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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Peternakan Integratif Elkom: Jurnal Elektronika dan Komputer Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization AdBispreneur Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Informatika Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mnemonic Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Infotech: Journal of Technology Information Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Applied Research (IJAR) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Information Technology (JIfoTech) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Nusantara of Engineering (NOE) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Irwan Sembiring
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Number of Cyber Attacks Predicted With Deep Learning Based LSTM Model Joko Siswanto; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.20210

Abstract

The increasing number of cyber attacks will result in various damages to the functioning of technological infrastructure. A prediction model for the number of cyber attacks based on the type of attack, handling actions and severity using time-series data has never been done. A deep learning-based LSTM prediction model is proposed to predict the number of cyberattacks in a time series on 3 evaluated data sets MSLE, MSE, MAE, RMSE, and MAPE, and displays the predicted relationships between prediction variables. Cyber attack dataset obtained from kaggle.com. The best prediction model is epoch 20, batch size 16, and neuron 32 with the lowest evaluation value on MSLE of 0.094, MSE of 9.067, MAE of 2.440, RMSE of 3.010, and MAPE of 10.507 (very good model because the value is less than 15) compared other variations. There is a negative correlation for INTRUSION-MALWARE, BLOCKED-IGNORED, IGNORED-LOGGED, and LOW-MEDIUM. The predicted results for the next 12 months will increase starting from the second month at the same time. The resulting predictions can be used as a basis for policy and strategy decisions by stakeholders in dealing with fluctuations in cyber attacks that occur.
Toddler Stunting Consulting Chatbot using Rasa Framework Wiwien Hadikurniawati; Sutarto Wijono; Danny Manongga; Irwan Sembiring; Kristoko Dwi Hartomo
Jurnal Rekayasa Elektrika Vol 19, No 4 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i4.33014

Abstract

Chatbots are artificial intelligence software that can communicate with users to assist them in certain tasks or provide information. They can reduce the need for human interaction and make processes more efficient. However, when it comes to more specific tasks related to handling the problem of stunting in toddlers these services are usually unable to provide an appropriate response. Chatbots were created with the help of the Rasa framework, which was designed to adapt the various components of natural language understanding (NLU). This adjustment allows him to understand more complex questions from respondents such as those related to healthy feeding of toddlers. This research explained the use of the Rasa framework to enhance their capabilities, describe the testing and evaluation process, and present the performance results of the chatbot model in addressing the issue of stunting in toddlers. The model is then tested using a confusion matrix, precision, accuracy, and F1 score, which measures how accurate the chatbot's responses are to the user's input. The model had a precision, accuracy, and F1 score of 0.928, 0.932 and 0.930, respectively.
ANALISIS PERILAKU PENGGUNA INTERNET DENGAN METODE K-MEANS CLUSTERING DAN PENDEKATAN DAVIES BOULDIN INDEX MENGGUNAKAN DATA LOG UNIVERSITAS XYZ Wijaya, Angga Zakharia; Sembiring, Irwan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 2 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i2.4750

Abstract

Aktivitas penggunaan jaringan Internet sangat berdampak pada penggunanya, perubahan perilaku menjadi penyebab dari penggunaan jaringan internet, Informasi yang dicari terkadang tidak sesuai dengan kebutuhan terhadap penggunaan jaringan Internet. Sehingga, situs website yang tidak memberikan manfaat, perlu diidentifikasi, dan aksesnya diblokir. Hal ini dilakukan bertujuan untuk meminimalisir dari penggunaan jaringan Internet yang menyimpang dari penggunaan nya. Sehingga dapat menunjang kinerja, baik dari bagian administrasi, maupun dalam proses pembelajaran. Penelitian ini memiliki tujuan untuk melakukan clustering data Access Log jaringan Internet di universitas xyz dengan menggunakan Algoritma K-Means, dan melakukan uji validasi hasil clustering berdasarkan Davies Bouldin Index. Hasil dari penelitian ini menunjukan bahwa perilaku penggunaan jaringan internet di universitas xyz masih menyimpang dari kebutuhan Informasi yang dicari. Dengan penggunaan Algoritma ­K-Means Clustering menghasilkan tingkat kualitas cluster yang baik, berdasarkan uji validasi data Davies Bouldin Index, yang mendapatkan nilai DBI 0,110369132, sehingga hasil dari clustering yang dilakukan sudah cukup baik. Dengan dilakukannya penelitian ini, diharapkan dapat memberikan gambaran terhadap pengelola jaringan Internet, berdasarkan metode Algoritma K-Means Clustering.
PENGEMBANGAN PERPUSTAKAAN SEKOLAH ANAK TERANG BETHANY SALATIGA Suharyadi, Suharyadi; Koerniawati, Tintien; Gundo, Adriyanto Juliastomo; Sembiring, Irwan; Wellem, Theophilus; Nataliani, Yessica
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2023)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v4i22023p196-206

Abstract

Perpustakaan sekolah dibangun oleh komponen sarana prasarana perpustakaan, pengelola peprustakaan dan kepala sekolah. Perpustakaan Sekolah Anak Terang Bethany Salatiga, membutuhkan sentuhan pengelolaan perpustakan secara profesional serta penerapan Teknologi Informasi. Program pengabdian masyarakat yang dilakukan bertujuan untuk mengatasi permasalahan Sumber Daya Manusia dengan memberikan pelatihan klasifikasi pustaka dan pelatihan pengelolaan perpustakaan berbasis Teknologi Informasi dengan penerapan SLiMS (Senayan Lybrary Management System). Hasil dari program ini Perpustakaan Sekolah Anak Terang Bethany Salatiga lebih mudah dalam penelusuran dan pengelolaan pustaka serta kemudahan anak-anak didik dalam mengakses buku-buku perpustakaan.
Analisis Pengguna Media Sosial Terhadap Isu UU Cipta Kerja Menggunakan SNA dan Naive Bayes Mau, Stevanus Dwi Istiavan; Sembiring, Irwan; Purnomo, Hindriyanto
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (521.217 KB) | DOI: 10.47065/bits.v4i1.1610

Abstract

In research about analysis issue analysis, UU Cipta Kerja aims to investigate aktor which has the most influence in the discussion on the network is based on the analysis of the most popular centrality values on the issues law copyright this working. Research is in use of the method of Social Network Analysis ( SNA ). The data in minutely as many as 1686 nodes and 1403 edges in extract through the API Twitter with the help of application WinPython and Netlytic with a period 08 October 2020 - 05 July 2021. The result of this research showed that account @BEMUI_ Official is account the most popular with the Degree Centrality 944, value Betweenness Centrality 640042.0. But on a calculation Closeness Centrality aktor @BEMUI_Official having value 0.701235, therefore nodes who have a centrality highest do not necessarily have the value that both in terms of the dissemination of information.
Implementasi Transfer Learning Pada Algoritma Convolutional Neural Network untuk Mengklasifikasikan Image Objek Wisata Mira, Mira; Sembiring, Irwan; Purnomo, Hindriyanto Dwi
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.196 KB) | DOI: 10.47065/bits.v4i1.1764

Abstract

This study classifies the image of a tourist attraction with 9 labels sky, tree, mountain, water, street, temple, garden, stone and ricefield. The results of multi-label labeling can be used to see the frequency and recommendations of tourist attractions in Central Java, and build a transfer learning model to determine the accuracy value. Classification with multi-label images has its own complexity in the labeling process and few people use it. Testing and evaluating the model uses the equation of accuracy and f-1 score. Several previous researchers also stated that the higher the amount of training data and the number of epochs per step, the higher the accuracy produced. Based on the results of training and evaluation of the four training processes, that 210 data using bs 8, lr 1e-3 and epoch 50 showed an accuracy of 0.8598 with a loss of 0.3245, while 290 data with bs 16, lr 1e-3 and epoch 50 showed an accuracy of 0.8685. with a loss of 0.2903. Then 594 data with bs 32, lr 1e-3 and epoch 50 showed an accuracy of 0.8852 with a loss of 0.2756, and 1000 data with bs 46, lr 1e-3 and epoch 50 showed an accuracy of 0.8833 with a loss of 0.2863. This can answer the statement that the greater the number of datas, the higher the accuracy produced, so that the transfer learning model on the ResNet-50 architecture with multi-label image datas can be applied by showing accuracy results close to the accuracy value on ResNet-50 in the imagenet project. In addition, the contribution of this research is to provide recommendations for potential tourist objects in Central Java, namely tourism objects with the theme of nature, then tourism processed by human hands such as historical places, cultural heritage and family recreation areas.
ANALISIS PENGARUH MINAT BERBELANJA PADA E-MARKETPLACE MENGGUNAKAN SUCCESS MODEL SYSTEM BERDASARKAN PERSPEKTIF PENGGUNA Lestari, Merryana; Sediyono, Eko; Sembiring, Irwan
Jurnal Mnemonic Vol 5 No 1 (2022): Mnemonic Vol. 5 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v5i1.4455

Abstract

Penggunaan internet yang pesat menciptakan suatu peluang bisnis bagi perusahaan, yaitu dengan munculnya e-Commerce. E-Commerce dikembangkan lagi menjadi jenis platform bisnis yang baru, yang dikenal sebagai e-Marketplace. E-Marketplace memungkinkan pengusaha kecil dan menengah serta individu sebagai konsumen akhir dapat memasarkan produk mereka secara internasional hanya dengan membuat sebuah toko online melalui website ataupun aplikasi mobile platform e-Marketplace tersebut. Perkembangan e-Marketplace di Indonesia masih memiliki kekurangan utama, yaitu kurangnya kepercayaan. Hal ini disebabkan karena masyarakat Indonesia, masih lebih mempercayai penjualan secara langsung. Selain masalah kepercayaan, e-Marketplace di Indonesia memiliki masalah di bidang keamanan karena belum ada payung hukum yang jelas menyangkut keamanan e-Marketplace. Penelitian ini menggunakan kuisioner dengan 30 pertanyaan yang dibagi menjadi 5 bagian berdasarkan Success Model System yang diciptakan oleh DeLone dan McLean, yaitu data responden, pertanyaan dasar mengenai e-Marketplace, penilaian responden terhadap kualitas sistem e-Marketplace, penilaian responden terhadap kualitas informasi e-Marketplace, penilaian responden terhadap kualitas layanan pada e-Marketplace, penilaian responden mengenai tingkat penggunaan e-Marketplace, dan penilaian responden mengenai tingkat kepuasan pengguna. Hasil penelitian yang diperoleh menunjukkan bahwa sistem e-Marketplace yang ada di Indonesia masih memiliki kekurangan dan keterbatasan yang membuat masyarakat belum dapat menggunakan e-Marketplace sebagai suatu sarana transaksi jual beli secara optimal.
PERANCANGAN USER INTERFACE/USER EXPERIENCE APLIKASI CAFÉ BIRU FTI MENGGUNAKAN FIGMA DENGAN PENDEKATAN DESIGN THINKING Yohnes Madawara, Herdin; Sembiring, Irwan; Iriani, Ade
Jurnal Mnemonic Vol 6 No 2 (2023): Mnemonic Vol. 6 No. 2
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v6i2.6474

Abstract

Café Biru FTI UKSW merupakan tempat bagi mahasiswa, pengajar, staf, sampai ke sivitas sebagai tempat bersantai dan bercanda bersama. Café Biru FTI berlokasi berlokasi pada Kampus 3 Universitas Kristen Satya Wacana (UKSW) Jl. Dr. O. Notohamidjojo No.1 - 10, Blotongan, Kec. Sidorejo, Kota Salatiga, Jawa Tengah. Melihat beberapa permasalahan yang ada sehingga hadirnya penelitian dengan melaraskan design interface dan prototype. Permasalahan yang dimaksud antara lain ; 1) Layanan pemesanan masih menggunakan kertas dan atau secara lisan 2) Terkadang terjadinya kesalahan komunikasi antara pelanggan dan kasir atau kasir dan bagian dapur. Melalui penelitian ini, penulis melakukan pendekatan dengan Design Thinking (Empathize, Define, Ideate, Wireframe, Prototype) dan yang terakhir yaitu pengujian sistem menggunaka System Usability Scale (SUS). Hasil akhir rata-rata dari nilai SUS berjumlah 87,625 sehingga terkategori A atau terbilang sangat baik. Oleh sebab itu dapat disimpulkan bahwa fungsi dari fitur yang telah dirancang berupa design interface dapat dimengerti oleh pengguna. Mengacu pada penelitian yang telah dilaksanakan, maka perlunya pengembangan berkelanjutan untuk merancang sistem aplikasi dari Café Biru FTI UKSW yang berfokus pada pemesanan barang (makan dan minum).
Implementasi Rapid Application Development dalam membangun sistem pengelolaan keuangan Homestay Linia berbasis web Julians, Adhe Ronny; Iriani, Ade; Sembiring, Irwan
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.1-13

Abstract

In running a business, the ease of managing financial data is essential because it is closely related to how income and expenditure data can be managed properly. The absence of an efficient system for managing financial data is a problem encountered in the object of this research, namely Homestay Linia, wherein managing the financial data in question, there are still certain complications, which result in financial data being inaccurate and irregular, related to these problems, it is necessary to build a financial management system. In developing the system, researchers use the Rapid Application Development method and will conduct system testing using the Black Box Testing method and User Satisfaction Survey through Online Questionnaires. The results showed that the system that has been built gets 100% positive reviews given by respondents. It shows that the system can help business activities effectively and efficiently.
Optimizing the long short-term memory algorithm to improve the accuracy of infectious diseases prediction Sediyono, Eko; Wahyuni, Sri Ngudi; Sembiring, Irwan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2893-2903

Abstract

This study discusses the implementation of the proposed optimizedlong short-term memory (LSTM) to predict the number of infectious disease cases that spread in Central Java, Indonesia. The proposed model is developed by optimizing the output layer, which affects the output value of the cell state. This study used cases of four infectious diseases in Indonesia's Central Java Province, namely COVID-19, dengue, diarrhea, and hepatitis A. This model was compared to basic LSTM and MinMax schaler LSTM improvement to see the difference in the accuracy of each disease. The results showed a significant difference in the average prediction results with real cases between the three models. The main objectives of this study were: modifying the LSTM algorithm to predict the number of infectious disease cases to get a smaller residual value, comparing the results of the optimization accuracy of the LSTM algorithm with the LSTM algorithm in previous studies, and evaluating the use of spatial variables in applying infectious disease prediction models using the LSTM algorithm. The results found that the performance difference between the proposed optimization algorithm and the model in the previous study was obtained. The proposed LSTM optimization algorithm had an accuracy improvement of about 2% over the previous model.
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Alamsyah, Ferry Andriana, Myra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Ginting, Jusia Amanda Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hany Makaruku, Yulian Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Hindriyanto Dwi Purnomo Huda, Baenil Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Joko Siswanto Jonas, Dendy Julians, Adhe Ronny Juneth Manuputty Krismiyati Kristoko D Hartomo Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Madawara, Herdin Yohnes Manongga, Daniel H.F Manongga, Daniel H.F. Manongga, Daniel HF Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nurtino, Tio Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hidriyanto Dwi Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini Rahardja.,M.T.I.,MM, Dr. Ir. Untung Raymond Elias Mauboy Rimes Jopmorestho Malioy Roy Rudolf Huizen Saian, Septovan Dwi Suputra Sandry Lanovela Pasaribu Santoso, Nuke Puji Lestari Sediyono, Eko - Setiawan Hakim Sri Ngudi Wahyuni Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Supriadi, Candra Suryantara, I Gusti Ngurah Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana, Teady Matius Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yulian Hany Makaruku