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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JURNAL ELEKTRO JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) SABDAMAS Jurnal Ilmiah Teknik Elektro International Journal of Engineering Continuity ROUTERS: Jurnal Sistem dan Teknologi Informasi Jurnal Pengabdian Masyarakat Charitas Cylinder : Jurnal Ilmiah Teknik Mesin Jurnal Serina Abdimas
Catherine Olivia Sereati
Program Studi Magister Teknik Elektro, Fakultas Biosains, Teknologi Dan Inovasi, Universitas Katolik Indonesia Atma Jaya,
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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PEMBUATAN INKUBATOR TUKIK UNTUK KONSERVASI PENYU PANTAI PANGUMBAHAN UJUNG GENTENG Octaviani, Sandra; Ghozali, Theresia; Basuki, Widodo Widjaja; Wijayanti, Linda; Sereati, Catherine Olivia
Jurnal Serina Abdimas Vol 1 No 2 (2023): Jurnal Serina Abdimas
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jsa.v1i2.26110

Abstract

Turtles are protected animals because of the emergency of extinction by a lot of conservation of turtle cultivation to increase its population. It is unavoidable if there are still many population reductions from turtles, one of which comes from the low survival rate of baby turtles called hatchlings. The process of laying eggs for female turtles requires warm beach sand to cover their eggs and this occurs at night when the moon is dark. After about two months the eggs will hatch, and the hatchlings usually go straight to the sea. There are many disturbances experienced by hatchlings to get to the sea such as being kidnapped, being preyed upon, and not even going to the sea. Improvements in conservation facilities are made to provide an incubator which are always kept warm by being provided with a bulb as a heater, a thermostat as a temperature regulator and a humidifier as a humidity regulator. After hatching the eggs are placed in a replacement pond which was built as a hatchling pond for temporary shelter for the newly hatched hatchlings, and the pond is placed in a cleaned hatchery room with the roof replaced with a mild steel frame The result of the upgrade from this facility is that hatchling success has increased to 91%, and newly hatched hatchlings can be closely monitored until they are ready to be released into the sea. It is hoped that the turtle population in the world can be maintained so that our children and grandchildren will be able to see the turtles directly. Penyu merupakan hewan yang dilindungi karena darurat akan kepunahannya. Sudah banyak konservasi budidaya penyu untuk meningkatkan populasi penyu. Tetapi tidak dapat dihindari jika masih banyak pengurangan populasi dari penyu, yang salah satunya berasal dari rendahnya tingkat keberhasilan hidup dari bayi penyu yang disebut tukik. Proses bertelur penyu betina memerlukan pasir pantai yang hangat untuk menutupi telur-telurnya dan hal ini terladi pada malam hari saat bulan gelap. Setelah sekitar dua bulan telur akan menetas dan tukik biasanya langsung berjalan menuju ke laut. Banyak gangguan yang dialami oleh tukik untuk bisa sampai ke laut seperti diculik, dimangsa, dan bahkan tidak menuju ke laut. Peningkatan fasilitas konservasi yang dibuat menyediakan ruang inkubator yang senantiasa dipertahankan hangat dengan diberi bohlam sebagai penghangat, thermostat sebagai pengatur suhu dan humidifier sebagai pengatut kelembaban. Setelah telur menetas ditempatkan di kolam pengganti yang dibangun sebagai kolam tukik untuk penampungan sementara bagi tukik yang baru menetas, dan kolam diletakkan dalam ruang tukik yang sudah dibersihkan dengan atap diganti dengan rangka baja ringan. Hasil dari peningkatan dari fasilitas ini adalah keberhasilan penetasan tukik meningkat menjadi 91 %, dan tukik yang baru menetas dapat diawasi dengan seksama sampai siap dilepas ke laut. Diharapkan populasi penyu yang ada di dunia dapat terjaga hingga anak cucu kita nanti dapat melihat langsung penyu yang ada.
Implementation and Analysis of Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for Irrigation Abdurohman Abdurohman; Marsul Siregar; Catherine Olivia Sereati; Silviana Windasari; MM. Lanny W. Pandjaitan
International Journal of Engineering Continuity Vol. 4 No. 1 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i1.399

Abstract

Efficient water management in agriculture is crucial due to dynamic environmental conditions and increasing resource scarcity. Fuzzy Inference System (FIS) is widely applied in irrigation control for its ability to handle uncertaintys using rule-based domain knowledge. However, conventional FIS lacks adaptability to environmental changes, limiting its long-term accuracy and responsiveness. Adaptive Neuro-Fuzzy Inference System (ANFIS) addresses this limitation by combining fuzzy logic with neural network learning, enabling automatic adjustment of model parameters based on data patterns. This study compares the performance of FIS and ANFIS in predicting optimal irrigation levels based on soil moisture, air temperature, relative humidity, and solar radiation. A synthetic dataset of 1,000 samples simulating realistic agricultural conditions was generated and normalized to improve computational consistency. The FIS model uses triangular membership functions and five expert-defined fuzzy rules, while ANFIS employs Gaussian membership functions with parameters optimized using the ADAM algorithm over 50 training epochs. Results show that ANFIS outperforms FIS, lowering RMSE from 0.13 to 0.07, halving MAE from 0.10 to 0.05, and increasing R² from 0.85 to 0.93, indicating a substantially better predictive performance. This study demonstrates that ANFIS is more adaptive, accurate, and computationally efficient, contributing to the advancement of intelligent and sustainable irrigation systems in precision agriculture.
Pelatihan Kecerdasan Buatan Menggunakan Teachable Machine untuk Siswa SMA Kelas XI Catherine Olivia Sereati; Ferry Rippun Gideon Manalu; Pascalis; Yudha Harnoko; Melisa Mulyadi; Sandra Octaviani B. Widiarto; Linda Wijayanti; Karel Octavianus Bachri; Widodo Widjaja Basuki; FLORENTIA ANGELINA
Jurnal Pengabdian Masyarakat Charitas Vol. 6 No. 01 (2026): Jurnal Pengabdian Masyarakat Charitas Juni 2026
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Katolik Indonesia Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/charitas.v6i01.7605

Abstract

Digital literacy is crucial today, especially as artificial intelligence (AI) technology begins to develop. AI technology is widely discussed because it can help to improve efficiency in various fields of activity. The development of AI technology is basically aimed at improving human welfare, but there are disadvantages when AI technology is not used properly, which can harm society. To achieve beneficial outcomes and avoid the harm caused by the misuse of AI technology, it is deemed necessary to provide AI technology training to the community as early as possible. This community service activity provided AI training to students from Strada Santo Thomas Aquino High School, which has a mission that strongly supports the objectives of this training. This training activity began with an introduction to AI technology, which aimed to make students familiar with and understand the features of AI technology so that they are aware of the existence of AI around them. Students were explained how AI works, from database collection to pattern recognition, and were made aware that the use and development of AI technology must be carried out ethically and responsibly. The training method included an explanation of the importance and dangers of AI technology through presentations, discussions, and teamwork using the "Teachable Machine" application. Evaluation of activities was carried out through pretests and posttests as well as student feedback. The results showed an improvement in students' understanding of AI technology after participating in this training. The students were highly satisfied with the AI technology training provided, both in terms of the accuracy of the material explanation, the abilities of the instructors, and the benefits they received.
P-D controller computer vision and robotics integration based for student’s programming comprehension improvement Nova Eka Budiyanta; Catherine Olivia Sereati; Lukas Lukas
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14881

Abstract

The 21st-century skills needed to face the speed of understanding technology. Such as critical thinking in computer vision and robotics literacy, any student is hampered by the programming that is considered complicated. This study aims at the improvement of student embedded system programming competency with computer vision and mobile robotics integration approach. This method is proposed to attract the students to learn about embedded system programming by delivering integration between computer vision and robotics using the P-D controller since both of the fields are closely related. In this paper, the researcher described computer vision programming to get the data of captured images through the camera stream and then delivered the data into an embedded system to make the decision of robot movement. The output of this study is the improvement of a student’s ability to make an application to integrate a sensor system using a camera and the mobile robot running follow the line. The result of the test shows that the integration method between computer vision and robotics can improve the student’s programming comprehension by 40%. Based on the Feasibility test survey, it can be interpreted that from the whole assessment after being converted to qualitative data, all aspects of the learning stages of programming application tested with the integration of computer vision and robotics fall into the very feasible category for used with a percentage of feasibility by 77.44%.
Tomato leaf disease recognition system using Faster R-CNN Karel Octavianus Bachri; Bryan Santoso; Duma Kristina Yanti Hutapea; Catherine Olivia Sereati; Lanny W. Pandjaitan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.25519

Abstract

The objective of this paper is to detect tomato leaf disease using Faster region-based convolutional neural network (R-CNN). The tomato leaf disease recognition system utilizes a dataset consisting of healthy tomato leaves and eight leaf diseases, including early blight, late blight, leaf mold, mosaic virus, septoria, spider mites, yellow leaf curl virus, and leaf miner. The dataset is obtained from various sources, such as Kaggle, Google Images, Bing Images, and Roboflow Universe. Pre-processing techniques, including collage, tile, static crop, and resize, are applied to prepare the dataset for training. Data augmentation methods, such as flipping, 90° rotation, exposure adjustment, and hue modification, are applied to enhance the model’s robustness and generalize its performance. Specifically, we implemented Faster R-CNN as part of Detectron2 using its base models and configurations. The results demonstrate that the X101-FPN base model for Faster R-CNN with the default configurations of Detectron2 is efficient and general enough to be applied to defect detection. This approach results in an average precision (AP) detection score of 87.01% for validation results.
Co-Authors Abdurohman Abdurohman Adang Suwandi Ahmad Arwin Datumaya Wahyudi Sumari Bryan Santoso Christanto, Henoch Juli Duma Kristina Yanti Duma Kristina Yanti Hutapea Ferry Rippun Gideon Manalu, Ferry Rippun Gideon FLORENTIA ANGELINA Hidayat, Renaldi Hilarius Radix W. C Jones, Danzel Maxdriel Samuel Juli Christanto, Henoch Karangga, Yusaphat Phosa Karel Octavianus Bachri Kartadinata, Budi Kartwidjaja, Maria Angela Kevin kevin Kumala Indriati Lanny W Lanny W Pandjaitan Lanny W. Pandjaitan Lestari, Hesti Tri Linda Wijayanti Lukas Lukas Lukas, Lukas Maria Angela Kartawidjaja Maria Angela Kartwidjaja Marsul Siregar Marten Darmawan Melisa Mulyadi MM. Lanny W. Pandjaitan Nova Eka Budiyanta Pangestu, Evan Sudira Pascalis Paul Ferdinand, Jean Pranadjaya, Egipta Radix W. C, Hilarius Rippun G. Manalu, Ferry Sandra Octaviani B. Widiarto Silviana Windasari Surya Permana, Rizky Tajuddin Nur Theresia Ghozali Trio Adiono Veronica Windha Mahyastuty W Pandjaitan, Lanny Widodo Widjaja Basuki Yudha Harnoko Zefanya, Maria Zenik, Andre