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Risky Aswi Ramadhani
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Generation Journal
Published by Universitas Nusantara PGRI Kediri
ISSN : 25804952     EISSN : -     DOI : https://doi.org/10.29407
Core Subject : Science,
Computer Science & IT
Generation (Genius Research Implementation Of Information Technology) Journal diterbitkan oleh Universitas Nusantara PGRI Kediri dan dikelola oleh Prodi Teknik Infomatika Universitas Nusantara PGRI Kediri. Tujuan dari Jurnal ini adalah untuk memfasilitasi publikasi ilmiah dari hasil-hasil penelitian di Indonesia dan berpartisipasi untuk meningkatkan kualitas dan kuantitas penelitian untuk akademisi dan peneliti dalam bidang teknologi informasi. GENERATION Journal diterbitkan setiap bulan Januari dan Juli.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol 7 No 1 (2023): Generation Journal" : 8 Documents clear
Application of Fuzzy Logic to an Arduino Microcontroller-Based Egg Quality Detection Tool M Mujiono; Nalendra, Adimas Ketut; Candrapuspa, Elok Hastari; Adimas Ketut; Elok Hastari
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.17239

Abstract

The process of selecting good eggs that are suitable for consumption is usually carried out using the candling method manually or by observing using a light or flashlight, then observing with the eyes. This method has weaknesses, because manual observations take a long time and the possibility of errors. it is necessary to make a tool that can efficiently detect eggs, using a Light Dependent Resistor (LDR) sensor and an Arduino. LDR Sensor is used to capture the intensity of light, which is emitted into the egg, then processed using Arduino basic for decision maker with fuzzy logic. This tool works with the results of the LDR sensor and displayed on the LCD and color LEDs. Based on the experimental results obtained that the accuracy of the tool is 95%
Classification of Guava Fruit Types Using Principal Component Analysis and K-Nearest Neighbor Algorithms Andrean Nugraha, Rezky; Wahyu Hidayat, Eka; Nur Shofa, Rahmi; Eka Wahyu Hidayat, S.T., M.T.; Rahmi Nur Shofa, S.T., M.T.
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.17900

Abstract

The maturity level of guava fruit can be determined by looking at various factors. Shape is one of the factors that play a role in identifying certain objects. The classification of guava fruit can be seen from the shape, texture and color. The shape of the guava fruit is quite diverse ranging from round (Round shape) to oval (Pear shape). So a Matlab application was built to determine the type of guava based on its color, shape and texture. K-Nearest Neighbor can classify objects based on learning data that is closest to the object so that the results can be more accurate. Principal Component Analysis (PCA) is a statistical technique for simplifying many-dimensional data sets into lower dimensions (extration features). The combination of K-Nearest Neighbor with Principal Component Analysis produces a fairly high accuracy for determining the type of guava using a total of 45 images and divided into two data including training data with a total of 36 guava data and test data with a total of 9 guava data.
Forecasting the Price Movement of Volatility Index using the Fuzzy Tsukamoto Method and Dstat Metric Evaluationindonesia Utomo, Wahyu Cahyo; Saputra, Muh Aris
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.19605

Abstract

Volatility index is one of the assets traded in trading activities. In this activity there are two possibilities that can be done by traders, namely buy and sell actions. This is the main problem in forecasting in the world of finance. With these two opportunities, an analysis is needed to estimate the direction of price movement correctly. In addition in trading the subjectivity factor sees very high price movements. In a sense, each individual trader has his own assumptions. So a non-subjective analysis system is needed. Based on these challenges, this research will focus on forecasting with a non-subjective approach with fuzzy logic or more precisely Fuzzy Tsukamoto and Dstat metric as an evaluation of the level of correctness of the prediction direction. From the results that have been tested in the study, the Fuzzy Tsukamoto Method by reading the Relative Strength Index and Stochastic Oscillators indicators received an evaluation value that met the trading industry standards of 64.13%.
Sistem Cerdas Penilaian Ujian Essay Menggunakan Metode Cosine Similarity Arifuddin, Muhammad Rizal; Ar Rafiq, Izzudin; Mubarok, Rifki; Susilo, Purnomo Hadi
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.18318

Abstract

Technological developments have grown rapidly without exception in the world of education. The development of technology in the field of education can be seen by the number of information systems used for the learning process. The online learning process has many obstacles, especially when the exam is being conducted. Not all educators can conduct online exams by utilizing information technology. One of the most difficult exams is the essay exam. The essay exam that was conducted experienced many obstacles in terms of correcting and assigning grades to students. By utilizing intelligent information technology, this can be solved because everything can be done by the system automatically. This study aims to build an intelligent system for assessing essay exams using the cosine similarity method. In the system built, all the exam processes can be done automatically. The system can correct the answers written by students then the system will also automatically give a value according to the answers entered. The results of the study indicate that the system built can assist teachers in conducting online essay exams effectively and efficiently. This is because the system can correct students' answers by automatically matching the answers from the teacher.
Adopsi Metode DevOps Sebagai Acuan Pengembangan Aplikasi Bantuan Hukum Riyadi, Slamet
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.19629

Abstract

Sekretariat Daerah terdiri dari beberapa bagian, salah satunya bagian hukum. Layanan Bantuan Hukum untuk kegiatan konsultasi hukum terdiri dari 3 sub kegiatan yaitu persiapan, pelaksanaan, serta pasca pelaksanaan. Secara geografis, banyak desa di Indonesia yang jauh dari sekretariat daerah. Kepala desa dan perangkat desa juga harus mengunjungi Sekretariat Daerah untuk mengatur penyuluhan dan bantuan hukum jarak jauh. Ini memakan waktu setidaknya satu hari dan biaya perjalanan/akomodasi tidak murah. Secara teori permasalahan yang ada dapat diatasi dengan membangun sebuah sistem pengolahan data yang berbasis teknologi informasi. Pada banyak organisasi, pengembangan perangkat lunak dan aktivitas operasi biasanya dilakukan secara terpisah dan memiliki tujuan yang terpisah. Pengembang bertugas membuat, menambah, dan memodifikasi sistem baru. Bagian operasi bertugas menjaga stabilitas sistem. Ini biasanya menyebabkan konflik ketika sistem baru akan diimplementasikan. Departemen operasi cenderung tidak menginginkan perubahan karena kekhawatiran tentang ketidakstabilan system. DevOps adalah tren baru yang muncul (tahun 2009) dari benturan dua tren lama: Agile Systems dan Agile Operations. Ini merupakan kolaborasi antara staf pengembangan dan staf operasi di setiap tahap siklus hidup DevOps. Metodologi DevOps tidak hanya mencakup fase pengembangan tetapi juga fase operasi. Fase yang disediakan cukup komprehensip sehingga sangat kecil kemungkinan aplikasi gagal untuk diimplementasikan secara berkelanjutan.
Perbandingan Algoritma Naive Bayes dan Decision Tree(C4.5) dalam Klasifikasi Dosen Berprestasi Supriyadi, Andy
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.19797

Abstract

Abstract – Enhancing the execution of Tri Dharma for lecturers is one of the factors in obtaining and sustaining the level of universities with good institution achievement. The Rectorate should exercise consideration while making a decision to reward lecturers who do very well. The information was gathered through speaking with members of the rectorate staff to classify lectures at Sebelas Maret University. In this study, accuracy results in the classification based on lecturers' accomplishments will be compared. International and national publications, education level, the length of doctoral studies, becoming an associate professor, and the length of certification as a lecturer are the features considered in the classification. To categorize lecturers according to their accomplishment, the algorithms Naive Bayes and Support Vector Machine were applied. 350 records of training data and 130 records of testing data total 500 records in this study. From 2018 to 2021, the study was carried out at Sebelas Maret University. The accuracy value obtained from 10-fold cross validation the testing using the Naive Bayes method is 94,80%, while the accuracy value obtained from the testing using the Decision Tree is 95,80%.
Implementation of Web Content Filtering on RT/RW Net Networks Using Pi-Hole DNS Server Miftahur Rahman
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.19818

Abstract

Penggunaan jaringan RT/RW Net supaya lebih maksimal perlu menerapkan keamanan jaringan yaitu dengan menerapkan Pi-Hole DNS Server untuk memfilter website negatif dan iklan yang tidak diinginkan. Hal ini sesuai dengan program yang dicanangkan oleh Pemerintah (Kemkominfo) yaitu penggunaan internet yang sehat dan aman. Tahapan penelitian yang digunakan adalah identifikasi masalah, studi pustaka, implementasi, pengujian dan analisis hasil atau penarikan kesimpulan. Menghasilkan penelitian bahwa penerapan Pi-Hole DNS Server terhadap topologi jaringan RT/RW Net berhasil dilakukan terbukti dapat memfilter atau menyaring website yang mengandung situs-situs negatif dan dapat memblokir iklan yang tidak diinginkan, keberhasilan dalam memfilter tersebut dikategorikan 100% efektif, serta kualitas jaringan setelah penerapan Pi-Hole DNS Server dikategorikan baik dalam metode pengujian QoS
Penerapan Metode XGBoost Untuk Memprediksi Jumlah Kejadian Kecelakaan Lalu Lintas di Kota Banjarmasin Alkaff, Muhammad; Baskara, Andreyan; Ainiyyah, Ainiyyah
Generation Journal Vol 7 No 1 (2023): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v7i1.19807

Abstract

Setiap tahunnya terjadi kecelakaan lalu lintas seperti yang tercatat pada data dari Polisi sejak tahun 2016 sampai dengan 2020 yang ditambah dengan data dari sosial media pada tahun 2021 sampai bulan Oktober. Selain berdasarkan data kecelakaan lalu lintas terdapat juga hal yang dapat mempengaruhi terjadinya kecelakaan seperti curah hujan. Berdasarkan permasalahan tersebut, penelitian ini akan melakukan prediksi terhadap jumlah kejadian kecelakaan lalu lintas yang akan terjadi di kota Banjarmasin menggunakan metode XGBoost. Data yang telah dikumpulkan akan diolah dalam rentang waktu bulanan serta pengujian model menggunakan dua metode yaitu RMSE untuk melihat tingkat error rate hasil prediksi dengan nilai nyata dan R-Squared atau R2 untuk melihat korelasi kecelakaan dengan curah hujan. Hasil penelitian menunjukkan metode XGBoost mendapatkan nilai RMSE sebesar 0.120 pada data per hari dengan variabel kecelakaan saja sedangkan nilai R2 mendapatkan 0.19 pada data per 4 bulan kebelakang dengan variabel kecelakaan dan curah hujan.

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