Articles
Generating Javanese Stopwords List using K-means Clustering Algorithm
Aji Prasetya Wibawa;
Hidayah Kariima Fithri;
Ilham Ari Elbaith Zaeni;
Andrew Nafalski
Knowledge Engineering and Data Science Vol 3, No 2 (2020)
Publisher : Universitas Negeri Malang
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DOI: 10.17977/um018v3i22020p106-111
Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created by a Javanese linguist. The accuracy of the proposed method is 78.28% (K=7). The result shows that the generation of Javanese stopword lists using a clustering method is reliable.
High Dimensional Data Clustering using Self-Organized Map
Ruth Ema Febrita;
Wayan Firdaus Mahmudy;
Aji Prasetya Wibawa
Knowledge Engineering and Data Science Vol 2, No 1 (2019)
Publisher : Universitas Negeri Malang
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DOI: 10.17977/um018v2i12019p31-40
As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
SQL Logic Error Detection by Using Start End Mid Algorithm
Jevri Tri Ardiansah;
Aji Prasetya Wibawa;
Triyanna Widyaningtyas;
Okazaki Yasuhisa
Knowledge Engineering and Data Science Vol 1, No 1 (2018)
Publisher : Universitas Negeri Malang
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DOI: 10.17977/um018v1i12018p33-38
Data base is an important part of a system and it stores data to be manipulated. A language called SQL (Structured Query Language) is used for manipulating those data to make needed information. There are two types of error which make SQL more difficult in practical implementation. They are syntax error and logic error. The difference between them is that syntax error can be detected by compiler so it is easy to learn by its warning. But compiler does not show error warning if logical error was occurred. It makes logic error is more difficult to understand than syntax error. To help data base's user to learn SQL in practical implementation, web based SQL compiler that be able to detect syntax and logic error is developed by using Start End Mid algorithm.
DESAIN SISTEM INFORMASI ADMINISTRASI PENDIDIKAN DI PASCASARJANA UNIVERSITAS NEGERI MALANG DENGAN METODE REKAYASA BALIK
Rendy Yani Susanto;
Aji Prasetya Wibawa;
Triyanna Widiyaningtyas
Jurnal Ilmiah Flash Vol 4 No 1 (2018)
Publisher : P3M- Politeknik Negeri Kupang
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DOI: 10.32511/flash.v4i1.210
Administrasi Pascasarjana Universitas Negeri Malang masih menggunakan teknologi lama yaitu aplikasi PFS:Professional File. Walaupun digunakan hampir 33 tahun, aplikasi ini masihlayakdan stabil untuk pelaksanaan proses administrasi. Berjalannya waktu, aplikasi ini menjadi tidak kompatibel dengan teknologi yang ada. Oleh karena itu, pembaharuan aplikasi sangat dibutuhkan agar kompatibel dengan sistem operasi tersebut. Akan tetapi, aplikasi tersebut tidak memiliki dokumentasi yang digunakan sebagai bahan pembaharuan.Dokumentasi program yang dimaksudadalahberupaSpesifikasiKebutuhanPerangkatLunak (SKPL). Untukmendapatkan SKPL tersebutmembutuhkanmetodeuntukmenganalisisaplikasi yang sudahada. dari permasalahan tersebut, metode yang tepat digunakan adalah metode rekayasa balik. Metode ini dapat mengekstrak informasi dari desain source code pada aplikasi yang tidak terstruktur. Sehingga diharapkan dengan penggunaan metode rekayasa balik, dokumentasi dari aplikasi PFS:Professional File bisa dibuat. Hasil dari dokumentasi tersebut nantinya akan dijadikan bahan pengembangan aplikasi baru diharapkan penggunaan metode rekayasa balik pada aplikasi tersebut bisa menjadi solusi.
SISTEM PEMILIHAN DOSEN PEMBIMBING SKRIPSI DENGAN METODE TOPSIS (STUDI KASUS: PENDIDIKAN TEKNIK INFORMATIKA)
Tantri Hari Mukti;
Syaad Patmantara;
Aji Prasetya Wibawa
Jurnal Ilmiah Flash Vol 4 No 1 (2018)
Publisher : P3M- Politeknik Negeri Kupang
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DOI: 10.32511/flash.v4i1.211
Penunjukan pembimbing skripsi di Program Studi Pendidikan Teknik Informatika Universitas Negeri Malang ditangani oleh tim dosen KBK (Kelompok Bidang Keahlian) dan dosen Koordinator Program Studi (Korprodi). Tim KBK dan Korprodi harus menyesuaikan kriteria-kriteria calon dosen pembimbing yang sesuai dengan kondisi dan judul yang diajukan mahasiswa. Selain itu Tim KBK dan Korprodi membutuhkan waktu yang lama untuk menyelesaikan banyaknya antrian pengajuan dosen pembimbing. Dari permasalahan tersebut, dibuat sistem yang dapat memberikan rekomendasi dosen pembimbing dengan menggunakan metode TOPSIS. Sehingga sistem tersebut dapat mempermudah tugas dosen KBK dan Korprodi. Pemilihan metode TOPSIS (Technique For Others Reference by Similarity to Ideal Solution) dirasa lebih cocok dengan kasus ini karena terdapatnya pemecahan unsur kriteria dan pembobotan pada masing-masing kriteria. Berdasarkan hasil studi kasus sistem seleksi menunjukan bahwa hasil perhitungan menggunakan sistem sama dengan perhitungan manual. Sistem ini mampu memberikan rekomendasi pemilihan dosen pembimbing
Choosing an Instant Messaging App: Security or Convenience? Comparison between Whatsapp and Telegram
Azzhan Shahrul;
Aji Prasetya Wibawa
Buletin Ilmiah Sarjana Teknik Elektro Vol. 3 No. 2 (2021): Agustus
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/biste.v3i2.2784
An increase in Instant Messenger (IM) application users makes it easier for people to get connected through social media. Application developers regularly offer updates. However, those updates don’t always satisfy users expectations, instead confuse them. Even users are sometimes hesitant to update the app thus they switch to another messaging platform. This research discusses the analysis and comparison of two IM applications that reached 100 million downloads on Play Store; Whatsapp and Telegram. The analysis process is carried out from the features use in the Instant Messenger application. The data collection procedure are conducted by viewing the traffic. The data acquisition technique is done by using literacy and observation study methods to get full access to smartphones. The results of the analysis are in the form of a comparing table between both IM applications and expected to be future reference for further reseach.Peningkatan pengguna aplikasi Instant Messenger (IM) memudahkan masyarakat untuk terhubung melalui media sosial. Pengembang aplikasi secara teratur menawarkan pembaruan. Namun, pembaruan tersebut tidak selalu memenuhi harapan pengguna, malah membingungkan mereka. Bahkan pengguna terkadang ragu untuk memperbarui aplikasi sehingga mereka beralih ke platform perpesanan lain. Penelitian ini membahas tentang analisis dan perbandingan dua aplikasi IM yang mencapai 100 juta unduhan di Play Store; Whatsapp dan Telegram. Proses analisis dilakukan dari fitur-fitur yang digunakan pada aplikasi Instant Messenger. Prosedur pengumpulan data dilakukan dengan melihat lalu lintas. Teknik akuisisi data dilakukan dengan menggunakan metode studi literasi dan observasi untuk mendapatkan akses penuh ke smartphone. Hasil analisis berupa tabel perbandingan antara kedua aplikasi IM dan diharapkan dapat menjadi acuan untuk penelitian selanjutnya.
Convolutional Neural Network (CNN) to determine the character of wayang kulit
Aji Prasetya Wibawa;
Wahyu Arbianda Yudha Pratama;
Anik Nur Handayani;
Anusua Ghosh
International Journal of Visual and Performing Arts Vol 3, No 1 (2021)
Publisher : ASSOCIATION FOR SCIENTIFIC COMPUTING ELECTRICAL AND ENGINEERING (ASCEE)
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DOI: 10.31763/viperarts.v3i1.373
Indonesia is a country with diverse cultures. One of which is Wayang Kulit, which has been recognized by UNESCO. Wayang kulit has a variety of names and personalities, however most younger generations are not familiar with the characters of these shadow puppets. With today's rapid technological advancements, people could use this technology to detect objects using cameras. Convolutional Neural Network (CNN) is one method that can be used. CNN is a learning process that is included in the Deep Learning section and is used to find the best representation. The CNN is commonly used for object detection, would be used to classify good and bad characters. The data used consists of 100 black and white puppet images that were downloaded one at a time. The data was obtained through a training process that uses the CNN method and Google Colab to help speed up the training process. After that, a new model is created to test the puppet images. The result obtained a 92 percent accuracy rate, means that CNN can differentiate the Wayang Kulit character
Evolution strategies based coefficient of TSK fuzzy forecasting engine
Nadia Roosmalita Sari;
Wayan Firdaus Mahmudy;
Aji Prasetya Wibawa
International Journal of Advances in Intelligent Informatics Vol 7, No 1 (2021): March 2021
Publisher : Universitas Ahmad Dahlan
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DOI: 10.26555/ijain.v7i1.376
Forecasting is a method of predicting past and current data, most often by pattern analysis. A Fuzzy Takagi Sugeno Kang (TSK) study can predict Indonesia's inflation rate, yet with too high error. This study proposes an accuracy improvement based on Evolution Strategies (ES), a specific evolutionary algorithm with good performance optimization problems. ES algorithm used to determine the best coefficient values on consequent fuzzy rules. This research uses Bank Indonesia time-series data as in the previous study. ES algorithm uses the popSize test to determine the number of initial chromosomes to produce the best optimal solution for this problem. The increase of popSize creates better fitness value due to the ES's broader search area. The RMSE of ES-TSK is 0.637, which outperforms the baseline approach. This research generally shows that ES may reduce repetitive experiment events due to Fuzzy coefficients' manual setting. The algorithm complexity may cost to the computing time, yet with higher performance.
The performance of text similarity algorithms
Didik Dwi Prasetya;
Aji Prasetya Wibawa;
Tsukasa Hirashima
International Journal of Advances in Intelligent Informatics Vol 4, No 1 (2018): March 2018
Publisher : Universitas Ahmad Dahlan
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DOI: 10.26555/ijain.v4i1.152
Text similarity measurement compares text with available references to indicate the degree of similarity between those objects. There have been many studies of text similarity and resulting in various approaches and algorithms. This paper investigates four majors text similarity measurements which include String-based, Corpus-based, Knowledge-based, and Hybrid similarities. The results of the investigation showed that the semantic similarity approach is more rational in finding substantial relationship between texts.
Rayleigh quotient with bolzano booster for faster convergence of dominant eigenvalues
M Zainal Arifin;
Ahmad Naim Che Pee;
Sarni Suhaila Rahim;
Aji Prasetya Wibawa
International Journal of Advances in Intelligent Informatics Vol 8, No 1 (2022): March 2022
Publisher : Universitas Ahmad Dahlan
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DOI: 10.26555/ijain.v8i1.718
Computation ranking algorithms are widely used in several informatics fields. One of them is the PageRank algorithm, recognized as the most popular search engine globally. Many researchers have improvised the ranking algorithm in order to get better results. Recent research using Rayleigh Quotient to speed up PageRank can guarantee the convergence of the dominant eigenvalues as a key value for stopping computation. Bolzano's method has a convergence character on a linear function by dividing an interval into two intervals for better convergence. This research aims to implant the Bolzano algorithm into Rayleigh for faster computation. This research produces an algorithm that has been tested and validated by mathematicians, which shows an optimization speed of a maximum 7.08% compared to the sole Rayleigh approach. Analysis of computation results using statistics software shows that the degree of the curve of the new algorithm, which is Rayleigh with Bolzano booster (RB), is positive and more significant than the original method. In other words, the linear function will always be faster in the subsequent computation than the previous method.