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All Journal Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Buana Informatika Bulletin of Electrical Engineering and Informatics Jurnal Simantec Jurnal Teknologi Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology JOIN (Jurnal Online Informatika) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology IJIE (Indonesian Journal of Informatics Education) Informatika Pertanian Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SINTECH (Science and Information Technology) Journal Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal ULTIMATICS Journal of Information Technology and Computer Engineering JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Mnemonic DEDIKASI: Community Service Reports Journal of Informatics and Vocational Education Journal of Soft Computing Exploration Journal La Edusci JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pemberdayaan Masyarakat JGHTT Indonesian Journal of Learning and Instructional Innovation
Febri Liantoni, Febri
Universitas Sebelas Maret
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure Liantoni, Febri; Perwira, Rifki Indra; Bataona, Daniel Silli
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.566 KB) | DOI: 10.24003/emitter.v6i2.306

Abstract

Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this research, Adaptive Ant Colony Optimization algorithm is proposed for edge image detection of leaf bone structure. The Adaptive Ant Colony Optimization method is a modification of Ant Colony Optimization, in which the initial an ant dissemination process is no longer random, but it is done by a pixel placement process that allows for an edge based on the value of the image gradient. As a comparison also performed edge detection using Robert and Sobel method. Based on the experiments performed, Adaptive Ant Colony Optimization algorithm is capable of producing more detailed image edge detection and has thicker borders than others. Keywords: edge detection, ant colony optimization, robert, sobel
KLASIFIKASI DAUN HERBAL MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER DAN KNEAREST NEIGHBOR Liantoni, Febri; Nugroho, Hendro
Jurnal Simantec Vol 5, No 1 (2015)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v5i1.1009

Abstract

ABSTRAKPerkembangan gacorwin ilmu tanaman telah mengalami kemajuan yang pesat, khususnya ilmu mengenai tanaman herbal. Tanaman herbal memiliki banyak manfaat bagi kehidupan manusia yaitu sebagai penyedian oksigen, bahan makanan, obat-obatan, maupun bahan kosmetika. Untuk mengetahui jenis-jenis tanaman herbal dapat dilakukan dengan proses klasifikasi. Klasifikasi tanaman herbal dapat dilakukan dengan cara mengidentifikasi bentuk citra daun dari tanaman tersebut. Proses klasifikasi tanaman herbal memerlukan ekstraksi fitur dari bentuk dari tanaman tersebut. Pada penelitian ini, fitur invariant moment dan fitur geometri digunakan gacorwin untuk ekstraksi fitur daun herbal. Fitur yang digunakan berjumlah 10 fitur. Ada beberapa macam metode klasifikasi yang biasa digunakan. Pada penelitian ini metode klasifikasi yang digunakan adalah metode Naïve Bayes Classifier dan K-Nearest Neighbor (KNN). Metode Naïve Bayes Classifier gacorwin merupakan metode Bayesian Learning yang paling cepat dan sederhana. Sedangkan metode KNN dapat melakukan klasifikasi dengan cepat berdasarkan jarak terdekat diantara objek data. Berdasarkan hasil uji coba yang dilakukan, penggunaan metode Naïve Bayes Classifier didapatkan nilai akurasi sebesar 75%, sedangkan dengan menggunakan metode K-Nearest Neighbor didapatkan nilai akurasi sebesar 70,83%. Hal ini menunjukkan bahwa kinerja metode Naïve Bayes Classifier lebih baik dibandingkan metode KNN.Kata Kunci: Fitur Invariant Moment, Fitur Geometri, Naïve Bayes Classifier, K-Nearest Neighbor, Bayesian Learning. ABSTRACTScience of the plant has made progress, particularly knowledge about herbs. Herb has many benefits for human life as provision of oxygen, foodstuffs, pharmaceuticals, and cosmetics. To determine the types of herbs with the classification process. Classification of herbs conducted by identifying the shape of the image of the leaves of these plants. Herbal plant classification process requires the extraction of features from the shape of plant. In this study, moment invariant features and geometrical feature is used for feature extraction of herbal leaves.Features used amounted to 10 features. There are several kinds of commonly used classification method. In this study, the classification method used is the method Naïve Bayes classifier and K-Nearest Neighbor (KNN). Naïve Bayes classifier is Bayesian Learning method of the most rapid and simple. While the KNN method can perform fast classification is based on the shortest distance between data objects. Based on the results of tests conducted, the use of methods Naïve Bayes Classifier accuracy values obtained by 75%, while using K-Nearest Neighbor value obtained an accuracy of 70.83%.These results indicate that the performance of Naïve Bayes Classifier method is better than KNN method.Keywords: Invariant Moment Feature, Geometrical Feature, Naïve Bayes Classifier, K-Nearest Neighbor, Bayesian Learning
Comparative analysis of ResNet backbones in single shot detector for visual-based waste detection Salsabila, Zahra Khalila; Prakisya, Nurcahya Pradana Taufik; Liantoni, Febri
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10540

Abstract

Waste has become a serious environmental issue that requires effective and efficient management systems. This study compares three residual network (ResNet) variants (ResNet-34, ResNet-50, and ResNet-101) within the single shot detector (SSD) framework for visual waste detection. The dataset consists of 800 images in four categories—food, plastic, paper, and wood—with a 70:20:10 split for training, validation, and testing. The backbone architecture, optimizer (stochastic gradient descent (SGD) and Adam), and learning rate are varied to evaluate fifteen experimental configurations. Model performance is assessed using precision, recall, F1-score, and mean average precision (mAP). The results show that SSD–ResNet-34 with SGD and a learning rate of 0.0005 works best, with a mAP of 91.02%, which is better than deeper backbones. Deeper backbone architectures do not consistently improve accuracy; instead, they increase the risk of overfitting on small datasets. These findings highlight that lightweight architecture, when used with the right hyperparameter settings, strikes a better balance between accuracy, computational efficiency, and generalization for small-scale waste detection tasks.
Implementation of the C4.5 Algorithm to Predict Student Achievement at SMK Negeri 6 Surakarta Putri, Giovanni Anggiesta; Maryono, Dwi; Liantoni, Febri
IJIE (Indonesian Journal of Informatics Education) Vol 4, No 2 (2020): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v4i2.47124

Abstract

Data mining is a knowledge used to get information from multiple data. C.45 Algorithm is one of data mining algorithm to classify data to many categories. Implementation of data mining not only could be used in industrial section but it could be used to in educational section (educational data mining) to help teacher and student improve their learning quality. This research purposed to know the implementation of data mining to predict student achievement from many factors could be effected . The research use Knowledge Discovery in Database method and it would be analyzed by accuration calculated from classify model that be form. Result of the research is the rules that formed by the decision tree and it could predict student achievement . Teacher could use it to give special treatment to student who got not good prediction.
Hand Detection on HSV Color Space Model and Syntactic Extraction of Fingertip by Thinning Method for Hand Gesture Recognition Aristyagama, Yusfia Hafid; Liantoni, Febri; Prakisya, Nurcahya Pradana Taufik
IJIE (Indonesian Journal of Informatics Education) Vol 5, No 2 (2021): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v5i2.51693

Abstract

In the discussion of computer vision, detection and recognition are an interesting topic to discuss. Basically, advanced computer vision technology requires a high-level interaction method above the text-based console interaction. Hand detection and gesture recognition is one of the interaction cases in computer vision. In this study, an experiment of hand detection and syntactic hand gesture recognition method are discussed. HSV (Hue Saturation Value) space color model is used as the basis of hand detection and segmentation. Then, the thinning method is used to get endpoint features of each fingertip.The proposed design is designed to meet with real-time video processing. The experiment intended to find some issues usually happened when the ZS thinning method is used to gain the detection and recognition. The result shows that the proposed design able to detect and recognize some gesture, but unstable hand movement may lead into a fault called by extra endpoint. In this research, extra endpoints are considered as a challenge that must be anticipated when using thinning method especially ZS algorithm to perform syntactic hand gesture recognition.
Pandemic and Online Learning at Engineering Colleges Ayuningrum, Erica Devi; Wihidayat, Endar Suprih; Liantoni, Febri
IJIE (Indonesian Journal of Informatics Education) Vol 7, No 1 (2023): July
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v7i1.63440

Abstract

The Covid-19 pandemic has resulted in social restrictions being implemented in all sectors of life, including the scope of education. The closure of schools, higher education, and other educational institutions resulted in face-to-face learning needing to be carried out as usual. Therefore, online learning is a learning strategy that can be applied in times of crisis like this. Application of online learning, which is carried out without planning and suddenly makes several obstacles arise when this learning is carried out. The purpose of this study is to find out what problems arise when implementing online learning in engineering universities during a pandemic and what solutions can be applied to overcome them. This research is a systematic literature review research with keywords used, namely "online learning" or "online course" and "covid-19" or "pandemic" or "Covid 19". In searching articles, articles that are indexed in the Scopus database are used and are limited to publication years, namely from 2019-2022 (during the COVID-19 pandemic). This study used descriptive analysis with secondary data sources. From the results of this study, the application of online learning, for now, is considered the best solution so that learning can still be carried out. But besides that, there are still many obstacles found in its application due to the need for careful planning and preparation for its implementation. Other obstacles are both technically, facilities, and infrastructure, as well as from the human resources themselves. It is hoped that in the future, the solutions found can add insight and be used as a reference in the application of online learning to be effective and better.
Desain dan Pemanfaatan Media Pembelajaran Flash Card dengan Canva untuk Disabilitas Yuana, Rosihan Ari; Budiyanto, Cucuk Wawan; Prakisya, Nurcahya Pradana Taufik; Hatta, Puspanda; Aristyagama, Yusfia Hafid; Liantoni, Febri
DEDIKASI: Community Service Reports Vol 6, No 1 (2024): DEDIKASI: Community Service Report - January
Publisher : FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/dedikasi.v6i1.77139

Abstract

Students with disabilities require suitable educational materials. Hence, one of the essential skills that a teacher must possess is the ability to provide suitable instructional materials for students. A workshop was organized by this community service activity at SLB YPCM Boyolali, focusing on creating educational media for instructors using Canva. The training instructs teachers on how to design flashcards specifically tailored for students with disabilities to facilitate their learning process. The advantage of this activity is the enhanced proficiency of SLB YPCM Boyolali teachers in creating digital educational materials. Another advantage is assessing instructor perspectives when employing digital media for educational purposes. The school will provide students with exceptional needs the opportunity to develop the skill of product branding using the processed foods they create. The post-workshop evaluation results indicate that this activity is highly successful and positively influences participants. Evidence demonstrates that 90% of participants can generate flashcard learning media products using Canva. The participants had a favorable opinion of Canva due to its user-friendly interface and comprehensive range of functions, despite most participants having limited computer proficiency. The session presented was met with a high level of satisfaction from most attendees.
Peningkatan Kreatifitas Dan Kemampuan Algoritma Melalui Workshop Game Development Liantoni, Febri; Budiyanto, Cucuk Wawan; Aristyagama, Yusfia Hafid; Hatta, Puspanda; Prakisya, Nurcahya Pradana Taufik
DEDIKASI: Community Service Reports Vol 7, No 1 (2025): DEDIKASI: Community Service Report - January
Publisher : FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/dedikasi.v7i1.93557

Abstract

Workshop pengabdian masyarakat ini bertujuan untuk memberdayakan para pendidik dalam menciptakan media pembelajaran yang lebih menarik dengan memanfaatkan teknologi digital, khususnya melalui pendekatan game-based learning. Tantangan yang dihadapi adalah rendahnya kreativitas dan pemahaman algoritma di kalangan pendidik, serta minimnya implementasi pembelajaran berbasis game di sekolah. Dilaksanakan di SMP Al Qolam Muhammadiyah Gemolong, workshop ini memanfaatkan fasilitas kelas yang tersedia, meliputi paparan teori, praktik langsung, dan pendampingan intensif dalam pengembangan game menggunakan Construct 2. Para peserta tidak hanya belajar membuat media pembelajaran interaktif, tetapi juga memperdalam pemahaman tentang literasi digital dan algoritma. Hasil kegiatan ini menunjukkan peningkatan yang signifikan dalam kemampuan desain pembelajaran, serta kepercayaan diri dalam menggunakan teknologi untuk mendukung proses mengajar. Dari pelatihan ini, terlihat bahwa penggunaan pendekatan berbasis game dapat merangsang kreativitas dan memperkuat pemahaman algoritma dalam konteks pembelajaran.
The Influence of the Learning Cycle Blended Learning Model on Student Learning Outcomes Safitri, Pratiwi Ajeng; Basori, Basori; Liantoni, Febri
Journal of Informatics and Vocational Education Vol 6, No 3 (2023): Journal of Informatics and Vocational Education - November
Publisher : Pendidikan Teknik Informatika dan Komputer, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v6i3.76753

Abstract

Learning in the 21st century requires students to be literate about the existence of technology. Technology users in Indonesia are increasing, but the quality of Indonesian education internationally, based on UNESCO records, is still far behind other ASEAN countries. COVID-19, once endemic in Indonesia, directly impacted education, which had to be carried out online. However, after Covid-19 subsided, learning was resumed face-to-face as usual. The Blended Learning learning model, suitable for the 21st century, should not be discontinued but should be improved and improved to make it more optimal. This research aims to determine the effect of the Learning Cycle Blended Learning model on student learning outcomes with the help of Moodle. This research uses quantitative methods with a quasi-experimental research design. This research involved 71 students in the experimental class with the Learning Cycle Blended Learning model and the control class with the Problem-Based Learning learning model. The instrument used is a learning outcomes test consisting of a pretest and a posttest. The t-test results show (1) differences in student learning outcomes between applying Problem-Based Learning and the 8E-Blended Learning cycle with a Sig value. (2-tailed) is 0.003. The n gain test results show (1) The 8E-Blended Learning cycle learning model is more effective in improving student learning outcomes with a gain score of 49.46 in the good category.
Penerapan Cooperative Learning Pada Pembelajaran Daring Mata Pelajaran Informatika Ditinjau Dari Keaktifan dan Prestasi Belajar Siswa di SMP. Karim, Rifa'i Abdul; Maryono, Dwi; Liantoni, Febri
Journal of Informatics and Vocational Education Vol 5, No 2 (2022): Journal of Informatics and Vocational Education - July
Publisher : Pendidikan Teknik Informatika dan Komputer, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v5i2.62546

Abstract

This study aims to increase student activity and learning achievement through the application of Cooperative Learning Type STAD in Informatics online learning by utilizing the Google Jamboard application. This research is included in the quasi-experimental type of research with the design of One Group Pretest-Posttest.  The population in this study was all grade VII students of a state owned school. The sample used was class VII G students with a total of 32 students. The sampling technique uses cluster random sampling. Data collection techniques use questionnaires and tests. The technologyk data analysis used is a normality test, homogeneity test, and hypothesis test using a paired sample t test. The results of the study, which were reviewed in terms of learning activity, statistically there was an increase from an average score  of 72.90 to 80.69. Meanwhile, in terms of learning achievement, it showsthat statistically the average pre-test score is46.56 and  the average  post test score is 65.03 so that there is an increase through the application of Cooperative Learning Type STAD in informatics online learning.
Co-Authors Abin Suarsa Acihmah Sidauruk Agus Efendi Agus Santoso Ananda, Rizky Putu Anas, Rizky Chairul Andini, Ratih Friska Dwi Annisa, Fitri Nur Anwar, Rizak Al Hasbi Aris Budianto, Aris Astuti, Asri Ayuningrum, Erica Devi B.M.A.S. Anaconda Bangkara Bambang Yuwono Basori Basori Bataona, Daniel Silli Bataona, Daniel Silli Belo Ximenes, Jose Feliciano Lim Bernadhed, Bernadhed Chaizara, Rezza Fariszal Hisyam Chastine Fatichah Cucuk Wawan Budiyanto Dwi Maryono Farizi, Muhammad Yusuf Hasyim, Jaka Wardana Hendro Nugroho, Hendro Hidayatulah Himawan Hidayatulloh, A. Nururrochman Jaelani, Muhammad Karim, Rifa'i Abdul Kesuma, Halim Perdana Larasati, Sukma Luky Agus Hermanto, Luky Agus Majid, Desva Fitranda Maruf, Irma Rachmawati Maryanti Mulia Sulistiyono Myrtha, Risalina Nanik Suciati Nugroho, Hendro Nurcahya Pradana Taufik Prakisya Palupi, Dian Exsi Prabaswara, Muhammad Arden Prakisya , Nurcahya Pradana Taufik Prakisya, Nurcahya Pradana Taufik Pratama, Kalistus Haris Purnama, Bayu Rizkhy Candra Puspanda Hatta Putri, Giovanni Anggiesta Putri, Nanditya Vianti Qurin, Milani Tanya Rahmawati, Weny M. Ramadhan, Firdaus Ditio Ramadhan, Raqael Fisabillah Rifki Indra Perwira Rosetya, Septiyawan Rosihan Ari Yuana, Rosihan Ari Rustanto, Diki Wahyudi Safitri, Pratiwi Ajeng Saida Ulfa Salsabila, Zahra Khalila Santoso, Agus Adi Saputro, Muhammad Naufal Adi Setianti, Suci Rhamadani Simanjuntak, Ondihon Siswoyo, Risya Ines Putri Sukmagautama, Coana Sukmaningrum, Agy Hafidzah Wahyudi, Yusuf Rois Weny Mistarika Rahmawati Wihidayat, Endar Suprih Yusfia Hafid Aristyagama