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Jurnal Riset Informatika dan Teknologi Informasi (JRITI)
Published by Jejaring Penelitian dan Pengabdian Masyarakat
ISSN : 30248167     EISSN : 31098959     DOI : https://doi.org/10.58776/jriti.v3i1
Core Subject : Science,
Computer Science & IT
Jurnal Riset Informatika dan Teknologi Informasi merupakan jurnal ilmiah yang diterbitkan oleh Jejaring Penelitian dan Pengabdian Masyarakat (JPPM) Banten. Jurnal ilmiah ini memuat hasil riset dosen, peneliti, mahasiswa dan masyarakat umum dibidang informatika dan teknologi informasi serta rumpun dan turunannya. Jurnal ini terbit tiga kali dalam setahun. Terbitan pertama di bulan Agustus 2023. Sedangkan untuk periode terbit adalah Agustus, Desember, dan April. Adapun bidang riset yang menjadi fokus jurnal ini (dengan tanpa bermaksud membatasi) adalah terkait dengan topik : data mining, data science, pembelajaran mesin (machine learning), kecerdasan buatan, sistem pakar, sistem informasi manajemen, sistem pendukung keputusan, cyber security, soft computing, logika samar (fuzzy logic), pengenalan pola, computer vission, pengolahan citra digital, software engineering, manajemen proyek, software testing, dan topik lain terkait informatika dan teknologi informasi yang relevan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
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Search results for , issue "Vol 3 No 1 (2025): Augustus - November 2025" : 7 Documents clear
Pengaruh Jumlah Jam Belajar Terhadap Nilai Siswa Dengan Metode Regresi Linear Sederhana Nawfal, Zaidan
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.129

Abstract

This research aims to determine the effect of study hours on student grades. To increase student grades, there are influencing factors, one of which is the number of study hours. Obstacles that often occur to improving grades are students' lack of awareness about their lack of interest in learning and the small number of study hours spent outside of class. This research uses a simple linear regression method and uses orange data mining tools, the results show that there is a relationship between study hours and student grades. Data shows that the more time students spend studying, the better their academic scores. The final results of this research can provide important information to teachers, parents and students about the importance of allocating sufficient study time to achieve the best grades and can help us understand the factors that influence student learning and provide a basis for developing better learning strategies.  
Implementasi Data Mining Penjualan Produk Kosmetik Pada PT. Habasa Natural Menggunakan Regresi Linear Sederhana Bahrul Saputra, Haikal
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.141

Abstract

Women’s lives are generally inseparable from the use of cosmetics, which not only serve to enhance appearance but also to maintain skin and body health, making them one of the basic needs with ever-increasing demand. PT. Habasa Natural, as a producer and seller of natural cosmetics, experiences daily growth in sales transactions, resulting in an ever-expanding volume of stored data. However, most of this data is merely archived without being optimally utilized, even though it contains valuable insights such as consumer purchasing patterns, the most popular products, and relationships between products that are often bought together. By properly leveraging sales data, the company can develop more effective marketing strategies, such as creating product bundles, offering special promotions, or arranging strategic product placement, enabling data-driven business decisions to improve operational efficiency, competitiveness, and customer satisfaction.  
Penerapan Regresi linier Berganda untuk Menganalisis Jumlah Kecelakaan Lalu Lintas Nurhasanah, Gita Aprilia
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.142

Abstract

Traffic accidents are a serious problem that can have negative impacts on both society and the economy of a region. This study aims to analyze the factors contributing to traffic accidents and identify possible prevention measures. The research method involves collecting traffic accident data from various sources, including police reports, witness statements, and medical records. The analysis of accident causes covers aspects such as speeding, non-compliance with traffic regulations, road conditions, and vehicle conditions. The results show that inappropriate speed, the use of mobile phones while driving, and violations of traffic rules are the dominant factors in traffic accidents. In addition, poor road infrastructure conditions and lack of vehicle maintenance also contribute to the high rate of accidents. This study contributes to a deeper understanding of the factors causing traffic accidents and provides insights into prevention strategies that can be adopted by the government and relevant stakeholders. By implementing these measures, it is expected that the number of traffic accidents can be reduced, thereby improving road safety for all road users. Multiple-unit vehicles, such as buses and large trucks, play an important role in mass transportation and logistics. However, traffic accidents involving these vehicles can have serious impacts on road safety and human life. This study aims to analyze the factors contributing to traffic accidents involving multiple-unit vehicles and identify prevention strategies that can be implemented..  
Analisis Tren Penjualan dan Dinamika Pasar: Studi Kasus PT. Enseval Putera Megatrading tri bakti purba, daud
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.160

Abstract

This study aims to analyze the sales trends and market dynamics of PT. Enseval Putera Megatrading over a specific period. The data used includes sales information from various branches across Indonesia, obtained from monthly and annual sales reports. Through this analysis, we identified consistent and fluctuating sales patterns, as well as the factors influencing sales, both internally, such as marketing strategies, service quality, and inventory management, and externally, such as economic conditions, market competition, and government policy changes. This research also measures the effectiveness of various sales strategies implemented by the company, with the aim of providing data-driven recommendations to enhance future sales performance. The results of the study show significant sales variations between branches and periods, caused by several internal factors like sales team performance and external factors such as market demand trends and raw material price fluctuations. These findings offer valuable insights for management in formulating more effective and adaptive strategies in response to the ever-changing market dynamics.  
Riset Pengaruh Pencapaian Akademik Terhadap Tingkat Stres Mahasiswa Menggunakan Metode Regresi Linier Berganda Saputra, Adi
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.179

Abstract

Stress is a condition that is felt when someone faces a challenge, or is in a situation that requires us to adjust quickly to a change. In the academic world, it is not uncommon for a student or student to experience stress due to several pressures such as assignments, exams, reports, and in the expected academic achievement. This study aims to analyze the effect of academic achievement on student stress levels, by applying multiple linear regression data mining methods. The data is obtained from 2028 students from 15 top-ranked universities in Bangladesh, including 9 public/government universities and 6 private universities. Through multiple linear regression analysis, this study evaluated the relationship between the independent variables, i.e., age of the students, GPA (Grade Point Average) of the students, frequency of feeling upset due to academic affairs, frequency of feeling unable to control important matters in academic affairs, frequency of feeling nervous and stressed due to academic pressure, frequency of feeling unable to cope with all mandatory academic activities, frequency of feeling confident in handling academic problems, frequency of feeling that academic affairs are going as desired, frequency of ability to control irritation in academic affairs, and the dependent variable, i.e., stress scores experienced by the students. This research provides insights for educational institutions to design strategies to help students manage academic stress, such as counseling and time management programs. By understanding the factors that influence stress, it is hoped that students can improve their psychological well-being during the lecture period.
Analisis Hubungan Antara Kadar Alkohol dengan Density dan pH Yang Terkandung di Dalam Red Wine Menggunakan Metode Regresi Linear Berganda Falih, Muhammad Rafi
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.182

Abstract

This study aims to analyze the relationship between alcohol content, density, and pH in red wine using multiple linear regression method. Alcohol content, density, and pH are important parameters that affect the quality and characteristics of red wine. In this study, red wine samples from different types and regional origins were analyzed to measure alcohol content, density, and pH using distillation, hydrometer, and pH meter techniques. The data obtained were then analyzed by multiple linear regression to identify the simultaneous influence of these variables on each other. The analysis showed that alcohol content had a significant effect on density, with a strong positive relationship. In addition, multiple linear regression revealed a significant effect between alcohol content and pH, although this effect was not linear and was influenced by other factors such as grape type and fermentation technique. The resulting regression model shows that alcohol content, density and pH are interrelated and provides a deeper understanding of the complex interactions between these parameters in red wine.
Implementasi Algoritma Simple Additive Weighting (SAW) dalam Menentukan Supplier Bahan Pokok Makanan Kusmanto, Tria Hadi; Fauzi, Ahmad; Harli, Eko
Jurnal Riset Informatika dan Teknologi Informasi Vol 3 No 1 (2025): Augustus - November 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v3i1.216

Abstract

The experience and subjective opinions of restaurant management are the only factors used in the manual supplier selection process. Uncertainty about product availability and quality, higher costs, and difficulty managing supplier relationships are just a few of the issues that can arise from this approach. Finding a balance between product quality and price is a common challenge when selecting suppliers. Restaurants must consider suppliers' prices and ensure they align with the quality of the food they serve. A multi-criteria research method for selecting restaurant suppliers is the Simple Additive Weighting (SAW) algorithm. Each relevant supplier selection criterion must be ranked and weighted according to this procedure. By using the Simple Additive Weighting (SAW) method, a decision support system for restaurant supplier selection can simplify and accelerate the supplier selection process and provide timely and accurate reporting.

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