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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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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.
Pembuatan Infrastruktur Database Menggunakan Metode Replikasi Untuk Pelanggan Jagoan Hosting Sulthan Shidqi; Danang Arbian Sulistyo; Fadhli Almu’iini Ahda
Jurnal Ilmiah Teknologi Informasi Asia Vol 16 No 1 (2022): Volume 16 Nomor 1 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v16i1.702

Abstract

ABSTRAK Penelitian ini membahas penggunaan dan penerapan cluster database untuk mengurangi dampak buruk pada website akibat server mengalami downtime, sehingga dapat tetap menjaga trafik pengunjung yang sedang beraktivitas pada website. Pada penelitian ini akan dilakukan implementasi perancangan cluster database dan pengujian hasil dari implemetasi cluster database pada server. Dari hasil tes tersebut akan ditemukan dampak yang ditimbulkan dengan adanya cluster database pada server supaya dapat digunakan sebagai refrensi pada pembuatan infrastruktur sebuah website. Dalam pengujian program dilakukan dengan membandingkan dari hasil system sebelum dilakukan implementasi cluster dan setelah dilakukan implementasi cluster. Dalam uji coba yang telah dilakukan mencapai hasil yang sesuai tidak terjadi downtime pada akses website apabila terjadi kegagalan pada salah satu server database. Dari hasil tersebut menunjukan bahwa cluster database berfungsi dengan baik dalam menjaga uptime website yang ada. Kata kunci: Cluster, Database, Infrastruktur, Website
Analisis Penempatan Access Point Pada Jaringan Wireless LAN STMIK Asia Malang Menggunakan One Slope Model Mukti, Fransiska Sisilia; Sulistyo, Danang Arbian
Jurnal Ilmiah Teknologi Informasi Asia Vol 13 No 1 (2019): Volume 13 Nomor 1 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

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

Abstract

Penelitian ini bertujuan untuk menganalisis penempatan access point (AP) pada jaringan WLAN STMIK Asia Malang, yang berdampak terhadap level daya atau kuat sinyal yang diterima oleh pengguna. Pendekatan pertama melalui site survey, dengan tujuan yakni mendapatkan informasi yang cukup mengenai jumlah dan penempatan AP yang saat ini diaplikasikan pada gedung kampus STMIK Asia Malang. Hasil dari walktest ini akan digunakan sebagai parameter untuk perhitungan teoritis menggunakan model propagasi One Slope Model (1SM). Berdasarkan perhitungan 1SM, didapatkan jarak optimal untuk penempatan AP tidak lebih dari 13 m pada propagasi LOS (rentang kuat sinyal -10dB sampai dengan -20dB, pada area koridor gedung) dan jarak 6 m pada propagasi NLOS (rentang kuat sinyal -40dB sampai dengan -50dB, pada area ruangan perkuliahan). Hasil analisis membuktikan bahwa keberadaan barrier mempengaruhi kekuatan sinyal yang diterima oleh user, sehingga penempatan perangkat WLAN, dalam hal ini AP perlu diperhatikan.
An enhanced pivot-based neural machine translation for low-resource languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almuíini
International Journal of Advances in Intelligent Informatics Vol 11, No 2 (2025): May 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i2.2115

Abstract

This study examines the efficacy of employing Indonesian as an intermediary language to improve the quality of translations from Javanese to Madurese through a pivot-based approach utilizing neural machine translation (NMT). The principal objective of this research is to enhance translation precision and uniformity among these low-resource languages, hence advancing machine translation models for underrepresented languages. The data collecting approach entailed extracting parallel texts from internet sources, followed by pre-processing through tokenization, normalization, and stop-word elimination algorithms. The prepared datasets were utilized to train and assess the NMT models. An intermediary phase utilizing Indonesian is implemented in the translation process to enhance the accuracy and consistency of translations between Javanese and Madurese. Parallel text corpora were created by collecting and preprocessing data, thereafter, utilized to train and assess the NMT models. The pivot-based strategy regularly surpassed direct translation regarding BLEU scores for all n-grams (BLEU-1 to BLEU-4). The enhanced BLEU ratings signify increased precision in vocabulary selection, preservation of context, and overall comprehensibility. This study significantly enhances the current literature in machine translation and computational linguistics, especially for low-resource languages, by illustrating the practical effectiveness of a pivot-based method for augmenting translation precision. The method's dependability and efficacy in producing genuine translations were proved through numerous studies. The pivot-based technique enhances translation quality, although it possesses limitations, including the risk of error propagation and bias originating from the pivot language. Further research is necessary to examine the integration of named entity recognition (NER) to improve accuracy and optimize the intermediate translation process. This project advances the domains of machine translation and the preservation of low-resource languages, with practical implications for multilingual communities, language education resources, and cultural conservation.
Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping Ahda, Fadhli Almu'iini; Aji Prasetya Wibawa; Didik Dwi Prasetya; Danang Arbian Sulistyo; Andrew Nafalski
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6511

Abstract

Stemming is an essential procedure in natural language processing (NLP), which involves reducing words to their root forms by eliminating affixes, including prefixes, infixes, and suffixes. The employed method assesses the efficacy of stemming, which differs according to language. Complex affixation patterns in Indonesian and regional languages such as Minangkabau pose considerable difficulties for traditional algorithms. This research adopts the enhanced fixed-stripping method to tackle these issues by integrating linguistic characteristics unique to Minangkabau. This study has three phases: data acquisition, pseudocode development, and algorithm execution. Testing revealed an average accuracy of 77.8%, indicating the algorithm's proficiency in managing Minangkabau’s intricate morphology. Nevertheless, constraints persist, particularly with irregular affixation patterns. Possible improvements could include adding more datasets, improving the rules for handling affixes, and using machine learning to make the system more flexible and accurate. This study emphasizes the significance of customized solutions for regional languages and provides insights into the advancement of NLP in various linguistic environments. The findings underscore the progress made in processing Minangkabau text while also emphasizing the need for further research to address current issues.
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