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Riau Jurnal Teknik Informatika
Published by Universitas Pasir Pengaraian
ISSN : -     EISSN : 28292529     DOI : https://doi.org/10.30606/rjti.v1i1
Core Subject : Science,
Computer Science & IT
Riau Jurnal Teknik Informatika dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian bidang ilmu komputer dan teknologi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Ilmu Komputer dan Teknologi. Riau Jurnal Teknik Informatika menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 115 Documents
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Klasifikasi Ekspresi Wajah Menggunakan Convolutional Neural Networks (CNN) pada Dataset FER-2013 Kodoati, Hizkia; Rengkung, Chezkiel; Takalamingan, Gerald; Yusupa, Ade; Tarigan, Victor
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3252

Abstract

Automatic facial expression recognition has become a rapidly growing research field driven by advancements in artificial intelligence and computer vision. However, facial expression classification still faces challenges, particularly in distinguishing expressions with similar characteristics. This study aims to develop a facial expression classification model using Convolutional Neural Networks (CNN) on the FER-2013 dataset. The research stages include data collection and preprocessing, CNN architecture design, model training using the Adam optimizer and categorical crossentropy loss function, and performance evaluation based on accuracy and the confusion matrix. The results indicate that the CNN model can recognize various facial expressions, achieving a maximum validation accuracy of 67.8%. Nevertheless, the model is still able to distinguish certain expressions accurately. Utilizing pretrained models such as VGG-16 or ResNet and implementing transfer learning techniques could enhance model accuracy and stability. With further development, this model has the potential to be applied in various fields, including facial expression-based security systems, human-computer interaction, and emotion analysis.
PENGEMBANGAN LEARNING MANAGEMENT SYSTEM (LMS) BERBASIS WEBSITE UNTUK MENINGKATKAN EFEKTIVITAS DAN EFISIENSI PEMBELAJARAN Panyili, Anwar S.; Sukardi; Alfonsius, Eric
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3254

Abstract

Penelitian ini bertujuan untuk membangun Learning Management System (LMS) berbasis website sebagai media pembelajaran yang mendukung proses belajar mengajar secara daring. Sistem yang dikembangkan memiliki fitur utama seperti manajemen pengguna, pengelolaan materi pembelajaran, forum diskusi, serta evaluasi pembelajaran yang dapat diakses oleh guru dan siswa.Metode pengembangan sistem menggunakan metode SDLC model waterfall, dengan tahapan analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Alat bantu pengembangan sistem menggunakan Unified Modeling Language (UML), sementara pengujian sistem dilakukan dengan metode BlackBox untuk memastikan semua fitur berfungsi dengan baik. Selain itu, evaluasi kelayakan sistem dilakukan menggunakan Skala Likert untuk mengukur tingkat efektivitas dan efisiensi pembelajaran siswa. Hasil pengujian menunjukkan bahwa seluruh fitur utama, termasuk fungsi tambah, edit, hapus, dan pencarian, bekerja sesuai harapan. Evaluasi menggunakan metode BlackBox menunjukkan keberhasilan implementasi dengan tingkat keberhasilan 100%, sedangkan hasil evaluasi efisiensi dan efektivitas penggunaan berdasarkan Skala Likert mencapai 82.22%, yang masuk dalam kategori Sangat Baik. Penelitian ini yang telah dikembangkan ini mampu meningkatkan efektivitas dan efisiensi dalam proses pembelajaran daring. Sistem ini memberikan kemudahan bagi guru dalam mengelola materi pembelajaran serta membantu siswa dalam mengakses dan memahami materi secara lebih fleksibel.
Pengembangan Sistem Informasi Geografis Berbasis Website untuk Optimalisasi Pengelolaan Kepemilikan Tanah Alfonsius, Eric; Kasim, Rachmat
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3258

Abstract

Pengelolaan data kepemilikan tanah yang akurat dan transparan merupakan aspek penting dalam administrasi pertanahan. Namun, banyak wilayah masih mengandalkan pencatatan manual yang rentan terhadap kesalahan, duplikasi data, dan kurangnya aksesibilitas informasi. Penelitian ini bertujuan untuk mengembangkan Sistem Informasi Geografis (SIG) berbasis website yang memungkinkan pemetaan kepemilikan tanah secara digital dan interaktif guna meningkatkan efisiensi serta transparansi dalam pengelolaannya. Dalam penelitian ini, sistem berhasil dikembangkan dengan fitur utama seperti pemetaan interaktif berbasis GIS, manajemen data kepemilikan tanah, pencarian berbasis atribut, serta akses pengguna berbasis peran. Teknologi yang digunakan mencakup PHP, MySQL, dan Leaflet.js untuk mendukung visualisasi geografis yang akurat. Pengujian sistem dilakukan menggunakan metode Black Box Testing untuk mengevaluasi fungsionalitas, serta uji kepuasan pengguna untuk mengukur efektivitas dan kemudahan penggunaan sistem. Hasil pengujian menunjukkan bahwa sistem mampu menampilkan data kepemilikan tanah dengan akurasi tinggi, meningkatkan efisiensi pencarian informasi hingga 60% dibandingkan metode konvensional, serta memperoleh tingkat kepuasan pengguna sebesar 85%. Dengan demikian, sistem ini dapat menjadi solusi efektif dalam digitalisasi administrasi pertanahan, mengurangi potensi sengketa, serta mendukung perencanaan tata ruang berbasis data yang lebih baik.
Analisis Sistem Pendukung Keputusan dalam Pemilihan Obat untuk Pasien Diabetes Menggunakan Metode Multi Criteria Dede Sunandar
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3259

Abstract

Choosing the right medication for diabetic patients is a complex challenge, given the large number of drug alternatives available and the various criteria that must be considered, such as effectiveness, side effects, cost, ease of use, availability, drug interactions, and patient satisfaction. Improper decisions can negatively impact the patient's health and the effectiveness of treatment. This research aims to develop a decision support system that can assist in the selection of the most appropriate diabetes medication based on relevant criteria, thereby improving the quality of treatment and patient satisfaction. To achieve this goal, this study uses the Analytic Hierarchy Process (AHP) method, which allows paired comparisons between criteria and drug alternatives. This method gives weight to each criterion and calculates a score for each drug alternative based on the assessment made. This study involved six alternative diabetes drugs, namely Metformin, Glibenclamide, Acarbose, Sitagliptin, Liraglutide, and Canagliflozin. The assessment criteria used included effectiveness, side effects, cost, ease of use, availability, drug interactions, and patient satisfaction. Data were collected through questionnaires and analysis was carried out using the AHP method to determine the weighting of the criteria and final score for each drug. The results of the analysis showed that Sitagliptin had the highest score, making it the best choice for diabetic patients based on predetermined criteria. This research provides valuable insights for medical professionals in making decisions regarding drug selection, as well as improving patients' understanding of available treatment options.
Penerapan Algoritma Naïve Bayes dan Aplikasi RadipMiner Untuk Penentuan Status Gizi Balita Molina, Jon Idrison
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3261

Abstract

Determining the nutritional status of toddlers is an important activity carried out by medical personnel at the health center as technical implementers. Because with the results of determining the nutritional status, intervention efforts to overcome the condition of toddlers who are in a status other than good nutrition can be overcome as early as possible. However, medical personnel often have difficulty in determining the nutritional status of toddlers due to limited human resources and equipment, so it is important to have a method used to determine the nutritional status of children under five years old quickly and accurately. For this reason, in this study we used the naïve Bayes algorithm in calculating the classification of determining the nutritional status of toddlers. The results of the study showed that the naïve Bayes algorithm can increase the level of data accuracy in determining the nutritional status of toddlers with a data accuracy value of 70.33%.
Perbandingan Algoritma Naive Bayes Dan Support Vector Machine Dalam Deteksi Berita Hoax Berbahasa Indonesia Mumbunan, Keren; Marchantia Betsi Bawata, Michyta; Prayer kusen, Miracle; Tarigan, Victor; Yusupa, Ade
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3262

Abstract

Abstrak Berita hoax menjadi masalah besar di era digital, terutama di Indonesia, di mana informasi yang tidak terverifikasi menyebar dengan cepat melalui media sosial. Penelitian ini membandingkan kinerja algoritma Naïve Bayes (NB) dan Support Vector Machine (SVM) dalam mendeteksi berita hoax berbahasa Indonesia. Dataset yang digunakan terdiri dari 4.599 berita, yang dikumpulkan dari Twitter dan repositori GitHub, dikategorikan sebagai hoax atau valid. Berbagai tahap preprocessing, seperti tokenisasi, stopword removal, stemming, dan TF-IDF vectorization, diterapkan untuk meningkatkan akurasi model. Model dievaluasi menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil eksperimen menunjukkan bahwa SVM memiliki performa lebih baik dibandingkan Naïve Bayes, dengan akurasi 70,87%, lebih tinggi dibandingkan 66,52% dari Naïve Bayes. SVM juga unggul dalam presisi (72%) dan F1-score (82%), sedangkan Naïve Bayes lebih unggul dalam recall (99%). Kesimpulan dari penelitian ini adalah bahwa SVM lebih efektif dalam klasifikasi berita hoax, sementara Naïve Bayes lebih cocok digunakan jika kecepatan pelatihan menjadi prioritas. Penelitian selanjutnya disarankan untuk menggunakan pendekatan deep learning seperti BERT atau LSTM, memperluas dataset, serta mengembangkan model hybrid yang menggabungkan Naïve Bayes dan SVM untuk mengoptimalkan akurasi dan efisiensi.
Sistem Manajemen Pengetahuan Untuk Perbaikan Pelayanan Pelanggan di Forenoon Cafe Araya menggunakan metode KLMSLC Nurwegiono, Muhammad; Abelia, Adinda; Mariska, Kamila
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3263

Abstract

Penelitian ini bertujuan untuk merancang dan mengembangkan sistem komentar dan informasi lokasi pada sebuah website berbasis WordPress untuk Forenoon Café. Desain penelitian menggunakan pendekatan deskriptif dengan pengembangan berbasis perangkat lunak. Metodologi yang digunakan adalah model pengembangan sistem dengan pendekatan waterfall, yang meliputi tahap analisis kebutuhan, desain, implementasi, pengujian, dan pemeliharaan. Hasil utama dari penelitian ini adalah terciptanya sistem komentar yang intuitif dan fitur informasi lokasi yang memudahkan pengguna mengakses alamat serta kontak café. Hasil menunjukkan bahwa sistem yang dikembangkan berfungsi dengan baik sesuai kebutuhan pengguna dan mampu meningkatkan interaksi pelanggan dengan Forenoon Café. Kesimpulan dari penelitian ini adalah bahwa sistem berbasis WordPress yang dirancang telah berhasil meningkatkan aksesibilitas dan keterlibatan pelanggan, sekaligus memberikan solusi yang efisien untuk penyampaian informasi.
Smart Farming: Optimalisasi Produksi Telur Ayam Petelur menggunakan Sistem Cerdas Monitoring Suhu dan Kelembaban Kandang Berbasis IoT Pratomo, Panji; Saputra, Kurniawan; Novita Sari, Dita; Rahsel, Yoeyong; Herdiyan Saputra, Ricco; Suprapto, Bambang; Simanjuntak, Henry
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3264

Abstract

Egg production of laying hens is influenced by various factors, including temperature, humidity, and the quality of the cage environment. The main problem in this study is the fluctuation of production due to changes in environmental conditions that are not optimal. This study aims to develop and implement a smart farming system based on the internet of things (IoT) that is able to optimize egg production of laying hens through automatic monitoring of cage temperature and humidity. The methods used include needs analysis, design, implementation and testing. The results showed that the accuracy of the system reached 80% which could maintain the cage environmental conditions within the optimal range, so that egg production increased from an average of 383.67 eggs per month to 390.33 eggs per month.
Implementasi Sistem Penggajian Karyawan Berbasis Web Menggunakan Metode RAD Munaldi
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3265

Abstract

In today's digital era, many companies face challenges in managing the employee payroll system which is still done manually. PT. Tryuasda Megah Warna, as one of the companies engaged in the industry, has difficulties in managing employee attendance and payroll data. The manual process that is carried out causes inaccuracies in data, delays in payroll, and difficulties in reporting that have an impact on employee satisfaction and the company's operational efficiency. Therefore, a system is needed that can automate and simplify the payroll process. The purpose of this study is to design and implement a web-based employee payroll system that can improve the accuracy, speed, and ease of payroll data management at PT. Tryuasda is a majestic color. The method used in this study is Rapid Application Development (RAD), which allows rapid system development by involving users in every stage of development. With this approach, the prototype of the system is developed and tested iteratively, so that it can better meet the needs of the user. The results of this study show that the implemented payroll system has succeeded in increasing the efficiency of the payroll process by up to 40%, reducing data errors by up to 30%, and increasing employee satisfaction with the payroll process. In addition, this system also provides convenience in reporting and analyzing payroll data, which was previously an obstacle for management. Thus, this research not only provides solutions to existing problems, but also contributes to increasing productivity and employee satisfaction at PT. Tryuasda is a majestic color
IMPLEMENTASI DATA MINING PREDIKSI KELULUSAN SISWA MENGGUNAKAN METODE DECISION TREE PADA SMK IPTEK TANGSEL Suryaningrat, Suryaningrat; Lina Mulani Sitio, Sartika; Suwarno Herry, Ayni
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3267

Abstract

Vocational High School (SMK) is a formal educational institution that prepares its graduates for the world of work. However, SMK Iptek Tangsel faces challenges in optimizing student data and overcoming labor shortages in the field of education administration. To overcome this problem, this study applies a prediction system using a data mining technique with the decision tree method. Aims to improve the accuracy of student graduation predictions. The methodology of this study adopts a quantitative approach with structured steps, including observation, interviews, data collection, and documentation. The results showed that the accuracy of Rapid miners in motorcycle and multimedia business engineering reached 98.49%, while in hospitality and accounting accommodation reached 99.05%. This graduation prediction system helps schools identify students at risk of not graduating and who are at potential to graduate, optimize data management, and enable appropriate interventions. This research makes a significant contribution to improving the decision-making process in the field of education through the use of data mining technology. Thus, the graduation prediction system can be an effective tool in supporting data management and increasing student graduation in vocational schools.

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