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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) dCartesian: Jurnal Matematika dan Aplikasi Jurnal Sistem Komputer Proceedings of KNASTIK Journal The Winners Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Penelitian Pendidikan IPA (JPPIPA) INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL PENDIDIKAN TAMBUSAI Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) Building of Informatics, Technology and Science JUKANTI (Jurnal Pendidikan Teknologi Informasi) Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Advance Sustainable Science, Engineering and Technology (ASSET) International Journal of Social Science Indexia J-SAKTI (Jurnal Sains Komputer dan Informatika) KINGDOM : Jurnal Teologi dan Pendidikan Agama Kristen Jurnal Minfo Polgan (JMP) Jurnal Teknologi Sistem Informasi Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Eduvest - Journal of Universal Studies Journal of Technology Informatics and Engineering Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Scientific Journal of Informatics CSRID Society Jurnal DIMASTIK Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Hendry
Universitas Kristen Satya Wacana
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Penjadwalan Kelas Praktikum Menggunakan Algoritma Steepest Ascent Hill Climbing Hendra Waskita; Hindriyanto Dwi Purnomo; Hendry Hendry
AITI Vol 13 No 2 (2016)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (473.853 KB)

Abstract

Penentuan jadwal praktikum merupakan permasalahan yang sering dihadapi oleh perguruan tinggi. Keterbatasan jumlah kelas seringkali tidak sebanding dengan kegiatan yang dilakukan. Untuk memaksimalkan penggunaan kelas dan juga tenaga pengajar/asisten praktikum, diperlukan system penjadwalan yang baik. Dalam penelitian ini dirancang system penjadwalan praktikum menggunakan metode steepest ascent hill climbing. Penelitian ini menggunakan contoh data kelas praktikum di Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana.
Consumer Behavior based on APP use for Food and Beverage Consumption Hendry Hendry; Rung Ching Chen
AITI Vol 15 No 1 (2018)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.396 KB) | DOI: 10.24246/aiti.v15i1.1-13

Abstract

McDonalds is one of the brands that release the APP on the Smartphone, the APP is called McDonalds McDelivery APP. It suitable for the way of today’s society way of life, where people are busy and don’t want to line and queue in store to buy foods and beverages for too long. People have a freedom to choose and to order through their Smartphone. The mobile APP offers the advantages, it is easy to operate, easy to use, and doesn’t spend a lot of money. In order to understand the consumers behaviour of using APP, this study conduct the descriptive statistical analysis, variance analysis and regression analysis to detect technology acceptance model for perceived usefulness, ease of use, behaviour intention and actual of use. This study conduct the questionnaire through online google forms and obtained 109 valid questionnaires for analysis. We finds that there was no significant effect on degree of the users, and frequencies of using internet. Perceived usefulness and ease of use of behavioural intentions, behavioural intentions and actual of use had significantly difference.
Multivariate Time Series Forecasting pada Penjualan Barang Retail dengan Recurrent Neural Network Robertus Bagaskara Radite Putra; Hendry Hendry
Jurnal Inovtek Polbeng Seri Informatika Vol 7, No 1 (2022)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v7i1.2398

Abstract

Intisari–Pasar ritel di Indonesia semakin berkembang seiring bertambahnya penduduk dan daya beli. Peluang ini harus dimanfaatkan, namun dalam bisnis ritel, kadangkala terjadi keadaan Out of Stock maupun over stock di dalam toko. Untuk mengatasi hal tersebut, kita bisa mengatasinya dengan melakukan peramalan atau prediksi penjualan yang akan terjadi di masa mendatang. Ada beberapa macam metode untuk melakukan peramalan, namun secara umum terbagi menjadi 2 jenis yaitu metode statistika dan juga computational intelligence. Penelitian ini mencoba untuk melakukan prediksi penjualan barang retail perhari menggunakan metode Recurrent Neural Network (RNN) sebagai bagian dari metode computational intelligence. Dari penelitian ini kita bisa dapatkan hasil bahwa dalam kasus prediksi penjualan ritel, performa akurasi RNN lebih baik dari metode statistika
Perbandingan Metode K-NN, Naïve Bayes, Decision Tree untuk Analisis Sentimen Tweet Twitter Terkait Opini Terhadap PT PAL Indonesia Franly Salmon Pattiiha; Hendry Hendry
JURIKOM (Jurnal Riset Komputer) Vol 9, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i2.4016

Abstract

PT PAL Indonesia is one of the state-owned enterprises engaged in the shipbuilding industry which has business advantages in shipbuilding and shipbuilding capabilities. Being a fairly large company, PT PAL gets opinions from the public regarding the performance and services provided. Therefore, a sentiment analysis was carried out on public opinion on Twitter social media using data that had been collected into a dataset and processed using Rapidminer tools. This study uses the Naïve Bayes, K-NN and Decision Tree methods to make comparisons by looking at the level of accuracy of the three methods used. The results of the study show that the Naïve Bayes method has an accuracy rate of 84.08% with class precision for pred. positive is 83.65%, pred. Neutral is 97.06%, pred. negative 100%, K-NN method is 83.38% with class precision for pred. positive is 83.05%, pred. Neutral is 96.43%, pred. negative 0.0% and the Decision Tree method is 81.09% with class precision for pred. positive is 81.09%, pred. Neutral is 0.0%, pred. negative 0.0%. The results of this study can show that the Naïve Bayes method has a higher accuracy rate than other methods used with an accuracy rate of 84.08%
Analisis Node Dengan Metode Degree Centrality Dan Follower Rank Pada Tagar Twitter Erits Talapessy; Hendry Hendry
JURIKOM (Jurnal Riset Komputer) Vol 9, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i2.4053

Abstract

Twitter is one of the most popular social media platform as a means of information and interaction with other people. Since its launch in 2006, Twitter has been classified as a microblogging site. Data in the form of node analysis (actors) on Twitter can be analyzed using a social network analysis method approach. This study was designed to analyze data on tweet containing the hastag “#LuhutPenghisapDarahRakyat”. This analysis uses the degree centrality method to identify influential nodes (actors) and the follower rank method to find popular nodes (actors). The data were 2803 nodes and 8030 edges data was taken from November 6,2021 to November 7,2021. The results show that the @arthan38836243 account is the actor with the higshest degree centrality value, which is 265 and the @teriwinarno account is the actor with the highest popularity value or follower rank, which is 0.988081224. This shows that influential actors are not necessarily the same as popular actor. This studt that among the 10 main actors with the highest degree centrality value, one of the actors was a buzzer account on Twitter
IMPLEMENTATION OF GENERATIVE ADVERSARIAL NETWORKS FOR CREATING DIGITAL ARTWORK IN THE FORM OF ABSTRACT IMAGES eric secada purba; Hendry
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.262

Abstract

Abstract painting always has its own place for the fans, the irregular shape in it, and the emotions depicted in the painting, make many people amazed to see it. The success of this abstract image sparked the idea of ​​being able to create an abstract image using Deep Learning Technology. Generative Adversarial Networks (GANs) is one of the Deep Learning technologies that can create it. With the GANs method which has Generator and Discriminator functions in it, it is possible for someone to be able to create it. The generator functions to generate new data through training the data(train), and the Discriminator functions to determine whether the new data is fake or not data through training (train) comparing the generator results with the original data. These two functions are used to create abstract images. Abstract images were obtained through training in 1369 paintings of nature, landscapes, and flowers. The images are trained by comparing the number of epochs used and the results of the abstract images generated from each epoch. The epoch will be divided into three parts, namely the first training using 10 epochs, the second training using 100 epochs, and the third training using 1000 epochs. In this journal, we will compare the results of the three trainings and reach a conclusion which training produces the best abstract image according to the author. From the training, 1000 epoch training was obtained which produces good abstract images.
Pengklasifikasian Aksara Jawa Metode Convolutional Neural Network Ivan Sukma Hanindria; Hendry Hendry
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2177

Abstract

Secara garis besar bentuk Aksara Jawa terbagi menjadi 3 set aksara yaitu Dasar,Pasangan dan Sandhangan. beberapa karakter dalam Aksara Jawa memiliki definisi bentuk yang serupa sehingga dapat menambah kompleksitas proses pengenalan. Metode Convolutional Neural Network (CNN) merupakan salah satu algoritma klasifikasi gambar dengan operasi konvolusi yang menggabungkan beberapa lapisan pemrosesan,Tujuan penelitian kali ini mengukur seberapa efektif algoritma Convolutional Neural Network dalam pengklasifikasian menggunakan Akasara Jawa Dasar.Percobaan menggunakan 20 kelas data aksara jawa yang masing masing terdapat untuk tiap folder berisi 108 citra.Pada penelitian ini klasifikasi aksara jawa dengan metode Convolutional Neural Network (CNN) bisa melakukan pengklasifikasian dengan tingkat akurasi sebesar 85%. Dari hasil terbukti dapat mengelompokkan aksara jawa “Ka” dan aksara jawa “Nya”.
COMPARISON OF PREDICTION ANALYSIS OF GOFOOD SERVICE USERS USING THE KNN & NAIVE BAYES ALGORITHM WITH RAPIDMINER SOFTWARE Agista Nindy Yuliarina; Hendry Hendry
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.294

Abstract

GoFood is a service provider that has a very important role in human life, especially in this growing era. Currently, many service providers are competing to meet the needs of users, including GoFood. However, not all service providers can meet and know the needs needed by users, because they focus on the services offered and only the quality of services provided. Therefore, survey analysis is needed to obtain customer satisfaction data that will be used to satisfy GoFood service users. The classification method uses the KNN and Naive Bayes algorithms, which are good algorithms for testing 1,000 records of GoFood user data that have been obtained previously. The test results using Cross Validation and T-Test show that the KNN algorithm is the best algorithm with 98.80% Accuracy and 100% Recall, while Naive Bayes obtains 94.10% Accuracy and 94.43% Recall.
DATA MINING TECHNIQUE USING NAÏVE BAYES ALGORITHM TO PREDICT SHOPEE CONSUMER SATISFACTION AMONG MILLENNIAL GENERATION Margaretha Intan Pratiwi Hant; Hendry Hendry
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.295

Abstract

Shopee is one of the largest e-commerce platforms currently being used by Millennials. The use of Shopee itself makes it very easy for consumers to process transactions. Shopee itself is committed to maintaining and improving customer satisfaction so they don't switch to other competitors. However, it is undeniable that there are still many cases that can harm consumers when using the platform. With the cases that occur, it is very possible that there will be a big influence on the level of consumer satisfaction on the platform. Consumers will feel satisfied when the product or service used can meet consumer expectations. This study was made with the aim of predicting the level of consumer satisfaction of Shopee Indonesia among the Millennial Generation. This study applies data mining using the Naive Bayes Algorithm. The Naive Bayes algorithm itself is a simple probability classification that can calculate all possibilities by combining a number of combinations and the frequency of a value from the database obtained. The attributes used in conducting this research include Name, Gender, Age, Price, Performance and Efficiency, Fulfillment, Reliability, Control and Security, Responsiveness, Compensation, Contact, and Description of Satisfaction Value. In this study, the results obtained from several input attributes that create a causal relationship when classifying satisfied and dissatisfied consumers. The results obtained can provide benefits for the Shopee company in increasing customer satisfaction. After carrying out the testing process, it can be concluded that the Naive Bayes Algorithm is an algorithm that is suitable for use in the classification process for measuring Shopee Indonesia's consumer satisfaction level among the Millennial Generation, with an accuracy rate of 89.65%.
PREDICTION OF BABY BIRTH RATE USING NAÏVE BAYES CLASSIFICATION ALGORITHM IN RANDAU VILLAGE Magda Kitty Hartono; Hendry Hendry
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.302

Abstract

The birth rate is one of the factors increasing the rate of population growth. Birth or fertility can affect the population, getting more lower of birth rate in an area, the higher the life expectancy in that area. The number of births in Randau Jekak Village is increasing every year. The Naïve Bayes algorithm can be used to predict the future births rate because this algorithm is a simple algorithm and uses a lot of data as information in collecting data groups, and with data mining techniques it can see the predictive pattern of each variable and test. The testing data and the training data are expected to help the Village Institution or Office in Randau Jekak to suppressing the rate of population growth which increases every year. The results of this study can be concluded that the Naïve Bayes Algorithm is suitable for predicting the birth rate of babies in Randau Jekak Village with the classification technique, the birth rate in Randau Jekak Village in 2021 is High. The results of this data will be very useful for the Randau Jekak Village office in suppressing the rate of population growth in the coming year.
Co-Authors Ade Iriani Adenia Kusuma Dayanthi Adriyanto Juliastomo Gundo Agista Nindy Yuliarina Agus Susanto Amanda, M. F. Anton Hermawan April Lia Hananto Atik Setyanti, Angela Aviv Yuniar Rahman Baihaqi, Kiki Ahmad Benedictus Lanang Ido Hernanto Christine Dewi Daniel, Benny Danny Manongga Dewasasmita, Elsha Yuandini Dewi Puspitasari Eka, Muhammad Eko Sediyono eric secada purba Erick Alfons Lisangan Erits Talapessy Erwien Christianto Ester Caroline Dwi Wijaya Wijaya Fauzi Ahmad Muda Fenny Fenny Franly Salmon Pattiiha Fredryc Joshua Pa'o Gunawan, Ricardho Handoko Handoko Handoko, Andrew C Hanita Yulia Hendra Waskita Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil Indriaty, Novica Irwan Sembiring Ismael, Ismael Ivan Sukma Hanindria Iwan Setiawan Iwan Setyawan Jessica Margaret Br Sembiring Joko Siswanto Julians, Adhe Ronny Kesumawati, Ramadini Kho, Delvian Christoper Krismiyati Kurnia, Sri Kurniawan Teguh Martono Leni Marlina Liawatimena, S. Lidia Gayatri Madawara, Herdin Yohnes Mado, Priscianus Mikael Kia Magda Kitty Hartono Mahulete, Ebenhaezer Yohanes Abdeel Manongga, Daniel Margaretha Intan Pratiwi Hant Martaliana Putri Agustina Merryana Lestari Muhammad Khahfi Zuhanda Muhammad Rizky Pribadi Nadia Sofie Soraya Nansy Stephanie Mongi Novrina, Putri Dwi Nugraha, Febrina Tesalonika Panja, Eben Paryono, Tukino Pratama Siregar, Hari Nanda Pratama, Arya Damar Purbaratri, Winny Purnomo, Hendryanto Dwi Raden Mohamad Herdian Bhakti Ramos Somya Ravensca Matatula Ravensca Matatula Richard V. Llewelyn Rizal, Chairul Robertus Bagaskara Radite Putra Ronny Julians, Adhe Rung Ching Chen Santoso, Joseph Teguh Saputri, Adelliya Dewi Septhiani, Angeline Sholikin, Muhammad Sjukun Suharyadi Suherman, Suherman Sukiman Sukiman Supiyandi Supiyandi Susanta, Vonny A. Sutarto Wijono Syefudin Syefudin Tarigan, Aldi Ekin Arapenta Teddy Marcus Zakaria Theopillus J. H. Wellem Tukino, Tukino Uly, Novem Untung Rahardja Vanisa Meifari Wahyuningsih, Novia Wibowo, Kurniawan Indra Widi, Anugerah Wijaya, Elyzabeth Winny purbaratri Yandra Rivaldo Yessica Nataliani Zulham Zulham