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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Sistemasi: Jurnal Sistem Informasi Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer SemanTIK : Teknik Informasi Knowledge Engineering and Data Science JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Teknoinfo Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Jurnal SITECH : Sistem Informasi dan Teknologi METIK JURNAL Sains, Aplikasi, Komputasi dan Teknologi Informasi Indonesian Journal of Data and Science SKANIKA: Sistem Komputer dan Teknik Informatika Innovation in Research of Informatics (INNOVATICS) Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII International Journal of Artificial Intelligence in Medical Issues
Taruk, Medi
Universitas Mulawarman
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Transportation

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Optimizing Neurodegenerative Disease Classification with Canny Segmentation and Voting Classifier: An Imbalanced Dataset Study Sinra, A.; Waluyo Poetro, Bagus Satrio; Angriani, Husni; Zein, Hamada; Musdar, Izmy Alwiah; Taruk, Medi
International Journal of Artificial Intelligence in Medical Issues Vol. 1 No. 2 (2023): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v1i2.97

Abstract

This study explores the efficacy of a Voting Classifier, combining Logistic Regression, Random Forest, and Gaussian Naive Bayes, in the classification of neurodegenerative diseases, focusing on Alzheimer's Disease (AD), Parkinson’s Disease (PD), and control groups. Utilizing a dataset pre-processed with Canny segmentation and Hu Moments feature extraction, the research aimed to address the challenges posed by imbalanced datasets in medical image classification. The classifier's performance was evaluated through a 5-fold cross-validation approach, with metrics including accuracy, precision, recall, and F1-Score. The results revealed a consistent recall rate of approximately 46% across all folds, indicating the model's effectiveness in identifying cases of neurodegenerative diseases. However, the precision and F1-Score were notably lower, averaging around 22% and 29%, respectively, underscoring the difficulties in achieving accurate classification in imbalanced datasets. The study contributes to the understanding of machine learning applications in medical diagnostics, specifically in the challenging context of neurodegenerative disease classification. It highlights the potential of using advanced image processing techniques combined with machine learning ensembles in enhancing diagnostic accuracy. However, it also draws attention to the inherent challenges in such approaches, particularly regarding precision in imbalanced datasets. Recommendations for future research include exploring data balancing techniques, alternative feature extraction methods, and different machine learning algorithms to improve the precision and overall performance. Additionally, applying the model to a broader and more diverse dataset could provide more generalizable and robust findings. This study is significant for researchers and practitioners in medical imaging and machine learning, offering insights into the complexities and potential of automated disease classification
Finite state machine for retro arcade fighting game development Firdaus, Muhammad Bambang; Waksito, Alan Zulfikar; Tejawati, Andi; Taruk, Medi; Anam, M. Khairul; Irsyad, Akhmad
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 14, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v14i1.pp102-110

Abstract

Traditional fighting games are a competitive genre where players engage in one-on-one combat, aiming to reduce their opponent's health points to zero. These games often utilize two-dimensional (2D) graphics, enabling players to execute various character movements such as punching, jumping, and crouching. This research investigates the effectiveness of the finite state machine (FSM) method in developing a combo system for a retro fighting game, focusing on its implementation within the Godot Engine. The FSM method, which structures game behavior through states, events, and actions, is central to the game's control system. By employing the game development life cycle (GDLC) methodology, this study ensures a systematic and structured approach to game design. Special attention is given to the regulation of the combo hit system for the game's protagonist in Brawl Tale. The research culminates in the successful development of the retro fighting game Brawl Tale, demonstrating that the FSM method significantly enhances the fluidity and responsiveness of character movements. The findings suggest that the FSM method is an effective tool for simplifying and improving gameplay mechanics in retro-style fighting games.
Penerapan Motion Graphic Pada Video Promosi Wisata Pantai Panrita Lopi Tejawati, Andi; Indrajit, Indrajit; Taruk, Medi; Arifin, Zainal; Riyayatsyah, Riyayatsyah; Alameka, Faza; Pakpahan, Herman Santoso
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 8, No 2 (2024): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v8i2.14615

Abstract

Berbagai pendekatan, efek, framing, panorama, dan vintage kini dihasilkan dari aspek-aspek tersebut dalam kemajuan teknis kontemporer, yang mampu menimbulkan kesan tersendiri saat pengguna melihatnya. Grafik gerak adalah bentuk media yang menggunakan teknologi animasi untuk menciptakan tampilan gerakan dan biasanya dipasangkan dengan audio dan teks untuk digunakan dalam output multimedia. Tujuan penelitian ini adalah membuat aplikasi video sinematografi untuk meningkatkan kualitas media promosi Pantai Panrita Lopi, memperluas pemasaran Pantai Panrita Lopi, dan menarik perhatian calon pengunjung sehingga memilih Pantai Panrita Lopi sebagai destinasi. Teknik dalam penelitian ini adalah penggunaan proses produksi video untuk membuat video yang sukses. Kamera Sony A6100, Canon 600D, drone DJI Mavic Air, dan alat pengeditan video Adobe Premiere Pro dan Adobe After Effects digunakan untuk membuat promosi. Dari 51 responden yang telah menonton video sinematografi dan menggunakan aplikasi, ditemukan banyaknya responden yang setuju di setiap pertanyaan kuesioner diantaranya pertanyaan pertama sebesar 64,70%, pertanyaan kedua sebesar 60,80%, pertanyaan ketiga sebesar 58,80% dan pertanyaan keempat sebesar 52,9%. Disarankan kedepannya untuk memperhatikan keseimbangan antara informasi yang disampaikan dengan estetika visual yang menarik, sehingga dapat menciptakan pengalaman yang memikat bagi penonton dan mendorong mereka untuk mengunjungi Pantai Panrita Lopi.
Pemilihan Asuhan Nutrisi Untuk Menjaga Kadar Kolesterol Menggunakan Metode Weighted Aggregated Sum Product Assessment (WASPAS) Syachmiral, Zidane Althaariq; Puspitasari, Novianti; Taruk, Medi
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 9, No 1 (2025): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v9i1.20551

Abstract

Di Indonesia sebagian besar masyarakat memiliki angka kadar kolesterol melebih batas normal. Pola makan yang tidak seimbang dan gaya hidup yang tidak sehat menjadi penyebab terbesar masyarakat mengalami peningkatan kadar kolesterol. Pengaturan pola makan yang memperhatikan zat gizi yang terkandung di dalam suatu makanan dapat menjadi solusi untuk mengurangi kadar kolesterol dalam tubuh. Namun, pemilihan asupan nutrisi yang sesuai dengan kebutuhan tubuh masih susah dilakukan oleh masyarakat. Sistem pendukung keputusan pemilihan asupan nutrisi yang optimal untuk menjaga kadar kolesterol menggunakan metode Weighted Aggregated Sum Product Assessment (WASPAS) menjadi solusi untuk mengatasi permasalahan tersebut. Metode WASPAS dipilih karena kemampuannya dalam mengintegrasikan keunggulan metode Weighted Sum Model (WSM) dan Weighted Product Model (WPM), sehingga mampu memberikan penilaian yang lebih akurat dan fleksibel terhadap alternatif nutrisi berdasarkan berbagai kriteria. Kriteria yang digunakan meliputi kandungan lemak jenuh, lemak tak jenuh, asam lemak omega-3, serat, dan vitamin C. Data diperoleh dari sumber literatur gizi terpercaya berupa jenis asupan nutrisi sebanyak 25 jenis untuk menghasilkan peringkat alternatif nutrisi terbaik. Hasil penelitian menunjukkan bahwa metode WASPAS mampu memberikan pilihan asupan makanan yang mendukung pengendalian kadar kolesterol.
Pengembangan Virtual Tour untuk Perpustakaan Universitas Mulawarman Muhammad Bambang Firdaus; Anjas, Andi; Tejawati, Andi; Taruk, Medi; Wardhana, Reza; Alameka, Faza
METIK JURNAL (AKREDITASI SINTA 3) Vol. 8 No. 1 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i1.765

Abstract

Advances in technology have now spread to all aspects of life and profession. When archiving, it is appropriate to use a computerized system to make archiving and processing letters easier. but there are still few who take advantage of current technological advances. One of them is the TEXMACO PURWASARI Vocational High School which still archives letters in paper form (hard copy). Manual archiving has weaknesses that pose many risks. By designing the UI/UX of an archival information system, it is hoped that it can solve existing problems. In designing the UI/UX, apply the user center design (UCD) method, which is a method for analyzing the UI/UX design of an electronic archival information system. seen from the system user's perspective, so that the system design is designed according to the user's needs. This research aims, apart from producing a UI/UX design design for an electronic archival information system using the User Centered Design (UCD) method, to also evaluate usability using the system usability scale method (SUS) to measure the feasibility of the Letter Archiving Information System that has been designed. The result of this research is an archival information system design that is equipped with a database design that is tailored to user needs.
Case Base Reasoning for Diagnosing the Level of Hyperemesis Gravidarum in Pregnant Women using K-Nearest Neighbor Puspitasari, Novianti; Rahayu, Ervina; Pakpahan, Herman Santoso; Taruk, Medi; Haviluddin, Haviluddin
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.2584

Abstract

Hyperemesis gravidarum is a disease that causes excessive nausea and vomiting in pregnant women. Due to dehydration, this disease can interfere with daily work and get worse. Medical personnel generally recognize hyperemesis gravidarum as one type of disease. In fact, hyperemesis gravidarum is divided into 3 levels, namely grade I or general hyperemesis gravidarum, grade II hyperemesis gravidarum and grade III. This shows that information about hyperemesis gravidarum has yet to be widely known by some medical personnel. If this is left untreated, these two conditions can cause deep vein thrombosis in pregnant women. This study aims to apply the Case-Based Reasoning and K-Nearest Neighbor (KNN) methods to produce accurate information on the diagnosis of hyperemesis gravidarum levels in pregnant women based on symptom management in cases of an old diagnosis. The study used medical record data for hyperemesis gravidarum sufferers in 2018-2019, totalling 228 data. The calculation results of the Case-Based Reasoning method with the K-Nearest Neighbor using the confusion matrix produce an accuracy value of 74%, a precision value of 55% and a recall value of 57%, which indicates that this method is good enough to diagnose levels in patients with hyperemesis gravidarum.
Comparative Analysis of BPNN and LVQ for Sundanese Character Recognition Haviluddin, Haviluddin; Pakpahan, Herman Santoso; Nurpadillah, Dinda Izmya; Setyadi, Hario Jati; Taruk, Medi; Alfred, Rayner
Knowledge Engineering and Data Science
Publisher : citeus

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

Abstract

The Sundanese script (Aksara Sunda), an essential part of Sundanese cultural heritage, has been used since the 14th century AD. However, recognizing handwritten Sundanese characters remains challenging due to variations in individual writing styles. This study compares the performance of Backpropagation Neural Network (BPNN) and Learning Vector Quantization (LVQ) for recognizing handwritten Sundanese vowel (Swara) characters. A dataset was collected from 15 individuals, each writing seven Sundanese vowel characters, which were then used for training and testing the recognition models. Experimental results show that BPNN outperforms LVQ, achieving a higher classification accuracy (95.23%), lower Mean Squared Error (MSE), and faster convergence compared to LVQ, which reached a maximum accuracy of 66.66%. Additionally, BPNN demonstrated better generalization and robustness. At the same time, LVQ was highly sensitive to learning rate variations, leading to unstable accuracy and slower training times. The findings highlight that BPNN is a more effective model for Sundanese script recognition, providing a reliable approach for preserving and digitizing traditional scripts. Future research should explore hybrid models, deep learning approaches, and larger datasets to enhance recognition accuracy and system robustness.
Studi Komparatif IndoBERT dan SVM-TF-IDF untuk Analisis Sentimen Program Makan Bergizi Gratis Nasional Zildjian, Septian Nuno; Nurdiana, Dian; Leviany, Fonda; Taruk, Medi
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 10, No 2 (2026): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v10i2.28221

Abstract

Program Makan Bergizi Gratis (MBG) merupakan kebijakan sosial yang memicu beragam respons masyarakat, khususnya di media sosial. Penelitian ini bertujuan menganalisis opini publik terhadap Program MBG melalui komentar TikTok, mengidentifikasi distribusi sentimen, serta membandingkan kinerja model IndoBERT dan Support Vector Machine (SVM) berbasis TF-IDF dalam klasifikasi sentimen berbahasa Indonesia. Data komentar diproses melalui tahapan preprocessing, meliputi pembersihan teks, penghapusan duplikasi, normalisasi bahasa, pengolahan emoji, case folding, dan penyesuaian format teks. Hasil penelitian menunjukkan bahwa IndoBERT memberikan performa yang lebih baik dibandingkan SVM-TF-IDF, dengan nilai accuracy sebesar 89,61% dan F1-makro 83,47%, sedangkan SVM-TF-IDF memperoleh accuracy 78,45% dan F1-makro 64,67%. Distribusi sentimen menunjukkan dominasi sentimen negatif (71,7%), diikuti sentimen netral (14,3%) dan positif (14,1%). Temuan ini mengindikasikan adanya kritik dan kekhawatiran masyarakat terhadap pelaksanaan Program MBG, namun tidak dapat dimaknai sebagai penolakan secara menyeluruh. Penelitian ini menunjukkan bahwa analisis sentimen berbasis Natural Language Processing dapat menjadi pendekatan yang efektif untuk memahami dinamika opini publik dan mendukung evaluasi komunikasi kebijakan berbasis data.
Klasifikasi Status Gizi Balita Menggunakan Metode K-Nearest Neighbor Syifani, Sarah; Septiarini, Anindita; Taruk, Medi; Wati, Masna; Tejawati, Andi
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 10, No 1 (2026): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v10i1.25641

Abstract

Status gizi balita merupakan indikator penting dalam menilai tingkat kesehatan anak yang dapat diketahui melalui pemeriksaan antropometri. Berdasarkan data Survei Status Gizi Indonesia (SSGI) tahun 2022, prevalensi gizi kurang di Provinsi Kalimantan Timur mencapai 23,9%, khususnya di Kota Samarinda sebesar 25,3%, yang menunjukkan bahwa masalah gizi masih perlu mendapatkan perhatian. Penelitian ini bertujuan untuk mengklasifikasikan status gizi balita menggunakan metode K-Nearest Neighbor (KNN) dengan variasi nilai K dan rumus jarak yang berbeda guna memperoleh performa terbaik. Data yang digunakan merupakan data sekunder dari Puskesmas Pasundan, Kota Samarinda, sebanyak 760 data balita usia 0–60 bulan. Tahapan penelitian meliputi pengumpulan data, perancangan data melalui proses preprocessing (data selection, penanganan outlier, dan transformasi data menggunakan min-max normalization serta encoding), implementasi metode KNN dengan variasi nilai K (1, 3, 5, 7, 9, 11) dan rumus jarak (Euclidean, Manhattan, Minkowski), serta evaluasi model menggunakan Confusion Matrix Multiclass. Berdasarkan hasil pengujian, akurasi tertinggi diperoleh sebesar 89,24% dengan nilai presisi 66,29%, recall 63,70%, dan F1-score 63,12% menggunakan nilai K = 1 dan rumus jarak Euclidean. Hasil ini menunjukkan bahwa metode KNN mampu memberikan performa klasifikasi yang baik dalam menentukan status gizi balita berdasarkan atribut usia, jenis kelamin, berat badan, dan tinggi badan.
Penerapan MOORA Pada Sistem Pendukung Keputusan Calon Penerima Bantuan Pangan Non Tunai (BPNT) Vebi C.G, Sindi; Puspitasari, Novianti; Taruk, Medi
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 10, No 2 (2026): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v10i2.26979

Abstract

Kemiskinan merupakan salah satu permasalahan sosial yang dihadapi oleh setiap bangsa, termasuk Indonesia. Bantuan sosial merupakan upaya pemerintah dalam menekan angka kemiskinan. Adapun salah satu program yang diusahakan dalam mengentaskan kemiskinan adalah program Bantuan Pangan Non Tunai (BPNT). Namun, pemberian dana BPNT memiliki kendala dalam keterbatasan dana yang akan disalurkan, sehingga proses penentuan penerima BPNT masih belum optimal dan cenderung bersifat subjektif yang menimbulkan permasalahan diantara masyarakat terkait penerima BPNT di Dinas Sosial dan Pemberdayaan Masyarakat yang tidak tepat sasaran. Hal ini menyebabkan warga yang lebih layak menerima BPNT tidak memperoleh haknya dan sebaliknya. Dari permasalahan tersebut penelitian ini membangun sistem pendukung keputusan penerima BPNT untuk membantu pihak Dinas Sosial dan Pemberdayaan Masyarakat dalam menentukan calon penerimah bantuan. Metode yang digunakan dalam penelitian ini adalah metode Multi-Objective Optimization on the basis of Ratio Analysis (MOORA). Metode MOORA digunakan untuk menentukan ranking dari 12 calon penerima BPNT berdasarkan 4 kriteria dari peraturan mentri yang terdiri dari usia, jumlah tanggungan, pekerjaan dan kondisi rumah. Hasil penelitian menunjukkan bahwa alternatif sepuluh (A10) mendapatkan nilai preferensi tertinggi sebesar 30.88 kemudian disusul oleh A5, A7, A1, dan A9 yang direkomendasikan sebagai penerima BPNT.
Co-Authors Abdul Haris Ade Fachreza Arman Adityo Permana Wibowo Alameka, Faza Ali Husni Anam, M Khairul Angriani, Husni Anindita Septiarini, Anindita Anjas, Andi Anton Prafanto Aqmarina Nur Alifiani Subingat Arba, Muhammad Hendra Arif Hidayat Asrul Abdullah Awang Harsa Kridalaksana Budiman, Edy Dedi Cahyadi Doni Kris Setiawan Eko Junirianto Eny Maria Eny Maria Fadlin, Feri Fahrul Agus Fandi Alief Al Akbar Firdaus, Muhammad Bambang Gst. Ayu Vida Mastrika Giri Gubtha Mahendra Putra Haeruddin, Haeruddin Hamada Zein Hans Christiaan Palondongan Haviluddin Haviluddin Herman Santoso Pakpahan Indah Fitri Astuti indrajit, Indrajit Irsyad, Akhmad izmy alwiah musdar Jimi, Jimi Jumriya Jumriya Lathifah Lathifah Leviany, Fonda Mahendra, Dicky Alvian Moh Safril Mohammad Yasin Muhammad Bambang Muhammad Bambang Firdaus Muhammad Habibi Muhammad Safar Muslimin B, Muslimin Nataniel Dengen Nurdiana, Dian Nurpadillah, Dinda Izmya Poetro, Bagus Satrio Waluyo Prafanto, Anton Puput Misliyana Puspitasari, Novianti Rahayu, Ervina Rayner Alfred Reza Wardhana Riyayatsyah, Riyayatsyah Rizky Ariesta Dwi RA Rosmasari Rosmasari Rosmasari Rosmasari Saputra, Riska Adi Setyadi, Hario Jati Setyadi, Hario Jati Sinra, A. Siswahyudianto Suci Ramadhani Suswanto Suswanto Syachmiral, Zidane Althaariq Syafaat Agung Prakoso Syifani, Sarah Tarigan, ⁠⁠Thomas Edyson Tejawati, Andi Ummul Hairah Vebi C.G, Sindi Wage Jason Waksito, Alan Zulfikar Wardhana, Reza Wati, Lisna Wati, Masna Willyardo Tampubolon Yuniar Rahayu Yunike Andrayani Zainal Arifin Zildjian, Septian Nuno