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All Journal Jurnal POINTER Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Reformasi : Jurnal Ilmiah Ilmu Sosial dan Ilmu Politik Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Bulletin of Culinary Art and Hospitality
Edy Santoso
Fakultas Ilmu Komputer , Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Implementasi Metode Support Vector Machine Dengan Query Expansion Pada Klasifikasi Review Di Situs Traveloka Meutya Choirunnisa; Nurul Hidayat; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 5 (2021): Mei 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Choosing a tourist destination when you want to go on vacation is a must for people so that they don't choose a tourist location wrong and so they don't get disappointed when they have visited a tour. A review is needed in this case, because with the review the public can find out the comments given by previous visitors. The comments given are not only in the form of praise, but sometimes there are visitors who feel disappointed so that they give bad comments too. The number of comments that sometimes makes people difficult and takes a long time to find out all the advantages and disadvantages of a tourist destination. To overcome this problem, a classification of tourism reviews is carried out using the SVM and QE methods. In this study, 200 data comments were used which were divided into positive and negative. The method used in this research is the Support Vector Machine method with a linear kernel with Query Expansion. QE in this case has the utility to expand the words that are in the test data that have synonyms for words that are not found in the training data. The results of the test produce an average accuracy value of 87.50% with the parameter value of learning rate = 10 and complexity value = 20. Based on the test results, the accuracy of using the SVM method with QE is 87.50% and accuracy using the SVM method without QE of 77.50%.
Pengembangan Sistem Manajemen Tengkulak Kopi Given Berbasis Web Muhammad Aulia Rahman; Fajar Pradana; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One type of beverage that comes from plants is coffee, coffee is made from processed coffee plant crops in the form of seeds. Coffee belongs to the Rubiaceae family with the genus Coffea. Coffee can also be included in the class of psychostimulant drinks which can temporarily relieve drowsiness, reduce fatigue, and increase energy as a physiological effect. The increase in the coffee industry in Indonesia is marked by the increase in consumption of processed coffee products with a percentage of up to more than seven percent in 2016 and continues to increase every year. Given coffee middlemen, as one of the coffee industry players run by the munte family, which began in 2000. Given's coffee middleman business process, which starts with purchasing coffee beans from the harvest that must be done on market days, from Thursday to Saturday every week is considered not effective to meet the needs of three tons of processed coffee stock every month. Furthermore, the sales or promotion process which is still by word of mouth is considered outdated and often reduces profits because there are often brokers who promote products to buyers and ask for profit sharing for their promotions. Based on these problems, a system is made to simplify the process of buying and selling coffee beans at given coffee wholesalers. The system development stage includes the stages of needs analysis, implementation, and testing. In the analysis step, there are 32 functional requirements and one non-functional requirement. The implementation stages use the PHP programming language on the CodeIgniter framework and MySQL in the database section. Then the testing step consists of several tests such as functional and non-functional testing. Functional testing consists of unit testing that successfully runs the test path based on 3 test cases, integration testing on the method obtains valid status and validation testing obtains 100% validity from 49 test cases. Non-functional testing using usability testing obtained system results that were acceptable to users with a final score of 73.25.
Rekomendasi Pengambilan Judul Skripsi Menggunakan PSO-Neighbor Weighted K-Nearest Neighbor (NWKNN) (Studi Kasus: Jurusan Ilmu Keolahragaan Fakultas Ilmu Keolahragaan Universitas Negeri Medan) Rizky Ramadhan; Imam Cholissodin; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

This research is non-implementative descriptive with the K-Means technique as the initial formation of the clusters of graduated student thesis titles, the PSO technique as a course selection, and the Neighbor Weighted K-Nearest Neighbor (NWKNN) technique as data classification and algorithm performance measurement using the technique. accuracy. The data collection of this research is in the form of document studies from 2016/2019 graduate students from the Faculty of Sport Sciences, State University of Medan. The purpose of this study was to determine the parameter value and accuracy value of the application of the NWKNN algorithm to provide the best recommendations regarding the thesis title raised by students. The results of this study can be concluded that in testing the percentage of many comparisons of training data and testing data used is 90%: 10%. The generation and feature testing resulted in a generation that began to be constant in the 50th generation and with 15 subjects, namely: MK2, MK6, MK7, MK11, MK12, MK13, MK14, MK15, MK21, MK24, MK26, MK27, MK28, MK31, MK32. In testing the K value, the optimum K value is 3. In testing the K and E values, the optimum K and E values ​​are 3 and 2. The PSO-Neighbor Weighted K-Nearest Neighbor (NWKNN) algorithm for recommendations for thesis title retrieval produces an optimum value using parameters previously obtained an accuracy of 88.28%.
Prediksi Nilai Ekspor Impor Migas Dan Non-Migas Indonesia Menggunakan Extreme Learning Machine (ELM) Dhatu Kertayuga; Edy Santoso; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 6 (2021): Juni 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia's resource wealth is one of the important assets for a developing country. To advance the wheels of the Indonesian economy, trade activities between countries are carried out, namely exports and imports. Resources exported and imported by Indonesia are oil and gas and non-oil and gas resources. Although Indonesia is capable of producing its own oil and gas and non-oil and gas products, Indonesia's imports of oil and gas and non-oil and gas are still higher than Indonesia's total exports of oil and gas and non-oil and gas. To assist Indonesia's economic development strategy, a prediction is needed to estimate the value of Indonesia's oil and gas and non-oil and gas exports and imports. In this study, the algorithm used is Extreme Learning Machine (ELM). Then, the data used are oil and gas and non-oil and gas export data as well as oil and gas and non-oil and gas import data obtained from the Badan Pusat Statistik (BPS) from January 1993 to December 2020. The results obtained from this study are export data with the average mean absolute percentage error (MAPE) value of 6.6742% for the comparison of the number of training : testing, the number of data features, and the number of hidden neurons the best is 70%:30%, 5, and 8. While for import datasets, the comparison of the number of training : testing, the number of data features, and the number of hidden neurons is the best 80%:20%, 4, and 10 with a final MAPE average of 10.0515%.
Prediksi Harga Saham Menggunakan Metode Extreme Learning Machine (ELM) (Studi Kasus: Saham PT Bank Rakyat Indonesia) Yunita Dwi Lestari; Edy Santoso; Achmad Ridok
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 7 (2021): Juli 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Shares are a sign of ownership or membership of an entity or individual. The profit from the purchase of shares is derived from the acquisition of dividends and capital gains. The existence of stock trading in the secondary market, making the ups and downs of the share price so that there is a capital gain. A person who becomes a stock investor and takes advantage by selling shares he owns when the share price is higher than his previous purchase price is referred to as a trader. Due to fluctuations in the stock price, a trader needs analysis before making a stock purchase in order to avoid the risk of losses. In order to avoid losses of traders in the stock market, a stock price prediction system was created using the Extreme Learning Machine (ELM) method. After the prediction test with ELM obtained the most optimal parameters to make stock predictions, namely by using the number of data inputs 3, the number of hidden nodes 5, the type of activation function is binary sigmoid, and the ratio of training data and test data by 90% : 10% so that the average value of MAPE is obtained by 1.59722%.
Pembentukan Daftar Stopword Goffman Transition Point dengan Pembobotan Emoji pada Analisis Sentimen di Twitter Rizky Maulana Iqbal; Yuita Arum Sari; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Implementasi Metode K-Nearest Neighbor untuk Penentuan Lokasi Flight Information Display System Dayu Aprellia Dwi Putri; Nurul Hidayat; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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The purpose of this study was to determine the location of the FIDS at Soekarno-Hatta International Airport in Jakarta using data from the FIDS equipment list. Non-implementatif analytical research methods are carried out by classifying data from the FIDS equipment list using the K-Nearest Neighbor method by dividing the data into training data and test data. The benefit of the research is to find out the results of the implementation using data from the FIDS equipment list and the results of the evaluation seen from the level of accuracy obtained so that it can determine the feasibility of using the K-Nearest Neighbor method to determine the location of FIDS. In this study it was found that the results of the implementation of the K-Nearest Neighbor method using IP Address and Terminal data as calculation data and Location data as target data can be applied properly in determining the location of FIDS because the resulting accuracy rate reaches 96,154% with the optimal K value for used in the system is 1.
Sistem Informasi Manajemen Pendataan Sandang dan Penjualan Online pada Toko DRESSCODE berbasis Web menggunakan metode Waterfall SDLC Faldo Sabillah Shidqi; Edy Santoso; Nurudin Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The Sistem Informasi Manajemen Pendataan Sandang Dan Penjualan Online is a system that created to aid the store owner and manager in managing goods so there wont be any mistakes managing and listing products. And costumer could access the store catalog without have to visit the store, and the store owner could see the trend based on the number products visited on the website. The system could also list the products that are running out of stock so the store manager could re-stock the items. And then theres a feature that shows income of the store. The software development process starts from analyzing the requirements and object oriented testing. There are 21 functional requirements based on the analyzing phase. The implementation phase was carried out using Laravel. Unit testing produces 100% valid data from 3 tested function, while the validation test produces 100% valid data from 21 tested function. Compatibility Tests were done using 3 different browsers : Google Chrome, Mozilla Firefox, and Microsoft Edge.
Penerapan Metode Extreme Learning Machine (ELM) dengan Optimasi Particle Swarm Optimization (PSO) untuk memprediksi Harga Cabai Keriting di Kota Malang Tara Dewanti Sukma; Imam Cholissodin; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Curly chili is a basic necessity for the people of Malang City, namely as a complement to cooking spices so that its existence is often sought after. This causes fluctuation due to the influence of the amount of demand on price change. So a price prediction system for curly chilies is needed in Malang City to minimize price instability. Extreme Learning Machine (ELM) is a prediction method that has high accuracy and faster execution time. ELM does not have a feature selection function, so an optimization method such as Particle Swarm Optimization (PSO) is needed. PSO is implemented as a solution to get optimal weight with the fitness value as a comparison. Based on the tests that have been carried out on the price of curly chilies, the average MAPE value is 1,133803% and the average fitness value is 0,400346 with optimal parameters consisting of 2 features, hidden neuron is 3, the percentage comparison between training and testing data is 90%: 10%, the weight of inertia is 0,5, c1 is 3, c2 is 1,5, the lower speed limit value is -0,8, the speed upper limit value is 0,8, the population is 100, and it is carried out by 260 iterations. From the test results, it can be concluded that PSO is able to optimize the ELM weight so it could gets optimal accuracy.
Sistem Pengelolaan Inventory Gudang (Studi Kasus: PT. Papua Utama Mitra) Bagus Aryo Herlambang; Edy Santoso; Achmad Arwan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 10 (2021): Oktober 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Warehousing basically functions to store goods for production in large quantities and a certain time span which is then distributed to the intended location. Warehousing will be able to operate more easily if there is a Warehouse Management System. Warehouse Management System that uses information systems will be able to assist in the management and supervision of incoming goods and outgoing goods in the warehouse. At this time, there are still some warehousing companies that use manual system processes starting from inbound customer documents, and others. There are problems found in the Admin and Checker PT. Papua Utama Partners. On the admin side, the problem is in the form of Time Working Efficiency. In this case, Time Working Efficiency is very influential on the quality of the company because it will be able to slow down the time in processing the queue of incoming or outgoing goods. The main purpose of this research is to make it easier for the Admin to process incoming mail and allocate goods by developing a warehouse inventory management system. This study uses one of the development methods, namely the waterfall model. Based on the needs elicitation carried out, there are 24 functional requirements and 1 non-functional requirement. In unit testing, validation testing, and integration, each result is 100% valid.
Co-Authors Abdul Juli Andi Gani Achmad Arwan Achmad Ridok Adam Hendra Brata Adhi Mulhaq Adhie Indi Arsyanto Adhipramana Raihan Yuthadi Adinugroho, Sigit Aditya Sudarmadi Agung Dwi Budiarto Agus Prayogi Ahmad Faizal Akbar Imani Yudhaputra Akhsana Zufar Masyhuda Alif Fachrony Alif Prasetyo Aji Andriko Hedi Prasetyo Annam Rosyadi Annisa Puspitawuri Arief Andy Soebroto Arinda Ayu Puspitasari Aulia Dinia Ayu Tifany Novarina Bagus Aryo Herlambang Bayu Rahayudi Bregaster Bregaster Brigitta Ayu Kusuma Wardhany Caesaredi Rama Raharya Candra Dewi Charisma Amadea Putri Dayu Aprellia Dwi Putri Dendry Zeta Maliha Denis Ahmad Ryfai Denny Sagita Rusdianto Dewan Rizky Bahari Dhatu Kertayuga Dian Eka R Dicky Manda Putra Sidharta Dimas Prenky Dicky Irawan Dino Keylas Dwi Tyas Fitriya Ningsih Dytha Suryani Edwar Budiman Ega Ajie Kurnianto Elkaf Fahrezi Soebianto Putra Elna Diaz Pradini Fahri Ariseno Faizatul Amalia Fajar Pradana Faldo Sabillah Shidqi Faris Dinar Wahyu Gunawan Faturrahman Muhammad Suryana Febri Fahrizal Freddy Ajax Pratama Galih Aulia Rahmadanu Genjah Amartha Gora Ghiffary Rizal Hamdhani Greviko Bayu Kristi Habib Putra Kusuma Negara Hafshah Durrotun Nasihah Heny Dwi Jayanti Herlina Devi Sirait Heru Nurwasito Heryadi Mochamad Ramdani Hinandy Nur Anisa Imam Cholisoddin Imam Cholissodin Indriati Indriati Irwan Andriyanto Ivan Agustinus Jauhar Bariq Rachmadi Jeffrey Simanjuntak Jodi Irjaya Kartika Jojor Yeanesy Sinaga Kenty Wantri A Khairinnisa Rifna Khrisna Indrawan Eka Putra Khusnul Aidil Santosa Komang Anggada Sugiarta Krisna Andryan Syahputra Effendi Lailatul Fitriah Lailil Muflikhah M. Ali Fauzi Made Bela Pramesthi Putri Marji Marji Maya Febrianita Meilinda Dwi Puspaningrum Meutya Choirunnisa Miga Palma Putri Mochamad Rafli Andriansyah Moh. Zulfiqar Naufal Maulana Mohammad Zahrul Muttaqin Muh Hamim Fajar Muh. Thanthowi Lathif Muhamad Danis Firmansyah Muhamad Fahrur Rozi Muhammad Alfian Nuris Shobah Muhammad Alimuddien Rasyid Muhammad Aminul Akbar Muhammad Ardhian Megatama Muhammad Atabik Usman Muhammad Aulia Rahman Muhammad Dimyathi Muhammad Fachry Noorchoolish Arif Muhammad Fauzan Ziqroh Muhammad Fuad Efendi Muhammad Miftah Dhiaulhaq Muhammad Shafaat Muhammad Tanzil Furqon Mukhlis Anshori Witanto Nendiana Putri Ninda Silvia Tri Cahyani Nonny Windarti Novanto Yudistira Novi Fadilla Ulfa Nurudin Santoso Nurul Hidaya Nurul Hidayat Paul Manason Sahala Simanjuntak Putra Aditya Primanda Ratih Kartika Dewi Regina Anky Chandra Renaldy Senna Hutama Reyhan Dzickrillah Laksmana Reynaldi Ricky Putra Utama Guinta Rezza Hary Dwi Satriya Rezza Pratama Rhayhana Putri Justitia Richard Emmanuel Johanes Riesma Rahman Nia Rio Cahyo Anggono Rizky Maulana Iqbal Rizky Ramadhan Rizqi Addin Arfiansyah Roma Akbar Iswara Salam Maulana Sari Narulita Hantari Satrio Hadi Wijoyo Sema Nabillah Dewi Shibron Arby Azizy Stefanus Bayu Waskito Supraptoa Supraptoa Surya Dermawan Sutrisno Sutrisno Syailendra Orthega Tara Dewanti Sukma Tibyani Tibyani Tjahjanulin Domai Tony Faqih Prayogi Tri Afirianto Tuahta Ramadhani Tubagus Agung Nugroho Vogue Nevarika Wa Ode May Zhara Averina Wahyu Dwiky Rahmadan Wayan Firdaus Mahmudy William Muris Parsaoran Nainggolan Wunsel Arto Negoro Yogi Pinanda Yudha Eka Permana Yuita Arum Sari Yulianus Wayan Yudistira Rudja Yunita Dwi Lestari Yuwilda Wilantikasari