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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] Indonesian Journal of Electrical Engineering and Computer Science Frontier Energy System and Power Engineering JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Prima Abdika: Jurnal Pengabdian Masyarakat Jurnal ilmiah teknologi informasi Asia Jurnal Abdimas Mahakam
Sulistyo, Danang Arbian
Institut Teknologi Dan Bisnis ASIA Malang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics 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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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
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.
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
LSTM-Based Machine Translation for Madurese-Indonesian Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almu'iini
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.113

Abstract

Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island in particular. The use of Madurese as a daily language has declined significantly due to a language shift in children and adolescents, some of which are caused by a sense of prestige and difficulty in learning Madurese. The scarcity of research or scientific titles that raises the Madurese language also helps reduce literacy in the language. Our research focuses on creating a translation machine for Madurese to Indonesian to maintain and preserve the existence of the Madurese language so that learning can be done through digital media. This study use the latest dataset for the Madurese-Indonesian language by using a corpus of 30,000 Madura-Indonesian sentence pairs from the online Bible. This study scrapped online Bible pages to organize the corpus based on the Indonesian and Madurese bilingual Bible. Then This study manually process text to match the two languages' scrapping results, normalization, and tokenization to remove non-printable characters and punctuation from the corpus. To perform neural machine translation (NMT), This study connected the RNN encoder with the RNN decoder of the language model, while for training and testing, This study used a sequential model with LSTM, while the BLEU measure was used to assess the accuracy of the translation results. This study used the SoftMax optimization function with Adam Optimizer and added some settings, including using 128 layers in the training process and adding a Dropout layer so that This study got the average evaluation result for BLEU-1 is 0.798068, BLEU-2 is 0.680932, BLEU-3 is 0.623489, and for BLEU-4 is 0.523546 from five tests conducted. Given the language differences between Madurese and Indonesian, this can be the best approach for machine translation of Indonesian to Madurese.
STEMMING IN MADURESE LANGUAGE USING NAZIEF AND ADRIANI ALGORITHM Moh Ashari; Sulistyo, Danang Arbian; Ahda, Fadhli Almu’iini
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.2024.5.4.2012

Abstract

Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island in particular. However, the use of Madurese is declining compared to other regional languages. This is partly due to a sense of prestige and difficulty in learning it. As a result, the future of Madurese as one of the regional languages in Indonesia is increasingly threatened by the decline in its use. In addition, academic literature and scientific publications in Madurese are difficult to find in public and academic libraries, so previous research on Madurese stemming is still very little and needs to be developed further. Therefore, this research aims to find the base word of Madurese language using Nazief & Adriani algorithm based on Madurese language morphology. The Nazief & Adriani method in previous studies has good performance. Stemming can also be developed into a Madurese language translator application into other languages. This research uses 650 words in the form of datasets, consisting of 500 prefix words and 150 suffix words. The resulting accuracy for the whole is 96.61% with 628 correct words, the prefix has 95.6% accuracy, and the suffix has 100% accuracy. Overstemming was found in 22 prefix words and no words experienced Understemming.
Sistem Pendukung Keputusan (SPK) Pemberian Beasiswa Berbasis TOPSIS (Studi Kasus Yayasan Pendidikan Al-Hikmah Bululawang Malang) Danang Arbian
Jurnal Ilmiah Teknologi Informasi Asia Vol 11 No 1 (2017): Volume 11 Nomor 1 (10)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v11i1.40

Abstract

Sistem Rekomendasi pemberian Beasiswa Dengan Metode TOPSIS Di Yayasan Pendidikan Al-Hikmah Bululawang Kabupaten Malang bertujuan untuk menerapkan metode TOPSIS, dalam menentukan penerima beasiswa berdasarkan kriteria yang telah ditentukan serta merancang dan membangun sistem dalam membantu memberikan alternatif keputusan dalam penentuan penerima beasiswa di Yayasn Pendidikan Al-Hikmah Bululawang Kabupaten Malang. Berdasarkan sumber data yang diperoleh, menggunakan data primer meliputi metode wawancara/interview dan pengamatan langsung/ observasi dan data sekunder diperoleh dengan studi pustaka yang relevan dengan masalah tersebut. Data beasiswa diolah kemudian dirangking berdasarkan nilai preferensi yang didapat dari perhitungan TOPSIS. Proses pemberian beasiswa berdasarkan kriteria berupa nilai rata-rata semester, nilai estrakurikuler wajib, jumlah pendapatan orang tua, jumlah tanggungan, dan jarak rumah ke sekolah. Hasil penelitian ini adalah berupa sistem pendukung keputusan dalam menentukan siswa yang memperoleh beasiswa dengan menggunakan metode TOPSIS, dimana alternatif yang mempunyai nilai preferensi paling besar yang akan menduduki peringkat teratas. Alternatif tersebut merupakan alternatif yang disarankan untuk menerima beasiswa
Pemodelan Sistem Dinamik untuk Prediksi Intensitas Hujan Harian di Kota Malang Philip Faster Eka Adipraja; Danang Arbian Sulistyo
Jurnal Ilmiah Teknologi Informasi Asia Vol 12 No 2 (2018): Volume 12 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v12i2.272

Abstract

Malang city located in the highlands that is not spared from the flood disaster which the number of events is increasing every year. This is due to many factors, such as the high intensity of daily rainfall coupled with less optimal infrastructure development. In this case, to mitigate the number of flood events, an easy first step is to predict the daily rain intensity. So that the prediction result can be used by the stakeholders to mitigate flood incident in Malang City in the following years. This study aims to create a simple model in predicting rain intensity over a three year period of 2018-2020. Modeling and simulation are done by using a system dynamics approach that can model the system with complex dynamics. The developed model of rain intensity integrates influencing factors such as humidity and temperature. The rainfall intensity model has validated with the error of E1 value is 3.86% and E2 is 4.13% and with RMSE result indicates the number of 8.4452.
Sistem Pakar Untuk Diagnosa Hama dan Penyakit Pada Bunga Krisan Menggunakan Forward Chaining Hanip Afandi; Danang Arbian Sulistyo
Jurnal Ilmiah Teknologi Informasi Asia Vol 13 No 2 (2019): Volume 13 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v13i2.409

Abstract

Chrysanthemum flowers are a type of flowering plant that is often planted as an ornamental plant or cut flower. Chrysanthemum flower farmers on average have less knowledge about pests and diseases in chrysanthemum flowers that are difficult to identify, so that it is too late in handling and prevention which will result in a decrease in the yield of chrysanthemum flowers. Expert system can solve this problem by designing a web-based computer system integrated with database and programming languages such as PHP-MySQL so as to help chrysanthemum farmers in Poncokusumo to diagnose pests and diseases. Expert system applications in decision making using inference engines such as Forward Chaining that works by tracing cases based on rules on the decision tree. Diagnosis of Pests and Diseases using Forward Chaining method. In this study the types of diseases that can be diagnosed as many as 12 diseases. The results of the system implementation of the system gives questions in the form of symptoms that must be answered by the farmerbased on symptoms experienced by chrysanthemum flowers and the results of the process the system will provide information on what pests or diseases to get treatment solutions and prevention.Tests used are accuracy testing with 21 data tester.
Sistem Pendukung Keputusan Untuk Pemilihan Supplier Buah Di PT.Indomarco Prismatama Menggunakan Metode Analytical Hierarchy Process Machrus Tohir; Fadhli Almu'iini Ahda; Danang Arbian Sulistyo
Jurnal Ilmiah Teknologi Informasi Asia Vol 16 No 2 (2022): Volume 16 Nomor 2 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v16i2.629

Abstract

ABSTRAK : Perkembangan pasar yang semakin pesat membuat perusahaan harus mampu bersaing secara global dengan tetap mempertahankan performance. Pemilihan supplier merupakan hal penting untuk menunjang performance perusahaan, karena pemilihan supplier yang tidak tepat dapat menyebabkan Kerugian dan menurunya service level yang diakibatkan stock out perusahaan. Penilitian ini bertujuan untuk memilih supplier terbaik dengan cara menyeleksi supplier berdasarkan kriteria dan subkriteria yang sesuai. Penelitian ini dilakukan di PT.Indomarco Prismatama dengan mengambil objek Merchandiser dan departemen buah. Sistem pendukung keputusan dengan metode Analytical Hierarchy Process yang digunakan untuk mendapatkan bobot-bobot kriteria supplier. Hasil yang didapatkan setelah melakukan pengujian perbandingan antara system dan reality didapatkan hasil menggunakan system jauh lebih baik dalam memilih supplier terbaik. Dan sistem ini hanya sebuah media yang bisa digunakan untuk merekomendasikan pilihan kepada pimpinan.
Co-Authors A.N. Afandi Achmad Noercholis Aji Prasetya Wibawa Andika Dwiyanto, Felix Andira, Aysza Belia Auly Andrew Nafalski Aripriharta - Armanda, David Didik Dwi Prasetya Fadhli Almu’iini Ahda Fahrudillah, Mochammad Fiqi Farokhah, Lia Fransiska Sisilia Mukti Gunawan Gunawan Hanip Afandi I Nyoman Gede Arya Astawa Ida Wahyuni Lilis Widayanti Machrus Tohir Machrus Tohir Moh Ashari Muhammad Rofiq Muhammad Rofiq Philip Faster Eka Adipraja Pratama, Ficho Pranandasya Andrian Rabbani, Muhammad Faruqi Setiadi, Erik Siti Maharani, Farah Shafiyah Suastika Yulia Riska Sulthan Shidqi Sulthan Shidqi Tampubolon, Surya Viari Vivi Aida Fitria Wayan Firdaus Mahmudy Yogie Susdyastama Putra