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All Journal International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal technoscientia Journal of ICT Research and Applications Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization JURTEKSI Jurnal Ilmiah Realtech JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Sains Indonesia Jurnal Pengabdian Masyarakat Nusantara IT For Society : Journal of Information Technology Eduvest - Journal of Universal Studies
Rila Mandala
School Of Electrical Engineering And Informatics, Bandung Institute Of Technology
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Other

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Penerapan Convolutional Neural Network (CNN) dan Euclidean Distance Matrices (EDM) untuk Mengurangi False Positive pada Pengenalan Aktifitas Finger Point Call Rila Mandala; Mohammad Deny Safari
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 1 (2023): Volume 9 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i1.61716

Abstract

Aktifitas finger point call (FPC) yang mengharuskan operator menunjuk (finger point) dan mengucapkan (call) sebelum menjalankan suatu proses, merupakan aktifitas yang umum diterapkan di industri manufaktur khususnya pada perusahaan Jepang. FPC terbukti efektif mengurangi human error, tetapi operator sering tidak konsisten dalam menerapkan FPC sehingga perlu sistem untuk mendeteksi aktifitas FPC sudah dilakukan dengan baik dan benar. Salah satu metode pengenalan aktifitas (activity recognition) yaitu menggunakan convolutional neural networks (CNN) untuk mengklasifikasikan aktifitas manusia. Namun, aktifitas FPC dinyatakan valid atau invalid setelah memastikan operator menunjuk dengan benar ke arah objek dan menunjuk ke arah referensi, sehingga harus dilakukan analisis pada beberapa frame video. Apabila hanya menggunakan CNN saja, akan menyebabkan tingkat false positive menjadi tinggi, karena CNN akan langsung melakukan analisis pada 1 frame video. Tujuan penelitian ini yaitu mengurangi false positive ketika mendeteksi aktifitas FPC dengan cara melakukan anlaisis lebih lanjut pada hasil deteksi menggunakan euclidean distance matrices (EDM). Hasil penelitian menunjukkan pada percobaan yang diperagakan oleh 1 orang: false positive berkurang hingga 100%, nilai Precision sebesar 1, dan nilai recall sebesar 0,96. Hasil ketika diperagakan oleh 10 orang: nilai Precision sebesar 0,9, dan nilai recall sebesar 0,9. lebih baik dibandingkan YOLOv7 versi original yang nilai Precisionnya hanya sebesar 0,5.
ANDROID-BASED MAID RECOMMENDATION Muhammad Ihsan; Rila Mandala
IT for Society Vol 6, No 2 (2021)
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/itfs.v6i2.4527

Abstract

Maidsareanimportantpartofthehousehold, in this case problems arise related to peoplewhohavehighactivitiessuchascareerwomen,including housewives, or other families. The dailyroutine which is quite dense makes them unable to doall household chores by themselves. Due to his busy lifein order to complete household chores, a householdassistant is needed. One solution to the above problemsis the availability of an Android-based application formaid recommendations. This application was createdto make it easy for consumers to find a maid quicklyand easily. This application can display various serviceproviders with complete and detailed information tomake it easier for consumers to choose the servicesneeded.
SISTEM PAKAR DIAGNOSIS GANGGUAN SISTEM MUSKULOSKELETAL MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS ANDROID Dejan Kalengkongan; Rila Mandala; Ivana Masala
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.v16i2.64

Abstract

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 menggunakan metode penalaran certainty factor untuk menghitung nilai kepercayaan dari hasil diagnosis sistem, diharapkan bisa mendapatkan hasil yang baik. Selanjutnya, untuk pengembangan sistem pakar ini juga menggunakan Expert System Development Life Cycle (ESDLC) dan kakas pemodelan Unified Modeling Language (UML) untuk menggambarkan prosesnya secara terperinci, 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%.
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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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.
Co-Authors Abdurrahman - Agus Priyanto Agus Susanto Ahmad Fajri Akbar, Saiful Alfonso Mario Tumewu Andreas Prasetia Antonius Sigit Arfan As’Sidiq Arry Akhmad Arman Audy Aldrin Kenap Ayi Purbasari Bambang Riyanto Trilaksono Bambang Riyanto Trilaksono Chong Min An Debby Paseru Dejan Kalengkongan Deny Haryadi Dewi Marini Umi Atmaja Dwi H. Widyantoro Erry Koryanti Fahmi, Hasanul Handwi, Narendra Rahman Harlili Harlili Iping Supriana Suwardi Irfan Nasrullah Ivana Masala Kalengkongan, Dejan Masala, Ivana Michael Aleng Min An, Chong Mohammad Deny Safari Muhammad Erwin Ashari Hariyono Muhammad Ihsan Oerip Slamet Santoso Rajesri Govindaraju Rasyid, Abdul Aziz Al Riady, Sasmitoh Rahmad Rinaldi Munir Rosalina Rosalina Sahuri, Genta Sahuri Sengkey, Axel Shita Dwi Ranti Tjong Wan Sen Zainal Abidin