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Hendry
Universitas Kristen Satya Wacana
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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IMPLEMENTATION OF MULTI-NODE SENSOR DATA DELIVERY USING THE MASTER-SLAVE METHOD IN LORA COMMUNICATION Hendry, Hendry; Manongga, Daniel
Journal of Technology Informatics and Engineering Vol. 3 No. 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.179

Abstract

This research explains the application of sending data from various sensor nodes using the master-slave method in Long Range (LoRa) communication. This system was created to increase efficiency and reliability in collecting sensor data spread across several locations. Sensor nodes function as slaves that collect and send data to the master. The master then processes and combines the data before sending it to a central server. Experimental results show that this method is successful in reducing latency and increasing data transmission speed and shows great potential for Internet of Things (IoT) applications that require wide communication range and low power consumption.
Pelatihan Pemanfaatan Gemini AI untuk Mendukung Pembelajaran pada SMA di Sumatera Utara Sukiman, Sukiman; Hendry, Hendry; Zuhanda, Muhammad Khahfi; Fenny, Fenny; Sjukun, Sjukun
Prioritas: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 01 (2024): EDISI MARET 2024
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/prioritas.v6i01.927

Abstract

Pada saat ini ditengah perkembangan teknologi informasi dan komunikasi yang pesat maka setiap individu diharapkan memiliki kemampuan untuk berpikir secara kritis dan sanggup merespon perkembangan zaman. Di sinilah peran teknologi, khususnya kecerdasan buatan (AI), menjadi penting dalam mendukung proses pembelajaran dan meningkatkan daya kritis siswa. Salah satu AI yang populer adalah Gemini AI. Model AI ini dikembangkan oleh Google. Gemini AI dapat memfasilitasi pembelajaran kolaboratif dan diskusi antara siswa. Platform ini memungkinkan siswa untuk bekerja sama dalam proyek, bertukar ide, dan saling memberikan umpan balik. Hal ini dapat meningkatkan kemampuan komunikasi, kerja sama tim, dan toleransi antar budaya. Kegiatan PKM ini dilaksanakan secara luring oleh Tim PKM untuk siswa SMA di Sumatera Utara. Hasil evaluasi post test menunjukkan adanya peningkatan pemahaman siswa terhadap pemanfataan Gemini AI. Selain itu juga respon siswa selama kegiatan PKM juga positif dan tim PKM berharap agar kegiatan ini dapat memberikan manfaat terhadap peningkatan kualitas pembelajaran pada SMA di Sumatera Utara.
Exploring Data Analytics in Attendance Systems: Unveiling Machine Learning Techniques, Patterns, Practices, and Emerging Trends Santoso, Joseph Teguh; Manongga, Danny; Setyawan, Iwan; Purnomo, Hindriyanto Dwi; Hendry
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.3438

Abstract

Purpose: The research aims to identify patterns and trends in attendance management through the application of reward and punishment systems as innovative solutions for improving employee attendance and well-being. Methods: This research utilizes a descriptive analysis approach with the application of Machine Learning (ML) techniques to enhance the accuracy of attendance pattern prediction and ML models for the classification of emerging trends and patterns. Research data were obtained through the company's attendance system and divided into two segments (80% for training and 20% for testing) while maintaining a balanced class proportion, then processed using SPSS and Python software with the Scikit-learn library. Result: The results of the study show that employee attendance is increased from 86.52% to 90.44% when the reward and punishment method is applied to the employee attendance system. Proper reward allocation can increase employee motivation to adhere to work schedules and consistently attend, while punishment tends to lead to lower attendance rates. Novelty: This research emphasizes the optimization of attendance management through data analytics approaches and the implementation of advanced technology in attendance systems with the application of ML techniques to analyze attendance data comprehensively and detect significant patterns.
Memberdayakan Dosen melalui Kepemimpinan Pelayan: Pengaruh Literasi Digital dan Adaptasi Budaya Susanto, Agus; Wijaya, Elyzabeth; Hendry, Hendry; Nabella, Septa Diana; Rivaldo, Yandra
Society Vol 12 No 2 (2024): Society
Publisher : Laboratorium Rekayasa Sosial, Jurusan Sosiologi, FISIP Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/society.v12i2.781

Abstract

This study examines the impact of digital literacy and adaptable culture on lecturer performance, with servant leadership as a mediating variable. The Institute of Information Technology and Business executed the study, with several lecturers participating as responders. Digital literacy is a crucial component in the age of technological transition, whereas adaptable culture signifies an institution’s capacity to adjust to evolving environmental conditions. This study proposes that servant leadership, prioritizing service-oriented leadership, mediates the association among digital literacy, adaptable culture, and lecturer performance. This study uses a validated questionnaire to gather data through a quantitative methodology and survey technique. We employ route analysis methodologies to examine the interrelationships among variables. The study’s outcomes are anticipated to elucidate how digital literacy and adaptable culture might enhance professor performance by reinforcing servant leadership conduct. These findings hold significant implications for formulating higher education policies, particularly in addressing the challenges of the digital age and the intricacies of the professional landscape. This study offers theoretical contributions by enhancing the comprehension of the interplay between digital literacy, corporate culture, and leadership within an academic framework.
PENGABDIAN DALAM PENDAMPINGAN DAN PEMBINAAN PEMBUKUAN SEDERHANA SEBAGAI BAHAN EVALUASI TERHADAP KEBERLANGSUNGAN USAHA PADA UMKM DI DESA BINTAN BUYU Indriaty, Novica; Kurnia, Sri; Meifari, Vanisa; Novrina, Putri Dwi; Hendry, Hendry
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 (2024): Vol. 5 No. 6 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i6.40500

Abstract

Laporan keuangan merupakan aspek terpenting dalam sebuh usaha, sekecil apa pun usaha yang dijalani perlu adanya pelaporan dalam hal pembukuan. Pembukuan yang baik mencerminkan tingkat kesehatan usahanya. Dengan adanya pembukuan pelaku UMKM dapat mengevaluasi perkembangan usahanya baik yang sekarang dan yang akan datang. Laporan keuangan dapat menjadi syarat dalam perolehan modal dari pihak ketiga dan sebagai syarat dalam penerimaan bantuan dari pemerintah. Melalui metode pendampingan dan pelatihan diharapkan masyarakat Desa Bintan Buyu dapat mengaplikasikan ilmu yang diberikan sehingga dapat mengevaluasi perkembangan usahanya. Pelaporan keuangan menjadi salah satu masalah yang sering kali terabaikan oleh para pelaku UMKM, khususnya berkaitan dengan penerapan kaidah-kaidah pelaporan keuangan dan akuntansi yang benar.
Application of the PIECES Framework Method in E-Report Evaluation Sholikin, Muhammad; Sediyono, Eko; Hendry, Hendry
Jurnal Penelitian Pendidikan IPA Vol 9 No SpecialIssue (2023): UNRAM journals and research based on science education, science applic
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9iSpecialIssue.6028

Abstract

The evaluation of the E-report application at SMK N 1 Banyudono is integral for assessing its alignment with the latest curriculum guidelines and its effectiveness in meeting students' learning and assessment needs. This evaluation ensures that learning support technologies, such as E-report, stay relevant, responsive to user needs, and supportive of the school's long-term educational objectives. Using the PIECES method, the assessment of user satisfaction comprehensively considers Performance, Information, Economy, Control, Efficiency, and Services indicators. The Likert scale aids in gauging user satisfaction across various aspects. Quantitative data analysis involves 26 respondents, including teachers, homeroom teachers, curriculum staff, and school principals, providing a holistic perspective on learning and assessments management. The PIECES method and Likert scale evaluation reveal a satisfaction level of 4.52, categorizing it as "SATISFIED." This comprehensive assessment covers system performance, information accuracy, cost-effectiveness, system control ease, time efficiency, and service flexibility. The qualitative descriptive approach using the PIECES method and Likert scale identifies areas for improvement, ensuring the E-report application remains efficient, relevant, and aligned with DITJEN VOKASI guidelines
YOLOv8 Analysis for Vehicle Classification Under Various Image Conditions Panja, Eben; Hendry, Hendry; Dewi, Christine
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49038

Abstract

Purpose: The purpose of this research is to detect vehicle types in various image conditions using YOLOv8n, YOLOv8s, and YOLOv8m with augmentation.Methods: This research utilizes the YOLOv8 method on the DAWN dataset. The method involves using pre-trained Convolutional Neural Networks (CNN) to process the images and output the bounding boxes and classes of the detected objects. Additionally, data augmentation applied to improve the model's ability to recognize vehicles from different directions and viewpoints.Result: The mAP values for the test results are as follows: Without data augmentation, YOLOv8n achieved approximately 58%, YOLOv8s scored around 68.5%, and YOLOv8m achieved roughly 68.9%. However, after applying horizontal flip data augmentation, YOLOv8n's mAP increased to about 60.9%, YOLOv8s improved to about 62%, and YOLOv8m excelled with a mAP of about 71.2%. Using horizontal flip data augmentation improves the performance of all three YOLOv8 models. The YOLOv8m model achieves the highest mAP value of 71.2%, indicating its high effectiveness in detecting objects after applying horizontal flip augmentation. Novelty: This research introduces novelty by employing the latest version of YOLO, YOLOv8, and comparing its performance with YOLOv8n, YOLOv8s, and YOLOv8m. The use of data augmentation techniques, such as horizontal flip, to increase data variation is also novel in expanding the dataset and improving the model's ability to recognize objects.
PENGENALAN GAME EDUKASI BAGI SISWA TK KRISTEN 1 SATYA WACANA SALATIGA USIA 5-6 TAHUN Anton Hermawan; Nataliani, Yessica; Hindriyanto Dwi Purnomo; Christianto, Erwien; Atik Setyanti, Angela; Yulia, Hanita; Krismiyati; Juliastomo Gundo, Adriyanto; Wellem, Theophilus; Hendry
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.12302

Abstract

Kemajuan teknologi informasi dan komunikasi menuntut adanya adaptasi dalam dunia pendidikan, termasuk pada jenjang pendidikan anak usia dini. Pengenalan teknologi sejak dini menjadi langkah strategis dalam membentuk kesiapan anak menghadapi era digital. Kegiatan pengabdian ini bertujuan untuk mengenalkan teknologi, khususnya komputer, kepada siswa Taman Kanak-kanak (TK) melalui game edukasi berbasis online. Kegiatan dilaksanakan secara luring di TK Kristen 1 Satya Wacana, Salatiga, dengan melibatkan siswa berusia 5–6 tahun. Metode pelatihan dilakukan dalam beberapa sesi, mencakup pengenalan bagian-bagian komputer, penggunaan mouse, serta pelatihan melalui game edukasi seperti pengenalan huruf, angka, bentuk geometri, dan jenis-jenis kendaraan. Hasil evaluasi menunjukkan bahwa siswa menunjukkan antusiasme tinggi selama pelatihan, serta mulai mengenal komputer sebagai media pembelajaran alternatif selain perangkat yang biasa digunakan di rumah seperti handphone dan tablet. Kegiatan ini membuktikan bahwa pendekatan belajar sambil bermain dengan teknologi dapat meningkatkan minat belajar dan keterampilan dasar siswa dalam menggunakan komputer.
Implementasi Sistem Informasi Pengaduan Masyarakat Berbasis Web dengan Automatic Ticketing Workflow Hendry, Hendry; Supiyandi, Supiyandi; Rizal, Chairul; Eka, Muhammad; Zulham, Zulham
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.694

Abstract

Penanganan pengaduan masyarakat sering terhambat oleh proses manual yang tidak terstruktur, menyebabkan respons yang lambat dan hilangnya riwayat penanganan. Penelitian ini mengembangkan dan menerapkan Sistem Informasi Pengaduan Masyarakat berbasis web yang dilengkapi dengan mekanisme automatic ticketing workflow untuk memastikan setiap laporan tercatat, terverifikasi, dan dialirkan ke unit terkait secara otomatis. Sistem dirancang menggunakan arsitektur modular dengan fitur inti berupa pelacakan status tiket, notifikasi otomatis, serta dashboard analitik untuk memantau kinerja penanganan. Metode pengembangan yang digunakan adalah pendekatan waterfall dengan tahapan analisis kebutuhan, desain sistem, implementasi, dan pengujian. Hasil penerapan menunjukkan bahwa otomatisasi alur tiket mampu mempersingkat waktu disposisi, meningkatkan akurasi distribusi laporan, dan memberikan transparansi proses bagi pengguna maupun admin. Pengujian fungsional juga menunjukkan tingkat keberhasilan fitur sebesar lebih dari 95%, menandakan sistem berjalan stabil dan memenuhi kebutuhan operasional. Temuan ini menegaskan bahwa integrasi automatic ticketing dalam sistem pengaduan mampu meningkatkan efisiensi, akuntabilitas, serta kualitas pelayanan publik.
Prediksi Harga Saham Menggunakan Model Multivariate Long Short-Term Memories Mahulete, Ebenhaezer Yohanes Abdeel; Hendry, Hendry
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7978

Abstract

This study aims to develop and evaluate a stock price prediction model for Bank Central Asia (BBCA) using a multivariate Long Short Term Memory (LSTM) approach. The model utilizes four key variables from historical stock data open, high, low, and close prices and is compared to a univariate model that uses only the closing price as input. The research process includes data preprocessing, LSTM architecture design, model training over 200 epochs, and performance evaluation using MAE, RMSE, and MAPE metrics. The results demonstrate that the multivariate LSTM model provides higher predictive accuracy, achieving a MAPE of 2.41%, outperforming the univariate model which recorded 2.71%. Moreover, the multivariate model shows better stability across validation and test data, and greater adaptability in capturing market dynamics. Prediction result visualizations support these findings, with the multivariate model producing more consistent forecasts that closely follow actual data. These results suggest that integrating OHLC variables enhances prediction accuracy and model reliability. This study contributes to the advancement of stock price prediction systems based on deep learning and serves as a valuable reference for investors and decision-makers in designing more data-driven investment strategies.
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 Darwin Lie 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 Giarti, Giarti 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 Kristoko Dwi Hartomo 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 Nalbraint Wattimena Nansy Stephanie Mongi Nugraha, Febrina Tesalonika Panja, Eben Paryono, Tukino Pratama Siregar, Hari Nanda Pratama, Arya Damar Purnomo, Hendryanto Dwi Putri Dwi Novrina Raden Mohamad Herdian Bhakti Ramos Somya Ravensca Matatula Ravensca Matatula Richard V. Llewelyn Rizal, Chairul Robertus Bagaskara Radite Putra Ronny Julians, Adhe Rostina, Cut Fitri Rung Ching Chen Santoso, Joseph Teguh Saputri, Adelliya Dewi Septhiani, Angeline Sholikin, Muhammad Simanjuntak, Dahnil Anzar Sjukun Suharyadi Suherman, Suherman Sukiman Sukiman Supiyandi Supiyandi Susanta, Vonny A. Sutarto Wijono Suvirocana, Suvirocana 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