Jurnal Teknoinfo最新文献

{"title":"RANCANG BANGUN SISTEM RAPORT DIGITAL BERBASIS JAVA (D-RAPORT) DI SDN SUKATANI 03 DEPOK","authors":"Maulana Agung Saputro, .. Khalidah","doi":"10.33365/jti.v16i1.1352","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1352","url":null,"abstract":"Administration of academic activities at SDN Sukatani still uses a manual process. This can allow academic files to be lost, damaged and even a buildup of documents so that the search for documents for a number of students will be ineffective and inefficient. Therefore, there is a need for a system that can facilitate academic services. This study aims to design a Java-based Digital Report Card (d-Raport) system at SDN Sukatani 03 Depok. The method used in the design of the system is the waterfall method. The stages of this method, namely analysis, design, implementation, and testing. This system is built based on a desktop with the Java programming language. This system produces student report cards, student attendance data modules, student savings data modules, and library book lending data modules. This system is useful for SDN Sukatani in academic administration management. In research using testing, namely by using black-box testing which serves to test the user interface so that it is easy to use by users. The results of this system produce a student report card score module, a student attendance data module, a student savings data module, and a library book borrowing data module. This system is useful for SDN Sukatani in academic administration management. This application makes it easier for schools, both teachers and students' guardians, to input or view academic activities that are running at SDN Sukatani 03 Depok. Keyword: Digital Report Card, Java, Waterfall, Design, Syistem","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129571152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pengenalan Motif Batik Banyuwangi Berdasarkan Fitur Grey Level Co-Occurrence Matrix","authors":"L. Hakim, Sepyan Purnama Kristanto, Dianni Yusuf, Fitri Nur Afia","doi":"10.33365/jti.v16i1.1320","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1320","url":null,"abstract":"Batik is one of Indonesia’s cultural heritages that is recognized around the world and has existed since the colonial era. Indonesia has a variety of different batik pattern in every Indonesia’s region. It causes many ordinary people and tourists to become harder to identify and recognize the existing patterns. Banyuwangi regency itself has more than 10 batik patterns, including the Gajah Oling pattern which in the oldest batik pattern. For preserving the culture and supporting the growing tourism aspect in Banyuwangi, this study developed a system for recognizing Banyuwangi batik patterns based on digital image processing. This system is built using python language and is able to recognize three classes of Banyuwangi batik patterns, such as Gajah Oling, Kopi Pecah and other Banyuwangi batik patterns. This system proposes Gray Level Co-occurrence Matrix (GLCM) as feature extraction method and k-Nearest Neighbors (kNN) as classification method. Based on the experiments that have been carried out, the optimal accuracy is 87,5% with the K parameter of kNN is 9.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128639973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PERBANDINGAN 3 ALGORITMA KLASIFIKASI DATA MINING DALAM PRO-KONTRA BAHAYA ROKOK ELEKTRIK","authors":"Eva Argarini Pratama, Corie Mei Hellyana, Nuzul Imam Fadlilah","doi":"10.33365/jti.v16i1.1534","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1534","url":null,"abstract":"","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123482939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENTERPRISE ARCHITECTURE PLANNING MENGGUNAKAN TOGAF ADM PADA INDUSTRI RETAIL","authors":"J. Andry, Lydia - Liliana, Monica - Clara","doi":"10.33365/jti.v16i1.1449","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1449","url":null,"abstract":"The use of information technology has become important to assist data processing, especially in the electrical equipment retail industry. Retail industry technology has not been fully utilized, especially in terms of marketing, production, delivery, finance and human resources. Problems that arise, such as long data processing times, miscalculation of financial invoices and many more. To harmonize business processes and information systems, business architecture and information systems are designed using the Open Group Architecture Framework (TOGAF) standard with the Architecture Development Method (ADM) method. The selection of TOGAF ADM aims to explain the architecture of the retail industry more specifically in terms of business, technology and information. This research phase includes preliminary, information technology strategy identification, solution identification, architectural vision and enterprise architecture. This research produces an enterprise architecture blueprint design in the form of proposed applications from the business, information and technology side, which is only limited to design. The implementation of the TOGAF ADM phase can maximize the retail industry's business processes in terms of concepts, techniques, integration between business and information technology and determine the transformation in all business, data, application and technology domains. Keyword: Enterprise Architecture, TOGAF ADM, Retail Industry, Blueprint, Business Architecture","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114179462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EVALUATION OF DISTANCE LEARNING SYSTEM (E-LEARNING): A SYSTEMATIC LITERATURE REVIEW","authors":"Ignatius Adrian Mastan, D. I. Sensuse, Ryan Randy Suryono, Kautsarina Kautsarina","doi":"10.33365/jti.v16i1.1736","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1736","url":null,"abstract":"Research in the field of e-learning is currently experiencing rapid development, especially due to the covid 19 pandemic. The application of e-learning in the world of education is currently the main thing and requires evaluation of its use. This study aims to determine the evaluation of models and trends in the development of e-learning (Learning Management System). Applying the Kitchenham approach, this System Literature Review (SLR) uses three main databases including Science Direct, ACM, SCOPUS. The final result obtained 38 articles published between 2016 and 2021. From this SLR, it was found that there were 7 criteria, namely Platform, Evaluation Model, Evaluation, Model, Approach, Problem, Trend and Challenge. These 7 criteria can be used for further research on e-learning. Thus this research provides knowledge about criteria that can be used further in research on E-learning and provides insight into its state-of-the-art.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128190832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"APLIKASI PENGENALAN TINGKAT KEMATANGAN BUAH TOMAT MENGGUNAKAN FITUR WARNA HSV BERBASIS ANDROID","authors":"Suwanto Sanjaya","doi":"10.33365/jti.v16i1.1489","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1489","url":null,"abstract":"Tomatoes ripen relatively quickly, so tomato farmers must be able to properly sort the tomatoes for distribution. Farmers typically sort the tomatoes by hand. Tomato farmers are generally experts at manually sorting tomatoes, but humans have many limitations, such as being tired and unfocused. Because these issues can lead to inconsistencies and inaccuracies in sorting, a tool is required to help with the process. As a result, it is necessary to create an Android application to aid in the sorting process. The reason for using Android as a platform is that it is a tool that a large number of people own. The LVQ algorithm is used as a learning algorithm to find the best model for tomato recognition. To build the model, the algorithm requires features. Colors with Hue, Saturation, and Value (HSV) are used. The Personal eXtreme Programming (PXP) system development methodology was used to create applications that recognize the level of ripeness of tomatoes. Unified Modeling Language (UML) is the analytic tool of choice. The application was successfully developed on the Android platform based on the test results. The application's use results in an accuracy of 80%. Green and red tomatoes are the most well-known types of tomatoes. Turning tomatoes are difficult to identify because many of them are mistaken for green tomatoes.Keyword: Android; eXtreme Programming; HSV; Recognition; TomatoBuah tomat memiliki waktu kematangan relatif cepat, sehingga petani tomat harus dapat menyortir buah tomat dengan tepat yang akan didistribusikan. Pada umumnya petani menyortir buah tomat secara manual. Petani tomat juga pada umumnya sudah ahli dalam menyortir tomat secara manual, tetapi manusia memiliki banyak keterbatasan seperti lelah dan tidak fokus. Masalah tersebut dapat meyebabkan inkonsistensi dan ketidaktepatan dalam penyortirannya, sehingga dibutuhkan alat bantu untuk membantu proses peyortiran tersebut. Oleh karena itu, perlu dikembangkan sebuah aplikasi Android yang dapat membantu proses penyortiran tersebut. Alasan penggunaan Android sebagai platform karena merupakan alat yang banyak dimiliki orang pada umumnya. Algoritme LVQ digunakan sebagai algoritme pembelajaran untuk mendapatkan model terbaik dalam mengenali buah tomat. Algoritme tersebut membutuhkan fitur untuk membangun modelnya. Fitur yang digunakan adalah warna Hue, Saturation, dan Value (HSV). Aplikasi pengenalan tingkat kematangan buah tomat dikembangkan menggunakan metodologi pengembangan sistem Personal eXtreme Programming (PXP). Alat analisis yang digunakan adalah Unified Modeling Language (UML). Berdasarkan hasil pengujian, aplikasi berhasil dikembangkan pada platform Android. Penggunaan aplikasi tersebut menghasilkan akurasi sebesar 80%. Tomat yang paling banyak dikenali adalah tomat Green dan Red. Tomat Turning cukup sulit dikenali, karena tomat tersebut cukup banyak yang dikenali sebagai tomat Green.Kata Kunci: Android; eXtreme Programming; HSV; Pengenalan; Tomat","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130023811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KOMBINASI METODE K-MEANS DAN DECISION TREE DENGAN PERBANDINGAN KRITERIA DAN SPLIT DATA","authors":"Elly Muningsih","doi":"10.33365/jti.v16i1.1561","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1561","url":null,"abstract":"Data mining is a process of looking for patterns or pulling large and selected data information using certain techniques or methods. The K-Means and Decision Tree methods are part of the Data Mining technique. This study will combine the K-Means method to cluster data into three clusters then the results of the clustering will be classified using the Decision Tree Method with a comparison of the Gain Ratio, Information Gain and Gini Index criteria. The data is processed into two, namely training data and testing data with a percentage of 70:30, 80:20 and 90:10. The results of the research are to find out which criteria produce the best decision tree and performance based on the highest accuracy value from each data group. The data is taken from the UCI Repository with a total of 811 records and 52 attributes. From the data processing carried out, it is known that for the 70:30 data split, the accuracy value with the Gain Ratio, Information Gain and Gini Index criteria gets the same value, namely 97.53. The Gain Ratio and Gini Index criteria produce the highest accuracy value, which is 98.15% for 80:20 split data. While Information Gain got the highest accuracy value of 98.77% for 90:10 data split. Keyword : data mining, clustering, k-means, classification, decision tree","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123332680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pemetaan Kelompok Sebaran Titik Gempa Bumi Mentawai Dengan Metode K-Medoids Clustering","authors":"Yudi Setiawan, Safroni Aziz Suprianto, Andang Wijanarko, Dyah Setyo Rini, Mochammad Yusa","doi":"10.33365/jti.v16i1.932","DOIUrl":"https://doi.org/10.33365/jti.v16i1.932","url":null,"abstract":"Secara geologis Kepulauan Indonesia berada pada jalur penumjaman lempeng bumi, seperti penunjaman Lempeng Samudra Indo-Australia dengan Lempeng Benua Eurasia yang memanjang dari pantai barat Sumatera hingga pantai selatan Jawa terus ke timur sampai Nusa Tenggara.  Jalur penunjaman lempeng bumi di wilayah Kepulauan Indonesia merupakan jalur penyebab gempa tektonik yang mana bersifat regional dan umumnya kerusakan yang ditimbulkan sangat parah. Sebagian jalur gempa bumi tersebut berada di laut sehingga sangat berpotensi menimbulkan bencana tsunami . Di Indonesia sendiri, Daerah yang sangat rawan terjadinya gempa bumi dari dasar laut adalah Kepulauan Mentawai di Sumatera Barat.  Pada tahun 2010 Mentawai mengalami sejumlah gempa, yaitu gempa berkekuatan 6,8 SR pada 5 Maret 2010, disusul 6.5 SR pada 5 Mei 2010 dan terakhir gempa berkekuatan 7,8 SR pada 25 oktober 2010 yang diikuti dengan bencana tsunami. United States Geological Survey (USGS) adalah sebuah agensi ilmiah pemerintah Amerika Serikat yang didirikan pada 3 Maret 1879. Organisasi ini memiliki empat disiplin ilmiah utama, yaitu biologi, geografi, geologi, dan air. Salah satu program dari USGS adalah memonitor aktivitas gempa bumi di seluruh dunia, tak terkecuali data gempa kepulauan mentawai yang disediakan dalam bentuk datasheet. Dengan adanya kemajuan teknologi saat ini, dibutuhkan suatu sistem yang dapat memberikan informasi mengenai pemetaan kelompok sebaran titik gempa bumi mentawai dengan clustering gempa bumi. Penelitian ini bertujuan untuk Membangun Sistem Informasi yang dapat melakukan pemetaan pola sebaran gempa bumi mentawai tahun 2010 – 2019 dan juga bertujuan untuk mengimplementasikan metode K-Medoid Clustering untuk menganalisis dan memetakan pola Sebaran gempa bumi mentawai tahun 2010 – 2019. Untuk memetakan pola sebaran gempa bumi tersebut digunakan dua (2) parameter yaitu kedalaman dan kekuatan gempa bumi dengan menggunakan metode K-Medoid Clustering. Luaran yang dihasilkan berupa layout peta hasil perhitungan dari metode K-Medoids Clustering selama sepuluh (10) tahun yaitu tahun 2010 – 2019 yang terdapat sebanyak 1356 data. Selain itu terdapat juga luaran yang dihasilkan berupa tampilan diagram batang dan diagram lingkaran.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131386012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AUGMENTED REALITY VISUALISASI ANIMASI GAMBAR PADA BAJU DENGAN METODE MARKER-BASED","authors":"Kharis Muqowam, Jati Sasongko Wibowo","doi":"10.33365/jti.v16i1.1546","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1546","url":null,"abstract":"","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123007857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WEB-BASED GEOGRAPHIC INFORMATION SYSTEM FOR LAMPUNG GIFT STORE","authors":"Andi Nurkholis, Yopita Anggela, A. F. Octaviansyah P","doi":"10.33365/jti.v16i1.1486","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1486","url":null,"abstract":"In the face of increasing technological advances, the development of society refers to the ability to keep up with technological developments and the ability to access and present useful information. Lack of information and knowledge about the location of the gift store makes the public or tourists only visit the nearest store or those suggested by friends and people around. This study aims to develop a web-based geographic information system to make it easier for people to find the location of Lampung gift store. In this study using extreme programming as a development method. Based on the results of testing ISO 25010 that has been carried out involving 50 respondents, the conclusion that the quality of the software produced has a success percentage with a total average of 90.66%. So it can be concluded that the percentage value obtained shows the overall software quality has a \"Very Good\" scale and is feasible to use.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124608027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}