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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) SemanTIK : Teknik Informasi JURNAL INTEGRASI Indonesian Journal of Artificial Intelligence and Data Mining JURNAL PENGABDI Journal of Applied Data Sciences Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen JAIA - Journal of Artificial Intelligence and Applications J-Icon : Jurnal Komputer dan Informatika The Indonesian Journal of Computer Science
Firdaus, Muhammad Bambang
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Penerapan Metode Finite State Machine Pada Mobile Game Side Scrolling “Utan Adventure” Firdaus, Muhammad Bambang; Arba, Muhammad Hendra; Tejawati, Andi; Taruk, Medi; Irsyad, Akhmad; Anam, M Khairul
SemanTIK : Teknik Informasi Vol 10, No 1 (2024):
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v10i1.47474

Abstract

Game ialah satu dari sekian sarana untuk menghilangkan kebosanan, dengan kemajuan teknologi smartphone saat ini, banyak game dengan platform mobile berkembang cepat. Android didukung oleh terjangkaunya smartphone android dipasaran sehingga lebih mudah diakses oleh anak-anak, remaja dan orang tua. Pengembangan game side-scrolling “Utan Adventure” ini untuk membangun game yang dapat mengasah otak dan kreativitas pemain serta untuk mempromosikan budaya lokal di Kalimantan. Game side-scrolling “Utan Adventure” ini adalah game dengan genre action adventure lebih tepatnya dengan subgenre side-scrolling dirancang menggunakan unity game engine dan menggunakan metode Finite State Machine yang diterapkan pada Player, Enemy dan mekanisme level. Finite State Machine ialah suatu metode untuk perancangan sistem kontrol yang memperlihatkan prinsip kerja sistem dengan fokus pada tiga hal penting : state (keadaan), event (kejadian), dan action (aksi). Berdasarkan hasil pengujian penelitian ini terdapat pengujian gameplay, pengujian artificial intelligence, pengujian kontrol pemain, dan pengujian mekanisme level. Hasil akhir dari game ini adalah game side-scrolling berbasis platform android, dengan fitur tambahan berupa toko, upgrade, leaderboard, dan Non-Playable Character (NPC) yang dapat patroli, mencari, dan menyerang pemain di setiap level. Kata kunci; Mobile Game, Finite State Machine, Non-Playable Character
Preparing Retro Arcade Fighting Game Asset Design Arifin, Zainal; Waksito, Alan Zulfikar; Firdaus, Muhammad Bambang; Puspitasari, Novianti
JAIA - Journal of Artificial Intelligence and Applications Vol. 3 No. 2 (2023): JAIA - Journal of Artificial Intelligence and Applications
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/jaia.v3i2.1062

Abstract

Games are increasingly popular in Indonesia because of the many things that make them exciting, such as esports. The Fighting Game genre is one that contains a fight between two characters in a place or arena with the aim of depleting the opponent's HP (health points). Fighting Games use 2-dimensional and/or 3-dimensional graphics where players play characters who can punch, jump or squat when fighting characters. other. In designing video game assets, researchers used the GDLC (Game Development Life Cycle) methodology so that this research proceeded systematically and focused on the design of game asset components. In designing a video game there are many elements, in this research the author focuses more on the control assets of the Combo Hit System on a game character called Brawl Tale.
VIRTUAL REALITY MUSEUM MULAWARMAN BERBASIS VIDEO 360° Firdaus, Muhammad Bambang; Tejawati, Andi; Budiman, Edy; Wahyudianto, Mochamad Rizky; Anam, M Khairul
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 11 No 2 (2021): September 2021
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (374.85 KB) | DOI: 10.33020/saintekom.v11i2.222

Abstract

Recent years, visitors have decreased in the Mulawarman Museum, located in Tenggarong Kutai Kartanegara. A small number of visitors to the Mulawarmen Museum could have been due to a lack of promotions. The purpose of this study is to develop and present the Mulawarman Museum as a promotional medium a Visual Video Application for the Mulawarman Tenggarong Kutai Kartanegara. A combination of VR and Android mobile technology, which is owned by most levels of society, enables application users to view the videos in 360 degrees, can serve this research purpose. The aim of the research is This research. The test results from Android devices show that the application is smooth to run and suitable for use in versions of Android 5.1 and later with a screen-like aspect ratio of 16:9 and 18:9. All of the questions in the questionnaire received agree and strongly agree between 85% and 100%.
Early Stopping on CNN-LSTM Development to Improve Classification Performance Anam, M. Khairul; Defit, Sarjon; Haviluddin, Haviluddin; Efrizoni, Lusiana; Firdaus, Muhammad Bambang
Journal of Applied Data Sciences Vol 5, No 3: SEPTEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i3.312

Abstract

Currently, CNN-LSTM has been widely developed through changes in its architecture and other modifications to improve the performance of this hybrid model. However, some studies pay less attention to overfitting, even though overfitting must be prevented as it can provide good accuracy initially but leads to classification errors when new data is added. Therefore, extra prevention measures are necessary to avoid overfitting. This research uses dropout with early stopping to prevent overfitting. The dataset used for testing is sourced from Twitter; this research also develops architectures using activation functions within each architecture. The developed architecture consists of CNN, MaxPooling1D, Dropout, LSTM, Dense, Dropout, Dense, and SoftMax as the output. Architecture A uses default activations such as ReLU for CNN and Tanh for LSTM. In Architecture B, all activations are replaced by Tanh, and in Architecture C, they are entirely replaced by ReLU. This research also performed hyperparameter tuning such as the number of layers, batch size, and learning rate. This study found that dropout and early stopping can increase accuracy to 85% and prevent overfitting. The best architecture entirely uses ReLU activation as it demonstrates advantages in computational efficiency, convergence speed, the ability to capture relevant patterns, and resistance to noise.
Rancang Bangun Aplikasi Mobile Crowdfunding untuk Donasi Sosial Kota Samarinda Firdaus, Muhammad Bambang; Efendy, Muhammad Yusuf; Prafanto, Anton; Rosmasari, Rosmasari; Suandi, Fadli; Lathifah, Lathifah
JURNAL INTEGRASI Vol 16 No 1 (2024): Jurnal Integrasi - April 2024
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v16i1.5083

Abstract

Donations are physical gifts made by individuals or legal entities that are given voluntarily and without imbalance. Advances in internet technology are now used to raise social and humanitarian funds and help victims of natural disasters. Crowdfunding takes advantage of this situation, because it uses the internet to generate funds from internet and social media users. This research will look at how to create an Android-based crowdfunding contribution application management system for the Samarinda City area. This study intends to use the Rational Unified Process technique to create an Android-based fundraising application for flood victims, fires of religious buildings, and social institutions in Samarinda City. The main goal is to create software that fits the needs of users. It not only meets system specifications and is usable but also validates whether the system is acceptable. In accordance with the objectives of this study, researchers succeeded in building a donation-raising application for disaster victims, and based on the results of functional testing with the Black Box, the Samarinda City Donation Application has an attractive appearance, the menus available in the application are easy to understand, and the Samarinda City Donation Application this is good enough.
Comparison Analysis of HSV Method, CNN Algorithm, and SVM Algorithm in Detecting the Ripeness of Mangosteen Fruit Images Anam, M. Khairul; Sumijan, Sumijan; Karfindo, Karfindo; Firdaus, Muhammad Bambang
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.29739

Abstract

Mangosteen contains a substance known as Xanthone, a phytochemical compound with the distinctive red component in mangosteen that is known for its properties as an anticancer, antibacterial, and anti-inflammatory agent. Additionally, Xanthone has the potential to strengthen the immune system, promote overall health, support mental well-being, maintain microbial balance in the body, and improve joint flexibility. The mangosteen fruit is consumable when it reaches maturity, displaying a dark purplish-black color. Besides the edible part of the fruit, the peel also possesses remarkable medicinal properties. To detect whether the fruit is ripe or not, this research employs image processing techniques. The study utilizes the HSV (Hue, Saturation, and value) color space method, CNN (Convolutional Neural Network) algorithm, and SVM (Support Vector Machine) algorithm. These methods and algorithms are chosen for their relatively high accuracy levels. The dataset used in this research is obtained from mangosteen datasets available on Kaggle. The results of this study indicate that the HSV method achieved an accuracy of 86.6%, SVM achieved an accuracy of 87%, and CNN achieved an accuracy of 91.25%. From the achieved accuracies, it is evident that the CNN algorithm yields higher accuracy compared to the others.
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.
Improved Performance of Hybrid GRU-BiLSTM for Detection Emotion on Twitter Dataset Anam, M. Khairul; Munawir, Munawir; Efrizoni, Lusiana; Fadillah, Nurul; Agustin, Wirta; Syahputra, Irwanda; Lestari, Tri Putri; Firdaus, Muhammad Bambang; Lathifah, Lathifah; Sari, Atalya Kurnia
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.459

Abstract

This study addresses emotion detection challenges in tweets, focusing on contextual understanding and class imbalance. A novel hybrid deep learning architecture combining GRU-BiLSTM with SMOTE is proposed to enhance classification performance on an Israel-Palestine conflict dataset. The dataset contains 40,000 tweets labeled with six emotions: anger, disgust, fear, joy, sadness, and surprise. SMOTE effectively balances the dataset, improving model fairness in detecting minority classes. Experimental results show that the GRU-BiLSTM hybrid with an 80:20 data split achieves the highest accuracy of 89%, surpassing BiLSTM alone, which obtained 88%, and other state-of-the-art models. Notably, the proposed model delivers significant improvement in detecting the emotion of joy (recall: 0.87, F1-score: 0.86). In contrast, the surprise category remains challenging (recall: 0.24). Compared to existing research, this study highlights the effectiveness of combining SMOTE and hybrid GRU-BiLSTM, outperforming models such as CNN, GRU, and LSTM on similar datasets. The incorporation of GloVe embeddings enhances contextual word representations, enabling nuanced emotion detection even in sarcastic or ambiguous texts. The novelty lies in addressing class imbalance systematically with SMOTE and leveraging GRU-BiLSTM's complementary strengths, yielding superior performance metrics. This approach contributes to advancing emotion detection tasks, especially in conflict-related social media data, by offering a robust, context-sensitive, and balanced classification method.
Enhancing the Performance of Machine Learning Algorithm for Intent Sentiment Analysis on Village Fund Topic Anam, M. Khairul; Putra, Pandu Pratama; Malik, Rio Andika; Karfindo, Karfindo; Putra, Teri Ade; Elva, Yesri; Mahessya, Raja Ayu; Firdaus, Muhammad Bambang; Ikhsan, Ikhsan; Gunawan, Chichi Rizka
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.637

Abstract

This study explores the implementation of Intent Sentiment Analysis on Twitter data related to the Village Fund program, leveraging Multinomial Naïve Bayes (MNB) and enhancing it with Synthetic Minority Over-sampling Technique (SMOTE) and XGBoost (XGB). The analysis categorizes tweets into six labels: Optimistic, Pessimistic, Advice, Satire, Appreciation, and No Intent. Initially, the MNB model achieved an accuracy of 67% on a 90:10 data split. By applying SMOTE, accuracy improved by 12%, reaching 89%. However, adding Chi-Square feature selection did not increase accuracy further. Incorporating XGB into the MNB+SMOTE model led to a 6% improvement, achieving a final accuracy of 95%. Comprehensive model evaluation revealed that the MNB+SMOTE+XGB model achieved 96% accuracy, 96% precision, 96% recall, and a 96% F1-score, with an AUC of 99%, categorizing it as excellent. These findings demonstrate that the combination of SMOTE for addressing class imbalance and XGBoost for boosting performance significantly enhances the MNB model's classification capabilities. The novelty lies in the integration of these techniques to improve intent sentiment classification for public opinion analysis on the Village Fund program. The results indicate that the majority of tweets labeled as "No Intent" reflect a lack of specific sentiment or actionable intent, providing valuable insights into public perception of the program.
PENGAMBILAN KEPUTUSAN PADA PENGAJUAN SISWA-SISWI KE BEASISWA PIP MENGGUNAKAN METODE AHP DAN TOPSIS Halim, Muhammad Yusuf; Firdaus, Muhammad Bambang
J-Icon : Jurnal Komputer dan Informatika Vol 13 No 1 (2025): March 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v13i1.16792

Abstract

Education is an effort to help individuals achieve their maximum potential. In accordance with Law Number 20 of 2003 concerning the National Education System, basic education is the earliest level in the national education system. State Elementary School (SD) 018 Loa Janan is an elementary school located in Tani Bahagia Hamlet, Batuah Village, Loa Janan District, Kutai Kartanegara Regency, East Kalimantan Province. To support the welfare of its students, the school enrolls its students in various scholarship programs, including the Smart Indonesia Program (PIP). However, the absence of clear criteria causes difficulties for schools in determining which students are eligible to apply for PIP scholarships. Therefore, a Decision Support System (SPK) will be implemented to assist schools in the selection process of students who will be proposed for PIP scholarships. This research aims to achieve this. Decisions will be taken using a combination of the Analytical Hierarchy Process (AHP) method to calculate criteria weights and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to rank alternatives. There are five criteria and 67 alternatives. Criteria weights will be calculated using the AHP method, while alternative ranking will be carried out using the TOPSIS method. The calculation results show that a student named Elbara Mukti received first place with a preference value of 0.8589. Students with the highest preference scores will be proposed by the school to receive a PIP scholarship
Co-Authors Agustin Anam, M Khairul Anam, M. Khairul Arba, Muhammad Hendra Budiman, Edy Efendy, Muhammad Yusuf Efrizoni, Lusiana Elva, Yesri Gunawan, Chichi Rizka Halim, Muhammad Yusuf Hamdani Hamdani Haviluddin Haviluddin Ikhsan Ikhsan Irsyad, Akhmad Irwanda Syahputra Karfindo, Karfindo Lathifah, Lathifah Lusiana Mahessya, Raja Ayu Malik, Rio Andika Munawir Munawir Nupa, Joy Disanto Nurul fadillah, Nurul Pandu Pratama Putra, Pandu Pratama Prafanto, Anton Puspitasari, Novianti Rosmasari Rosmasari, Rosmasari Saragih, Muhammad Nabil Sari, Atalya Kurnia Sarjon Defit Setiawan, Maulana Agus Suandi, Fadli Sumijan Sumijan Taruk, Medi Tejawati, Andi Teri Ade Putra Tri Putri Lestari, Tri Putri Triyani Arita Fitri Wahyudianto, Mochamad Rizky Waksito, Alan Zulfikar Wati, Masna Wirta Agustin Zainal Arifin