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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Infotech Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Buletin Profesi Insinyur Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) JUSTE (Journal of Science and Technology) Jurnal Jalan Jembatan
Andreyan Rizky Baskara
Universitas Lambung Mangkurat
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Klasifikasi Laporan Keluhan Pelayanan Publik Berdasarkan Instansi Menggunakan Metode LDA-SVM Alkaff, Muhammad; Baskara, Andreyan Rizky; Maulani, Irham
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 6: Desember 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021863768

Abstract

Sebuah sistem layanan untuk menyampaikan aspirasi dan keluhan masyarakat terhadap layanan pemerintah Indonesia, bernama Lapor! Pemerintah sudah lama memanfaatkan sistem tersebut untuk menjawab permasalahan masyarakat Indonesia terkait permasalahan birokrasi. Namun, peningkatan volume laporan dan pemilahan laporan yang dilakukan oleh operator dengan membaca setiap keluhan yang masuk melalui sistem menyebabkan sering terjadi kesalahan dimana operator meneruskan laporan tersebut ke instansi yang salah. Oleh karena itu, diperlukan suatu solusi yang dapat menentukan konteks laporan secara otomatis dengan menggunakan teknik Natural Language Processing. Penelitian ini bertujuan untuk membangun klasifikasi laporan secara otomatis berdasarkan topik laporan yang ditujukan kepada instansi yang berwenang dengan menggabungkan metode Latent Dirichlet Allocation (LDA) dan Support Vector Machine (SVM). Proses pemodelan topik untuk setiap laporan dilakukan dengan menggunakan metode LDA. Metode ini mengekstrak laporan untuk menemukan pola tertentu dalam dokumen yang akan menghasilkan keluaran dalam nilai distribusi topik. Selanjutnya, proses klasifikasi untuk menentukan laporan agensi tujuan dilakukan dengan menggunakan SVM berdasarkan nilai topik yang diekstraksi dengan metode LDA. Performa model LDA-SVM diukur dengan menggunakan confusion matrix dengan menghitung nilai akurasi, presisi, recall, dan F1 Score. Hasil pengujian menggunakan teknik split train-test dengan skor 70:30 menunjukkan bahwa model menghasilkan kinerja yang baik dengan akurasi 79,85%, presisi 79,98%, recall 72,37%, dan Skor F1 74,67%. AbstractA service system to convey aspirations and complaints from the public against Indonesia's government services, named Lapor! The Government has used the Government for a long time to answer the problems of the Indonesian people related to bureaucratic problems. However, the increasing volume of reports and the sorting of reports carried out by operators by reading every complaint that comes through the system cause frequent errors where operators forward the reports to the wrong agencies. Therefore, we need a solution that can automatically determine the report's context using Natural Language Processing techniques. This study aims to build automatic report classifications based on report topics addressed to authorized agencies by combining Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM). The topic-modeling process for each report was carried out using the LDA method. This method extracts reports to find specific patterns in documents that will produce output in topic distribution values. Furthermore, the classification process to determine the report's destination agency carried out using the SVM based on the value of the topics extracted by the LDA method. The LDA-SVM model's performance is measured using a confusion matrix by calculating the value of accuracy, precision, recall, and F1 Score. The test results using the train-test split technique with a 70:30 show that the model produces good performance with 79.85% accuracy, 79.98% precision, 72.37% recall, and 74.67% F1 Score
Perbandingan Metode Pembobotan Tf-Rf Dan Tf-Idf Dikombinasikan Dengan Weighted Tree Similarity Untuk Sistem Rekomendasi Buku Sari, Yuslena; Baskara, Andreyan RIzky; Prakoso, Puguh Budi; Royani, Noorhanida
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022935709

Abstract

Unit Pusat Terpadu Perpustakaan merupakan perpustakaan pusat yang ada di Universitas Lambung Mangkurat. Perpustakaan ini mempunyai sistem pencarian buku namun sistem tersebut belum adanya fitur rekomendasi buku sehingga anggota menjadi kesulitan dalam melakukan pencarian buku yang sesuai dengan keinginan anggota. Oleh karena itu, dengan adanya rekomendasi buku atau saran buku yang lain dapat menjadi alternatif untuk membantu anggota dalam melakukan pencarian buku yang sesuai. Dalam penelitian ini menggunakan perbandingan pembobotan kata TF-IDF dan TF-RF dengan weighted tree similarity sebagai pengukur kemiripan diantara beberapa data dengan parameter tree yang sudah ditentukan dan dilakukan perbandingan perhitungan dengan menghitung tf-idf dengan tf-rf menggunakan perhitungan excel mendapatkan nilai yang berbeda antara tf-idf dengan tf-rf, pembobotan tf-idf dapat mengukur kemiripan antara dokumen dan kata kunci buku yang paling mirip dengan buku yang dianggap paling relevan. Sehingga anggota memasukan kata kunci kemudian akan menemukan kemiripan buku dari kata kunci yang dimasukan sebelumnya namun untuk pembobotan tf-rf memberikan kata kunci dari setiap kategori. Hasil perbandingan yang di dapat yaitu 96% untuk tf-idf dan 98% untuk tf-rf. Sistem ini menggunakan bahasa pemrograman python dengan web framework django. AbstractThe Central Integrated Library Unit is the central library at Lambung Mangkurat University. This library has a book search system but the system does not have a book recommendation feature so that members find it difficult to search for books that match the wishes of members. Therefore, the existence of book recommendations or other book suggestions can be an alternative to assist members in searching for suiTabel books. In this study using a comparison of the weighting of the words TF-IDF and TF-RF with weighted tree similarity as a measure of the similarity between several data and a comparison of calculations is carried out by calculating tf-idf with tf-rf using excel calculations to get different values between tf-idf and tf -rf, tf-idf weighting can measure the similarity between documents and keywords of the book that is most similar to the book that is considered the most relevant. So that members enter keywords and then find the similarity of books from the keywords entered previously but for weighting tf-rf provides keywords from each category. The comparison results obtained are 76% for tf-idf and 80% for tf-rf. This system uses the python programming language with the django web framework.
Penerapan Metode K-Means Berbasis Jarak untuk Deteksi Kendaraan Bergerak Sari, Yuslena; Baskara, Andreyan Rizky; Prakoso, Puguh Budi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 4: Agustus 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022945768

Abstract

Deteksi kendaraan bergerak adalah salah satu elemen penting dalam aplikasi Intelligent Transport System (ITS). Deteksi kendaraan bergerak juga merupakan bagian dari pendeteksian benda bergerak. Metode K-Means berhasil diterapkan pada piksel cluster yang tidak diawasi untuk mendeteksi objek bergerak. Secara umum, K-Means adalah algoritma heuristik yang mempartisi kumpulan data menjadi K cluster dengan meminimalkan jumlah kuadrat jarak di setiap cluster. Dalam makalah ini, algoritma K-Means menerapkan jarak Euclidean, jarak Manhattan, jarak Canberra, jarak Chebyshev dan jarak Braycurtis. Penelitian ini bertujuan untuk membandingkan dan mengevaluasi implementasi jarak tersebut pada algoritma clustering K-Means. Perbandingan dilakukan dengan basis K-Means yang dinilai dengan berbagai parameter evaluasi yaitu MSE, PSNR, SSIM dan PCQI. Hasilnya menunjukkan bahwa jarak Manhattan memberikan nilai MSE = 1.328 , PSNR = 21.14, SSIM = 0.83 dan PCQI = 0.79 terbaik dibandingkan dengan jarak lainnya. Sedangkan untuk waktu pemrosesan data memperlihatkan bahwa jarak Braycurtis memiliki keunggulan lebih yaitu 0.3 detik. AbstractDetection moving vehicles is one of important elements in the applications of Intelligent Transport System (ITS). Detection moving vehicles is also part of the detection of moving objects. K-Means method has been successfully applied to unsupervised cluster pixels for the detection of moving objects. In general, K-Means is a heuristic algorithm that partitioned the data set into K clusters by minimizing the number of squared distances in each cluster. In this paper, the K-Means algorithm applies Euclidean distance, Manhattan distance, Canberra distance, Chebyshev distance and Braycurtis distance. The aim of this study is to compare and evaluate the implementation of these distances in the K-Means clustering algorithm. The comparison is done with the basis of K-Means assessed with various evaluation paramaters, namely MSE, PSNR, SSIM and PCQI. The results exhibit that the Manhattan distance delivers the best MSE = 1.328 , PSNR = 21.14, SSIM = 0.83 and PCQI = 0.79 values compared to other distances. Whereas for data processing time exposes that the Braycurtis distance has more advantages 
Evaluation of User Experience in the Game "Night's Reach" Using the Game Experience Method Questionnaire (GEQ) Sherly Damaiyanti; Andreyan Rizky Baskara; Muhammad Fajrian Noor; Muti'a Maulida
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 1 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i1.463

Abstract

Students from Lambung Mangkurat University developed a game called "Game Night's Reach" aimed at introducing and preserving wetland environments. To assess the game's viability for release, it is crucial to test the UI/UX to gauge its efficiency. This involves understanding how well players interact with the game and their over-all user experience. The testing is conducted through distributing questionnaires to collect gameplay experience data from new users. The method used is the Game Experience Questionnaire (GEQ), which measures the efficiency of user experience by evaluating players' feelings and experiences while playing the game, beyond just usability aspects like efficiency, perspective, and dependency. Based on the questionnaire data, a redesign was performed in the first phase to improve the game, which will be compared in the second phase. The usability evaluation of "Game Night's Reach" using the GEQ method showed the following changes after redesign: Competence, Increased by 0.198 from 0.872 to 1.068. Immersion, Increased by 0.196 from 0.853 to 1.051. Flow, Increased by 0.29from 0.742 to 1.032. Tension, Increased by 0.1 from 0.51 to 0.61. Challenge, Increased by 0.13 from 0.588 to 0.718.Negative affect, Decreased by 0.103 from 0.545 to 0.442. Positive affect, Increased by 0.106 from 0.894 to 1.008.Empathy, Increased by 0.235 from 0.723 to 0.958. Negative feelings, Decreased by 0.072 from 0.482 to 0.41. Behavioural involvement, Increased by 0.388 from 0.59 to 0.978. Positive experience, Increased by 0.168 from 0.89to 1.058. Negative experience, Decreased by 0.078 from 0.501 to 0.423. Tiredness, Decreased by 0.01 from 0.505 to 0.495. Returning to reality, Increased by 0.334 from 0.646 to 0.986.
Quality Analysis of the Digital Library Website of Universitas Lambung Mangkurat with Webqual 4.0 Method and User Experience Questionnaire (UEQ) Nurul Huda; Andreyan Rizky Baskara; Nurul Fathanah Mustamin; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 1 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i1.464

Abstract

The current digital literature resources are widely provided by various libraries, especially those associated with higher education institutions. One such example of a digital library is the Lambung Mangkurat University Digital Library (Digilib ULM). Pre-evaluation results indicate that around 50% of the issues are related to the quality of the website, such as its appearance and functionality. Therefore, this research examines the quality of the ULM Digital Library to identify indicators that match user preferences and require improvement. The Webqual 4.0 method and User Experience Questionnaire are uti- lised for this purpose. The research is quantitative with a descriptive approach. Data is collected through a questionnaire, with 100 respondents sampled from the entire population, consisting of ULM students. Webqual 4.0 comprises three dimensions: usability, information quality, and service interaction. Meanwhile, UEQ consists of six aspects: attractiveness, dependability, efficiency, perspicuity, stimulation, and novelty. The research findings from Webqual 4.0 indicate a service interaction score of 2.75, information quality of 2.68, and usability of 2.45. The usability aspect falls into the low category or does not meet user expectations, while the other aspects fall into the moderate category. The UEQ results show an attractiveness score of 1.130, efficiency of 0.648, and novelty of 0.673, all scoring below the average compared to benchmarks, while other aspects score above average. Based on these results, it is evident that the Digilib ULM website does not meet user expectations and can be considered suboptimal, requiring improvement and enhancement.
Co-Authors Ahmad Rivaldy Akhmad Rivaldy Ferry Pratama Halimah Halimah Husnul Khatimi Maulani, Irham Muhammad Adetya Ashari Muhammad Alkaff Muhammad Andri Firdaus Muhammad Arif Rahman Muhammad Faidhorrahman Muhammad Fajrian Noor Muhammad Syauqi Al Fath Muti'a Maulida Mutia Maulida Muti`a Maulida Nurul Fathanah Mustamin Nurul Huda Nurul Qamaria Prakoso, Puguh Budi Puguh Budi Prakoso Puguh Budi Prakoso Rahman, Muhammad Arif Rico Silas Dwi Kasanda Royani, Noorhanida Sherly Damaiyanti Taufiq Abrory Wijaya, Eka Setya Yuslena Sari, Yuslena