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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JOISIE (Journal Of Information Systems And Informatics Engineering) Simpatik: Jurnal sistem Informasi dan Informatika
Gusrianty Gusrianty
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Computer Science & IT

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Penerapan Metode Left Corner Parsing dan Analisis Kontekstual Pada Natural Language Processing Deny Jollyta; Muhammad Zarlis; Gusrianty Gusrianty; Yulvia Nora Marlim
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 7 No 1 (2020): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (68.29 KB) | DOI: 10.35957/jatisi.v7i1.269

Abstract

Natural language translation is very helpful in understanding each word or sentence based on the intended meaning. Variety of languages that are not easy to understand, cause miscommunication. Natural Language Processing (NLP) is the choice to translate human language with computer naturally. As one method of parsing, the left corner parsing describes languages ranging from the largest to the smallest constituent, namely the word. The decomposition is followed by representing the meaning or known as contextual interpretation. This study aims to describe the language using the left corner parsing which is equipped with analysis to determine the purpose of sentence using. The test results showed that the Left Corner Parsing method succeeded in deciphering sentences in accordance with the initial language pattern specified and provided the true contextual analysis and easily understood translation results.
Sistem Pendukung Keputusan Seleksi Atlet Poomsae Taekwondo Dengan Metode Analityc Hierachy Process Wahyu Joni Kurniawan; Gusrianty Gusrianty
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 2 No 1 (2018)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (821.099 KB) | DOI: 10.35145/joisie.v2i1.244

Abstract

Beladiri taekwondo memeliki dua jenis pertandingan, salah satunya poomsae. Untuk bisa menjadi atlet maka dibutuhkan banyak kriteria yang harus dipenuhi, dikarenakan menjadi atlet itu tidaklah mudah. Dengan banyaknya kriteria yang menjadi indikator seorang menjadi atlet, maka digunakanlah metode analityc hierarchy process (AHP). Yang merupakan sebuah teori pengukuran melalui perbandingan berpasangan dan bergantung pada penilaian dari para ahli untuk menentukan prioritas. Ada beberpa kriteria yang menjadi acuan bagi anggota yang ingin menjadi atlet poomsae, seperti kedisiplinan, sikap, kerajinan, teknik, daya tahan, keindahan, sabuk dan tim. Juga beberapa sub kriteria dari sabuk, yakni hijau, biru, merah, dan hitam. Secara keseluruhan, pemerolehan data keputusan dari setiap alternatif didapatlah hasil akhirnya adalah jika dimabil 4 alternatif yang memungkinakan, maka yanng terpilih sesuai pembobotan adalah E (042), A (0,23), D (0,16), dan B(0,11). Dengan menggunakan metode ini, maka akan membantu pelatih dalam memilih anggota manakah yang lebih tepat untuk bisa mengikuti pertandingan poomsae.
Aplikasi Simulasi Tes Hanyu Shuiping Kaoshi Menggunakan Algoritma Collaborative Filtering Suyan Suyan; Dwi Oktarina; Yenny Desnelita; Gusrianty Gusrianty
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 5 No. 2 (2025): Desember 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v5i2.11228

Abstract

Mandarin has become one of the most important global languages, particularly in the fields of education and business. The HSK exam, as a standard measure of Mandarin language proficiency, requires effective and structured preparation. However, the manual methods still used by language institutions such as Happy Mandarin Course are considered inefficient in helping students identify their personal weaknesses. This study aims to design a web-based HSK exam simulation application equipped with a question recommendation system using the Collaborative Filtering algorithm. The recommendation system is supported by similarity calculations using the Pearson Correlation Coefficient to match questions to users' abilities based on previous results. The application was developed using the waterfall approach, implemented with the Python programming language and the Flask framework. Testing results show that the system can recommend questions adaptively, assist students in improving their skills, and ease the teaching process for instructors. The application can identify users’ weaknesses individually and provide targeted practice, thus offering an effective and adaptive solution for enhancing HSK exam readiness.
Co-Authors Deny Jollyta Desnelita, Yenny Dwi Oktarina Marlim, Yulvia Nora Muhammad Zarlis Suyan Suyan Wahyu Joni Kurniawan