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All Journal Teknika Syntax Jurnal Informatika Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal Informatika Jurnal CoreIT JURNAL MEDIA INFORMATIKA BUDIDARMA JIEET (Journal of Information Engineering and Educational Technology) Indonesian Journal of Artificial Intelligence and Data Mining Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika Sebatik Jurnal Nasional Komputasi dan Teknologi Informasi Krea-TIF: Jurnal Teknik Informatika JURIKOM (Jurnal Riset Komputer) JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Multimedia Jurnal Informatika dan Rekayasa Elektronik Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika Jurnal Inovasi Teknik Informatika Jurnal Ilmu Komputer Jurnal Teknik Informatika (JUTIF) Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Sains dan Informatika : Research of Science and Informatic SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Febi Yanto
Teknik Informatika, Universitas Islam Negeri Sultan Syarif Kasim Riau, Indonesia
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Transportation Other

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Journal : Bulletin of Computer Science Research

 1 
Implementasi Fuzzy Sugeno Berbasis IoT untuk Peringatan Kualitas Air Akuarium Ikan Mas Koki Rahman, Muhammad Taufikur; Yanto, Febi; Haerani, Elin
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.627

Abstract

The manual monitoring of aquarium water quality is often ineffective due to time constraints and the potential delays in detecting critical parameter changes that can threaten fish health. This research develops a real-time water quality monitoring system for goldfish aquariums based on the Internet of Things (IoT) using the Sugeno fuzzy logic method. The system utilizes an Arduino Uno R4 WiFi microcontroller to process data from turbidity, Total Dissolved Solids (TDS), and water temperature sensors. The Sugeno fuzzy method is chosen for its ability to produce precise numerical outputs based on fuzzy rules. To assess water quality, the sensor data undergoes fuzzification, rule evaluation, implication/aggregation function application, and defuzzification stages. The measurement results are then processed in real-time and sent via WiFi connection to the Blynk application, which serves as a monitoring medium and sender of warning notifications to users when water quality falls outside safe limits, while information is also displayed on the OLED screen of the system. Water quality assessment is classified based on fuzzy output values into several condition categories: 0-20 (Very Good), 21-40 (Good), 41-60 (Fair), 61-80 (Poor), 81-100 (Very Poor). Based on the test results, the system has been proven to effectively detect and classify water quality conditions with high accuracy, as well as provide effective warning notifications. This system is expected to assist aquarium owners in maintaining optimal environmental conditions for the health of goldfish in an automatic, sustainable, and efficient manner.
Perbandingan Akurasi Arsitektur EfficientNet-B0, VGG16, dan Inception V3 Dalam Deteksi Tumor Ginjal Pada Citra CT-Scan Muhammad Fahri; Yanto, Febi; Syafria, Fadhilah; Abdillah, Rahmad
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.670

Abstract

Kidney dysfunction can trigger the development of various diseases, including kidney tumors. Early detection of kidney tumors is very important to increase the effectiveness of treatment and the chances of patient recovery. The use of deep learning technology in medical image classification has become a promising approach, especially in detecting abnormalities in the kidney organ through CT-Scan images. This study compares the performance of three Convolutional Neural Network (CNN) architectures, namely EfficientNet-B0, Inception-V3, and VGG16, in detecting kidney tumors. The dataset used was obtained from the kaggle website, namely CT-scan images with normal and tumor classes and divided by a ratio of training  data and test data of 80:20. The hyperparameter used is Stochastic Gradient Descent (SGD) with a learning rate of 0.001 and 0.0001. The evaluation was carried out using a confusion matrix with metrics of accuracy, precision, recall, and F1-score . According to the test outcomes, the VGG16 model configured with a 0.001 learning rate achieved the highest classification performance, recording 99.46% accuracy, precision, recall, and F1-score.
Implementasi Metode RBMT dalam Penerjemahan Bahasa Indonesia ke Bahasa Makassar Hanif, Wan Muhammad; Yusra, Yusra; Muhammad Fikry; Febi Yanto; Siska Kurnia Gusti
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.935

Abstract

?This research was conducted to address the limited availability of linguistic resources for regional languages, particularly Makassar Language, which does not yet have adequate automatic translation support. The main problem addressed in this study is the absence of a reliable automatic translation system for Makassar Language. The objective of this research is to apply a rule-based translation method to translate text from Indonesian into Makassar Language. This study focuses on the implementation of the Rule-Based Machine Translation (RBMT) method for translating Indonesian text into Makassar Language using the Python programming language. The RBMT implementation involves tokenization, morphological analysis, vocabulary matching, and the application of grammatical rules, including the identification of prefixes and suffixes. The data used consist of a bilingual dictionary compiled from various sources and a set of test sentences representing everyday sentence structures. Translation evaluation was carried out using the Word Error Rate (WER) method, yielding a result of 0.289, and the Character Error Rate (CER) method, with a result of 0.21, which fall into the “Good” category based on the evaluation scale. The main findings indicate that the application of the RBMT method is capable of producing reasonably accurate translations at both the word and character levels. These findings demonstrate that a rule-based approach can be effectively applied to regional languages with limited digital data and provide an initial overview of the potential use of rule-based methods to support the development and preservation of regional languages.
Co-Authors Abdul Haris Abdussalam Al Masykur Adha, Martin Afiana Nabilla Zulfa Afriyanti, Liza Afroni, Hallend Agustina, Auliyah Alfitra Salam Alwis Nazir Andri Andri Aprilia, Risma Arif Mudi Priyatno Ariq At-Thariq Putra Baehaqi citra ainul mardhia putri Dafwen Toresa Dea Ropija Sari Destri Putri Yani Dewi, Nurika Dicky Abimanyu Dimas Ferarizki Dwitama, Raja Zaidaan Putera Dzaky Abdillah Salafy Edriyansyah Eka Pandu Cynthia Eka Pandu Cynthia Eka Pandu Cynthia, Eka Pandu Elin Haerani Elvia Budianita Fadhilah Syafria Fajar Febriyadi Fajri Fahreza Azeta Faris Apriliano Eka Fardianto Faris Fauzan Ray T Fauziyyah, Laila Nurul Fitra Kurnia Fitri Insani Fitri Insani Gusman, Deddy Gusti, Gogor Putra Hafi Puja Gusti, Siska Kurnia Hallend Afroni Hanif, Wan Muhammad Harni, Yulia Hatta, M Ilham Hidayat, Rizki Ichsan Permana Putra Idhafi, Zaky Iis Afrianty Iis Afrianty Ikhsan Hidayat Ikhwanul Akhmad DLY Illahi, Ridho Iqbal Salim Thalib Irma Welly, Irma Irsyad , Muhammad Isnan Mellian Ramadhan Iwan Iskandar Iwan Jannata, Nanda Jasril Jasril Jasril Jasril Jasril Jasril Jeki Dwi Arisandi Kurniansyah, Juliandi Lestari Handayani Lestari Handayani Lisnawita Lisnawita M Fikry M Ikhsan Maulana M. Afdal M. Fadil Martias Masaugi, Fathan Fanrita Mazdavilaya, T Kaisyarendika Morina Lisa Pura Muhammad Affandes Muhammad Fahri Muhammad Fikry Muhammad Fikry Muhammad Fikry Muhammad Haiqal Dani Muhammad Irsyad Muhammad Irsyad Muhammad Irsyad Mustasaruddin Mustasaruddin Nabyl Alfahrez Ramadhan Amril Nadila Handayani Putri Nazruddin Safaat H Nazruddin Safaat H Negara, Benny Sukma Niken Aisyah Maharani Herwanza Nining Erlina Novriyanto Novriyanto Nurika Dewi Okta Silvia M Permata, Rizkiya Indah Pizaini Pizaini Prananda, Alga Pratama, Dandi Irwayunda Putra, Wahyu Eka Putri Ayuni, Desy Putri Zahwa Rahma Shinta Rahmad Abdillah Rahman, Muhammad Taufikur Rahmat Al Hafiz Raja Joko Musridho Reski Mai Candra Reski Mai Candra Reski Mai Candra Rometdo Muzawi, Rometdo Roni Setyawan RR. Ella Evrita Hestiandari Sandy Ilham Hakim Syasri Sarah Lasniari Sarah Lasniari Shahira, Fayza Siti Ramadhani Sofiyah, Wan Sugandi, Hatami Karsa Surya Agustian Suwanto Sanjaya Syafria, Fadhillah Ulfah Adzkia Wang, Shir Li Wijaya, Andy Huang Wirdiani, Putri Syakira Yenggi Putra Dinata Yuli Novita Sari, Yuli Novita Yusra Yusra Yusra Yusra Yusra Yusra Yusra Yusra Yusra, Yusra