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<![CDATA[KLASIFIKASI JENIS BUAH JAMBU BIJI MENGGUNAKAN ALGORITMA PRINCIPAL COMPONENT ANALYSIS DAN K-NEAREST NEIGHBOR ]]>
<![CDATA[Rezky]]>;
<![CDATA[Ika Kurniati, Neng]]>;
<![CDATA[Eka]]>;
<![CDATA[Rahmi]]>
<![CDATA[ Generation Journal Vol 6 No 2 (2022): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v6i2.17777
<![CDATA[Jambu biji sering disebut juga jambu klutuk, jambu siki, jambu batu dan bangkok. Tingkat kematangan buah jambu biji dapat ditentukan dengan cara melihat berbagai faktor. Bentuk adalah salah satu faktor yang berperan mengidentifikasi objek tertentu. Klasifikasi buah jambu biji dapat dilihat dari bentuk maupun warnanya. Terdapat dua cara untuk mengklasifikasi buah jambu biji yaitu secara destruktif dan non-destruktif. Kematangan buah jambu biji secara destruktif dilakukan dengan membuka buah jambu biji untuk mengetahui jenisnya berdasarkan warna daging dan biji. Maka di bangunlah sebuah aplikasi Matlab untuk menentukan jenis jambu biji berdasarkan warna, bentuk dan teksturnya. K-Nearest Neighbor dapat melakukan klasifikasi terhadap objek berdasarkan data pembelajaran yang jaraknya paling dekat dengan objek tersebut sehingga hasilnya bisa lebih akurat. Principal Component Analysis (PCA) adalah teknik statistik untuk menyederhanakan kumpulan data banyak-dimensi menjadi dimensi yang lebih rendah (extration feature). Kombinasi antara K-Nearest Neighbor dengan Principal Component Analysis mengahasilkan akurasi yang cukup tinggi untuk penentuan jenis jambu biji menggunakan data latih dengan jumlah 36 data jambu biji dan data uji dengan jumlah 9 data jambu biji.]]>
<![CDATA[Implementation of the Waterfall Method in the Design of a Website-Based Mail Filing System ]]>
<![CDATA[Rohman, Auliya’ur]]>;
<![CDATA[Syarif Hidaytullah, Athia]]>;
<![CDATA[Rohman, MGhofar]]>
<![CDATA[ Generation Journal Vol 6 No 2 (2022): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v6i2.17871
<![CDATA[The use of information technology and computers has become a necessity in daily work, both in private and public agencies, especially in terms of service to the community, the use of information technology is certainly very supportive of existing activities. One of the activities at the Department of Population and Civil Registration is the large number of incoming and outgoing letters, this causes problems in archiving, both incoming and outgoing letters, so to overcome this a website-based archive system for incoming and outgoing mail is built. This system was built using the waterfall method. The test results on the archive of incoming and outgoing letters based on this website indicate that this application has been running well, this can be seen in the results of the black box testing which shows that the application is running as expected, and makes it easier for employees to carry out their duties of archiving incoming and outgoing mail.]]>
<![CDATA[Penerapan Fungsi Exponential Pada Pembobotan Fungsi Jarak Euclidean Algoritma K-Nearest Neighbor ]]>
<![CDATA[Muhammad Jauhar Vikri]]>;
<![CDATA[Rohmah, Roihatur]]>
<![CDATA[ Generation Journal Vol 6 No 2 (2022): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v6i2.18070
<![CDATA[– k-Nearest Neighbor (k-NN) is one of the popular classification algorithms and is widely used to solve classification cases. This is because the k-NN algorithm has advantages such as being simple, easy to explain, and easy to implement. However, the k-NN algorithm has a lack of classification results that are strongly influenced by the scale of input data and Euclidean which treats attribute data evenly, not according to the relevance of each data attribute. This causes a decrease in the classification results. One way to improve the classification accuracy performance of the k-NN algorithm is the method of weighting its features when measuring the Euclidean distance. The exponential function of the optimized Euclidean distance measurement is applied to the k-NN algorithm as a distance measurement method. Improving the performance of the k-NN method with the Exponential function for weighting features on k-NN will be carried out by experimentation using the Data Mining method. Then the results of the performance of the objective method will be compared with the original k-NN method and the previous k-NN weighting research method. As a result of the closest distance decision, taking the closest distance to k-NN will be determined with a value of k=5. After the experiment, the goal algorithm was compared with the k-NN, Wk-NN, and DWk-NN algorithms. Overall the comparison results obtained an average value of k-NN 85.87%, Wk-NN 86.98%, DWk-NN 88.19% and the k-NN algorithm given the weighting of the Exponential function obtained a value of 90.17%.]]>
<![CDATA[Sistem Informasi Izin Online Berbasis Web Menggunakan Framework Codeigniter ]]>
<![CDATA[Rizki Wahyu Nugroho]]>;
<![CDATA[Teguh Andriyanto]]>;
<![CDATA[Rini Indriati]]>
<![CDATA[ Generation Journal Vol 6 No 2 (2022): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v6i2.18361
<![CDATA[So far, the absence of work permit that is still valid until now is consodered inefficient, when an employee want to apply for leave of absence from work, the employee must first come to the office, then ask or approval from his superiors and the application letter is approved and then printed as evidence. The purpose of this study is to make easier for employee to apply for leave absence from work online and to help manage employee data and data for an absent work permit automatically enter the Development Sector. The system development model in this study is the Waterfall Model. Software testing is carried out using User Acceptance Testing (UAT). Data collection techniques used in this study were observation, interviews and documentation. The application used to support sending notifications is the Whatsapp API. This system is built using sublime text 3 editor and uses the PHP as programming language and MySQL as database management. The final result of this research is an online validation system or submitting a permit for not going to work.]]>
<![CDATA[Application of Fuzzy Logic to an Arduino Microcontroller-Based Egg Quality Detection Tool ]]>
<![CDATA[M Mujiono]]>;
<![CDATA[Nalendra, Adimas Ketut]]>;
<![CDATA[Candrapuspa, Elok Hastari]]>;
<![CDATA[Adimas Ketut]]>;
<![CDATA[Elok Hastari]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.17239
<![CDATA[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%]]>
<![CDATA[Classification of Guava Fruit Types Using Principal Component Analysis and K-Nearest Neighbor Algorithms ]]>
<![CDATA[Andrean Nugraha, Rezky]]>;
<![CDATA[Wahyu Hidayat, Eka]]>;
<![CDATA[Nur Shofa, Rahmi]]>;
<![CDATA[Eka Wahyu Hidayat, S.T., M.T.]]>;
<![CDATA[Rahmi Nur Shofa, S.T., M.T.]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.17900
<![CDATA[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.]]>
<![CDATA[Forecasting the Price Movement of Volatility Index using the Fuzzy Tsukamoto Method and Dstat Metric Evaluationindonesia ]]>
<![CDATA[Utomo, Wahyu Cahyo]]>;
<![CDATA[Saputra, Muh Aris]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.19605
<![CDATA[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%.]]>
<![CDATA[Sistem Cerdas Penilaian Ujian Essay Menggunakan Metode Cosine Similarity ]]>
<![CDATA[Arifuddin, Muhammad Rizal]]>;
<![CDATA[Ar Rafiq, Izzudin]]>;
<![CDATA[Mubarok, Rifki]]>;
<![CDATA[Susilo, Purnomo Hadi]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.18318
<![CDATA[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.]]>
<![CDATA[Adopsi Metode DevOps Sebagai Acuan Pengembangan Aplikasi Bantuan Hukum ]]>
<![CDATA[Riyadi, Slamet]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.19629
<![CDATA[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.]]>
<![CDATA[Perbandingan Algoritma Naive Bayes dan Decision Tree(C4.5) dalam Klasifikasi Dosen Berprestasi ]]>
<![CDATA[Supriyadi, Andy]]>
<![CDATA[ Generation Journal Vol 7 No 1 (2023): Generation Journal ]]>
Publisher : <![CDATA[Universitas Nusantara PGRI Kediri ]]>
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DOI: 10.29407/gj.v7i1.19797
<![CDATA[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%.]]>
