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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Innovation and Applied Technology Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Habitat Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JAST : Jurnal Aplikasi Sains dan Teknologi International Journal of Engineering, Science and Information Technology J-Intech (Journal of Information and Technology)
Arief Andy Soebroto
Universitas Brawijaya
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer

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Pelatihan Feedforward Neural Network Menggunakan Particle Swarm Optimization untuk Peramalan Harga Saham Fildzah Amalia; Imam Cholissodin; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 10 (2020): Oktober 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Stock is a promising investment and very flexible, investors can sell their stock at any time either part or all of their stock. The high potential yield offered is what makes the stock so famous among the investors. However, the level of participation of the Indonesian people in investing in the stock market is still very low. Fluctuating stock prices are also one of the factors people are reluctant to become stock investors. Therefore, investment in stocks requires a good analysis so that investors can increase profits, one of them is by predicting stock prices from time to time so that future stock prices can be predicted by conducting technical analysis. In this study, forecasting is done using one of the artificial neural network methods, namely Feedforward Neural Network (FFNN) which is trained using the Particle Swarm Optimization (PSO) method. PSO algorithm is considered capable of replacing the Backpropagation algorithm in training networks. The error rate from forecasting results is calculated using Mean Absolute Percentage Error (MAPE). In the test the smallest MAPE value is 1,793% and fitness value is 0.98239 with 4 input layers, 2 hidden layers, and 1 output layer on the network architecture.
Implementasi Wireless Sensor Network Untuk Mendeteksi Gas Amonia Pada Kandang Ayam Menggunakan Modul Wifi ESP8266 Mahdi Fiqia Hafis; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 11 (2020): November 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

We as Indonesian citizens feel proud of the high potential they have, especially in the field of animal husbandry and agriculture. With the existence of chicken farming, there are not a few who become new job creators and become independent in their work. The problem that is often experienced by chicken farmers is ammonia gas caused by chicken manure itself, this ammonia gas can later cause disruption in humans and also the chicken itself. Disorders in humans include respiratory problems, eye irritation, and poisoning in the form of seizures. The existence of internet of thing technology, can facilitate us in monitoring ammonia gas levels in the area of ​​chicken farms presented in the form of ppm by utilizing the mq-135 sensor that can detect ammonia gas levels. Data that has been taken by the client will be accommodated by the master and will be displayed on a web page with the help of a gateway to determine the level of ammonia gas in the area of ​​the chicken farm. The results of the study began with testing the quality of service to determine the performance of the network connection time for sending data to the server. And testing the function of a successful tool works perfectly where the mq-135 sensor can detect levels of dangerous gas ammonia (NH3).
Implementasi Deteksi Hujan dan Banjir Secara Real Time Monitoring berbasis MQTT Over Websocket Menggunakan Modul ESP32 Muhammad Rouzikin Annur; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Indonesia is a country traversed by the equator, which means that rainfall in Indonesia is quite high. Rainfall in several areas, one of which is in the city of Malang, is one of the areas that has high rainfall. The uneven road conditions in Malang City make part of the road flooded with water when it rains and some roads that are not flooded are inundated, therefore the authors make a tool that can provide information on the latest conditions on roads prone to rain and floods with standing water by installing a detection tool in the form of a sensor that is connected to the internet so that it can be accessed by the general public. The way this tool works is by detecting rain and water levels on the highway, precisely on roads where floods often occur during heavy rain, then the detection data is sent to the internet so that it can be accessed by users or the general public. The results of this study are expected to be able to help users or the general public find alternative roads when there is rain or a flood of standing water on the highway.
Implementasi Wireless Sensor Network untuk Monitoring Kesuburan Lahan Pertanian Padi menggunakan Modul Wifi ESP8266 Krisna Wahyu Aji Kusuma; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesian is a country where a third of its population works from the agricultural sector, especially rice fields. Most farmers expect maximum yields without knowing the soil fertility with the factors that support this fertility. Factors such as soil pH, soil moisture, soil temperature and various other factors. Especially the factors can also change at any time that could interfere with the process of plant growth if farmers do not pay attention to these changes. With the developing technology, we can make it easier to monitor soil pH, soil moisture and soil temperature using the YL-69, DS18B20 and soil pH meter sensors. The data taken by the three sensors will be accommodated in the sensor node and then sent to the gateway via the websocket and forwarded to firebase and then displayed to the web interface. Testing is done using quality of service to determine the performance of the network performance from delivery speed, packet lost during delivery, and time interval of each delivery. Then the performance test results obtained, namely the throughput of H-1 to H-3 is 12.11 bps, 10.88 bps, and 16.13 bps. Packet loss from H-1 to H-3 is 0.4%, 0.3%, and 0.2%. The delay from H-1 to H-3 is 0.12 s, 0.09 s, and 0.09 s. The tool's function test works successfully with data taken from the three sensors that can be displayed on the web interface.
Sistem Monitoring Kebocoran Gas Berbahaya di Lingkungan Kawasan Industri berbasis Bluetooth Low Energy (BLE) Bambang Gunadi; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 4 (2021): April 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Some factories have been using gas as a source of combustion fuel for production purposes, resulting in emissions from the combustion process. Most of the gas used for the fuel source consists of methane gas or CH4. Meanwhile, emissions from the combustion system are in the form of carbon monoxide gas or CO. One of the technologies in the industrial sector that can observe gas leaks and air quality in industrial areas is the Wireless Sensor Network technology. Wireless Sensor Networks are a set of nodes that are arranged in a wireless network to monitor the surrounding environment and able to communicate with each other through protocols, one of which is Bluetooth Low Energy. Compare to the other protocols, there are some advantages that Bluetooth Low Energy has such as better power savings, being able to send data quickly, easy configuration, and a wide coverage. Therefore, the researcher decided to conduct a research by applying Bluetooth Low Energy in real life, by observing temperature, humidity, CH4 gas and CO gas levels. Through Bluetooth Low Energy, Raspberry Pi is able to send observations to the clients. In this study, two scenarios are used to test the delivery performance of Bluetooth Low Energy. The scenarios are changes in distance without obstacles and changes in distance with obstacles. The test results showed that the change in distance without obstacles and with obstacles had an average total delay of 0.0752 ms and 0.1587 ms.
Optimasi Input weight dan Bias Extreme Learning Machine menggunakan Ant Colony Optimization untuk Peramalan Cuaca di Kabupaten Malang Khoifah Inda Maula; Arief Andy Soebroto
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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Artikel dipublikasikan di Jurnal Nasional Terakreditasi
Pengembangan Sistem Rekam Medis Pasien Berbasis Web (Studi Kasus : Klinik Rafael Malang) Himawan Sutanto; Faizatul Amalia; Arief Andy Soebroto
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

There are a lot of medical facilities that use information technology to simplify data storing, one of those technologies is an electronic health record. In Rafael Clinic Malang, the health record process that was done there is still not efficient enough because the process still uses manual writing and excel. The procedure is carried out at least three times, that is, writing the data in a patient visitation book, patient ID, then rewrite the data to excel. The health record data are still kept in patient ID so it need some times to search for the ID, not including if the ID is missing or damaged. Based on those problems, the author developed a web-based electronic health record system. The purpose of this research is to know the result of requirement analysis, design, implementation, and the testing result of the developed system. Waterfall model is used as the development method, which has the principle that the next development stage cannot be carried out if the previous stage has not been completed. 47 functional requirements and one non functional requirement were obtained through requirement elicitation, in which security being the non functional requirement. Designing was done using object oriented approach, which produces sequence diagram and class diagram. Database, algorithm, and interface designing is also done. Unit testing using the white-box method gives 100% valid results. Acceptance testing with the black-box method for 80 test cases got 100% valid results. Integration testing gives 100% valid results. Security testing of electronic payments and login sessions has met expectations.
Implementasi Wireless Sensor Network untuk Monitoring Limbah Cair Gondorukem Menggunakan Modul Wifi Esp8266 Risqi Nur Ifansyah; Nurul Hidayat; Arief Andy Soebroto
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 is a country that is rich in natural resources, there are many pine trees that produce sap. Pine tree sap has many uses in the cosmetic, antiseptic and pharmaceutical industries. But pine sap produces a waste effect. There are still many things that need to be improved on the processing of gondorukem for wastewater treatment. Especially in the disposal section, it is not possible to predict a good standard of liquid waste disposal. The standard for wastewater disposal has several parameters such as pH, temperature and turbidity of the waste. With IoT technology, it makes it easier for us to reduce the pH, temperature and turbidity of the waste by using a pH meter water sensor, DS18B20 and Turbidity. The data of the three sensors are collected to the sensor node, then sent to the gateway via a websocket, then forwarded to firebase which will be displayed on the web interface. Testing uses Quality of Service, to determine a network speed performance when sending, which is useful for knowing the time of each delivery and packets lost during delivery. The water meter's pH sensor function, DS18B20 and Turbidity, worked well during research. Then obtained from the test results based on the throughput h-1 to h-4 testing is 17.01 bps, 20.89 bps, 19.83 bps and 18.86 bps. For packet loss h-1 to h-4, namely 0.1%, 0%, 0% and 0.%. Then the delay h-1 to h-4 is 0.08 s, 0.07 s, 0.07 s, and 0.07 s.
Sistem Pendukung Keputusan Kelompok untuk Menentukan Penerima Bantuan Kemiskinan di Kota Malang Menggunakan Metode PROMETHEE II dengan Copeland Score Ridwan Fajar Widodo; Arief Andy Soebroto
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

Malang City is one of the most populous cities in Indonesia. Poverty data collection is often a problem in determining poverty support beneficiaries, and some of the problems arising from poverty data collection are not found for residents without E-KTP, human resources are not eligible, and the data collection process is still done manually using paper, which requires a longer selection time. The PROMETHEE II method, Weighted Product, and Simple Additive Weighting are used in decision making by decision-makers. The system test is made by providing different criteria for each variable and indicator, and five tests were performed to measure the accuracy of the system, and the test results obtained 4 tests that obtained 100% results for each variable. The family variable in the second test tube can reach 20% and for the individual variable, it can reach 60° in the third data test. The level of accuracy obtained as a result of these tests is that the differences in the distribution data used are not evenly distributed. This will cause the level of accuracy obtained to fluctuate based on the data for each reference weight. Testers, the level of accuracy of the site can explain the results more accurately.
Sistem Pendukung Keputusan Diagnosis Penyakit Stroke menggunakan Metode Fuzzy K-Nearest Neighbor (FK-NN) (Studi Kasus Puskesmas Kendal Kerep Kota Malang) Yearra Taufan Ardy Rinaldy; Arief Andy Soebroto; Catur Ari Setianto
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

Stroke constitute disease that can cause death and disablement, but the number of patient is still very high. So that new stroke cases do not continue to grow, needed a way for early detection of stroke risk so that people who have the potential to suffer a stroke can take preventative. However, stroke is a complex disease that shows different symptoms between one patient and another. Moreover, the cause of stroke between one person and another person can also be different so that early detection of possible risk of stroke in a patient should be made with care.Decision support systems built using FK-NN are considered capable of assisting early detection of stroke risk quickly, thoroughly, and objectively.support system built with FK-NN will observe to stroke risk factors and calculate using framingham risk score, the method commonly used by doctors to calculate the risk of cardio vascular disease.The system then classifies data using the FK-NN method in the class of low risk stroke, moderate risk stroke, and high risk stroke. The results of this study indicate that the FK-NN is able to properly assist early detection of stroke risk, which resulting in an accuracy of 61.1% when K is 4 and the percentage of training data is 50% of the entire data set.
Co-Authors Achmad Arwan Achmad Ridok Adam Hendra Brata Ade Wija Nugraha Adi Setyo Nugroho Admaja Dwi Herlambang Agi Putra Kharisma Agi Putra Kharisma, Agi Putra Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Mustafirudin Ahmad Shofi Nurur Rizal Aizul Faiz Iswafaza Alfarisi, Muhammad Asnin Ali Akbar Alysha Ghea Arliana Amira Ibtisama Ana Kusuma Ardani Andreas Tommy Christiawan Andri Wijaya Kusuma Asrul Syawal Asrul, Divanda Arya Inasta Asus Maizar Suryanto H Austenita Pasca Aisyah Baghaz, Renanda DSP Bambang Gunadi Brilliansyach, Raihan Fikri Caesar, Canny Amerilyse Candra Dewi Candra Dewi Catur Ari Setianto Dama Yuliana Deby Putri Indraswari Denny Sagita Rusdianto Destyana Ellingga Pratiwi Destyana Ellingga Pratiwi Dhea Azahria Mawarni Dian Eka Ratnawati Djoko Pramono Dwi Cindy Herta Turnip Dwi Puri Cemani Dzikrullah, Muhammad Aulia Fachruz Edy Santoso Eka Miyahil Uyun Eko Ari Setijono Marhendraputro Eko Arisetijono Elza Fadli Hadimulyo Enggar Septrinas Enggarsita Auliasin Eugenius Yosep Korsan N Evi Irhamillah Azza Faisal Roufa Rohman Faizatul Amalia Fajar Pradana Fauziah Mayasari Iskandar Febrianita Indah Perwitasari Fendy Yulianto Ferdy Wahyurianto Fildzah Amalia Galuh Mazenda Guruh Prayogi Willis Putra Habib Yafi Ardi Hanafi, Andy Hastian Bayu Hendra Darmawan Herman Syantoso Himawan Sutanto I Gede Adi Brahman Nugraha I Putu Bagus Arya Pradnyana Ibnu, Mohammad Ibrahim Kusuma Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra Ekaristio P Indriana Candra Dewi Indriati Indriati Indriati Indriati Ishak Panangian Sinaga Ismiarta Aknuranda Issa Arwani Issa Arwani Karmia Larissa Br Pandia Khoifah Inda Maula Khrisna Widhi Dewanto Krisna Wahyu Aji Kusuma Lailatul Rizqi Ramadhani Lailil Muflikhah Laode Muhamad Fauzan Latifah Hanum Lily Montarcih Limantara Mahdi Fiqia Hafis Maria Tenika Frestantiya Maria Tenika Frestantiya, Maria Tenika Maya Febrianita Moh. Sholichin Mohammad Imron Maulana Muh. Arif Rahman Muhammad Iqbal Kurniawan Muhammad Rois Al Haqq Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Taruna Praja Utama Mutia Ayu Sabrina Nadya Rahmasari Nadya Sylviani Nainggolan, Yohana Beatrice Niftah Fatiha Armin Niken Hendrakusma Wardani Nizar Rahman Kusworo Nurannisa, Nadhira Nuriya Fadilah Nurudin Santoso Nurul Faizah Nurul Faridah, Nurul Nurul Hidayat Nurul Hidayat Nurul Hidayat Odhia Yustika Putri Priyambadha, Bayu Randy Cahya Wihandika Raymond Gunito Farandy Junior Rekyan Regasari Restia Dwi Oktavianing Tyas Reynald Daffa Pahlevi Ridwan Fajar Widodo Rio Andika Dwiki Adhi Putra Rio Arifando Risda Nur Ainum Riski Ida Agustiyan Risqi Nur Ifansyah Rivaldy Raihan Syams Rizal Setya Perdana Rizal Setya Perdana Saiful Kirom, Muhammad Ihsan Santoso, Nurudin Sativandi Putra Satrio Agung Wicaksono Sitepu, Yosua Christiansen Stefan Levianto Sukamto, Anjas Pramono Surya Wirawan SUTRISNO Sutrisno Sutrisno Sutrisno, Sutrisno Teddy Syach Pratama Thareq Ibrahim Tiara Rossa Diassananda Tryse Rezza Biantong Vasya, M Azka Obila Vicky Virdus Vivien Fathuroya, Vivien Wayan Firdaus Mahmudy Welly Purnomo Wijaya, Aldi Rahman Wildan Ziaulhaq Wildan Ziaulhaq Wildansyah Maulana Rahmat Yearra Taufan Ardy Rinaldy Yusril Iszha Eginata Zaien Bin Umar Alaydrus Ziya El Arief Ziya El Arief, Ziya El