Jurnal Informatika: Jurnal Pengembangan IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
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431 Documents
<![CDATA[Analisis Perbandingan Metode Fuzzy Logic Dan Metode SAW Dalam Pemilihan Keluarga Penerima Bantuan Sosial ]]>
<![CDATA[Latifah, Siti Ma'rifatul]]>;
<![CDATA[Diartono, Dwi Agus]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 8, No 3 (2023) ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v8i3.5374
<![CDATA[Ensuring and fulfilling the needs of the community isa form of government responsibility to reduce existing socialinequalities. One of the efforts that the government has made isto provide social assistance through the Non-Cash FoodAssistance program. However, the process of selecting recipientsof social assistance is often not on target. For this reason, it isnecessary to build a system that is able to support in determiningdecisions for the selection of families receiving social assistance.To help the selection process of social assistance recipients, ofcourse, it must use the right and appropriate method so that theselection process produces social assistance recipients who reallydeserve assistance. The selection process in this study uses twodecision support methods, namely Fuzzy Logic and SimpleAdditive Weighting (SAW) and has conducted accuracy tests onboth methods against the suitability of recipient eligibility data,so that it can be seen which method has the highest level ofaccuracy in the selection of social assistance recipients. Theresults of the accuracy test carried out in this study are that bothmethods produce the same high level of accuracy in thesuitability of prospective recipient eligibility results, namely100%, this means that both methods can be used in determiningrecipients of social assistanc.]]>
<![CDATA[Penerapan Product Knowledge dan Strategi UpSelling Pada Chandra Tech Palembang ]]>
<![CDATA[Fitri Purwaningtias]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 3, No 2 (2018): JPIT, Mei 2018 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v3i2.826
<![CDATA[Chandra Tech store is a store that sells computer along with other computer accessories. In the Chandra store sales system is still having difficulties in searching for existing products and difficulties in finding information on goods products in the store and information specifications of goods to be purchased and still lack of public knowledge about the existence of this Chandra store. To overcome this problem then the application of product knowledge is suitable for this research is to provide information about the product to be sold with detail of goods, and recommends an up selling strategy in sales by explaining the most expensive products, product searches, and about purchases and payments as well as about purchases and payments that can be done so that customers become more interested in purchasing the most expensive products. The research is website for product selling with the application of product knowledge and sales up selling strategy with a descriptif method for research and system development method is OOAD (Object Oriented Analysis and Design) starting from requirements, analysis, design, implementation and testing. With this website can help customers in facilitating the purchase of products in this store and can help the store to promote products sold and can raise services to customers through online sales.]]>
<![CDATA[Ekstraksi Ciri Polip dan Pendarahan Berdasarkan Citra Endoskopi Kolorektal ]]>
<![CDATA[Ummi Athiyah]]>;
<![CDATA[Izzati Muhimmah]]>;
<![CDATA[Erlina Marfianti]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 3, No 1 (2018): JPIT, Januari 2018 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v3i1.704
<![CDATA[Cancer is one of the main causes of mortality in the world. Colorectal cancer, also known as colon cancer, is a malignant tumor of the colon and rectum that begins with a polyp. Early inspection is needed to prevent and cure of colorectal cancer because in the early stages colorectal cancer showed no symptoms. At this time the development of information technology allows the quick information retrieval from an image. The aim of this research is to produce a preliminary work in the stages of information analyzing on colorectal endoscopic image extraction result in the form of polyp and bleeding by utilizing extraction technique of image information based on shape and texture. This research aimed can be the basis for the development of colorectal cancer detection system framework. The research that has been carried out gives result of characteristics that can be differentiate between colon bleeding, colon polyp, and normal colon conditions, they are aspect ratio, triangle, correlation, and energy.]]>
<![CDATA[Perancangan Kantor Digital Berbasis Framework dengan Metode Waterfall pada Politeknik Negeri Lampung ]]>
<![CDATA[Tri Sandhika Jaya]]>;
<![CDATA[Dwirgo Sahlinal]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 2, No 2 (2017): JPIT, Juli 2017 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v2i2.518
<![CDATA[MVC dikembangkan untuk memetakan input, process, output. Web framework sangat cocok untuk pengembangan aplikasi berbasis web karena lebih fleksibel dan secure. Proses bisnis di perguruan tinggi tidak akan lepas dari berbagai permasalahan, seperti manajemen projek yang kurang rapi, atau proses manajemen lainnya, informasi yang kurang akurat dan responsi naskah atau dokumen menggunakan kertas, apabila dilakukan berulang maka dapat memicu pengeluaran dana yang tidak sedikit, pencarian dokumen hardcopy dimasa yang akan datang juga sulit dilakukan karena tidak ada tempat penyimpanan secara elektronik. Maka untuk mengatasi permasalahan tersebut maka peneliti mengembangkan Kantor Digital berbasis framework dengan Metode Waterfall.]]>
<![CDATA[Analisis Kinerja Rantai Pasok Produk Kedelai Menggunakan Metode Supply Chain Operation Reference ]]>
<![CDATA[Fathoni, M Yoka]]>;
<![CDATA[Prabowo, Dedy Agung]]>;
<![CDATA[Wijayanto, Sena]]>;
<![CDATA[Fernandez, Sandhy]]>;
<![CDATA[Susanto, Ardi]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 7, No 2 (2022) ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v7i2.3740
<![CDATA[Indonesia is a country that has one of the advantages, namely as the largest agricultural country that has natural wealth, one of which is the agricultural sector. Soybean is one of the most widely grown crops in Indonesian agriculture and is included in the legumes group which has the highest vegetable protein content when compared to other types of beans such as red beans, green beans, and peanuts. The use of the SCOR method in this study is to measure good SCM performance, because SCOR divides supply chain processes into five 5 core processes, namely plan, source, make, deliver and return, where these processes have represented all supply chain activities. management from upstream to downstream in detail, so that it can define and categorize the measurement indicators needed in measuring Supply Chain Management performance. Based on the SCOR method, the results of the calculation of the final performance value of the soybean supply chain in the province of Central Java are 76.8 out of 100 which are in the "good" category.]]>
<![CDATA[Perbandingan Algoritma Word Matching dan Naive Bayes untuk Klasifikasi Sentimen Analisis Komentar Instagram ]]>
<![CDATA[Agnes Asthika Setyawinda]]>;
<![CDATA[Barep Setiyadi]]>;
<![CDATA[Anggit Dwi Hartanto]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 5, No 1 (2020): JPIT, Januari 2020 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v5i1.1733
<![CDATA[Analisis sentimen telah menunjukkan bahwa otomatisasi dan pengenalan komputasi terhadap sentimen adalah mungkin dan berkembang seiring berjalannya waktu, karena faktor munculnya tren teknologi baru dan keadaan yang semakin dinamis dari bahasa manusia sebagai bentuk komunikasi. Dengan adanya media sosial semakin banyak pula teks-teks berupa data informal, menyebabkan proses ekstraksi dan penguraian informasi yang relevan menjadi masalah. Oleh karena itu pada penelitian ini penulis mengusulkan dua metode klasifikasi yang kemudian akan melakukan perbandingan hasil dari kedua metode tersebut.]]>
<![CDATA[Deep Learning untuk Identifikasi Daun Tanaman Obat Menggunakan Transfer Learning MobileNetV2 ]]>
<![CDATA[Hendri Butar-Butar, Rio Juan]]>;
<![CDATA[Marpaung, Noveri Lysbetti]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 8, No 2 (2023) ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v8i2.5217
<![CDATA[Medicinal plants are plants used as alternative medicines for healing or preventing various diseases due to their active substances. The utilization of medicinal plants in Indonesia has been widespread among the community since ancient times and is a heritage passed down from ancestors. Medicinal plants have leaf structures that are almost similar between one plant and another, which can lead to confusion for some people and require precision in identifying the leaves of medicinal plants. Incorrect identification can have negative consequences for the users. In recent years, deep learning has been used to identify objects because of its ability to interpret images. This study used a transfer learning method to identify medicinal plants. Transfer learning utilizes a pre-trained model to learn and perform new tasks, making it suitable for smaller datasets. The pre-trained model used in this study is MobileNetV2. MobileNetV2 has a lightweight architecture and high accuracy. Fine-tuning techniques were applied in this study to improve the model's performance. Several experiments were conducted with parameters such as epochs and fine-tuning layers to obtain the best results. The research yielded a training accuracy of 97%, validation accuracy of 96%, and testing accuracy of 93%.]]>
<![CDATA[Analisa Perbandingan Algoritma Klasifikasi Studi Kasus: Prediksi Area Rawan Kebakaran di DKI Jakarta ]]>
<![CDATA[Rafika Awaliah]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 6, No 2 (2021): JPIT, Mei 2021 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v6i2.2430
<![CDATA[sering terjadi di perkotaan kebakaran yang terjadi tidak dapat di prediksikan penyebabnya dan kapan terjadinya bencana itu datang, dengan persiapan dan peringatan dini adalah salah satu upaya pengecahan bencana kebakaran. Masalah yang sering dihadapi adalah masyarakat yang kurang informasi terhadap pencegahan kebakaran di daerah tersebut. Meningkatnya di daerah rawan kebakaran tersebut membutuhkan upaya perlindungan kebakaran. Kebakaran di DKI Jakarta membutuhkan perhatian khusus dalam menanggulangi kebakaran. Salah satu upaya pencegahan kebakaran yaitu dengan memberikan langkah-langkah mitigasi terhadap daerah yang terindentifikasi sebagai daerah rawan dan memberikan informasi kepada pemerintah terkait strategi yang akan dilakukan untuk daerah yang rawan kebakaran. Berdasarkan hal tersebut penelitian ini mengaplikasikan dengan metode data mining untuk membandingkan kinerja algoritma Multilayer Perceprton dan Convolutional Neural Network dari berbagai eksperimen untuk menemukan algoritma yang memiliki akurasi tertinggi dengan prediksi yang tepat dalam mengklasifikasikan kebakaran sebagai durasi kebakaran yaitu sebentar, sedang atau lama.Proses klasifikasi di evaluasi dengan menggunakan cross Validation dan Confusion matrix. Dari hasil perbandingan penggunaan kedua algoritma menunjukkan bahwa Multilayer Perceptron dengan akurasi sebesar 99% , Hasil Epoch dengan hasil akurasi terbaik pada epoch 50 yaitu 99.61% dan cross validation menggunakan 10 fold untuk nilai validasi akurasi sebesar 98.12%. Sedangkan algoritma Convolutional Neural Network dengan akurasi sebesar 97% , Hasil Epoch dengan hasil akurasi terbaik pada epoch 50 yaitu 97.5% dan cross validation menggunakan 20 fold untuk nilai validasi akurasi sebesar 86.52%. Dari Hasil dataset tersebut menunjukkan bahwa algoritma Multilayer Perceptron lebih mengungguli dari pada algoritma Convolutional Neural Network. Untuk pengembangan berikutnya, studi ini bisa dilanjutkan menjadi model dalam sebuah aplikasi peringatan dini terhadap bencana kebakaran di DKI Jakarta.]]>
<![CDATA[Penerapan Teori Graf Pada Jaringan Komputer Dengan Algoritma Kruskal ]]>
<![CDATA[Fajar Mahardika]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1032
<![CDATA[Graph theory a branch of mathematics that studies graphs of a problem that arises. Problems related to graph theory include electricity grid planning, water networks, computer networks and so on. In this graph theory, many of the methods studied include Minimum Spanning Tree (MST). This MST method is used to determine a minimum of a graph. In this MST there is an algorithm which is a kruskal algorithm. This kruskal algorithm is used to determine the shortest distance or minimum tree of a graph. The author conducted several trials related to the algorithm to be used. The author also conducts literature studies to determine the existing problems. In this study, choosing graph theory on a computer network with the algorithm used is the kruskal algorithm. In this study the authors conducted several stages such as hypotheses, trials and results. The results of this study are graph theory can be applied to computer networks, the number of devices needed can be known and in this experiment the algorithm gives a very maximum total used.]]>
<![CDATA[Prototype of Personal Knowledge Management on Higher Education ]]>
<![CDATA[Ilyas Nuryasin]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 3, No 1 (2018): JPIT, Januari 2018 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v3i1.662
<![CDATA[This study proposed a prototype of personal knowledge management system on higher education. Personal knowledge management system is a method that used by person to manage his own knowledge. The knowledge will be classified and stored in the databases system and retrieved when needed. This study is focused for the students who take courses during undergraduate program period. All academics activities will be recorded in the system and published as portfolio on the end of study as a complementary document along certificate and transcript. This prototype offers the students to manage their knowledge from their projects, prototypes, patents, researches, seminars and work experiences.]]>
