Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika
Jurnal Teknologi Informasi (JTI) diterbitkan adalah Jurnal Jurusan Teknik Informatika Universitas Palangka Raya dengan ISSN 1907-896X, E-ISSN 2656-0321. Jurnal Teknologi Informasi (JTI) merupakan Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika yang menyajikan hasil penelitian yang fokus pada bidang informatika. Jurnal Teknologi Informasi (JTI) terbit dua kali dalam satu tahun (Januari dan Agustus). JTI ini fokus mempublikasi hasil penelitian orisinal yang belum diterbitkan di mana pun, isu yang dipublikasi oleh JTI meliputi pengembangan ilmu pengetahuan komputer dan informatika, fokus pada sains ilmu komputer, teknologi komputer tepat guna, dan rancang bangun sistem informasi.
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<![CDATA[SMARTBOX PENERIMA PAKET BELANJA ONLINE ]]>
<![CDATA[Deddy Ronaldo]]>;
<![CDATA[Nahumi Nugrahaningsih]]>;
<![CDATA[Edy Pratamajaya]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.8782
<![CDATA[At the time of the development of industry 4.0, freight forwarding services urgently needed increased online buying and selling services supported by e-commerce. Problems with delivery services are usually caused by the sender himself. For example, such as damage and loss of goods sent, high shipping costs and erratic delivery times. To overcome the above problems, the researcher created a design in the form of a package receiving box using a linear sequential method such as analysis, design, coding and testing where this box can later be used when the box owner is not at the box's house. The box that is made has a camera that is used to monitor the whereabouts of the person in front of the box, if someone is in front of the box, the box will send a notification to the telegram so that later the owner can control the box to open so that packages can be put into the box. The final result of this research is a package receiving box that can be controlled and provides notification via telegram, where this tool uses a camera as a person detector and ultrasonic to detect items in the box, which will later provide notifications to the telegram bot so that the package owner knows if there is a courier or not in front of the package receiving box, and also telegram can control the servo to unlock the package receiving box itself.]]>
<![CDATA[PERANCANGAN APLIKASI KAMUS DIGITAL BAHASA LAWANGAN – BAHASA INDONESIA ]]>
<![CDATA[Ariesta Lestari]]>;
<![CDATA[Nahumi Nugrahaningsih]]>;
<![CDATA[Dwiani Septiana]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.9095
<![CDATA[Local language is a representation of cultural identity. Apart of being used as communication tools, local language also contains valuable values and local language. Central Kalimantan has a lot of undocumented local language, etiher conventially, let alone digitally. The purposes of this research is to provide a digital vocabulaty of Dayak Lawangan in Central Kalimantan. The stages in Rapid Application Develoment (RAD) method was adopted to build the application. The method was chosen because it is suitable for the lack of development time but it still can provide a precise and complies with the stages of making an application. With this applicatioin, it is hoped that the existence of local language of Dayak Lawangan community can be well documented in order to maintain the diversity.]]>
<![CDATA[FORECASTING SALES DATA ON E-COMMERCE USING SINGLE EXPONENTIAL SMOOTHING METHODS ]]>
<![CDATA[Ida Jubaidah]]>;
<![CDATA[Dian Pratiwi]]>;
<![CDATA[Teddy Siswanto]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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<![CDATA[Forecasting is predicting the occurrence of something in the future by referring to historical data that occurred in the past that can be used to conduct business analysis. Fairez Shop is an MSME engaged in selling clothing which in its operations generates tens of thousands of data that has never been used for business purposes. Fairez shop also requires a forecasting analysis to predict sales of its products in order to manage supply and help make decisions related to future business. From the problems described above, this research will forecast sales data at the Fairez Shop. The ETL process for designing the OLAP database in this study uses Pentaho Data Integration and the forecasting method used is single exponential smoothing and standard error mean absolute percentage error with R Studio tools, then forecasting results are visualized using Power BI tools. From the trial results, the standard error was obtained in January 2023 of 36.99655%, in February 2023 of 2.817564% and in March 2023 of 2.884921%. With a standard error percentage value below 50%, it can be concluded that this forecasting is feasible and applicable.]]>
<![CDATA[RANCANG BANGUN SISTEM DETEKSI KEMATANGAN BUAH KELAPA SAWIT BERDASARKAN DETEKSI WARNA MENGGUNAKAN ALGORITMA K-NN ]]>
<![CDATA[Ade chandra Saputra]]>;
<![CDATA[Enny Dwi Oktaviyani]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.9232
<![CDATA[The rapid growth of the palm oil industry has made it increasingly important to develop applications that can detect the maturity level of oil palm fruit. This paper presents the design and development of an application for detecting the maturity level of oil palm fruit based on color composition using the K-NN algorithm. The K-NN algorithm is used to classify the oil palm fruit based on the color composition that is related to its maturity level. The application uses image processing technology to measure the qualitative and quantitative parameters of various maturity indicators, such as color, size, and texture. Different color compositions of the oil palm fruit indicate different maturity levels, and using the K-NN algorithm, the fruit can be classified based on its maturity level. The application helps reduce production costs and losses caused by errors in harvesting the fruit. The application is designed to be user-friendly and accessible to farmers and plantation managers. The user interface is simple and intuitive, allowing users to easily input the image of the oil palm fruit and get a quick analysis of its maturity level. The results are displayed in a clear and understandable way, making it easy for users to make informed decisions about when to harvest the fruit. In conclusion, the application for detecting the maturity level of oil palm fruit based on color composition using the K-NN algorithm is a useful tool in the palm oil industry. It helps farmers and plantation managers determine the optimal time for harvesting the fruit, reducing production costs and increasing productivity. The user-friendly interface makes it accessible to a wider range of users and facilitates informed decision-makin]]>
<![CDATA[PERBANDINGAN PERFORMA ALGORITMA K-MEANS, K-MEDOIDS, DAN DBSCAN DALAM PENGGEROMBOLAN PROVINSI DI INDONESIA BERDASARKAN INDIKATOR KESEJAHTERAAN MASYARAKAT ]]>
<![CDATA[Ferista Wahyu Saputri]]>;
<![CDATA[Dede Brahma Arianto]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.9558
<![CDATA[One of the development orientations in Indonesia is to improve the welfare of society. Therefore, it is important to identify and understand the characteristics of community welfare in each province in order to determine effective and targeted development strategies. Cluster analysis is one of the analyses that can be used to group provinces in Indonesia that have homogeneous characteristics within a cluster. The partition method is the simplest and fundamental approach to cluster analysis, but it can only find clusters with spherical-shaped forms. On the other hand, DBSCAN is a density-based clustering algorithm that can be used to find clusters with arbitrary shapes. In this study, the performance of the K-Means, K-Medoids, and DBSCAN algorithms was compared using data that had been dimensionally reduced using the t-SNE method. The data used was the indicator data of community welfare in the year 2022. The evaluation results of clustering based on the highest Silhouette coefficient (0.917) and the lowest Davies-Bouldin index (0.089) indicate that the best clustering methods are K-Means and DBSCAN with parameters perplexity = 1, minPts = 2, and epsilon = 9. Both methods produce the same result, which is the formation of eight clusters.]]>
<![CDATA[PERANCANGAN PROTOTIPE DAPUR PINTAR BERBASIS IOT MENGGUNAKAN NODEMCU ESP8266 DAN APLIKASI BLYNK ]]>
<![CDATA[Aryo Lukito]]>;
<![CDATA[Andhika Solihan Asbi Adimart Permana]]>;
<![CDATA[Seandy Satrio Rianto]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 1 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v18i1.9795
<![CDATA[Industrial revolution 4.0 allows the integration of digital technology with human life through the Internet of Things. One form of IoT application is in kitchen devices. In this case, kitchen safety is the main concern. In this research, an IoT device was developed that can detect gas leaks in the kitchen. The success of previous studies using gas sensors Arduino Uno and MQ2, MQ3 and MQ5 proved to be able to detect gas leaks, but there are still some deficiencies in these devices such as not being connected to mobile devices and efforts to reduce gas levels. Therefore this study adds a feature to monitor room temperature and humidity using the DHT11 sensor, as well as a remote connection feature via a smartphone. In addition, an automatic fan feature is also added to suck up excess gas levels. So that this research is expected to facilitate the process of monitoring the kitchen and reduce the risk of gas leaks which are harmful to health and safety.]]>
<![CDATA[KOMPARASI ALGORITMA NAIVE BAYES DAN K-NEAREST NEIGHBOR PADA ANALISIS SENTIMEN TERHADAP ULASAN PENGGUNA APLIKASI TOKOPEDIA ]]>
<![CDATA[Ryfan Maulana]]>;
<![CDATA[Muhammad Raihan]]>;
<![CDATA[Imam Santoso]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.10071
<![CDATA[Tokopedia is one of the leading e-commerce platforms in Indonesia. The use of e-commerce platforms has increased rapidly in recent years. This is due to technological advances, increased internet access, and consumer behavior that prefers to shop online. In today's digital era, user reviews have an increasingly important role in shaping consumer perceptions of a product or service. The purpose of this research is to conduct sentiment analysis on application performance based on user reviews of the Tokopedia application. Researchers made the decision to use sentiment analysis because it is the most suitable method for processing data sets. From 1019 Tokopedia user reviews on the Play Store that were collected, 176 positive reviews and 843 negative reviews were obtained. Then, the data is classified using the Naive Bayes and K-Nearest Neighbor algorithms, then optimized using Particle Swarm Optimization. The results of the research conducted obtained an accuracy of 76.30% for the Naive Bayes accuracy value without feature selection, 74.09% for Naive Bayes results using feature selection. Then the accuracy value obtained for K-Nearest Neighbor without feature selection is 83.10%, and with feature selection is 83.53%. From the results obtained, the effect of using Particle Swarm Optimization selection features on the two algorithms does not have a big impact, there is an insignificant change in accuracy and AUC values which in the Naïve Bayes algorithm actually decreases]]>
<![CDATA[SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN KREDIT MENGGUNAKAN METODE ELECTRE (Studi Kasus : Koperasi Kredit Immaculata) ]]>
<![CDATA[Mayela Wete]]>;
<![CDATA[Yoseph P.K Kelen]]>;
<![CDATA[Siprianus S. Manek]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.10347
<![CDATA[The Immaculata Credit Cooperative is a cooperative organization whose mission is to advance the Immaculata Credit Cooperative as a reliable, independent and professional microfinance empowerment institution. One of the cooperative sectors is the credit sector because credit is a source of financing for cooperatives. Lending at the Immaculata Credit Cooperative is currently still subject to manual analysis by the credit committee, so that an inaccurate determination of credit granting can increase the number of bad or default loans. Therefore the researcher proposes to build a decision support system using the electre method where the output of the electre method calculation is in the form of ranking so that it can determine recommended prospective customers by looking at 5 assessment criteria including income, length of time to return, occupation, age, and collateral. The results of this study are in the form of desktop-based applications that can make it easier for cooperatives, especially credit committees, to determine which customers to recommend.]]>
<![CDATA[RANCANG BANGUN APLIKASI INFORMASI TATA LETAK PERPUSTAKAAN BERBASIS VIRTUAL REALITY ]]>
<![CDATA[Kania Aulia]]>;
<![CDATA[Missi Hikmatyar]]>;
<![CDATA[Ruuhwan]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 2 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v7i2.10456
<![CDATA[Technological developments are developing very quickly, so in this digital era, the use of technology as an effort to improve the delivery of information and promotional media at Perjuangan University uses Virtual Reality technology. Because not all students know or even have never visited the library. This study aims to produce a library layout information application based on Virtual Reality. An Android-based application that can provide information about the layout and usability of the library in a virtual form as if it were in a location using the VR Box tool as the media. The tests were carried out using ISO 25010 quality standards, namely the parameters of functional suitability, portability, and usability using a Likert scale measurement. The results of this study obtained a score of 84% in the "Good" category based on user satisfaction when using the application.]]>
<![CDATA[PREDIKSI HARGA SAHAM MENGGUNAKAN ALGORITMA NEURAL NETWORK ]]>
<![CDATA[Muhamad Zulfani]]>;
<![CDATA[Dapadeda, Ardiyanto]]>
<![CDATA[ Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 1 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform ]]>
Publisher : <![CDATA[Universitas Palangka Raya ]]>
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DOI: 10.47111/jti.v18i1.11303
<![CDATA[In recent years, the development of technology and artificial intelligence has brought forth new opportunities in analyzing and predicting stock prices. One of the approaches used is the Neural Network algorithm, which is a part of the branch of artificial intelligence known as Deep Learning. This algorithm can learn complex patterns and relationships among data by modeling inspired by the human neural network. This research utilizes the Neural Network for stock price prediction and aims to understand the application of Neural Network in predicting stock prices, which can benefit investors and market participants. Additionally, historical stock price data can be used as input for the Neural Network algorithm. The Neural Network is a frequently used algorithm for accurate predictions and is widely employed in prediction-based or forecasting research. The result of this research is the Root Mean Squared Error (RMSE) value of 19.734 +/- 0.000. The use of the Neural Network as an algorithm for stock price prediction provides investors with valuable information for making investment decisions for companies..]]>
