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All Journal The Journal of Experimental Life Sciences (JELS) International Journal Science and Technology (IJST) Seminar Nasional Produk Terapan Unggulan Vokasi Frontier Advances in Applied Science and Engineering
Motulo, Firmansyah Reskal
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Pengembangan Asesmen Kinerja Berbasis STEM Untuk Menilai Kemampuan Pemecahan Masalah Matematika Mahasiswa Pada Pembelajaran Matematika Teknik Lambonan, Oldi Malfri; Motulo, Firmansyah Reskal; Runtuwene, Steven Johny
Prosiding Seminar Nasional Produk Terapan Unggulan Vokasi Vol 2 No 1 (2023): Prosiding Seminar Nasional Produk Terapan Unggulan Vokasi Politeknik Negeri Manad
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat Politeknik Negeri Manado

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

Abstract

Sistem pembelajaran sangat penting untuk direvitalisasi karena melalui sistem pembelajaran yang efektif dan efisien, akan diperoleh lulusan perguruan tinggi atau calon tenaga kerja yang berkualitas, produktif, dan mampu bersaing. Dalam penelitian ini merujuk pada salah satu bagian dalam sistem pembelajaran berupa sebuah perangkat pembelajaran yaitu asesmen yang dapat menilai secara utuh pemecahan masalah dalam pembelajaran matematika teknik. Penelitian ini bertujuan untuk mengembangkan instrumen yang digunakan untuk menilai kinerja kemampuan pemecahan masalah mahasiswa pada pembelajaran matematika teknik yang memenuhi kriteria valid dan reliabel dan menerapkan asesmen kinerja berbasis STEM (Science, Technology, Engineering, and Mathematics) untuk menilai kemampuan pemecahan masalah matematika mahasiswa. Penelitian ini termasuk penelitian dan pengembangan yang mengacu pada dua model yakni 4D: define, design , develop, dan disseminate dan Oriondo & Antoni. Desain pengembangan dikelompokkan atas enam prosedur yakni: (a) eksplorasi, (b) pengembangan, (c) pengembangan prototype, (d) uji coba produk dan revisi, (e) uji validitas teoritis dan empirik, dan (f) penerapan produk. Hasil penelitian menunjukkan asesmen kinerja yang dikembangkan valid dan reliabel sebagai instrument penilaian kinerja berbasis STEM. Asesmen yang dikembangkan adalah asesmen untuk pemecahan masalah. Berdasarkan hasil penelitian diketahui kemampuan pemecahan masalah mahasiswa tergolong rendah
Multi-Stage Computer Vision Framework with Ensemble Learning for Real-Time Glass Packaging Defect Detection in Industrial Applications Jonah Alfred Mekel; Rick Resa Wahani; Motulo, Firmansyah Reskal; Alfred Noufie Mekel; Tineke Saroinsong; Tammy Tinny V. Pangow; Jerry Heisye Purnama; Jedithjah Naapia Tamedi Papia
Frontier Advances in Applied Science and Engineering Vol. 3 No. 2 (2025)
Publisher : Tinta Emas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59535/faase.v3i2.572

Abstract

Transparent glass packaging inspection presents significant challenges for automated quality control systems due to optical complexities including reflections, refractions, and low-contrast defect patterns. This research develops a comprehensive multi-stage computer vision framework integrating specialized algorithmic modules with ensemble machine learning for real-time defect detection in industrial glass packaging lines. The framework implements four specialized detection stages: (1) meniscus-corrected liquid level measurement using dual-camera validation and polynomial surface fitting, (2) seal integrity assessment through Circular Hough Transform combined with geometric, texture, and color feature extraction, (3) lid positioning evaluation via calibrated geometric centroid analysis with tolerance-based classification, and (4) multi-method contamination detection integrating color aberration analysis, histogram-based particle detection, and morphological operations. The system employs an ensemble classification architecture combining modified MobileNetV2 convolutional neural network with Random Forest classifier, optimized for edge computing deployment. Industrial validation at PT AQUWAR Bintang Semesta demonstrated 91.6% overall detection accuracy with 347 milliseconds average processing time per container across 2,847 test samples spanning multiple defect categories. The modular framework architecture enables independent optimization of detection stages while maintaining real-time processing capabilities, providing a robust foundation for transparent packaging quality control in high-volume manufacturing environments.
Computational Analysis of Bioethanol Production from Arenga Pinnata Sap using Rice Husk Biomass Heating: Statistical Modeling of Fermentation Time Effects on Alcohol Yield Saroinsong, Tineke; Mekel, Alfred Noufie; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2348

Abstract

This study presents a comprehensive computational analysis of sustainable bioethanol production from Arenga pinnata sap using rice husk biomass as a renewable heating source. The research investigated fermentation time effects on alcohol yield through systematic experimentation and Python-based statistical modeling across four conditions: fresh sap, 1-day, 3-day, and 18-day fermentation periods. Distillation processes utilized 8.5 kg rice husk biomass at 80°C for 1.42 hours, producing 600 ml bioethanol per batch. Statistical analysis revealed a highly significant inverse correlation (r = -0.965, p < 0.05) between fermentation duration and alcohol content. Fresh palm sap yielded optimal alcohol concentration of 39.67 ± 7.76%, while 18-day fermentation reduced yield to 2.50 ± 2.50%, representing 93.7% decrease. The exponential decay model (R² = 0.984) demonstrated superior predictive accuracy compared to linear regression. The integrated system achieved 70.6 ml bioethanol per kg rice husk with positive energy balance (1.23 MJ output per MJ input), confirming commercial viability for rural renewable energy applications. This computational framework establishes optimal processing parameters for agricultural waste-powered biofuel systems, supporting circular economy principles and rural energy independence through effective biomass utilization in tropical regions.
Computer Vision-Based Automated Waste Sorting System for Plastic and Organic Waste Classification Using Color and Shape Features Rick Resa Wahani; Michael Edward G. Kimbal; Deko Trio Desembara; Leonardo Frando Pasla; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2384

Abstract

The increasing volume of municipal solid waste demands low-cost, real-time sorting solutions to improve recycling efficiency and reduce landfill burden. Objective: This study develops and evaluates a low-cost, real-time computer vision system to classify plastic waste and organic leaf waste for automated sorting. Methodology: The system uses a standard RGB camera (640×480, 30 fps) and OpenCV-based processing, including Gaussian blurring, HSV color-space conversion, morphological operations, contour detection, and geometric feature extraction (circularity, solidity, aspect ratio, and extent). Classification is performed using a hierarchical rule-based logic that combines HSV color masks with a proposed overlap ratio to quantify the spatial correspondence between object contours and leaf-color regions. Findings: Experimental testing under controlled illumination (500–1000 lux) achieved 89% overall accuracy with an average processing time of 45 ms/frame and an operational throughput of approximately 7 objects/min. The system correctly classified 8 plastic items and 7 leaf samples in the initial test set. Implications: The proposed approach supports practical deployment in small-scale or resource-constrained waste management facilities by enabling real-time sorting without large, labeled datasets or GPU hardware. Originality: This work introduces an interpretable hybrid decision framework that integrates a mask-based overlap ratio with multiple geometric shape descriptors, improving discrimination between plastic and leaf waste while maintaining computational efficiency.
Intelligent Robotic Arm Control System with Adaptive Learning Algorithm Based on Motion Pattern Recognition Excellsdeo Ndahawali; Jonah Mekel; Jaqlin Tamaka; GheridsDipipi, GheridsDipipi; Rick Resa Wahani; Michael Edward G. Kimbal; Deko Trio Desembara; Motulo, Firmansyah Reskal
International Journal Science and Technology Vol. 4 No. 3 (2025): November: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v4i3.2386

Abstract

Robotic-arm deployment beyond specialized facilities is often constrained by time-intensive programming and the need for expert operators, while gesture-based control can lose reliability due to sensor noise, drift, and inter-user variability. Objective: This study develops a low-cost, embedded robotic arm control system that learns from human demonstrations. Methodology: A quantitative experimental prototyping approach was used by building a 3-DOF robotic arm with an MPU6050 IMU and an Arduino Mega 2560. Multi-user gesture trials were collected, and system performance was analyzed through end-to-end evaluation of recognition accuracy, response time, learning efficiency, and motion replication error. Findings: The system achieved 85% gesture recognition accuracy, a 195 ms average response time, and a 4.2° mean absolute joint-angle error (SD = 2.1°), reaching target performance within ≤5 adaptation iterations while operating within microcontroller memory limits. Implications: The results support the feasibility of real-time, gesture-driven robotic arm control on resource-constrained embedded hardware for educational and light industrial use, enabling faster setup and user personalization without extensive pre-training. Originality: This work integrates embedded motion pattern recognition with error-based adaptive learning in a low-cost 3-DOF platform and reports consolidated end-to-end evidence (accuracy–latency–learning convergence–replication fidelity) to demonstrate practical feasibility.
Design and Development of a Press Machine for Biobriquettes Made from Patchouli Distillation Waste and Rice Husk Tandiapa, Vincen; Pantow, Rifan; Simanjuntak, Simon; Manoppo, Friani; Raphaela, Josephine; Saroinsong, Tineke; Mekel, Alfred Noufie; Motulo, Firmansyah Reskal; Muaja, Estrela Bellia
International Journal Science and Technology Vol. 5 No. 1 (2026): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v5i1.2378

Abstract

The increasing availability of biomass residues such as patchouli distillation waste and rice husk presents an opportunity for renewable energy production; however, their utilization remains limited due to the lack of efficient and safe small-scale processing equipment. Developing practical briquette production systems is therefore essential to support sustainable energy use at household and MSME levels. Objective: This study aims to develop and evaluate a hydraulic briquette press capable of producing biomass briquettes from patchouli distillation waste and rice husk while enhancing operational safety, maintenance efficiency, and usability for small-scale production. Method: The research employed an engineering research-and-development approach involving machine design, prototype fabrication, and functional testing. Data were collected through technical observation and performance monitoring of pressing cycles, followed by descriptive analysis to evaluate operational functionality, safety response, and cleaning effectiveness. Findings: The developed press integrates a pressure-sensor-based safety system and an automatic pneumatic cleaning mechanism. The machine is capable of forming six briquettes per cycle at an operating pressure of approximately 50 kg/cm². The integrated systems functioned as intended, supporting stable operation, reducing manual cleaning needs, and improving operational safety. Implications: The proposed design demonstrates potential for improving briquette production efficiency and reliability in small-scale applications. By reducing downtime and enhancing safety, the system can support wider adoption of biomass briquette technology and contribute to community-level renewable energy utilization. Originality/Value: This study offers a novel integration of hydraulic pressing, automatic pneumatic cleaning, and pressure-based safety monitoring within a single multi-cavity briquette press, providing a practical and user-oriented solution for transforming agricultural waste into renewable energy products.
Optimal Control of Tumor Growth Model with Dendritic Cells as Immunotherapy Motulo, Firmansyah Reskal; Trisilowati, Trisilowati; Rouf, Abdul
The Journal of Experimental Life Science Vol. 8 No. 2 (2018)
Publisher : Graduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1053.56 KB) | DOI: 10.21776/ub.jels.2018.008.02.06

Abstract

In this paper, optimal control of tumor growth model with dendritic cells as immunotherapy is provided. The model equation can be expressed into a nonlinear differential equation system consisting of four compartments namely, tumor cells, CTL cells, helper T cells, and dendritic cells. Dendritic cells as immunotherapy are injected to the body at time t. The aim of this optimal control is to minimize the tumor cells density as well as the cost of dendritic cells to be administered to the body.Optimal control problem is carried out based on Pontryagin's maximum principle and numerical simulation is solved by using Forward-Backward Sweep methods. Simulation results show that control strategy shrinks tumor cells density which is shown by tumor cells density graph that monotonically decreases after applying dendritic cells as immunotherapy.Keywords: immunotherapy, optimal control, Tumor cell.
Co-Authors Abdul Rouf Alfred Noufie Mekel Deko Trio Desembara Excellsdeo Ndahawali GheridsDipipi, GheridsDipipi Jaqlin Tamaka Jedithjah Naapia Tamedi Papia Jerry Heisye Purnama Jonah Alfred Mekel Jonah Mekel Leonardo Frando Pasla Manoppo, Friani Mekel, Alfred Noufie Michael Edward G. Kimbal Muaja, Estrela Bellia Oldi Malfri Lambonan Pantow, Rifan Raphaela, Josephine Rick Resa Wahani Runtuwene, Steven Johny Saroinsong, Tineke Simanjuntak, Simon Tammy Tinny V. Pangow Tandiapa, Vincen Tineke Saroinsong Trisilowati Trisilowati, Trisilowati