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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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Pengembangan Aplikasi Sistem Informasi Pelayanan Desa berbasis Website (SIMPEDE) pada Desa Dawuhan Kecamatan Poncokusumo Kabupaten Malang Ahmad Shofi Nurur Rizal; Djoko Pramono; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Dawuhan Village is located in the Poncokusumo District, Malang Regency, East Java. Dawuhan is a developing village with a population of 7115 people. However, in this case, administrative services and population data processing in Dawuhan village still use conventional methods, which still use book archives to process written data so that the processing of certificate documents and civil registration letters still encounters many problems. To solve this problem, an information system that handles letter requests is needed. This research was conducted to find out the Village Service Information System (SIMPEDE) is running effectively. Answering these problems, business process modeling, needs analysis, system design and implementation, and testing are carried out to find out the system is running as desired. Business process modeling generates AS-IS and To-Be business processes. Requirements analysis is done by identifying actor activities with the system, identifying functional and non-functional requirements, visualizing use case diagrams, use case scenarios, and sequence diagrams, then makes database design with MySql, as well as system interface design. System implementation produces a specification for hardware and software environment, the implementation of the source code, then produces a system interface according to what user expects.
Implementasi Simple Network Management Protocol (SNMP) pada Bot Monitoring Telegram Muhammad Taruna Praja Utama; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One useful network management function to determine whether the network is still practical, viable, or needs more capacity is network monitoring. If an administrator is looking to redesign an existing network, monitoring the results may also be helpful. Monitoring device status, such as CPU percentage, RAM, and traffic using SNMP, is one of many network monitoring techniques. To facilitate this monitoring process, it can be done remotely with a program that provides alert messages to the user. One of the communication media is using the Telegram application, Telegram also has bot facilities that can be programmed to run continuously without stopping. The purpose of the research is to find out how to design a monitoring bot program using SNMP that sends notification messages to Telegram and to find out how to test the Telegram monitoring bot program using SNMP.
Sistem Pendukung Keputusan Pemilihan Kost di Kota Malang menggunakan Metode Analytical Hierarchy Process dan Weighted Product (AHP-WP) Thareq Ibrahim; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Boarding House is a place to live for people who come from other regions or cities, especially such as students or workers. In the city of Malang, there are many students who come from outside the city to carry out lectures at their university. Especially for Brawijaya University where every year there are thousands of students who come from outside Malang. However, choosing the right boarding house is difficult because there are many factors that can influence students such as price, distance, facilities, surrounding areas, etc. From these problems, a system is needed that can help students choose the right boarding house. The solution to the problem is to create a decision support system. The purpose of this research is to create a decision support system to help students choose the right boarding house. The method used is the Analytical Hierarchy Process and Weighted Product (AHP-WP) method. The results of testing using the Spearman rank method get the best results on the number of alternatives as many as 31 with a value of 0.8362 which states that the relationship between the ranking results of the system and users is very strong.
Prediksi Penjualan Ponsel Pintar menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Kombinasi Particle Swarm Optimization Wildansyah Maulana Rahmat; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The use of smartphones in Indonesia tends to increase. Smartphone users alone have reached 28% of the total Indonesian population in 2019 and experienced an increase of 2% from the previous year. In certain months mobile phone sales can increase rapidly and may also decline. But often some phones go unsold for months and find that the selling price is decreasing. Therefore, an effort is needed to reduce the losses from this and increase profits. Taking into account the number of phones to be restocked one way to reduce losses on phones that have not been sold for a long time. Manfaat Cell is a mobile phone sales store domiciled in Karangploso, East Java. Over time some phones were not sold according to the target in the month due to the large number of goods but the interest of buyers was small, it took a plan for the number of products to be restocked, one of which was to implement a method to predict the number of goods to be restocked. The prediction system uses the backpropagation method and is optimized using particle swarm optimization. The data used is monthly Cell Benefit sales data from 2018 to 2021, with a 70% share for training data and 30% for testing data. The result of the backpropagation performance of the particle swarm optimization combination is a MAPE value of 3.453%, which is obtained from the combination of optimal parameters, namely input as many as 3, hidden as many as 3, output as many as 1, number of iterations as many as 200, inertia weight value of 0.9, and the number of pop sizes as many as 40.
Sistem Diagnosis Kerusakan pada Iphone dengan Metode Dempster Shafer Yusril Iszha Eginata; Nurul Hidayat; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 2 (2023): Februari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Smartphones are devices that have advantages over other communication tools. Damage to Smartphones is natural and normal, as well as damage to iPhones, examples of damage ranging from fast battery drain, no image on the screen, camera not working etc. However, technicians face obstacles when diagnosing iPhone defects, which results in less than optimal technician performance. This expert system uses the Dempster-Shafer method. Inferences are made based on the symptoms of existing iPhone damage, and the frequency of each symptom is determined by the Smartphone technician. From the calculation of the visible density of damage that occurs on the iPhone, the system has 20 symptoms of damage and 14 types of damage. The purpose of this study is to help technicians determine the damage that occurs on the iPhone, which will select symptoms and give the results of this study an accuracy score of 90%.
Comparative Study of SVR, Regression and ANN Water Surface Forecasting for Smart Agriculture Arief Andy Soebroto; Imam Cholissodin; Destyana Ellingga Pratiwi; Guruh Prayogi Willis Putra
HABITAT Vol. 33 No. 1 (2022): April
Publisher : Department of Social Economy, Faculty of Agriculture , University of Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.habitat.2022.033.1.9

Abstract

In the smart agriculture system based on green-based technology of artificial intelligence (AI), flooding can be predicted early by forecasting the water surface and good agricultural irrigation. The process of rising and falling of the water surface in a water basin area can be explained theoretically, but since there are many related variables and the complexity of dependencies between variables, the mathematical model is difficult to construct. Forecasting water surface in the field of irrigation needs too many variable parameters, such as cross-sectional area, depth, volume of rivers and so on. Based on patterns in each period, forecasting can be done using a statistical method and AI. This study uses the support vector regression (SVR) method, regression, multiple linear regression, and algorithm backpropagation, all compared to one another. The results of tests carried out between SVR and multiple linear regression show that SVR is superior. This can be seen from the result of the mean square error (MSE) obtained for each method. SVR 0.03 and for multiple linear regression, 0.05. The result is also supported by the best MSE result in the regression method, which is 0.338, and the best MSE value in artificial neural network (ANN), which is 0.428.
Klasifikasi Masa Panen Varietas Unggul Kedelai menggunakan K-Nearest Neighbor Zaien Bin Umar Alaydrus; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 5 (2023): Mei 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kedelai merupakan bahan pokok yang dibutuhkan masyarakat pada setiap tahunnya. Fakta pada lapangan, para petani di Indonesia mengalami penurunan hasil produksi kedelai. Hal tersebut dikarenakan ketidakmampuan para petani dalam meliputi kualitas dan kuantitas kedelai pada saat masa panen. Solusi dari masalah tersebut adalah menggunakan klasifikasi K-Nearest Neighbor untuk mendapatkan masa panen kedelai berkualitas dan berkuantitas tinggi. Algoritma dari penelitian ini menggunakan K-Nearest neighbor menggunakan pre-processing manualisasi min-max. Manualisasi diperlukan untuk menyamakan jarak antara nilai satu fitur dengan nilai fitur lainnya, pada penilitian ini akan menggunakan nilai yang hanya berjarak antara 1 sampai 0. Setelah semua nilai pada data latih maupun data uji melewati fase manualisasi, maka baru bisa masuk ke proses Klasifikasi menggunakan K-NN. Pada proes K-NN nilai dari fitur data latih akan dihitung jaraknya terhadap data uji menggunakan euclian distance, diurutkan, dan kemudian diambil sejumlah nilai K teratas. Nilai K yang akan digunakan dalam sistem ialah bernilai 5. Proses terkahir pada K-NN ialah mengambil voting untuk mendapatkan kelas baru data uji. Berdasarkan hasil pengujian yang telah dilakukan, algoritma dari sistem mendapatkan presentase keberhasilan sebesar 80% dengan nilai K paling optimal yaitu bernilai 5.
Pengembangan Sistem Informasi Manajemen Penilaian Pendidikan berbasis Web (Studi Kasus: Yayasan Darul Itqon Kabupaten Malang) Ahmad Mustafirudin; Fajar Pradana; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 5 (2023): Mei 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Yayasan Darul Itqon bergerak dalam bidang Pendidikan SMP dan SMK. Dengan keterbatasan tenaga pendidik, proses untuk mengisikan dokumen penilaian masih menggunakan sistem pengisian nilai secara manual, sehingga menyulitkan tenaga pendidik dalam proses perhitungan nilai pemahaman, perekapan nilai dan pembuatan laporan penilaian peserta didik. Untuk menyelesaikan masalah ini, sistem informasi diperlukan. Ini akan membuat proses penilaian kinerja guru lebih cepat dan lebih akurat, dan membuat laporan penilaian siswa akan menjadi lebih mudah. Dalam proses pengembangan sistem informasi menggunakan pendekatan Framework Application of Systems Thinking (FAST) yang dapat menyelesaikan pembuatan sistem dengan fleksibel. Dalam metode FAST, proses penggalian kebutuhan menggunakan model analisis Performance, Information, Economic, Control, Efficiency, and Service (PIECES). Proses ini menggabungkan beberapa masalah dari sistem lama ke dalam kelompok aspek untuk menghasilkan solusi untuk sistem baru. Penggunaan framework PIECES menghasilkan proses bisnis baru yang dapat mempermudah tenaga pendidik terutama untuk guru dalam melakukan penilaian. Implementasi sistem ini memiliki fitur utama kelola nilai siswa, import nilai siswa, cetak nilai siswa dan mengelola pengguna. Hasil dari pengujian menunjukkan hasil valid, sehingga sistem dapat membantu tenaga pendidik dalam mengelola nilai peserta didik dengan baik.
Sistem Pendukung Keputusan Deteksi Dini Penyakit Strok dengan Multiple Attribute Decision Making Simple Additive Weighting (SAW) Rio Andika Dwiki Adhi Putra; Arief Andy Soebroto
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 5 (2023): Mei 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Penyakit strok atau cerebrovaskuler accident ialah gangguan saraf diakibatkan oleh pecahnya pembuluh darah dalam otak, sehingga kehilangan fungsi otak seseorang. Penyakit strok dapat menyebabkan gangguan pada sistem fungsi otak yang vital dan gangguan gerakan yang menghambat aktivitas individu. Menurut World Health Organizasion (WHO), diperkirakan ada sekitar 7,6 juta kematian akibat strok, dengan tingkat kematian sebesar 77%, menunjukkan bahwa penyakit strok termasuk penyakit yang berbahaya. Penting untuk melakukan pencegahan dini melalui pemeriksaan medis karena risiko strok yang tinggi. Deteksi risiko penyakit strok dapat dilakukan dengan mudah jika parameter-parameter yang relevan diketahui. untuk mengatasi masalah pola yang tidak terstruktur, diperlukan sistem yang dapat mempermudah dalam pengambilan keputusan, bisa juga dijadikan sebagai solusi. Alasan memilih metode tersebut dikarenakan sanggup mengatasi permasalahan yang sering terkait dengan ketidakpastian dalam penelitian deteksi penyakit. Hasil akurasi yang didapat dari sistem pendukung keputusan deteksi dini penyakit strok dengan metode multiple attribute decision making simple additive weighting sebesar 74,1%. Dari hasil perhitungan baik secara manual maupun sistem mendapatkan hasil yang sama dimana terdapat beberapa alternatif yang di duga menderita strok, bagi alternatif yang diduga menderita strok diketahui bahwa nilai alternatifnya  0,84 (threshold).
Sistem Pendukung Keputusan Penyakit Stroke menggunakan Metode Fuzzy Tsukamoto dengan Basis Pengetahuan Framingham Risk Score Arief Andy Soebroto; Muhammad Tanzil Furqon; Eko Ari Setijono Marhendraputro; Wildan Ziaulhaq
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 8, No 2 (2022): Volume 8 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v8i2.56362

Abstract

Penyakit stroke adalah salah kerusakan pada otak yang muncul secara mendadak akibat gangguan peredaran darah otak non-traumatis. Gangguan tersebut dapat berupa pembuluh darah tersumbat yang dapat menghambat atau menghentikan aliran darah ke otak. Penyakit stroke di Indonesia telah mengalami peningkatan, angka prevalensi per mil telah meningkat dari 7% pada tahun 2013 menjadi sebesar 10,9% pada tahun 2018. Penyakit stroke dapat dikurangi dengan melakukan deteksi dini pada masyarakat supaya dapat melakukan tindakan preventif. Deteksi dini penyakit stroke memiliki kondisi data yang semi terstruktur karena banyaknya faktor untuk mengidentifikasi risiko penyakit stroke. Kondisi data semi terstruktur akan mempersulit deteksi dini penyakit stroke sehingga diperlukan alat bantu berupa sistem pendukung keputusan (SPK). Penelitian dilakukan dengan membangun sistem pendukung keputusan deteksi dini penyakit stroke menggunakan metode Fuzzy Tsukamoto. Model basis pengetahuan menggunakan Framingham Risk Score sebagai dasar untuk pembuatan aturan (rule) klasifikasi dengan 120 data pasien Puskesmas Kendalkerep Kota Malang. Hasil pengujian yang didapatkan adalah akurasi sebesar 0,8444, presisi sebesar 0,7801, recall sebesar 0,796, specificity sebesar 0,8891, dan F1 score sebesar 0,751.
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