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All Journal Prosiding SNATIKA Vol 01 (2011) Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics The Asian Journal of Technology Management (AJTM) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Network Engineering Research Operation [NERO] Jurnal Abdimas Mahakam Indonesian Journal of Electrical Engineering and Computer Science Frontier Energy System and Power Engineering Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Prima Abdika: Jurnal Pengabdian Masyarakat Jurnal ilmiah teknologi informasi Asia
Sulistyo, Danang Arbian
Institut Teknologi Dan Bisnis ASIA Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Penyelesaian Fill-In Puzzle Dengan Algoritma Genetika Sulistyo, Danang Arbian; Gunawan, Gunawan
Prosiding SNATIKA Vol 3 (2015): Prosiding Snatika (Seminar Nasional Teknologi, Informasi, Komunikasi dan Aplikasinya)
Publisher : LPPM STIKI Malang

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Abstract

Penelitian ini berisikan tentang pembuatan solver untuk menyelesaikan sebuah permainan Fill – In Puzzle. Tahapan – tahapan dan proses pada penelitian ini adalah dengan membaca template dan value yang sudah ditetapkan untuk kemudian dikodekan dalam bentuk grid pada program yang ada. Setelah melewati proses tersebut kita bisa menentukan nilai populasi awal yang akan dibuat, semakin besar nilai populasi awal yang akan dibuat, maka nilai random juga akan semakin besar sehingga mempengaruhi proses seleksi entity yang akan di crossover. Perhitungan nilai fitness disini dibagi menjadi 2, yaitu pPada tingkat gen, perhitungan nilai fitness dilakukan dengan cara pemberian nilai atau score pada tiap gen yang ada, jika nilainya lebih besar dari 1 maka nantinya gen tersebut akan ditukar tempat dengan gen yang lain. Sedangkan pada tingkat kromosom nilai fitness yang dihitung adalah jumlah seluruh titik potong yang benar dibagi dengan jumlah keseluruhan titik potong yang ada
Peningkatan Literasi Pengetahuan Kesehatan dan Teknologi untuk Pencegahan dan Deteksi Penyakit Menggunakan Digital Image Processing Farokhah, Lia; Noercholis, Achmad; Ahda, Fadhli Almuiini; Rofiq, Muhammad; Sulistyo, Danang Arbian
Jurnal Abdimas Mahakam Vol. 5 No. 2 (2021): JURNAL ABDIMAS MAHAKAM
Publisher : Institute for Research and Community Services (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/jam.v5i2.1399

Abstract

Perkembangan penyakit dan alat Kesehatan di dunia sangat berdasar dengan import. Alat Kesehatan cukup mahal harganya. Adapun tujuan dari pengabdian ini adalah meningkatkan literasi mengikuti model The European Health Literacy Survey: the 12 subdimensions. Adopsi model ini diharapkan akan pada tahap dimensi menilai atau mengevaluasi informasi yang relevan dengan Kesehatan. Metode yang digunakan adalah edukasi masyarakat khususnya perguruan tinggi yang memiliki fokus keilmuan Teknologi dan Kesehatan untuk meningkatkan literasi Kesehatan. Adapun hasil yang didapatkan selama pengabdian melalui kolaborasi webinar adalah cukup bagus untuk meningkatkan iterasi Kesehatan. Hal ini didasarkan atas fakta saat proses tanya jawab dalam penggalian informasi. Kolaborasi dua keilmuan yaitu kesehatan dan teknologi bisa membuat alat deteksi maupun pencegahan penyakit yang lebih murah namun akurat menggunakan sistem cerdas.
METODE AGILE DALAM PENGEMBANGAN SISTEM PREDIKSI PREVALENSI STUNTING DI INDONESIA Danang Arbian Sulistyo; Yogie Susdyastama Putra; Suastika Yulia Riska
Network Engineering Research Operation Vol 5, No 2 (2020): NERO
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v5i2.160

Abstract

Stunting merupakan kejadian balita pendek dan berhubungan dengan gizi. Anak yang menderita stunting akan lebih rentan terhadap penyakit, dan dalam jangka panjang akan mempengaruhi kecerdasan pada anak.Untuk meminimalisir kasus stunting perlu dirancang sistem prediksi berbasis web sehingga dapat diakses oleh dinas kesehatan seluruh Indonesia. Sebelum mengembangkan suatu sistem perlu dilakukan perancangan sistem yang dapat mempermudah proses pengembangan sistemnya. Pada penelitian ini menerapkan Metode Agile untuk perancangan sistem. Adapun tahapan metode ini mencakup define, build, dan release. Dari ketiga tahap tersebut dapat dilakukan iterasi berulang kali berdasarkan identifikasi sistem. Dengan menggunakan metode Agile, sistem ini lebih sederhana dan dapat dikembangkan sesuai dengan kebutuhan. Hasil perancangan menunjukkan bahwa sistem akan dapat mengolah data untuk prediksi dan akan menampilkan data sebaran setiap provinsi.
Pemodelan Fuzzy Inference System Tsukamoto untuk Prediksi Kejadian Banjir di Kota Malang Philip Faster Eka Adipraja; Danang Arbian Sulistyo; Ida Wahyuni
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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Abstract

Saat ini Malang menjadi kota yang mulai padat dengan perumahan penduduk. Hal tersebut mengakibatkan jumlah ruang terbuka hijau untuk penyerapan air hujan menjadi bekurang dan menyebabkan bencana banjir di beberapa tempat. Bencana banjir yang terjadi di Kota Malang merupakan bencana yang cukup serius dan membutuhkan penanganan cepat, karena banjir sering terjadi di perumahan padat penduduk. Oleh sebab itu, prediksi bencana banjir perlu dilakukan terlebih dahulu agar antisipasi dan mitigasi dapat dilakukan sedini mungkin. Tujuan dari penelitian ini adalah mengimplementasikan pemodelan algoritma Fuzzy Inference System (FIS) Tsukamoto untuk memprediksi terjadinya kejadian banjir di Kota Malang. Data yang digunakan adalah data curah hujan dan intensitas hujan di Kota Malang. Data tersebut diprediksi kedepannya sebagai masukan dalam memodelkan metode FIS Tsukamoto untuk memprediksi kejadian banjir dengan nilai error terkecil. Hasil prediksi yang dihasilkan oleh algoritma FIS Tsukamoto adalah jumlah kemungkinan kejadian banjir yang akan terjadi. Dari hasil pengujian yang dilakukan pada data jumlah kejadian banjir pada tahun 2016-2017 dihasilkan nilai error RMSE yang cukup kecil yaitu 2.76. Maka, dengan menggunakan data hasil perkiraan curah hujan dan intensitas hujan tiga tahun kedepan dari penelitian sebelumnya, pemodelan FIS Tsukamoto dapat diimplementasikan untuk memprediksi jumlah kejadian banjir di Kota Malang untuk tiga tahun kedepan mulai tahun 2018-2020. AbstractToday, Malang is a city that is starting to become crowded with population housing. This has resulted in the amount of green open space for absorption of rainwater to be reduced and causing floods in several places. The flood disaster that occurred in Malang City was a quite serious disaster and needed rapid handling, because flooding often occurs in densely populated housing. Therefore, the prediction of floods needs to be done in advance so that anticipation and mitigation can be done as early as possible. The purpose of this study is to implement the Tsukamoto Fuzzy Inference System (FIS) algorithm to predict the occurrence of flooding in Malang City. The data used are rainfall and rainfall intensity data in Malang City. The data is predicted in the future as input in modeling the Tsukamoto FIS method to predict flood events with the smallest error value. The prediction results generated by the Tsukamoto FIS algorithm are the number of possible flood events that will occur. From the results of the tests conducted on the data on the number of flood events in 2016-2017, the RMSE error value that was quite small was generated, which was 2.76. So, by using the results of rainfall and rainfall intensity estimates from the previous research, Tsukamoto's FIS modeling can be implemented to predict the number of flood events in Malang City for the next three years starting in 2018-2020.
Peningkatan Literasi Pengetahuan Kesehatan dan Teknologi untuk Pencegahan dan Deteksi Penyakit Menggunakan Digital Image processing Lia Farokhah; Achmad Noercholis; Fadhli Almuiini Ahda; Muhammad Rofiq; Danang Arbian Sulistyo
Jurnal Abdimas Mahakam Vol. 5 No. 02 (2021): Juli
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

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Abstract

Pada era sekarang, penyakit muncul bervariasi. Alat kesehatan di Indonesia sangat bergantung dengan impor karena beberapa produk yang dibutuhkan tidak diproduksi di dalam negeri. Selain itu, harganya menjadi cukup mahal. Adapun tujuan dari pengabdian ini adalah meningkatkan literasi mengikuti model The European Health Literacy Survey: the 12 subdimensions. Adopsi model ini diharapkan akan pada tahap dimensi menilai atau mengevaluasi informasi yang relevan dengan kesehatan. Metode yang digunakan adalah edukasi masyarakat khususnya perguruan tinggi yang memiliki fokus keilmuan teknologi dan kesehatan untuk meningkatkan literasi kesehatan. Adapun hasil yang didapatkan selama pengabdian melalui kolaborasi webinar adalah cukup bagus untuk meningkatkan literasi kesehatan. Hal ini didasarkan atas fakta saat proses tanya jawab dalam penggalian informasi. kolaborasi dua keilmuan yaitu kesehatan dan teknologi bisa membuat alat deteksi maupun pencegahan penyakit yang lebih murah namun akurat menggunakan sistem cerdas.
Perancangan dan Pembuatan Website Majelis Ulama Indonesia Kota Batu Malang Lia Farokhah; Achmad Noercholis; Fadhli Almu’iini Ahda; Danang Arbian Sulistyo; Muhammad Rofiq
Prima Abdika: Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2024): Volume 4 Nomor 1 Tahun 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v4i1.3746

Abstract

Community service is one of the activities required for lecturers at Institut Teknologi dan Bisnis ASIA Malang every semester. This activity is carried out in groups to distribute knowledge to the community. This activity is in partnership with the Batu City MUI in creating a digital website for distribution of information to the wider community. Problems arise when a partner's website is hacked or damaged by a hacker. The service team wanted to teach how to recover or mitigate after damage, but the technical team could not provide information regarding the website and suggested creating a new website. In the initial stage, this service will create a new website. The method of this service approach is to carry out discussions in group discussion forums (FGD). The results of the discussion were realized in the form of a website for the Batu City MUI. Evaluations were carried out regarding design and functionality requirements. The partners are satisfied but it must be developed further. In ongoing collaboration this website will continue to be developed. After that, training in mitigating data when exposed to hackers will be carried out in the next service.
Comparison of Adam Optimization and RMS prop in Minangkabau-Indonesian Bidirectional Translation with Neural Machine Translation Fadhli Almu'iini Ahda; Aji Prasetya Wibawa; Didik Dwi Prasetya; Danang Arbian Sulistyo
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1818

Abstract

Language is a tool humans use to establish communication. Still, the language used is one language and between regions or nations with their languages. Indonesia is a country that has a diversity of second languages and is the fourth most populous country in the world. It is recorded that Indonesia has nearly 800 regional languages, but research activities in natural language processing are still lacking. Minangkabau is an endangered language spoken by the Minangkabau people in Indonesia's West Sumatra province. According to UNESCO, the Minangkabau language is listed as a language that is "definitely endangered," with only around 5 million speakers worldwide. This study uses neural machine translation (NMT) to create a formula based on this information. Neural machine translation, in contrast to conventional statistical machine translation, intends to build a single neural network that can be built up to achieve the best performance. Because it can simultaneously hold memory for a long time, comprehend complicated relationships in data, and provide information that is very important in determining the outcome of translation, LSTM is one of the most powerful machine-learning techniques for translating languages. The BLUE score is utilized in the NMT evaluation. The test results use 520 Minangkabau sentences, conducting tests based on the number of epochs ranging from 100-1000, resulting in optimization using Adam being better than optimization RMSprop. This is evidenced by the results of the best BLUE-1 score of 0.997816 using 1000 epochs.
ROUTING OPTIMIZATION ON SOFTWARE DEFINED NETWORK ARCHITECTURE USING BREADTH FIRST SEARCH ALGORITHM David Armanda; Fransiska Sisilia Mukti; Danang Arbian Sulistyo
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2000

Abstract

Software Defined Network (SDN) is a network modelling that separates the control plane and data plane. SDN is a new form of paradigm used for large-scale networks, one of which is for routing. Most types of routing used today use single-path routing. Single-path only uses one path as data transmission. This will result in reduced performance on the network which is often referred to as network congestion. In this test, the routing algorithm used is Breadth First Search (BFS) by modifying the path so that congestion on the network can be minimised. The BFS algorithm is implemented using Mininet emulator, Ryu Controller, and fat-tree topology. In the test, 20 scenarios were used with a bandwidth of 50 - 1000 Mbps within 15 seconds. Tests were conducted to measure the performance of the BFS algorithm, namely the path and QOS (Quality Of Service) parameters which include testing delay, packet loss, jitter, and throughput. The data obtained in testing using the conventional BFS algorithm is compared with the modified BFS algorithm data in the same test method. In path testing, the modified BFS algorithm is superior and in parameter testing, it is produced with a degraded percentage value in delay (65%), packet loss (99%), jitter (84%), and throughput has increased by (41%). So the modified BFS algorithm is superior due to the utilisation of path modification for routing optimisation which is more effective in handling network congestion.
Optimization of Double Exponential Smoothing Using Particle Swarm Optimization Algorithm in Electricity Load Vivi Aida Fitria; Arif Nur Afandi; Aripriharta Aripriharta; Danang Arbian Sulistyo
Frontier Energy System and Power Engineering Vol 5, No 2 (2023): July
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i2p58-64

Abstract

Electricity load forecasting plays a critical role in ensuring the efficient allocation of resources, maintenance optimization, and uninterrupted power supply. The double exponential smoothing (DES) method is widely used in forecasting time series data due to its adaptability and robustness, particularly in handling linear trends without seasonal patterns. However, determining the optimal value of the alpha parameter in DES is crucial for accurate forecasting results. This study proposes the use of the Particle Swarm Optimization (PSO) algorithm to optimize the alpha parameter in DES for electricity load forecasting. PSO is a computational method that iteratively improves candidate solutions by moving particles in the search space based on simple mathematical formulas. By optimizing the alpha parameter using PSO, we aim to enhance the accuracy of short-term electricity load forecasts. Our results demonstrate that the PSO-optimized DES approach achieves a Mean Absolute Percentage Error (MAPE) of 2.89% and an accuracy of 97.11%, indicating significant improvements in forecasting performance. While the PSO algorithm provides promising results, future research may explore the application of other metaheuristic algorithms, such as the whale or orca algorithms, to further enhance the optimization of DES parameters for electricity load forecasting. This study contributes to the advancement of forecasting techniques in the power industry, facilitating more efficient power generation and distribution planning.
NFT Investments Analysis: A Strategic Approach with Ranking Insights and Sales Forecasting System for Informed Decision-Making Fitria, Vivi Aida; Afandi, Arif Nur; Aripriharta, Aripriharta; Widayanti, Lilis; Sulistyo, Danang Arbian
The Asian Journal of Technology Management (AJTM) Vol. 16 No. 2 (2023)
Publisher : Unit Research and Knowledge, School of Business and Management, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12695/ajtm.2023.16.2.2

Abstract

Abstract. The non-fungible token (NFT) is a unique token used to represent digital assets such as art, music, videos, and other collections. NFT has gained significant attention from the business and industry sectors in recent years. This study reports an increase in the number of active NFT users from 77,000 to 222,000 in early 2021. Investment in NFT has advantages and disadvantages, and one of the challenges faced by investors is that they may not have enough knowledge about investing risks and may find it difficult to recognize and evaluate potential dangers. To address this problem, this study proposes a system that provides information on NFT collection sales rankings and volume sales forecasts. The simple additive weighting (SAW) method is used to determine the NFT collection rankings, and exponential smoothing is used to forecast sales volume. The Particle Swarm Optimization (PSO) method is applied to optimize the parameter alpha of the Exponential Smoothing method. With an accuracy rate of 80.38%, the combination of using the Single Exponential Smoothing method with PSO optimization can provide good predictions for future NFT sales. The proposed system aims to provide investors with accurate information to make informed decisions when investing in NFT. Keywords:  Forecasting system, pso, ranking system, saw, single exponential smoothing
Co-Authors A.N. Afandi Achmad Noercholis Achmad Noercholis Aji Prasetya Wibawa Andika Dwiyanto, Felix Andrew Nafalski Aripriharta - David Armanda Didik Dwi Prasetya Fadhli Almu’iini Ahda Farokhah, Lia Fitria, Vivi Aida Fransiska Sisilia Mukti Fransiska Sisilia Mukti Gunawan Gunawan Hanip Afandi I Nyoman Gede Arya Astawa Lia Farokhah Lilis Widayanti Machrus Tohir Machrus Tohir Moh Ashari Muhammad Rofiq Muhammad Rofiq Muhammad Rofiq Philip Faster Eka Adipraja Pratama, Ficho Pranandasya Andrian Siti Maharani, Farah Shafiyah Suastika Yulia Riska Sulthan Shidqi Sulthan Shidqi Vivi Aida Fitria Wahyuni, Ida Yogie Susdyastama Putra