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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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PERFORMANCE ANALYSIS OF GRADIENT BOOSTING MODELS VARIANTS IN PREDICTING THE DIRECTION OF STOCK CLOSING PRICES ON THE INDONESIA STOCK EXCHANGE Kho, Delvian Christoper; Purnomo, Hindriyanto Dwi; Hendry, Hendry
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1393-1408

Abstract

Accurately predicting stock market trends remains a significant challenge for investors due to its dynamic nature. This study explores the performance of Gradient Boosting models, including XGBoost, XGBoost Random Forest, CatBoost, and Gradient Boosting Scikit-Learn, in predicting stock market trends such as sideways movement, uptrends, downtrends, and volatility. Using four datasets from the Indonesia Stock Exchange, the research integrates technical, fundamental, and sentiment data, encompassing 37 features. Modeling and testing are conducted using Orange tools and Python, with performance evaluated through metrics such as Mean Absolute Percentage Error (MAPE), R-squared (R²), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Results indicate that XGBoost and XGBoost Random Forest consistently outperform other models in predicting stock price movements. These findings highlight the potential of Gradient Boosting models in providing accurate and reliable predictions, offering valuable insights for investors, financial analysts, and researchers to enhance investment strategies and adapt to market fluctuations effectively.
Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm Winny purbaratri; Hindriyanto Dwi Purnomo; Danny Manongga; Iwan Setyawan; Hendry Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
Perancangan Sistem Informasi Data Pasien Rehabilitasi Pada Institusi Penerima Wajib Lapor (IPWL) Bukit Doa Berbasis Web Daniel, Benny; Hendry, Hendry
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.14706

Abstract

Pengelolaan data yang baik memungkinkan institusi untuk menyimpan, mengakses, danmenganalisis informasi secara efektif untuk mendukung pengambilan keputusan yang lebihakurat. Namun, tanpa sistem yang terstruktur dan terintegrasi, data dapat sulit diatur, rentanterhadap kesalahan, dan berisiko hilang atau tidak terdokumentasi dengan baik. InstitusiPenerima Wajib Lapor (IPWL) merupakan institusi yang ditunjuk oleh pemerintah untukmemberikan layanan rehabilitasi bagi penyalahguna narkoba yang melaporkan diri secarasukarela. Dalam menjalankan fungsinya, IPWL Bukit Doa menangani berbagai data pasien,mulai dari riwayat kesehatan, program rehabilitasi yang diikuti, hingga perkembangan pasienselama masa rehabilitasi. Namun, pengelolaan data yang masih dilakukan secara manual ataumenggunakan sistem konvensional sering kali menyebabkan keterlambatan dalam mengaksesinformasi, risiko kehilangan data, dan kurangnya efisiensi dalam pelaporan dan pemantauanpasien. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem informasiberbasis web yang dapat membantu IPWL Bukit Doa dalam mengelola data pasien rehabilitasisecara lebih sistematis dan efisien. Sistem ini dirancang agar mudah digunakan oleh tenagakesehatan dan petugas rehabilitasi, serta dapat diintegrasikan dengan kebijakan dan proseduryang telah diterapkan di IPWL.
SISTEM INFORMASI PENJUALAN BERBASIS WEB MENGGUNAKAN METODE WATERFALL PADA TOKO FAMILY CELL Pratama Siregar, Hari Nanda; Suherman, Suherman; Hendry, Hendry
Indexia Vol. 7 No. 1 (2025): INDEXIA : Informatics and Computational Intelligent Journal Volume 7 Nomor 1 Me
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/indexia.v7i1.9653

Abstract

Sales information systems are an important component in supporting the efficiency and effectiveness of business operations, especially in the retail sector such as Toko Family Cell. The recording process that is still done manually causes various obstacles, such as inaccuracy in sales reports, errors in stock recording, and slow decision-making processes. This study aims to design and develop a web-based sales information system using the Waterfall method consisting of five stages: needs analysis, design, implementation, testing, and maintenance. The system developed only has one user level, namely admin, in accordance with the needs of the store which is only managed by the owner and one employee. The main features in this system include login, product data management (card and voucher stock), sales transactions and balance top-ups, and report printing. The system has been tested using the Lighthouse method which showed positive results. In addition, a simple embedding algorithm is applied to represent product data in numeric form to support the development of product recommendation features in the future. The final results show that this system is able to increase the speed, accuracy, and ease of transaction processes and sales data management at Toko Family Cell.
ANALYSIS OF LAND COVER CHANGE IN MOROWALI USING LANDSAT 8 SATELLITE IMAGERY AND UNSUPERVISED CLASSIFICATION METHOD Benedictus Lanang Ido Hernanto; Hendry, Hendry
International Journal of Social Science Vol. 5 No. 2: Agustus 2025
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/ijss.v5i2.10997

Abstract

Land use changes reflect the ecological and socio-economic dynamics of a region. This study aims to analyze land cover changes using Landsat 8 satellite imagery with the unsupervised classification method. Land cover is categorized into five classes: light vegetation, dense vegetation, rice fields, plantations, and settlements and mining areas. The analysis was conducted by comparing data from 2013 and 2018. The results indicate a significant increase in the area of mining and settlements by 71.60 km² and 476.88 km², respectively. Conversely, the area of rice fields and light vegetation decreased by 1117.93 km², natural canopy decreased by 672.03 km², and plantations decreased by 524.84 km². These findings indicate land conversion from natural vegetation to non-vegetative areas due to mining industry expansion and settlement growth. This study provides valuable insights for more sustainable land-use planning in the future
Implementasi Algoritma Clustering K-Means untuk Segmentasi Pelanggan di E-Commerce Mado, Priscianus Mikael Kia; Hendry, Hendry
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 3 (2025): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i3.1563

Abstract

In the increasingly advanced digital era, competition in the e-commerce world requires companies to understand customer behavior in depth in order to maintain loyalty and increase sales. This study aims to segment e-commerce customers by applying the K-means clustering algorithm using RFM (Recency, Frequency, Monetary) analysis. Customer transaction data is processed through pre-processing stages such as data cleaning and normalization, then the K-means algorithm is applied to group customers into homogeneous segments based on their purchasing behavior characteristics. Optimal grouping is obtained using the Silhouette Score evaluation metric, resulting in three main customer segments. The results of this segmentation can help companies design more effective and focused marketing strategies according to the needs of each customer segment.
Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm purbaratri, Winny; Purnomo, Hindriyanto Dwi; Manongga, Danny; Setyawan, Iwan; Hendry, Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
Analisis sentimen ulasan tamu terhadap layanan hotel menggunakan pendekatan machine learning Gunawan, Ricardho; Hendry, Hendry
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 4 No 3 (2025): IT-Explore Oktober 2025
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v4i3.2025.pp295-306

Abstract

Sentiment analysis of guest reviews is a crucial aspect in improving the quality of hotel services. This study aims to analyze the sentiment of guest reviews regarding the services of Grand Diamond Hotel Yogyakarta using a machine learning approach with the Support Vector Machine (SVM) algorithm. SVM was chosen because it can handle high-dimensional data such as text and is capable of forming an optimal separating hyperplane between sentiment classes. The research data was obtained through web scraping from Traveloka, yielding 1,119 reviews, which were processed through preprocessing, translation, and sentiment labeling using the TextBlob library. After TF-IDF weighting, the data was divided into 80% for training and 20% for testing. The linear kernel SVM model achieved 80% accuracy in classifying the reviews into positive, negative, and neutral categories. The results of this study were implemented in a web-based application equipped with data visualization and model evaluation features, allowing hotel management to efficiently monitor and analyze guest sentiment and support data-driven service quality improvement.
Prediction of the Birth Rate of Babies at Regional Hospitals in Salatiga City Using the Naïve Bayes Algorithm Saputri, Adelliya Dewi; Hendry, Hendry
Advance Sustainable Science, Engineering and Technology Vol 6, No 2 (2024): February - April
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i2.18466

Abstract

Birth rates have a significant impact on population growth and large populations can be a burden on development. In the Salatiga City Regional Hospital, the numbers tend to change every year, with the current population density making it a special concern for the City of Salatiga. Therefore, it is hoped that the application of Data Mining Techniques with the Naive Bayes algorithm can help predict the number of births in the future using the RapidMiner Application. In this research, the population used was Population Data from Salatiga City with a total of 989,674 residents. Then the sample used was 4699 babies from the Salatiga City Regional Hospital. All data was taken from 2019 – 2023 by conducting observations, literature studies and documentation. By analyzing the pattern of each variable and testing the training data against the testing data, a calculation was produced which shows the Testing Data Prediction, namely the "High" label with the number 4.77192E-06, with this the predicted result of the Baby Birth Rate in the Salatiga City Regional Hospital which is influenced by Population Density in 2024 it will be even higher.
A Comparison Support Vector Machine, Logistic Regression And Naïve Bayes For Classification Sentimen Analisys user Mobile App Baihaqi, Kiki Ahmad; Setyawan, Iwan; Manongga, Danny; Purnomo, Hendryanto Dwi; Hendry, Hendry; Fauzi, Ahmad; Hananto, Aprilia
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.962

Abstract

Data is the most important thing, the use of data can be useful to get an evaluation from the user of a system or application that is built based on mobile. Not only, the assessment or acceptance results of mobile applications during the trial stage are considered important, assessments and comments from direct users are also important things that can be input for mobile application developers. Data mining, or known in English as data mining, is the answer to the process of retrieving data on any media. In this research, data mining is carried out on the media mobile application download service provider Google Playstore, which provides data in the form of comments and ratings. After scraping the data and obtaining the latest data parameters determined by the latest 2000 comments, the data is pre-processed by removing the emot icon character and eliminating unneeded variables so that the data obtained can be processed to the next stage, namely classification based on ratings and sentiment comments. The algorithms used or compared in this research are Support Vector machine, logistic regression and naïve bayes which are known to be reliable in data mining processing. In this research, the accuracy results are 88% for SVM, 90.5% for Logistic Regression and 91% for naïve bayes.
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