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INDONESIA
Syntax Jurnal Informatika
Published by Universitas Singaperbangsa Karawang
ISSN : 2302156X     EISSN : 25415344     DOI : -
Core Subject : Science,
Computer Science & IT
Syntax Jurnal Informatika berfokus pada Rekayasa Perangkat Lunak, Teknik Kompilasi, Perancangan Basis Data, Data Mining, Teknologi Web Services, Business Intelligent, Kecerdasan Buatan, Logika Fuzzy, Computer Vision, Embedded System, Robotika, Sistem Pakar, Machine Learning, E-Commerce, Digital dan Network Security, Neuro Fuzzy, E-Goverment, Bioinformatika, Sistem Informasi Geografis, Applikasi Mobile, Teknologi Games, Jaringan Komputer, Cloud Computing
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 11 No 02 (2022): Oktober 2022" : 6 Documents clear
Penerapan Deep Learning Pada Kamera Pengawas Jalan Raya Dalam Mendeteksi Kecelakaan Heru Triana; Ultach Enri
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.6356

Abstract

Kecelakaan dalam lalu lintas adalah suatu perkara yang tidak bisa dianggap sepele. Kecelakaan dapat menimbulkan banyak korban jiwa dan kerugian yang besar. Bahkan Indonesia menjadi penyumbang angka kematian terbesar di ASEAN. Untuk mencegah korban jiwa saat kecelakaan terjadi, dapat dicegah dengan memberikan pertolongan pertama dan menghubungi pihak rumah sakit terdekat untuk segera mendapatkan perawatan medis. Untuk itu, dibutuhkan sebuah terobosan untuk membuat sebuah sistem pendeteksi kecelakaan. Untuk itu, penggunaan metode deep learning dan algoritma convolutional neural network dalam membuat model klasifikasi yang dapat mendeteksi kecelakaan adalah pilihan tepat karena dapat menghasilkan model dengan akurasi yang tinggi dan dapat mendeteksi kecelakaan, yang nantinya model tersebut dapat diimplementasikan pada kamera pengawas karena dengan kamera pengawas tersebut kita dapat mendeteksi kecelakaan terjadi dan secara otomatis memberikan pesan darurat ke pihak rumah sakit. Dalam penelitian ini, model dievaluasi menggunakan akurasi dan categorical cross entropy dan mendapatkan akurasi pelatihan sebesar 0, 9393 dengan loss pelatihan sebesar 0, 3228 dan akurasi validasi sebesar 0, 9080 dan loss validasi sebesar 0, 4166 yang berarti sudah layak digunakan untuk mendeteksi kecelakaan yang terjadi. Setelah model dievaluasi dan mendapatkan evaluasi yang cocok, baru model dapat diekspor dan diimplementasikan kedalam kamera pengawas.
Penerapan Synthetic Minority Oversampling Technique (SMOTE) untuk Imbalance Class pada Data Text Menggunakan kNN Sultan Maula Chamzah; Merinda Lestandy; Nur Kasan; Adhi Nugraha
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.6940

Abstract

Tokopedia is one of the online marketplace providers in Indonesia that facilitates internet users to buy and sell online. Tokopedia gets an average of 147.79 million website and application visitors per month. Although it has many users, of course in an application it has advantages and disadvantages. This was conveyed by users through reviews or reviews contained in the Google Play Store. In the review, it can be seen that more users who gave 5-star rating reviews than users gave 1 star rating. The Synthetic Minority Oversampling Technique or SMOTE is a popular method applied in order to deal with class imbalances. This study aims to determine the performance of the K-Nearest Neighbor algorithm in dealing with imbalance class using Synthetic Minority Oversampling Technique (SMOTE). This study uses 5000 data consisting of 3975 negative data and 1025 positive data. Of the 5000 data divided into two parts, 70% training data and 30% test data. The SMOTE-kNN method shows a better accuracy result, which is 90% compared to using only kNN with an accuracy value of 82%.
The Application of Waterfall Model in Web-Based Social Assistance Application Development: Web-Based Social Assistance Application Development ratna sari; Zulkifli Zulkifli
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.7160

Abstract

Poverty in Indonesia is a very important problem at this time, so that it becomes a focus of attention for the government and becomes a development issue in Indonesia. The main strategy for reducing poverty in Indonesia is one of the many steps taken to suppress growth and eliminate poverty. Various efforts and policies have been made by the government to overcome this problem, one of which is by providing social assistance to people who have a weak economy. The social assistance includes the Hopeful Family Program, Non-Cash Food Assistance, Joint Business Group Assistance, Uninhabitable House Assistance, Cash Direct Assistance, Assistance for the Abandoned and Disabled Elderly, Access to Public Services, and Other Social Services. Good policies must be guarded so that the assistance can be channeled according to the target. The aspect of equitable distribution of aid is also important so that no one feels disadvantaged by the community in need. In the success of this effort, it is necessary to apply the Waterfall Model in the Development of Web-Based Social Assistance Applications to find out which communities need this assistance more and it can be channeled on target.
Penerapan Algoritma Stemming Nazief & Adriani Pada Proses Klasterisasi Berita Berdasarkan Tematik Pada Laman (Web) Direktorat Jenderal HAM Menggunakan Rapidminer Septian Firman S Sodiq; Wahyu Desena; Arief Wibowo
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.7192

Abstract

Abstract. Website is a medium used to convey information. Currently the news on the website of the Directorate General of Human Rights is not well categorized. there are only three news categories, namely news highlights, news, activities, and regional office info, but there is no information related to news categories based on thematics. this study aims to cluster news on the ham.go.id website based on the thematic using rapidminer, in rapidminer there is a stemporter feature but it is not yet available in Indonesian, therefore the author carried out the stemming process by utilizing the Nazief & Adriani stemming algorithm to improve clustering performance. To determine the best number of clusters, the author uses the lowest DBI value and performs external testing using the Confusion Matrix. From this study, the DBI value without going through the stemming process was 4,351 with an accuracy of 81.58%, recall 83.15%, precision 80.59%. After stemming using the Nazief & Adriani algorithm, the DBI value was 3,935 with an accuracy value of 86.84%, recall 85.71%, precision 82.50%.
Aplikasi Absensi Berbasis UI/UX Eka Puspita Sari; Yuyun Yuningsih
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.7206

Abstract

QR code sendiri merupakan teknologi yang dapat digunakan dalam beberapa bidang maka dari itu QR code sangat berguna. Perkembangan tersebut membawa dampak yang besar di dalam berbagai aspek kehidupan contohnya dalam bidang Pendidikan atau kantoran. Dapat menggantikan sistem yang bersifat manual dengan cara memanggil ataupun melakukan absensi dengan melihat kandidat/murid yang hadir satu persatu. Berdasarkan uraian permasalahan tersebut, maka dibutuhkan solusi yang tepat untuk mambantu pihak sekolah dapat membuat aplikasi berbasis absensi yang menggunakan QR code untuk mempermudah sistem absensi pada saat pandemic ini.
Deteksi Lahan Pertanian Yang Terdampak Hama Tikus Menggunakan Yolo v5: Indonesia Kiki Ahmad Baihaqi; Candra Zonyfar
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.7226

Abstract

Rats are one of the pests that cause damage that can be seen by the naked eye, where the damage is in the form of poor growth and development of rice plants [1]. Because the shoots of rice or the fruit are eaten and damaged. In addition, rice plants are the staple food of the Indonesian people from the upper to the lower classes[2], Karawang Regency is the largest contributor to food availability in West Java with data obtained from the agricultural office, the total area of ​​rice fields amounted to 95,906 hectares in 2016 [3]. The number is likely to continue to decrease along with the conversion of land, which is one of the factors for the decline in rice production. With the development of digital image processing technology, a system can be made to detect affected or unaffected rice fields. So that farmers can calculate the yield of their rice harvest in the future. The results of the research using CNN in Yolo v5, from 260 photo data taken from the drone were divided into 230 datasets and 30 testing data. Which is then obtained an accuracy of 88% on average. An error occurs if the testing data uses rice plants that have just started to bear fruit because usually the growth and development of fruit does not coincide, causing it to almost resemble rice plants affected by rat pests.

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