carried out by calculating the accuracy value of the classification of testing data in 3 classes, namely Ginger, Kuyit, and Galangal classes using both methods. The rhizome recognition system using the second method of classification is expected to help get good accuracy and can be more easily recognized by the name of the rhizome. Keywords— Rhizome; SVM; KNN Abstrak— Rimpang merupakan bagian dari tanaman yang memiliki banyak manfaat. Beberapa jenis rimpang yang sering dijumpai adalah jahe, kunyit dan lengkuas. Namun pada kenyataannya untuk ketiga jenis rimpang tersebut masih banyak yang tidak bisa dalam mengenalinya. Hal tersebut dikarenakan pada beberapa jenis rimpang memang memiliki kemiripan dalam bentuk dan teksturnya. Dalam penelitian ini diajukan sebuah sistem pengenalan rimpang dengan metode klasifikasi SVM (Support Vector Machine) dan KNN (K-Neirest Neighbor). SVM mencari hyperplane terbaik dengan memaksimalkan jarak antar kelas. KNN melakukan klasifikasi terhadap objek yang berdasarkan dari data pembelajaran yang jaraknya paling dekat dengan objek tersebut Jenis rimpang yang digunakan dalam dataset penelitian ini adalah ketiga jenis rimpang yang disebutkan di atas. Sedangkan untuk jumlah citra dalam penelitian ini terdiri dari 150 citra training dan 30 citra testing. Pengujiannya dilakukan dengan menghitung nilai akurasi dari klasifikasi data testing pada 3 kelas, yaitu kelas Jahe, Kuyit, dan Lengkuas dengan menggunakan kedua metode tersebut. Sistem pengenalan rimpang menggunakan kedua metode klasifikasi ini diharapkan mendapatkan akurasi yang baik dan dapat membantu masyarakat untuk lebih mudah mengenali nama rimpang. Keywords— Rimpang; SVM; KNN]]>
<![CDATA[Pengembangan Multimedia Interaktif Pengenalan Hewan Untuk Anak TK Berbasis Augmented Reality ]]>
<![CDATA[Darmawan Aditama]]>;
<![CDATA[Fardani Annisa Damastuti]]>;
<![CDATA[Mohammad Robihul Mufid]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.251
<![CDATA[Abstract—The development of Information and Communication Technology (ICT) has changed the new face of education. The implementation of Information and Communication Technology (ICT) in educational institutions has become a must in educational institutions, not to close our eyes that schools are naturally responsive to technological developments. The use of interactive multimedia as a support for the teaching and learning process is considered to be able to increase flexibility in teaching and learning activities, especially for Kindergarten (TK) students. Children at this age should be introduced to the benefits of technology. So that in the future it is not wrong to use technology. An interactive multimedia application that makes it easy for students to learn anywhere and anytime using a mobile device. Learning abilities are focused on making animal recognition applications for kindergarten (TK) students. Because knowledge related to animals must be introduced to students from an early age. Interactive multimedia applications are made by utilizing mobile android and Augmented Reality which are packaged in the form of games (games).]]>
<![CDATA[Perancangan User Interface Sistem Informasi Alumni Menggunakan Metode Webuse Dan User Centered Design ]]>
<![CDATA[Agung Nugroho Pramudhita]]>;
<![CDATA[Putra Prima Arhandi]]>;
<![CDATA[Ferina Bayu Sukmadewi]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.266
<![CDATA[Alumni Information System is a system that facilitates data collection process and obtains information about alumni. Based on results of interviews with several alumni who just graduated in 2020 at State Polytechnic of Malang, results were obtained, they had problems accessing website, such as updating data, searching for alumni data, and registration for graduation ceremony. Based on results of online survey to several alumni of State Polytechnic of Malang, problems were founded in content organizing, ease of reading content, navigating links, UI/UX, and website effectiveness. To make website with interface is user friendly, design improvements are needed to provide recommendations for problems that arise. User Centered Design method was chosen to design user interface according to user experience and webuse was chosen because it focuses on evaluating usability of website and helping web designers and developers based on responses given by visitors. Results Both of evaluation from UI design in content organizing & readability category and navigation & links category are 0.85 with an “Excellent” usability level. In user interface design category result is 0.86 with an “Excellent” usability level, and performance & effectiveness category result is 0.81 with an “Excellent” usability level. So that entire webuse category has increased.]]>
<![CDATA[Model Perilaku Keamanan Siber Pada Pengguna Sosial Media Pada Masa Pandemi Covid-19 ]]>
<![CDATA[Ameilia Nur Aini]]>;
<![CDATA[Edy Wahyudi]]>;
<![CDATA[Imannurdin Abdillah]]>;
<![CDATA[Ery Setiyawan Jullev Atmadji]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.272
<![CDATA[The use of social media is very developed during the COVID-19 pandemic, this increases the risk of data leakage, most of which are caused by internal parties from social media users themselves. For that we need an instrument that can measure the behavior of users who are at risk of social media that is used to minimize the potential for such leaks. This research consists of three stages including a literature review on aspects that affect the security of the social media system. The second stage is the preparation of a questionnaire design regarding the risk of cyber attacks on social media. Then the third stage is testing the reliability and validity of the questionnaire. Based on the research, there are 4 aspects that affect the security of social media, namely the use of electronic devices, access to social media, internet behavior, and unusual events in health facilities. The developed questionnaire consists of 27 question items which are divided into these 4 aspects. In the overall validity test the items are valid (r count > r table). While the reliability test of the questionnaire was reliable with Cronbach's Alpha value of 0.867. The developed questionnaire design can be applied to assess the risk of cyber attacks on social media among workers. Further research is needed to implement the questionnaire design]]>
<![CDATA[Penerapan Metode AHP dan SAW untuk Rekomendasi Keluarga Kurang Mampu Penerima Bantuan ]]>
<![CDATA[Laurentinus Laurentinus]]>;
<![CDATA[Okkita Rizan]]>;
<![CDATA[Hamidah .]]>;
<![CDATA[Sarwindah .]]>;
<![CDATA[Kiswanto .]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.275
<![CDATA[Dalam meningkatkan pertumbuhan ekonomi masyarakat kurang mampu di tengah pandemi covid 19, pemerintah dituntut untuk memberikan perlindungan kepada masyarakat kurang mampu baik dari segi infrastruktur, prakerja, maupun pendanaan. Namun sayangnya belum adanya distribusi yang baik oleh aparat desa dalam menentukan masyarakat yang paling layak menerima bantuan jika memenuhi kriteria yang ditetapkan pemerintah. Penelitian ini mengusulkan decision support system dalam menilai prioritas penerima bantuan menggunakan metode simple additive weighting (SAW) berdasarkan kriteria seperti : Status Perkawinan, Cacat, Yatim Piatu, Gaji, Lansia, Tanggungan. Metode SAW memberikan penilaian yang lebih tepat karena dihitung berdasarkan nilai kriteria dan bobot preferensi yang diperoleh dari wawancara serta observasi di Desa Silip. Metode SAW dapat merekomendasikan alternatif paling berhak menerima bantuan dari sejumlah alternatif yang ada. Hasil dari pengujian penelitian ini menggunakan pengujian user acceptance testing mendapatkan tingkat penerimaan sebesar 84.89%]]>
<![CDATA[Deteksi Pembuluh Darah pada Citra Fundus Retina Menggunakan Gabungan Metode Segementasi Pembuluh Darah Lebar dan Tipis ]]>
<![CDATA[Khafidurrohman Agustianto]]>;
<![CDATA[Shabrina Choirunnisa]]>;
<![CDATA[Nuzula Afianah]]>;
<![CDATA[Choirul Huda]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.276
<![CDATA[Organs in the human body provide a lot of knowledge about human body health. One of them is the organ in the human eye, more specifically the retina.Furthermoreeven some accute diseases can be detected through the retina image. One of the diseases that can be detected through retinal images is diabetic retinopathy. This disease can be identified through segmentation to find abnormalities in the retinal blood vessels. These abnormalities include enlarged blood vessels, abnormal branching, and so on. Manual detection of blood vessels on the retina is less accurate, so a comperhensive program is required in order to segment the blood vessels in eye fundus images, more accurately. In this research, some method and algorithms are approached by combining the segmentation process for wide vessels and the segmentation process for thin vessels. There are three stages in this research. First, the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm and 2D Gabor Wavelet are applied as the preprocessing stage. Then, active contour and region growing methods are required as the processing to segment the thin and wide vessels in fundus retina image. And the last stage is postprocessing using the logical operator method or. The trial in this research uses color eye fundus images on the DRIVE dataset consisting of 20 retinal photos. By using this dataset, the average accuracy is 94.32%, sensitivity is 77.09% and specificity is 96.04% in 20 trials.]]>
<![CDATA[Implementasi Model CNN Dan Tensorflow Dalam Pendeteksian Jenis Daging Hewan Ternak ]]>
<![CDATA[Zulfa Febriana Dewi Mellinia]]>;
<![CDATA[Eri Zuliarso]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.278
<![CDATA[Abstrak—Daging banyak dikonsumsi oleh masyarakat Indonesia dan banyak dijual di supermarket maupun pasar tradisional. Namun demikian , ada sebagian masyarakat yang kurang memiliki pengetahuan dalam memilih daging yang layak konsumsi dengan tepat. Penelitian ini menggunakan model Convolutional Neural Network (CNN) dan tensorflow untuk membangun sistem yang dapat mendeksi jenis daging yang layak konsumsi. Berdasarkan data yang didapat oleh peneliti data tersebut digunakan untuk pengolahan dataset yang nantinya akan dikelompokkan. Dataset tersebut terdapat 7 kategori dengan pengklasifikasian menggunakan model CNN. Model CNN cocok diterapkan karena model ini dapat memproses input gambar, yang menghasilkan sistem deteksi jenis daging yang layak dikonsumsi dengan akurasi 80,95%. Dengan sistem yang compatible dengan perangkat mobile, dengan CNN dapat memudahkan masyarakat memilih daging dengan tepat.]]>
<![CDATA[Pemanfaatan Restful Api Pada Mobile based test Untuk Sertifikasi Karyawan ]]>
<![CDATA[Anggraini Kusumaningrum]]>;
<![CDATA[Asih Pujiastuti]]>;
<![CDATA[Satya Wira Wicaksana]]>;
<![CDATA[Yuliani Indrianingsih]]>;
<![CDATA[Mardiana Irawaty]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 9 No 1 (2022) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
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DOI: 10.25047/jtit.v9i1.279
<![CDATA[A test is something that is used to test the quality of intelligence, ability, learning outcomes and so on. The test is always associated with an assessment or evaluation of a person to determine the person's mastery of the material. The rapid development of the digital world makes it easier for people to complete their work, the use of mobile tests is one of the technologies used by using the Application Programming Interface (API). Restful API is one of the architectures in the API which has 4 important components, namely URL Design, HTTP Verbs, HTTP Response Code, and Response Format. Rest client will access data to the Rest server, each data is distinguished based on Global ID or Universal Resource Identifier (URI) in the form of formal text XML or JSON. From the test results using WhiteBox on the admin side, there are 4 paths for 3 days with 100% success. While on the client side there are 8 paths for 3 days with 100% success.]]>
