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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 2 No 1 (2024): Agustus - November 2024" : 7 Documents clear
Clustering of Child Nutrition Status using Hierarchical Agglomerative Clustering Algorithm in Bekasi City ardhiyanto, ozzi; Ajif Yunizar Pratama Yusuf, S.Si, M.Eng; Salam Asyidqi, Muhammad; Dr. Tb. Ai Munandar, S.Kom., MT
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.41

Abstract

Clustering infant nutrition based on weight, height, and age is a data analysis method used to group infant nutritional status based on these characteristics. The research on clustering infant nutrition aims to analyze whether there are still many infants in the area with insufficient or excessive nutrition, and to identify groups of infants requiring special attention regarding their nutritional intake. In the analysis of infant nutrition clustering, data on weight, height, and age of infants are collected and then grouped based on similarities in body height and weight at certain ages. The method used in this research is hierarchical clustering, which can help in grouping the data. Clustering analysis can help understand how infants' feeding patterns vary based on their weight, height, and age. The results of research on clustering infant nutrition based on weight, height, and age can provide valuable insights for nutrition experts, pediatricians, and community health workers in developing appropriate intervention programs to improve infant feeding patterns and meet their nutritional needs. Additionally, the results of clustering infant nutrition can also be used to identify groups of infants requiring special attention regarding their nutritional needs, thus minimizing the risk of malnutrition and unhealthy growth in infants.
Deteksi Status Internal Battery UPS Berdasarkan Hasil Pengukuran Resistansi Dari Battery Tester Menggunakan Algoritma C4.5 Kusumah, Muhammad Assegaf Raja; Setyawati, Ananda; Wardana, Muhammad Bisma Arya; Tb Ai Munandar; Ajif Yunizar Pratama Yusuf
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.44

Abstract

The purpose of this research is to propose a classification model using the decision tree method that can detect the internal status of UPS batteries by using resistance measurements from a battery tester. Resistance data of UPS batteries were collected from measurements conducted under various conditions. This study focuses on supervised learning models, where the data is processed to form a decision tree using the C4.5 classification algorithm. The test results show that the classification of UPS battery internal status can be achieved with high accuracy. The data presentation results were obtained from 100 units of battery systems in UPS, with two conditions identified: 38 units of batteries with a Normal condition and a presentation data accuracy rate of 100%, and 62 units of batteries with a Fault condition and a presentation data accuracy rate of 100%. By using this classification model, users can monitor the performance of the internal battery in the UPS system and take necessary actions to maintain stable UPS system operation and usage.
Deteksi Penyakit Pembibitan Pada Tanaman Durian Berdasarkan Citra Menggunakan Convolutional Neural Network RIZKI NURFIRDAUS, MUH. IQBAL
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.61

Abstract

ABSTRAKSI Pembudidayaan tanaman durian di Indonesia memiliki nilai ekonomi yang tinggi, berbagai macam varian menjadikannya sangat diminati banyak orang. Namun keterbatasan pengetahuan tentang penyakit menjadikan alasan rendahnya kualitas dan harga dipasaran. Maka dari itu diperlukan sistem deteksi yang dapat mengelompokan ciri serta bentuk dari beberapa penyakit, Penelitian ini untuk mempermudah petani melakukan perawatan. Menggunakan metode Convolutional Neural Network(CNN) yang termasuk supervised learning sehingga dapat dilakukan untuk klasifikasi bagian tanaman durian yang terdampak dan pendekatan data yang sudah di latih serta bervariabel. Tujuan penelitian ini mengetahui jenis penyakit yang terdapat pada tanaman durian. Hasil pengujian yang telah dilakukan dengan tingkat akurasi kalisifikasi menggunakan CNN sebesar 0.9233 dengan pengulangan sebanyak 200 epochs dari proses yang dilakukan di dapatkan hasil berupa gambar dan keterangan jenis penyakit sehingga dapat membantu meningkatkan kualitas dan harga. Kata Kunci: CNN, pembibitan tanaman, deteksi, penyakit, kualitas dan harga. ABSTRACT The cultivation of durian plants in Indonesia has a high economic value, various variants make it very attractive to many people. However, limited knowledge about the disease is the reason for the low quality and price in the market. Therefore a detection system is needed that can classify the characteristics and forms of several diseases. This research is to make it easier for farmers to treat them. Using the Convolutional Neural Network (CNN) method which includes supervised learning so that it can be carried out for classification of affected parts of the durian plant and a data approach that has been trained and is variable. The purpose of this study was to determine the types of diseases found in durian plants. The results of tests that have been carried out with a classification accuracy level using CNN of 0.9233 with a repetition of 200 epochs from the process carried out get results in the form of pictures and descriptions of the types of diseases so that they canhelpimprovequalityandprice.Keywords: CNN, plant nursery, detection, disease, quality and price.
Pengaruh Keluarga Terhadap Banyaknya Sampah Yang Ada Di Lingkungan Rt01 Banten Indah Permai Dengan Metode Regresi Linear Sederhana Menggunakan Orange Data Mining Hasbi Assiddiq, Muhamad
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.130

Abstract

Waste is the accumulation of refuse generated by humans, which in the household context is categorized into organic, inorganic, and domestic waste. In the RT 01 RW 027 community of Perumahan Banten Indah Permai, each household produces waste daily, and these quantities are recorded by the neighborhood head to calculate the daily fee for waste collectors—where the tariff is based on the weight of waste (in kilograms) transported. By employing predictive methods and simple linear regression on the Orange platform, this study aims to measure the influence of family size on the daily volume of waste collected. The analysis results demonstrate a positive and significant relationship between family size, consumption patterns, and levels of environmental awareness with the rate of waste accumulation. These findings provide valuable insights for designing more effective waste management strategies, emphasizing the active role of each family in waste reduction and organization efforts. 
Pengaruh Iklan di TV Terhadap Penjualan Dengan Metode Regresi Linear Sederhana Hidayat, Deni
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.131

Abstract

Penelitian ini menggunakan metode regresi linear sederhana dan bertujuan untuk mengetahui dan menganalisis pengaruh iklan televisi terhadap penjualan produk. Teknik yang digunakan dalam menganalisis adalah regresi linier sederhana untuk menguji hubungan antara variabel independen (iklan di TV) dan variabel dependen (penjualan produk). Penelitian ini melibatkan pengumpulan data dari iklan di TV berbagai perusahaan dan penjualan produk. Data dianalisis menggunakan regresi linier sederhana untuk mengetahui apakah iklan di TV dapat mempengaruhi perubahan penjualan produk. pada penelitian ini menunjukkan dampak yang signifikan dan positif dari kedua variabel tersebut. Pada hasil regresi linear menunjukkan angka yang positif yaitu . sehingga memiliki kekuatan hubungan antara kedua variabel tersebut. Selain itu, dilakukan juga perhitungan korelasi pearson untuk mengukur kekuatan dan hubungan pada kedua variabel tersebut dan hasilnya positif yaitu . Hasil penelitian ini memberikan pemahaman kepada para pengambil keputusan pemasaran dan periklanan mengenai efektivitas iklan televisi dalam meningkatkan penjualan. Hasil penelitian ini dapat membantu perusahaan dalam mengembangkan strategi periklanan yang lebih baik dan efektif. Kata kunci : iklan, penjualan, regresi linear sederhana, orange
Data Mining Prediksi Jumlah Kematian Berjenis Kelamin Perempuan Berdasarkan Usia Dengan Menggunakan Metode Regresi Linear Sederhana raksa negara, syahrizal
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.132

Abstract

This study aims to analyze the relationship between the number of female deaths and age. It uses mortality data collected from relevant agencies and applies simple linear regression to model the relationship between these two variables. The results show a positive association: as age increases, the risk of death among females also rises. The derived simple linear regression model can be used to predict the number of female deaths based on age. This research contributes to understanding age‑related patterns of female mortality and can inform policymakers in designing health programs and policies targeted at the most at‑risk female age groups. However, the study is limited by its use of data from a single year and one region; future research with a broader dataset and more sophisticated analytical methods is needed to achieve a more comprehensive understanding of factors influencing female mortality by age.  
Pengaruh Umur Pemain Tenis Lapangan Terhadap Ranking Dunia Di Jumlah Point Pemain Tenis Lapangan Menggunakan Metode Regresi Linear Sederhana Gustian, Ifan
Jurnal Riset Informatika dan Teknologi Informasi Vol 2 No 1 (2024): Agustus - November 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat (JPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/jriti.v2i1.133

Abstract

This study aims to analyze the relationship between the number of points scored and the age of tennis players using a simple linear regression method. Data were collected from active players, including the points they earned in matches and their ages. Simple linear regression analysis was employed to determine the extent of the linear relationship between these two variables. The results indicate a correlation between players’ age and the number of points they obtain. The regression coefficients and their statistical significance are examined to assess the strength and relevance of this relationship. Findings from this research offer deeper insights into the factors that may influence on-court performance, with a particular focus on age. The discussion covers the interpretation of results, implications for tennis coaching and management, and potential applications in training programs. Study limitations and recommendations for future research are also addressed. Ultimately, this research is expected to contribute to a better understanding of the determinants of tennis performance, especially regarding the role of age.

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