Garuda - Garba Rujukan Digital

SISTEM PAKAR DIAGNOSIS GANGGUAN SISTEM MUSKULOSKELETAL MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS ANDROID Kalengkongan, Dejan; Mandala, Rila; Masala, Ivana
Jurnal Ilmiah Realtech Vol 16 No 2 (2020)
Publisher : Fakultas Teknik, Universitas Katolik De La Salle Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52159/realtech.v16i2.137

Gangguan sistem muskuloskeletal adalah gangguan yang terjadi pada sistem tubuh sehingga mengakibatkan rasa sakit pada struktur tubuh tertentu. Minimnya pengetahuan tentang gangguan sistem muskuloskeletal adalah salah satu faktor yang menyebabkan gangguan sistem muskuloskeletal terlebih khusus osteoporosis dan osteoarthritis. Dengan menggunakanmetode penalaran certainty factor untuk menghitung nilai kepercayaan dari hasil diagnosis sistem, diharapkan bisa mendapatkan hasil yang baik. Selanjutnya, untuk pengembangansistem pakar ini juga menggunakan Expert System Development Life Cycle (ESDLC) dan kakas pemodelan Unified Modeling Language (UML) untuk menggambarkan prosesnya secaraterperinci, serta didukung oleh bahasa pemrograman yang java. Pengujian yang dilakukan, memberikan hasil bahwa sistem dapat menyediakan diagnosis nama penyakit, persentase dan solusi dari penyakit. Dari contoh 10 kasus menggunakan data acak, sistem memiliki tingkat akurasi 70%.

Data Partition and Communication On Parallel Heuristik Model Based on Clonal Selection Algorithm Ayi Purbasari; Iping Supriana Suwardi; Oerip Slamet Santoso; Rila Mandala
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 1: March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i1.728

Researchers conducted experiments on parallel algorithms, which are inspired by the clonal selection, called Clonal Selection Algorithm (CSA). This algorithm is a population-based heuristic solution. Course-grained parallelism model applied to improve the execution time. Inter-process communication overhead is addressed by adjusting the communication frequencies and size of data communicated. In this research, conducted experiments on six parallel computing models represent all possible partitions and communications. Experiments conducted using data of NP-Problem, Traveling Salesman Problem (TSP). The algorithm is implemented using the model of message passing libraries using MPJExpress. Experiments conducted in a cluster computation environment. Result shows the best parallelism model is achieved by partitioning the initial population data at the beginning of communication and the end of generation. Communication frequency can be up to per 1% of the population size generated. Using four dataset from TSPLib, this reseache shows effect of the communication frequency that increased the best cost, from 44.16% to 87.01% for berlin52.tsp; from 9.61% to 53.43% for kroA100.tsp, and from 12.22% to 17.18% for tsp225.tsp. With eight processors, using communication frequency will be reduced the execution time e.g 93.07%, 91.60%, 89.60%, 74.74% for burma14.tsp, berlin52.tsp, kroA100.tsp, and tsp225.tsp respectively. We conclude that frequency of communication greatly affects the execution time, and also the best cost. It improved execution time and best cost.

Meningkatkan Pemahaman Siswa SMA Don Bosco 3 Cikarang Mengenai Internet Sehat, Gamifikasi Dan Pergaulan Lawan Jenis di Era Digital Rosalina, Rosalina; Sahuri, Genta; Mandala, Rila; Fahmi, Hasanul
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 2 (2023): Agustus 2023 - Januari 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i2.1679

In today's digital age, high school students have to survive a dynamic and interconnected online environment. Promoting responsible digital citizenship and cultivating pleasant contacts, particularly those with the opposite sex, is critical as kids develop both intellectually and socially. The goal of this activity is to: (1) educate high school students about the responsible and ethical use of the internet, emphasizing the importance of online safety, privacy, and respect for others; (2) encourage students to develop healthy internet usage habits by providing them with the knowledge and tools to navigate the digital world responsibly; and (3) use gamification principles to engage and motivate high school students to adopt responsible online behavior. The activity was held at SMA Don Bosco 3 Cikarang and was attended by students as well as teachers.

Peningkatan Sarana Pembelajaran Daring Dengan Optimalisasi Penggunaan Video Editing Di SMPIT Annida Rosalina, Rosalina; Sahuri, Genta; Min An, Chong; Mandala, Rila
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 1 (2023): Februari-Juli 2023
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i1.846

The advantage of video media in education is that it can boost students' interest in the subject matter by allowing them to watch and hear. Teachers are expected to be able to develop engaging learning materials that encourage students to participate actively in their education. This PkM activity was completed at SMPIT Annida as an activity partner. The issues that were identified were 1) The teacher's ability to self-produce learning media, particularly in making learning videos, 2) The availability of free software that could be used to produce video learning media, but never utilized by teachers, and 3) the improvement process for teaching and learning that is effective, efficient, and more engaging. The focus of this activity was on the instructors and students.

Meningkatkan Pemahaman Siswa SMA Don Bosco 3 Cikarang Mengenai Internet Sehat, Gamifikasi Dan Pergaulan Lawan Jenis di Era Digital Rosalina, Rosalina; Sahuri, Genta; Mandala, Rila; Fahmi, Hasanul
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 2 (2023): Agustus 2023 - Januari 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i2.1679

In today's digital age, high school students have to survive a dynamic and interconnected online environment. Promoting responsible digital citizenship and cultivating pleasant contacts, particularly those with the opposite sex, is critical as kids develop both intellectually and socially. The goal of this activity is to: (1) educate high school students about the responsible and ethical use of the internet, emphasizing the importance of online safety, privacy, and respect for others; (2) encourage students to develop healthy internet usage habits by providing them with the knowledge and tools to navigate the digital world responsibly; and (3) use gamification principles to engage and motivate high school students to adopt responsible online behavior. The activity was held at SMA Don Bosco 3 Cikarang and was attended by students as well as teachers.

Enhancing Work Safety Systems Through Real-Time Speech Emotion Detection Classifier Using CNN Algorithm Handwi, Narendra Rahman; Mandala, Rila
Eduvest - Journal of Universal Studies Vol. 5 No. 7 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i7.51808

Speech emotion detection has emerged as a significant research area due to its potential applications in various domains. In work safety systems, the ability to accurately recognize emotions can provide vital information about the mental state of workers, which can be utilized to prevent work accidents and ensure a safer work environment. The objective of this study is to develop a speech emotion detection classifier using the CNN algorithm. The classifier aims to accurately classify emotions from speech signals, enabling real-time recognition of workers' emotional states. By achieving this objective, the study aims to contribute to the enhancement of work safety systems. The proposed methodology involves training a Convolutional Neural Network (CNN) model using a comprehensive dataset of labeled speech samples. The dataset will encompass various emotions, including happiness, sadness, anger, and fear. The CNN model will be trained to extract relevant features from speech signals and learn the patterns associated with different emotional states. Preprocessing techniques, such as audio segmentation, feature extraction, and data augmentation, will be employed to enhance the training process. The expected result of this study is a robust speech emotion detection classifier that can accurately classify emotions from speech signals. The classifier will be capable of real-time emotion recognition, providing immediate insights into workers' emotional states. By integrating this classifier into work safety systems, proactive measures can be taken to prevent work accidents based on workers' emotional conditions.

Customers Segmentation for Digital Signature Implementation: RFC Analysis Using KMeans Algorithms Rasyid, Abdul Aziz Al; Mandala, Rila
Eduvest - Journal of Universal Studies Vol. 5 No. 8 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i8.51004

To cluster institutions that utilize the digital signature service provided by BSrE, with over 200 million digital signature transactions involving 750 institutions, this study conducted an RFC (Recency, Frequency, Conversion Rate) analysis, which is an adaptation of the RFM (Recency, Frequency, Monetary) framework and the K-Means clustering algorithm. The purpose of this analysis is to find significant clusters that reflect user activity patterns. The study found four clusters by using the Elbow Method to determine the ideal number of clusters. It is expected that these findings will help BSrE optimize resource allocation, increase the adoption of digital signature services, and support Indonesia's digital transformation. The findings contribute to the literature on clustering techniques in the context of public services and provide actionable recommendations to improve government policy strategies.

Storychart: A Character Interaction Chart for Visualizing the Activities Flow Abidin, Zainal; Munir, Rinaldi; Akbar, Saiful; Mandala, Rila; Widyantoro, Dwi H.
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1608

Event-predicate-based storyline extraction results in a chronologically ordered activity journal. The extraction results contain complex human activities, so the activity journal requires a visualization model to describe actor interactions. This paper proposes a chart to visualize the activities' flow to describe the characters' interactions in an activity journal. This chart is called a storychart. Storycharts have an actor channel that can accept single entities or teams. The actor channel allows changing the type from single to a team or vice versa and moving members to other teams. The activity channel serves as a connector to accommodate interactions between actors. The activity channel provides a visual space for the elements of what, where, and when. Event predicates are the core of what. Therefore, the storychart visualizes the event predicate using glyphs to attract the reader’s attention. The main contribution of this paper is to introduce a team channel that can visualize the identity of team members and an activity channel that can visualize the details of events. We invited participants to discover the reader’s perception of the ease of team recognition and the integrity of the meaning of the narrative visualized by the storychart. Participants involved in the evaluation were filtered by literacy score. Evaluation of storychart reading showed that readers could easily distinguish teams from single actors, and storycharts could convey the story in the activity journal with little reduction in meaning.

Generating intelligent agent behaviors in multi-agent game AI using deep reinforcement learning algorithm Rosalina, Rosalina; Sengkey, Axel; Sahuri, Genta; Mandala, Rila
International Journal of Advances in Applied Sciences Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v12.i4.pp396-404

The utilization of games in training the reinforcement learning (RL) agent is to describe the complex and high-dimensional real-world data. By utilizing games, RL researchers will be able to evade high experimental costs in training an agent to do intelligence tasks. The objective of this research is to generate intelligent agent behaviors in multi-agent game artificial intelligence (AI) using deep reinforcement learning (DRL) algorithm. A basic RL algorithm called deep Q network is chosen to be implemented. The agent is trained by the environment's raw pixel images and the action list information. The experiments conducted by using this algorithm show the agent’s decision-making ability in choosing a favorable action. In the default setting for the algorithm, the training is set into 1 epoch and 0.0025 learning rate. The number of training iterations is set to one as the training function will be repeatedly called for every 4-timestep. However, the author also experimented with two different scenarios in training the agent and compared the results. The experimental findings demonstrate that our agents learn correctly and successfully while actively participating in the game in real time. Additionally, our agent can quickly adjust against a different enemy on a varied map because of the observed knowledge from prior training.

Title

Found 9 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 9 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 9 Documents
Search