Article Per Year (5 Year)
p-Index From 2021 - 2026
8.547
P-Index
This Author published in this journals
All Journal Jurnal Pendidikan Vokasi Jurnal Pendidikan Teknologi dan Kejuruan Voteteknika (Vocational Teknik Elektronika dan Informatika) JTEV (Jurnal Teknik Elektro dan Vokasional Jurnal Pendidikan Indonesia Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Jurnal Penelitian Pendidikan IPA (JPPIPA) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JETL (Journal Of Education, Teaching and Learning) JTP - Jurnal Teknologi Pendidikan Jurnal Teknologi Informasi dan Pendidikan PAKAR Pendidikan INCARE Journal of Innovation in Educational and Cultural Research Jurnal Pengabdian UNDIKMA Jurnal Vokasi Informatika (JAVIT) Abdimas Indonesian Journal Scientica: Jurnal Ilmiah Sains dan Teknologi Jurnal Teknik Komputer dan Informatika (JTeKI) Journal of Hypermedia & Technology-Enhanced Learning Jurnal Informatika: Jurnal Pengembangan IT The Indonesian Journal of Computer Science HUMANIORASAINS Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Akademika Dinasti Information and Technology
Yeka Hendriyani
Universitas Negeri Padang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Nursing Physics Public Health Social Sciences Transportation Other

Published : 98 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 98 Documents
Search

 6   7   8   9   10 
Pengembangan Media Pembelajaran Berbasis Android pada Mata Kuliah Pemrograman Visual dengan Metode Addie Juanda, Yeni Marita; Hendriyani, Yeka
Jurnal Vokasi Teknik Informatika Vol 2 No 1 (2022)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/javit.v2i1.81

Abstract

Learning media is a medium used to support learning and teaching proccess. Through the use of learning media, both educators and students can be facilitated by using learning media. The development of learning media aims to improve the quality and quantity of understanding and comprehending of a teaching material for each student. The learning media in the Visual Programming course of the Informatics Engineering Education Study Program, Department of Electronics Engineering, FT UNP usually uses a jobsheet. Since the Corona Virus Disease 2019 (Covid-19) pandemic, the lecture process for these courses, both lecturers and students, has been facing several problems. One of the problems experienced is that direct interaction in the FT UNP Laboratory cannot be carried out when doing this practicum. According to the problems occured, it is required to develop a learning media. The solution given to these problems is to develop a video tutorial-based learning median. Development of video tutorial-baseds learning median aims to support the learning process in Visual Programming courses for students of the Informatics Engineering Education Study Program. The method used in the development of this learning media is ADDIE. Video tutorial-based learning media developed by utilizing Camtasia Studio 8.0 and Android Studio as the main tools. This learning media provides several main menus including RPS, materials, videos, quizzes, scores, and about. Through this learning media application, both students and lecturers will be helped in organizing teaching and learning activities both online and offline.
An Analysis of Factors Influencing Vocational Graduates’ Decision to Pursue Higher Education in Computer and Informatics Engineering Silvia Gina Rahayu Alvi; Resmi Darni; Yeka Hendriyani; Legiman Slamet
Jurnal Vokasi Teknik Informatika Vol 5 No 2 (2025)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/javit.v5i2.255

Abstract

In the context of global competition and rapid technological advancement, vocational education plays a critical role in preparing students for direct entry into the workforce. Nevertheless, a growing number of vocational graduates are choosing to pursue higher education as a means to expand their career opportunities and social mobility. This study investigates the factors influencing such decisions, focusing on students from the Computer and Informatics Engineering Department at a vocational school in Indonesia. Using a mixed-methods design, quantitative data were gathered through structured questionnaires administered to 12th-grade students, while qualitative insights were obtained via in-depth interviews. The analysis reveals that Better Career Opportunities, Family Support, and Social Environment all have a statistically significant effect on students’ decisions to pursue tertiary education. Among these, Social Environment emerged as the most influential factor, accounting for 32.4% of the variance, followed by Family Support (3.1%) and Career Opportunities (3.1%). These findings underscore the importance of peer influence, school climate, and familial encouragement in shaping educational aspirations beyond vocational training. The results contribute to a deeper understanding of post-secondary transition dynamics in vocational contexts and provide implications for policy and practice aimed at supporting students' academic advancement.
Ordering Information System Design Weddings Organizer Putri Minang uses YII2 Framework Maulana Putra, Risky; Hendriyani, Yeka
Dinasti Information and Technology Vol. 1 No. 1 (2023): Dinasti Information and Technology (July 2023)
Publisher : Dinasti Research & Yayasan Dharma Indonesia Tercinta (DINASTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dit.v1i1.255

Abstract

Wedding Organizer is services that work in a manner personal For help candidate bride in planning And supervision implementation party wedding in accordance timetable And budget that has set . Objective study This is produce design For build application web- based that provides service related booking at the Princess Wedding Organizer Minang does the ordering process product during This done Still the manual way then need built system information in a manner hurry And more easy . Where system information this is made use use Object Oriented Programming (OOP) concepts and use Unified Modeling Language (UML) modeling . Frameworks used is Yii2 with Language mainly PHP and Java Script. Analysis observation system walk covers a number business processes and data against service booking . Testing to results developed design _ showing that application can used as where should , be proper service _ complete application _ And capable help with the ordering process product.
Rancang Bangun Kamus Digital Komputer Mobile dengan Algoritma Knuth Morris Pratt dan Fitur Text-to-Speech Fahlevi, Muhammad Farel; Darni, Resmi; Hendriyani, Yeka; Sriwahyuni, Titi
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.26856

Abstract

Kamus digital merupakan solusi efektif untuk mengatasi keterbatasan kamus cetak, khususnya dalam hal aksesibilitas dan kecepatan pencarian. Penelitian ini bertujuan untuk mengembangkan kamus digital komputer berbasis mobile dengan penerapan algoritma Knuth-Morris-Pratt sebagai optimasi pencarian, serta integrasi Fitur Text-to-Speech untuk mendukung pelafalan istilah secara real-time. Pengembangan dilakukan menggunakan model prototyping dengan penerapan React Native sebagai antarmuka pengguna, Node.js sebagai pengelola backend, dan MySQL sebagai basis data. Hasil pengujian menunjukkan bahwa algoritma Knuth-Morris-Pratt mampu memberikan waktu respons pencarian rata-rata antara 0,0048 hingga 0,1539 milidetik untuk kata kunci dengan panjang 3 hingga 15 karakter. Fitur Text-to-Speech berhasil menghasilkan pelafalan istilah secara langsung dengan kualitas suara yang jelas dan respons cepat. Uji praktikalitas dan efektivitas menunjukkan skor masing-masing sebesar 89 persen dan 91 persen, yang mengindikasikan aplikasi sangat praktis dan efektif. Dengan demikian, aplikasi TechVocab dinilai layak menjadi media referensi istilah komputer dengan performa tinggi dan antarmuka yang intuitif.
Analisis Sentimen Ulasan Pengguna Aplikasi Bibit Menggunakan Algoritma Naive Bayes dan K-Nearest Neighbors (KNN) Azmi, Arafil; Hendriyani, Yeka; Dewi, Ika Parma; Budayawan, Khairi
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.27464

Abstract

Perkembangan aplikasi investasi digital seperti Bibit menuntut pemahaman mendalam terhadap persepsi pengguna. Penelitian ini menganalisis sentimen ulasan pengguna aplikasi Bibit di Google Play Store menggunakan algoritma Naïve Bayes dan K-Nearest Neighbors (KNN). Sebanyak 2.586 ulasan dikumpulkan, kemudian diproses melalui pelabelan data, praproses teks, pemberian bobot menggunakan TF-IDF, dan klasifikasi dengan rasio data latih-uji 60:40, 70:30, 80:20, dan 90:10. Hasil penelitian menunjukkan bahwa sentimen positif mendominasi dengan persentase 74,2%, sedangkan sentimen negatif sebesar 25,8%. Naïve Bayes unggul dengan akurasi tertinggi 89,70% pada rasio 90:10, dengan presisi dan recall yang seimbang serta stabilitas yang lebih baik dibandingkan KNN yang mencapai akurasi tertinggi 88,84%, tetapi fluktuatif. Temuan ini merekomendasikan Naïve Bayes sebagai algoritma yang konsisten untuk analisis sentimen ulasan aplikasi investasi. Hasil penelitian ini dapat menjadi referensi berbasis data bagi calon investor dalam pengambilan keputusan.
Penerapan Pipeline ETL Apache Airflow Menggunakan Algoritma Collaborative Filtering untuk Pemberian Rekomendasi Gastrodiplomasi Indonesia Ramadhan, Heri; Hendriyani, Yeka; Sriwahyuni, Titi; Resmidarni, Resmidarni
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.27485

Abstract

Gastrodiplomasi, sebagai strategi diplomasi budaya melalui kuliner, memerlukan pendekatan berbasis data untuk meningkatkan efektivitasnya. Penelitian ini mengembangkan sistem rekomendasi berbasis Collaborative Filtering dan pipeline ETL (Extract, Transform, Load) menggunakan Apache Airflow untuk mengintegrasikan data survei rempah (2021-2024), restoran internasional, dan distribusi bumbu. Data diolah dengan algoritma user-based untuk merekomendasikan kombinasi bumbu, menu, serta strategi promosi restoran Indonesia di pasar global. Hasil evaluasi menunjukkan akurasi tinggi dengan Nilai MAE 0,058-0,088, yang menegaskan kemampuan sistem dalam memprediksi preferensi pasar. Analisis hasil divisualisasikan melalui dashboard Tableau interaktif, memudahkan pemantauan tren distribusi rempah dan preferensi kuliner secara real-time. Penelitian ini membuktikan efektivitas integrasi workflow ETL terotomatisasi dengan analitik machine learning untuk mendukung diplomasi berbasis data. Sistem yang dikembangkan tidak hanya menyediakan rekomendasi strategis bagi promosi kuliner Indonesia, tetapi juga menawarkan kerangka kerja yang dapat diadaptasi untuk skala lebih luas. Ke depannya, pengembangan model hybrid dan integrasi data real-time dapat meningkatkan presisi rekomendasi serta responsivitas kebijakan. Temuan ini menjadi langkah awal dalam membangun praktik gastrodiplomasi Indonesia yang lebih terukur dan adaptif terhadap dinamika pasar global.
Penerapan Data Mining Untuk Klasifikasi Calon Siswa Penerima Program Indonesia Pintar (PIP) Menggunakan Algoritma Naive Bayes Suciko, Adelina; Hendriyani, Yeka; Budayawan, Khairi; Syafrijon, Syafrijon
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.27930

Abstract

Program Indonesia Pintar (PIP) merupakan bantuan pendidikan yang ditujuakan bagi siswa dari keluarga kurang mampu. Namun, proses penentuan kelayakan penerima di sekolah masih dilakukan secara manual sehingga rawan ketidaktepatan sasaran. Penelitian ini bertujuan untuk membangun model klasifikasi kelayakan penerima PIP menggunakan algoritma Naive Bayes. Data yang digunakan mencakup 379 siswa dengan atribut penghasilan ayah, penghasilan ibu, jumlah saudara kandung, penerima KIP, penerima KPS serta status layak PIP. Tahapan klasifikasi dilakukan menggunakan perangkat lunak Orange dan hasilnya divisualisasikan melalui Tableau. Model dievaluasi dengan metrik akurasi, precision, recall dan AUC. Hasil menunjukkan bahwa model memiliki akurasi 85,9%, precision 86,3%, recall 85,9% dan AUC 0,973. Visualisasi membantu memperjelas distribusi dan kelayakan PIP. Model ini dapat mendukung keputusan yang lebih objektif dalam penyaluran bantuan PIP.
Implementasi Model Yolov8 untuk Deteksi Jenis Sampah Organik dan Anorganik Berbasis Android Ridha, Muhammad Rasyid; Syafrijon, Syafrijon; Hendriyani, Yeka; Hadi, Ahmaddul
Abdimas Indonesian Journal Vol. 5 No. 1 (2025)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v5i1.655

Abstract

The mismanagement of waste poses serious environmental and public health issues in Indonesia, exacerbated by the increasing volume of waste due to population growth. To address this problem, this research develops a mobile application based on Flutter, utilizing YOLOv8 object detection technology to classify organic and inorganic waste. The application aims to simplify household waste sorting, raise public awareness, and support better and more sustainable waste management. The research methodology involves using a dataset of waste images trained with the YOLOv8 algorithm via google colab. The dataset is divided into training (70%), testing (20%), and validation (10%) portions. The model training process is conducted over 25 and 50 epochs, showing improved accuracy with more epochs. At the 50th epoch, the model achieved a precision of 0.81 and a recall of 0.61, demonstrating good performance in detecting and classifying waste. The implementation of this application is expected to facilitate waste sorting, reduce environmental pollution, and improve public health. Recommendations for further development include enhancing detection accuracy, expanding the range of detectable waste types, and optimizing application performance to ensure a better user experience.
The Effect of Teaching Factory, Industrial Work Practices and Vocational Competence Through Self-Efficacy on Work Readiness of Vocational High School Students Hatta, Mega Amelia Prihatini; Rizal, Fahmi; Rahmiati, Rahmiati; Hendriyani, Yeka
JETL (Journal of Education, Teaching and Learning) Vol 10 (2025): Special Issue
Publisher : STKIP Singkawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26737/jetl.v10i1.7095

Abstract

This study aims to examine the effect of Teaching Factory (TeFa), Industrial Work Practices (Prakerin), and vocational competence on students' work readiness, with self-efficacy as a mediator. The method used is Systematic Literature Review (SLR), which collects and synthesizes various studies related to learners' work readiness, focusing on variables that play a role in vocational education. The findings show that Teaching Factory and Prakerin have an important role in improving learners' technical and non-technical skills, as well as bridging the gap between academic learning and industry needs. Self-efficacy was found to be a factor that strengthens learners' confidence and performance in the industrial environment. This study concludes that holistic development of technical competencies, work-based experiences, and strengthening self-efficacy can improve learners' readiness to face the challenges of the world of work. Further research needs to focus on the long-term impact of these programs as well as the role of teachers in facilitating industry-based learning
Deteksi Anomali menggunakan Isolation Forest pada Permintaan Kebutuhan Farmasi Pasien di Rumah Sakit Mitra Sejati Medan Novaldi, Farhan; Syafrijon, Syafrijon; Hendriyani, Yeka; Anwar, Muhammad
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.30808

Abstract

Rumah Sakit Mitra Sejati Medan menghadapi tantangan dalam mengelola volume permintaan farmasi yang tinggi, menyebabkan proses verifikasi manual menjadi tidak efisien dan berisiko. Penelitian ini bertujuan merancang dan mengimplementasikan sistem deteksi anomali untuk meningkatkan efektivitas pengelolaan permintaan. Metode yang digunakan adalah algoritma Isolation Forest dengan menerapkan metodologi Cross-Industry Standard Process for Data Mining. Data historis permintaan obat, barang medis habis pakai, dan alat kesehatan diolah menggunakan Python untuk melatih model secara kontekstual. Hasil penelitian menunjukkan dari 2.167.942 transaksi, model berhasil mengidentifikasi 13.503 (0,62%) permintaan sebagai anomali statistik. Sistem yang dikembangkan melalui aplikasi web ini terbukti berhasil menjadi alat bantu keputusan berbasis data untuk meningkatkan efisiensi operasional, akurasi stok, dan memberikan peringatan dini.
Co-Authors Afifah Rizki, Putri Agariadne Dwinggo Samala Agung Gemilang Ahmaddul Hadi, Ahmaddul Akbar Ilahi Akbar Ilahi Almasri Almasri Ambiyar, Ambiyar Amelia Zahra Anni Faridah Ardiyanti, Sri Arifin, Ari Syaiful Rahman Arita Arita Arita, Arita Ariyadi Armi Asmar Yulastri Asmara, Delvi Asrul Huda Aswardi Aswardi Aulia Putri, Rahilla Azizah, Fauzana Azmi, Arafil Bayu Ramadhani Fajri Bobby Rachman Budayawan, Khairi Budayawan, Khairi Cheng-Hong Yang Cheng-Hong Yang, Cheng-Hong Chintia Ningsih, Nur Dedy Irfan Dekry, Muhammad Reviza Delvi Asmara Deny Kurniadi Desi Susanti Dessy Hardeyenti Dhanil, Muhammad Dina Febrianti Dini Sumanti Dony Novaliendry Dony Novaliendy Edi Prasetio Effendi, Hastria Elfi Tasrif Emelsy, Nalurry Fadhilah Fadhli Ranuharja Fahlevi, Muhammad Farel Fahmi Rizal Fajri, Bayu Ramadhani Fanny Oktavia Farizi, Habib Al Fatni Mufit Fauzan Jamza Firdaus Firdaus Firza, Fahira Utami Fitri, Yolanda Idha Ganefri . Geovanne Farell Giatman, M Hadi Kurnia Saputra Hadi, Ahmadul Hafilah Hamimi Hafilah Hamimi Hafilah Hamimi, Hafilah Hamdani . Hamimi, Hafilah Hansi Effendi Hardeyenti, Dessy Hasan Maksum Hasnita, Sri Hastria Effendi Hatta, Mega Amelia Prihatini Hayati Rahmatika Hendra Hidayat Henny Yustisia Huda , Asrul Huda, Asrul Huda, Asrul Huda, Yasdinul Igor Novid Ika Parma Dewi Insan, Khoirul Irma Delianti , Vera Irma Delianti, Vera Islapirna Islapirna Jayadi, Ridho Dimas Tri Prasetyo Jayandra Jayandra Jefry Herianto Juanda, Yeni Marita Karmila Sari, Nanda Kasman Rukun Kasman Rukun Khairi Budayawan Khairy, Mubarakh Hayatna Kurniadi, Denny La Ode Alwin Syahputra Putra Laila Fajri Lathifah, Ulfi Latifah Annisa Lativa Mursyida Lativa Mursyida Legiman Slamet Lusi Tridarni Mariani Mariani Mariani Mariani Masrizal Masrizal Maulana Putra, Risky Mawarni, Junia Melri Deswina Muadzah, Kayla Nahda Muhammad Adri Muhammad Anwar Muhammad Anwar Muhammad Decky Andani Muhammad Rasyid Ridha Mukhaiyar, Riki Muskhir, Mukhlidi Mutiara Pertiwi Nabila Azzahra Shammi Nasution, Marsinah Dewi Feiyska Nizwardi Jalinus Nobi Albion Ziqkra Novaldi, Farhan Novaliendy, Dony Nurindah Dwiyani Nursyafti, Yolana Parma Dewi, Ika Pepi Resmanti Ponimin Purwanto, Wawan Putra, La Ode Alwin Syahputra Putra, Meiyaldi Eka Putri Khairunisak Putri, Alfiola Eka Putri, Dessy Hardeyenti Rahmatika, Hayati Rahmi Ramadhani Rahmi, Salsabila Tri Rahmiati Rahmiati Rakhel Cakra Sandika Ramadhan, Heri Resmi Darni Resmidarni, Resmidarni Reza Aurora Rizkayeni Marta Rizki Kurniawan, Rizki Rizky Ananda Ronaldo Ronaldo Saari, Erni Marlina SABRINA, ELSA Sandika, Rakhel Cakra Santuni, Nofrizal Silvia Gina Rahayu Alvi Sri Ardiyanti Sri Muliani Sianipar Suciko, Adelina Sukmawati, Murni Suriyani, Cici Syafrijon , Syafrijon Syafrijon, Syafrijon Titin Sriwahyuni Vera Indriani Vera Irma Delianti Vera Irma Delianti Wakhinuddin Waskito Waskito Yang, Cheng-Hong Yolanda Idha Fitri Yuda Putra Utama Yuliarnis, Sri Kurnia Yusmerita Yusmerita Zulhendra Zulhendra Zulhendra Zulhendra Zulhijra Rahma Dia Zulmi Arifah