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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer JSI: Jurnal Sistem Informasi (E-Journal) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal on Emerging Mathematics Education Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi Journal of Information Technology and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) ICIT (Innovative Creative and Information Technology) Journal Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) IAIC Transactions on Sustainable Digital Innovation (ITSDI) JOINTER : Journal of Informatics Engineering International Journal of Engineering, Science and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences) Metris: Jurnal Sains dan Teknologi Scientific Journal of Informatics International Journal of Information Technology and Business INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
Hindriyanto Dwi Purnomo
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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IPv6 flood attack detection based on epsilon greedy optimized Q learning in single board computer April Firman Daru; Kristoko Dwi Hartomo; Hindriyanto Dwi Purnomo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5782-5791

Abstract

Internet of things is a technology that allows communication between devices within a network. Since this technology depends on a network to communicate, the vulnerability of the exposed devices increased significantly. Furthermore, the use of internet protocol version 6 (IPv6) as the successor to internet protocol version 4 (IPv4) as a communication protocol constituted a significant problem for the network. Hence, this protocol was exploitable for flooding attacks in the IPv6 network. As a countermeasure against the flood, this study designed an IPv6 flood attack detection by using epsilon greedy optimized Q learning algorithm. According to the evaluation, the agent with epsilon 0.1 could reach 98% of accuracy and 11,550 rewards compared to the other agents. When compared to control models, the agent is also the most accurate compared to other algorithms followed by neural network (NN), K-nearest neighbors (KNN), decision tree (DT), naive Bayes (NB), and support vector machine (SVM). Besides that, the agent used more than 99% of a single central processing unit (CPU). Hence, the agent will not hinder internet of things (IoT) devices with multiple processors. Thus, we concluded that the proposed agent has high accuracy and feasibility in a single board computer (SBC).
Pengembangan Stochastic Gradient Descent dengan Penambahan Variabel Tetap Adimas Tristan Nagara Hartono; Hindriyanto Dwi Purnomo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 3 (2023): JULY-SEPTEMBER 2023
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v7i3.840

Abstract

Stochastic Gradient Descent (SGD) is one of the commonly used optimizers in deep learning. Therefore, in this work, we modify stochastic gradient descent (SGD) by adding a fixed variable. We will then look at the differences between standard stochastic gradient descent (SGD) and stochastic gradient descent (SGD) with additional variables. The phases performed in this study were: (1) optimization analysis, (2) fix design, (3) fix implementation, (4) fix test, (5) reporting. The results of this study aim to show the additional impact of fixed variables on the performance of stochastic gradient descent (SGD).
Analisis Kesiapan Pembelajaran Artificial Intelligence di Tingkat Pendidikan Dasar (Studi Kasus di SMP Negeri 1 Salatiga) Lea Klarisa; Angela Atik Setiyanti; Hindriyanto Dwi Purnomo; Adriyanto Juliastomo Gundo
EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 5, No 3 (2023): June
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/edukatif.v5i3.5271

Abstract

Abstrak Penelitian ini bertujuan untuk mengetahui kesiapan pembelajaran Artificial Intelligence pada jenjang pendidikan dasar yang dilihat dari kesiapan siswa, kesiapan guru, kesiapan sarana dan prasarana, serta kesiapan kurikulum. Tempat penelitian adalah SMP Negeri 1 Salatiga. Penelitian ini merupakan penelitian deskriptif kualitatif dengan subjek penelitian yaitu 2 guru mata pelajaran Informatika dan 16 siswa kelas VIII. Data penelitian dikumpulkan dengan teknik wawancara terstruktur, dan observasi. Hasil dari penelitian menunjukan bahwa kesiapan siswa dari kesiapan kondisi fisik, mental, emosional, kebutuhan, pengetahuan dan keterampilan pada kategori siap. Kesiapan guru dari latar belakang pendidikan, pengetahuan, keterampilan dan kompetensi profesional pada kategori siap. Kesiapan sarana dan prasarana dalam kategori sangat siap. Sedangkan kesiapan kurikulum masih kurang siap karena masih perlu adanya pendalaman mengenai pembelajaran AI. Dengan demikian pembelajaran AI di sekolah dapat dilaksanakan namun perlu dilakukan pendalaman dan pengembangan lebih lanjut mengenai persiapan pembelajaran AI dalam hal kurikulum
Penerapan Algoritma Apriori dan FP-Growth Untuk Market Basket Analisis Pada Data Transaksi NonPromo Andrew Aquila Chrisanto Pabendon; Hindriyanto Dwi Purnomo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6153

Abstract

This research aims to find association rules based on the transactions of Aksesmu members on non-promo items. The method in this study uses Association rules using the a priori algorithm and FP-Growth to obtain Frequent Itemsets. The data analysis phase is carried out starting with Exploratory Data Analysis, Pre-Processing Data, Transformation Data, and Data Mining, to evaluate the results of the formed association rules. Researchers conducted 4 experiments with a minimum support of 0.02 and a minimum confidence of 0.25 on a priori and FP-Growth was the best by producing 52 frequent itemsets and 17 association rules. With a dataset of 379,635, a priori is faster in processing frequent itemsets with a time of 1.10 seconds while FP-Growth is with 1.86 seconds. Apriori and FP-Growth produce the same frequent itemset, namely the highest category is obtained by SKT with a support of 0.32 and SKM with a support of 0.26, but the best association rules are produced by the Extruded & Pellet and Sweetened Condensed Milk categories with a confidence of 0.47, which if items in the Extruded & Pellet category are purchased together with Sweetened Condensed Milk category items have a success rate of 47%.
Penerapan Metode TOPSIS Dalam Sistem Pendukung Keputusan Seleksi Penerimaan Asisten Dosen Berbasis Web Richard William Kho; Hindriyanto Dwi Purnomo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6268

Abstract

Technological developments in the field of education in tertiary institutions help and facilitate students in carrying out lecture processes such as conducting online classes, making it easy to obtain material provided by lecturers and various administrative processes that can be taken care of online. In the classroom, lecturers in teaching need teaching assistants as companions so that one of the success factors in the lecture process is based on the interaction between teaching assistants and students where the teaching assistant acts as a liaison between students and lecturers. At the Faculty of Information Technology, Satya Wacana Christian University, Informatics Engineering Study Program, to register as a teaching assistant, various processes are needed to meet the criteria that help in the selection process for teaching assistants, but in the selection process for accepting teaching assistants, it is still influenced by personal preferences which causes injustice in assessment and decision making. , various selection processes are complicated and time-consuming due to the many criteria with different levels of importance, the selection process is still done manually so that the selection process for hiring assistant lecturers is not effective and efficient. And in the process of storing data that is also ineffective, it is possible that it can be damaged or deleted. By using a decision support system and the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) it can assist in calculating all criteria simultaneously and giving weight to each criterion so that criteria can be identified that have more influence on the selection process and produce mathematical calculations so that the results which can be determined at the best value. The purpose of this study is to speed up the process of selecting teaching assistants by implementing the TOPSIS method to assist in selecting admission assistant lecturers. The results obtained are websites using the PHP programming language, Laravel framework, Bootstrap framework and MySQL database which are running well and have an attractive appearance. black box testing, validation of manual calculations where the results of the calculations are in accordance with the results on the website made with brandon which gets the highest prevalence value of 0.58.
Analisa Market Basket Analysis untuk Melihat Pola Transaksi Customer Menggunakan Algoritma Apriori dan FP-Growth Griya Jitri Pabutungan; Hindriyanto Dwi Purnomo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6152

Abstract

Online sales are considered an alternative approach that can positively impact product marketing. But the more online shops, the greater the competition in the business world. From the problems above, so that the store can survive among busy competitors, a strategy that is qualified as an effort to attract customer attention is needed. One effort that can be done is to look at customer patterns or tendencies during transactions. Knowing this is expected to provide additional information to stores to increase loyalty and meet customer needs so that online business stores that are built can last a long time. Based on the description that has been explained, the purpose of writing this research is to find customer spending patterns so that it can support XYZ company as one of the retail application managers in creating business strategies that can be used to attract customer interest using the market basket analysis method and the help of the a priori algorithm and fp-growth as a comparison. The market basket looks at product categories often purchased together in one receipt by customers. This study uses transaction data of 34,159,477, a minimum confidence value of 0.2, and a minimum support of 0.01 for both algorithms. The results of the two algorithms using the same minimum value give the same result in the form of 10 association rules itemset.
Soccer game optimization for continuous and discrete problem Hindriyanto Dwi Purnomo
Jurnal METRIS Vol. 15 No. 02 (2014): 2014
Publisher : Prodi Teknik Industri, Fakultas Teknik - Universitas Katolik Indonesia Atma Jaya

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

Abstract

Soccer games optimization is a new metaheuristics method that mimics the soccer player’s movement, wherein each player decides their best positions to dribble the ball towards the goal based on the ball position and other players’ position. This paper discussed the method for continuous and discrete problems based on ‘pair cooperation’ between a player and the ball position. The algorithm is implemented in eight benchmark problems consisting of continuous unconstrained problems, continuous constrained problems and discrete problem. The performance of the algorithm for the continuous unconstrained problems is compared to two meta-heuristic algorithms, the genetic algorithm and the particle swarm optimization. The continuous constrained problems and the discrete problem are compared with the result in the literature. The experimental results show that the algorithm is a potentially powerful optimization procedure that can be applied for various optimization problems.
Analisis Sentimen Produk Herbal Jamu pada Media Sosial Instagram DANIEL KURNIAWAN; HINDRIYANTO DWI PURNOMO; ADE IRIANI
Jurnal Sistem Informasi Vol 15, No 2 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v15i2.21901

Abstract

Meningkatnya kapasitas dan jumlah industri dan usaha kecil yang bergerak pada bidang herbal jamu di Indonesia mengindikasikan peningkatan dan perubahan gaya hidup masyarakat untuk mengkonsumsi tanaman obat [1]. Produk herbal jamu bagi sebagian besar masyarakat Indonesia telah dipercaya dan lebih aman dalam mengobati penyakit. Produk herbal jamu juga terbukti memberikan manfaat bagi perawatan penderita batu saluran kemih dan diabetes melitus [2][3]. Meski demikian, terdapat faktor lain seperti budaya dan kepercayaan dalam memilih obat herbal [4]. Pemasaran sebuah produk herbal jamu dengan memanfaatkan media sosial saat ini menjadi kebutuhan primer dan memiliki potensi untuk memperluas jangkauan pemasaran bahkan meningkatkan omset penjualan produk [5][6]. Pelaku usaha seperti UMKM juga telah menyertakan media sosial seperti facebook, dan instagram sebagai media pemasaran yang dirasa lebih mudah dalam penggunaannya [7]. Pelaku usaha dan industri herbal jamu dapat memanfaatkan kemudahan dan efisiensi dari media sosial dalam melakukan penjualan. Penelitian ini bertujuan untuk mengungkap sentimen pengguna media sosial Instagram terhadap tren penjualan herbal jamu. Hasil penelitian akan mengungkap signifikansi penggunaan media sosial Instagram pada pemasaran produk herbal jamu.
Neuroevolution untuk optimalisasi parameter jaringan saraf tiruan Hindriyanto Dwi Purnomo; Tad Gonsalves; Teguh Wahyono; Pratyaksa Ocsa Nugraha Saian
AITI Vol 20 No 2 (2023)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v20i2.125-134

Abstract

Artificial Neural Network is a supervised learning method for various classification problems. Artificial Neural Network uses training data to identify patterns in the data; therefore, training phase is crucial. During this stage, the network weight is adjusted so that they can recognize patterns in the data. In this research, a neuroevolution approach is proposed to optimize artificial neural network parameters (weight) Neuroevolution is a combination of evolutionary algorithms, including various metaheuristics algorithms, to optimize neural network parameters and configuration. In particular, this research implemented particle swarm optimization as the artificial neural network optimizer. The performance of the proposed model was compared to backpropagation, which uses gradient information to adjust the neural network parameter. There are five datasets used as the benchmark problems. The datasets are iris, wine, breast cancer, ecoli, and wheat seeds. The experiment results show that the proposed method has better accuracy than the backpropagation in three out of five problems and has the same accuracy in two problems. The proposed method is also faster than the backpropagation method in all problems. These results reveal that neuroevolution is a promising approach to improving the performance of artificial neural networks. Further studies are needed to explore more benefits of this approach.
Fast and Accurate Indonesian QnA Chatbot Using Bag-of-Words and Deep-Learning For Car Repair Shop Customer Service Muchamad Taufiq Anwar; Azzahra Nurwanda; Fajar Rahmat; Muhammad Aufal; Hindriyanto Dwi Purnomo; Aji Supriyanto
Advance Sustainable Science Engineering and Technology Vol 5, No 2 (2023): May-July
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v5i2.14891

Abstract

A chatbot is a software that simulates human conversation through a text chat. Chatbot is a complex task and recent approaches to Indonesian chatbot have low accuracy and are slow because it needs high resources. Chatbots are expected to be fast and accurate especially in business settings so that they can increase customer satisfaction. However, the currently available approach for Indonesian chatbots only has low to medium accuracy and high response time. This research aims to build a fast and accurate chatbot by using Bag-of-Words and Deep-Learning approach applied to a car repair shop customer service. Sixteen different intents with a set of their possible queries were used as the training dataset. The approach for this chatbot is by using a text classification task where intents will be the target classes and the queries are the text to classify. The chatbot response then is based on the recognized intent. The deep learning model for the text classification was built by using Keras and the chatbot application was built using the Flask framework in Python. Results showed that the model is capable of giving 100% accuracy in predicting users’ intents so that the chatbot can give the appropriate responses and the response time is near zero milliseconds. This result implies that developers who aim to build fast and accurate chatbot software can use the combination of bag-of-words and deep-learning approaches. Several suggestions are presented to increase the probability of the chatbot’s success when released to the general public.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Ade Iriani Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Andre Kurniawan Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Ani, Nyree Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Arseta, Gama Astawa, I Wayan Aswin Dew Atik Setyanti, Angela Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Cesna, Galih Putra Chandra Halim Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eko Sediyono Eliansion Ivan eremia Silvester Sutoyo Erwien Christianto Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Heni Pujiastuti Hermanto Abraham, Rendy Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Kainama, Marchel Devid Karema Sarajar, Dewita Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Nurrokhman, Nurrokhman Nurtino, Tio Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purwanto - Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Safitri, Adila Sakalessy, Afelia Jozalin Elisa Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Santoso, Joseph Teguh Setiyaji, Akhfan Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Walangara Nau, Novriest Umbu Wibowo, Mars Caroline Widyarini, Liza Wilujeng Ayu Nawang Sari Winny purbaratri Wisnu Wibisono, Indra Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yos Richard Beeh Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yusuf, Natasya Aprila Zakaria, Noor Azura