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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal INSYPRO (Information System and Processing) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Soft Computing Exploration Online Learning in Educational Research Internet of Things and Artificial Intelligence Journal Teknovokasi : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal of Deep Learning, Computer Vision and Digital Image Processing Jurnal Sipakatau: Inovasi Pengabdian Masyarakat Jurnal MediaTIK Media of Computer Science
Adiba, Fhatiah
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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KLASIFIKASI RASA JERUK SIAM BERDASARKAN WARNA DAN TEKSTUR BERBASIS PENGOLAHAN CITRA DIGITAL Lapendy, Jessica Crisfin; Resky, Andi Aulia Cahyana; Makmur, Haerunnisya; Kaswar, Andi Baso; Andayani, Dyah Darma; Adiba, Fhatiah
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 2 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i2.5384

Abstract

Jeruk merupakan salah satu buah yang sangat populer di kalangan masyarakat Indonesia karena memiliki rasa yang segar, enak, dan memiliki banyak manfaat bagi kesehatan. Kandungan vitamin C yang melimpah membuat buah ini banyak dijadikan sebagai suplemen kesehatan sehingga jeruk memiliki nilai komersial dan pangsa pasar yang besar. Untuk mendapatkan manfaat yang maksimal dari buah ini, diperlukan kualitas jeruk yang baik, dilihat dari segi rasa dan tingkat kematangan buah jeruk. Salah satu jenis jeruk yang populer adalah jeruk siam. Akan tetapi, dari segi rasa buah jeruk asam dan manis masih sulit untuk dibedakan jika hanya dilihat oleh mata. Oleh karena itu, pada penelitian ini diusulkan sistem klasifikasi rasa buah jeruk siam berdasarkan warna dan tekstur kulit menggunakan jaringan syaraf tiruan berbasis pengolahan citra digital. Pada penelitian ini, rasa jeruk dibagi ke dalam 2 kelas, yaitu manis dan asam. Metode yang diusulkan terdiri atas 7 tahapan utama yaitu tahap akuisisi citra, preprocessing, segmentasi menggunakan Otsu Thresholding, penghilangan noise citra biner menggunakan K-Means, operasi morfologi, ekstraksi fitur warna serta tekstur, dan klasifikasi menggunakan jaringan syaraf tiruan. Beberapa skenario pengujian dilakukan dan diperoleh skenario penggabungan fitur warna LAB dengan fitur tekstur contrast, correlation, energy dan homogeneity yang menghasilkan akurasi tertinggi. Adapun nilai akurasi, precision, dan recall yang diperoleh, yaitu 98,75%, 100%, dan 97,56%. Hal ini menunjukkan bahwa metode yang diusulkan memiliki kinerja yang baik dalam mengklasifikasian rasa buah jeruk ke dalam kelas manis atau asam.
The implementation of mamdani fuzzy logic in determining student concentration in the computer engineering program Liku, Antika Diana; Adiba, Fhatiah; Kartika, A.Amalia
Journal of Soft Computing Exploration Vol. 4 No. 3 (2023): September 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i3.211

Abstract

The selection of a concentration is an important stage for students in the Computer Engineering program at the State University of Makassar before entering the fifth semester. Each student must choose one of the concentrations in the fields of networking, embedded systems, or smart systems. This concentration selection has a significant impact on academic activities and future career abilities. However, the lack of awareness among students about their talents and interests has resulted in many students having difficulty in choosing the right concentration. To address this issue, this research proposes using the Mamdani fuzzy logic method to assist students in selecting the appropriate concentration based on their talents and interests. The approach is carried out by collecting information through questionnaires filled out by students who have completed the fourth semester of the Computer Engineering program. The collected data is then processed using the concepts of Mamdani fuzzy logic in the MATLAB environment to generate concentration scores for each field. The research results show the effectiveness of Mamdani fuzzy logic in determining the concentration of students in networking, embedded systems, and smart systems, with an accuracy rate of up to 80%. By using the appropriate linguistic variables, students' levels of interest and abilities in each field can be accurately represented. This research has benefits for students and the university in identifying the right concentration that aligns with the interests and abilities of students at the State University of Makassar.
Meningkatkan Kesadaran Mahasiswa terhadap Peraturan Akademik dan Kemahasiswaan melalui Program Sosialisasi di Fakultas Teknik Universitas Negeri Makassar Wardani, Ayu Tri Wardani; NFH, Alifya; Husna Nasrullah, Asmaul; Akbar, Muh.; Adiba, Fhatiah
Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2024): Jurnal Pengabdian Masyarakat (AbdiMas)
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/abdimas.v2i2.5355

Abstract

Peningkatan kualitas pendidikan di perguruan tinggi memerlukan pengelolaan tata laksana akademik dan kemahasiswaan yang sistematis dan terstruktur. Fakultas Teknik Universitas Negeri Makassar (FT UNM) menyelenggarakan kegiatan sosialisasi peraturan akademik dan kemahasiswaan sebagai langkah strategis untuk mendukung terciptanya lingkungan akademik yang kondusif. Kegiatan ini bertujuan untuk memberikan pemahaman yang mendalam kepada mahasiswa tentang hak dan kewajiban, tata tertib akademik, serta mekanisme kerja organisasi kemahasiswaan, sehingga menciptakan mahasiswa yang tidak hanya memahami peraturan tetapi juga dapat menerapkannya. Sosialisasi ini diikuti oleh 200 peserta yang terdiri atas pengurus organisasi mahasiswa, pembina organisasi, dan mahasiswa baru angkatan 2024. Metode yang digunakan mencakup pemaparan materi oleh narasumber ahli, diskusi interaktif, dan evaluasi yang menyeluruh. Hasil dari kegiatan ini berupa dokumen rekomendasi yang merangkum poin-poin diskusi, solusi terhadap tantangan pengelolaan organisasi, dan rencana aksi yang relevan. Dokumen tersebut kemudian disebarluaskan dalam bentuk poster dan banner informatif untuk meningkatkan kesadaran mahasiswa terhadap pentingnya tata kelola organisasi yang profesional dan berbasis integritas. Dampak kegiatan ini diharapkan dapat mendukung pengembangan budaya akademik yang lebih terstruktur dan kolaboratif, meningkatkan sinergi antarjurusan, serta mencetak mahasiswa yang kompeten, berkarakter, dan siap menghadapi tantangan global. Dengan langkah ini, FT UNM menunjukkan komitmennya dalam mencetak lulusan berkualitas yang tidak hanya unggul secara akademik, tetapi juga mampu memberikan kontribusi positif bagi masyarakat.
ANALISIS PERFORMA CONVOLUTIONAL NEURAL NETWORK DENGAN HYPERPARAMETER TUNING DALAM MENDETEKSI GAMBAR DEEPFAKE Darmatasia, Darmatasia; Ramli, Abdur Rahman; Salsabila, Azizah; Adiba, Fhatiah
Jurnal INSYPRO (Information System and Processing) Vol 9 No 2 (2024)
Publisher : Prodi Sistem Informasi UIN Alauddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/insypro.v9i2.51928

Abstract

This research analyzes the performance of Convolutional Neural Network (CNN) in detecting deepfake images with a focus on hyperparameter tuning. The study consists of two classes: fake images and real images, with each class containing 5000 data samples. Hyperparameter tuning is conducted using the Keras-tuner library, a framework used for automatic hyperparameter tuning on models built with Keras, eliminating the need for manual trial and error tuning. The hyperparameter search strategy employed is random search. The results of the study indicate that hyperparameter tuning significantly improves the model's detection accuracy. Various experiments were conducted to evaluate the impact of hyperparameter settings, such as the number and size of filters, learning rate, and optimizer. Analysis of different optimizers showed significant variations in performance, with Adam Optimizer achieving the highest accuracy of 83% using a combination of 32 filters sized 3x3 in the first layer and 128 filters sized 5x5 in the second layer. RMSProp and AdamW each achieved 82% accuracy, SGD Optimizer achieved 75% accuracy, while Adadelta Optimizer achieved 71% accuracy. The findings of this study affirm that the selection of optimizer and appropriate hyperparameter settings have a significant impact on the model's performance in detecting patterns in the data. This study also emphasizes the importance of optimizing filters and sizes in each layer to enhance model accuracy.
Pembelian Tiket Bus Aneka Trasport Dan Po.Sejahtra Menggunakan Metode Fuzzy Inference System Syair, Andi Irfandiari Syair; Prasetya, Muhammad Fahril; Adiba, Fhatiah
Journal of Deep Learning, Computer Vision, and Digital Image Processing Volume 1 Issue 2 September 2023
Publisher : CV. Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/decoding.v1i2.172

Abstract

Aneka Transport and Po.Sejahtar is a public transportation service that has a Selayar-Makassar route, various transports and Po.Sejahtra with millions to solve problems caused by the increasing volume of vehicles going back and forth from Selayar - Makassar. This research was carried out to determine bus ticket prices using fuzzy inference system. to overcome the uncertainty and complexity in making decisions in terms of pricing based on influencing factors, such as the distance traveled, facilities, and the number of buyers.
Digital Image Based DSS for Assessing Tomato Quality using AHP-TOPSIS Method Wulandari; Surianto, Dewi Fatmarani; Parenreng, Jumadi M.; Adiba, Fhatiah
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 2 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v15i2.19060

Abstract

Tomatoes are a major export commodity in the country's plantation sector. This increases the urgency of efforts to increase tomato productivity, both in terms of quantity and quality. Evaluation of tomato quality currently relies on the degree of ripeness and skin texture. The conventional method currently used involves manual inspection, which can allow for misjudgment and economic loss. This research aims to use a digital image-based approach by utilizing a decision support system that combines the AHP and TOPSIS methods to assess tomato quality based on color and texture criteria. This research evaluates and ranks nine tomato images that have good quality, by giving higher priority to skin texture than skin color. Evaluation results from three tests showed that the system was able to determine the quality of tomatoes with an average kappa value of 0.78, which interpreted the results of good agreement between the system and expert judgments.
Facial Expression Detection System for Students in Classroom Learning Process Using YoloV7 Aglaia, Alifya Nuraisyar; Afdhaliyah, Mukhlishah; Adiba, Fhatiah; Kaswar, Andi Baso; Muhammad Fajar B; Andayani, Dyah Darma; Yahya, Muhammad
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.83978

Abstract

The utilization of technology in education is not only about using hardware or software, but also how technology can facilitate effective learning experiences. However, in the learning process there is a problem for teachers to know the level of student attention in the classroom to the material presented, so that the teacher does not know accurately the concentration of students during the learning process until it has an impact on the teacher's learning methods that are not in accordance with the characteristics of students. The purpose of this research is to detect students' facial expressions in the classroom learning process using yolov7. The implementation of several architectural models on CNN consists of several proposed methods, namely data collection, data augmentation, data annotation, split dataset, training, and model evaluation. System testing is done by measuring accuracy and comparing with other methods, namely CNN, CNN MobileNet, CNN EfficientNet-B0 and YoloV7. The test results show the average accuracy of CNN 80%, CNN MobileNet 93%, CNN EfficientNet-B0 31% and YoloV7 96%. Based on these results, it can be concluded that the YoloV7 method can detect student concentration effectively and efficiently compared to CNN, CNN MobileNet, and CNN EfficientNet-B0.  
Pendidikan Berbasis Masyarakat: Transformasi Pendidikan dan Keterampilan di Kampung Pemulung Makassar Risal, Andi Akram Nur; Kaswar, Andi Baso; Surianto, Dewi Fatmarani; Adiba, Fhatiah; Rivai, Andi Tenri Ola
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 2: Issue 2 (May 2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v2i2.2239

Abstract

Program Pendidikan dan Pengembangan Keterampilan di Kampung Pemulung Adhyaksa berhasil menciptakan dampak yang signifikan dalam meningkatkan partisipasi dan kesejahteraan anak-anak serta keluarga mereka. Melalui serangkaian kegiatan seperti pelatihan keterampilan, lomba keagamaan, dan pemeriksaan kesehatan, anak-anak kampung pemulung menunjukkan antusiasme tinggi dan kemampuan belajar yang luar biasa. Mereka tidak hanya meningkatkan pengetahuan akademis, tetapi juga mengasah keterampilan artistik, keterampilan teknologi, dan nilai-nilai keagamaan. Kerjasama antara komunitas Sahabat Indonesia Berbagi Makassar (Sigi) dan Universitas Negeri Makassar telah membuktikan efektivitas pendekatan pendidikan berbasis komunitas dalam mengatasi tantangan pendidikan dan kesejahteraan di kampung pemulung. Dengan fokus pada pemenuhan kebutuhan lokal dan pemberdayaan masyarakat, program ini telah memberikan kontribusi yang berarti terhadap peningkatan kesadaran akan pentingnya pendidikan, keterampilan, dan kesehatan di kalangan anak-anak dan keluarga di kampung pemulung. Kesuksesan program ini menyoroti pentingnya kemitraan antara institusi akademis, komunitas, dan pemerintah dalam mendukung pendidikan dan pengembangan komunitas. Evaluasi kontinu dan pengembangan lebih lanjut dari program ini diharapkan dapat memperkuat manfaatnya dan memberikan inspirasi bagi upaya serupa di tempat-tempat lain. Dengan demikian, pendekatan pendidikan berbasis komunitas terbukti menjadi instrumen yang efektif dalam memperjuangkan hak pendidikan dan meningkatkan kualitas hidup masyarakat yang rentan seperti di kampung pemulung Adhyaksa.
Enhanced Laptop Recommendation System Using Tsukamoto Fuzzy Logic Nasrullah, Asmaul Husnah; Adiba, Fhatiah; Anastasia, Tezza; Farghina, Syakira Ayma; Akbar, Muh.
Media of Computer Science Vol. 1 No. 1 (2024): June 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i1.186

Abstract

One of the most popular and rapidly growing needs among the general public is laptops. Currently, there are many types of laptops with varying features, and not everyone knows the advantages and disadvantages of each type. The purpose of this research is to develop and build a Fuzzy inference system that applies the Tsukamoto method. This is to address issues in providing unclear or inaccurate services to customers during the laptop sales process. By developing a recommendation system that can provide guidance or suggestions in purchasing a laptop based on interest and needs in searching for references, and the type of laptop that meets the criteria. The decision to purchase a laptop uses parameters such as screen size, RAM capacity, SSD capacity, and price. The implementation of the Fuzzy Tsukamoto method for providing laptop purchase recommendations is able to give good recommendations.
Evaluation Of Fuzzy C-Means Method For District Clustering Nasrullah, Asmaul Husnah; Fajar, Andi Muhammad; Taufiq, Muhammad Aqsha; Rahmat, Nuzulul; Adiba, Fhatiah
Media of Computer Science Vol. 1 No. 2 (2024): December 2024
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v1i2.203

Abstract

This study analyses the use of Fuzzy C-Means algorithm to cluster districts in South Sulawesi based on the education level of the population. Two distinct groups were found with several districts falling into each group after 17 iterations to reach the optimal solution. The clustering results were visualised with a point spread graph. The Fuzzy C-Means algorithm was executed using Python with certain parameters. The research aims to improve the quality of education with proper resource allocation and identification of districts based on the highest education. The data used includes education indicators and district minimum wage. The results are expected to provide input for a more targeted education policy in South Sulawesi. Fuzzy C-Means algorithm is effective for analysing and clustering education data in education policy decision making.
Co-Authors Abdul Wahid Afdhaliyah, Mukhlishah Aglaia, Alifya Nuraisyar Akbar, Muh. Aksa, Muhammad Amaliah, Annisa Shela Amukune, Stephen Anastasia, Tezza Andani, Andi Ferry Adlian Tri Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Arifiyanti, Fitria Asmaul Husnah Nasrullah Awaluddin, Muh. Ghazali Azis, Putri Alysia Baso, Fadhlirrahman Bittara, Andi Ghizzania Sirih DARMATASIA, DARMATASIA Dewi Fatmarani Surianto Edy, Marwan Ramdhany Fajar, Andi Muhammad Fardan, Muhammad Farghina, Syakira Ayma Fathahillah Fathahillah Febriansyah Ramadhan, Haekal Firdaus Firdaus Hasnining, Ayu Husna Nasrullah, Asmaul Jannah, Ghina Raodatul Jumadi Mabe Parenreng Kartika, A.Amalia Khaida, Fatihah Kurnia Prima Putra Lapendy, Jessica Crisfin Lia, Resky Amalia Liku, Antika Diana M. Miftach Fakhri Makmur, Haerunnisya Maolani, Muh. Alfi Muhammad Fajar B Muhammad Yahya Muhtadi Muliadi Munawir Munawir Naoval, Ahmad Nasrullah, Asmaul Husna Nasrullah, Asmaul Husnah Nasurllah, Asmaul Husna Nasurullah, Asmaul Husna NFH, Alifya Nida Rifqi, Ainun Nurfitri, Andi Aisyah Parenreng, Jumadi M. Prasetya, Muhammad Fahril Qadri, Zul Rahmat, Nuzulul Ramli, Abdur Rahman Resky, Andi Aulia Cahyana Rivai, Andi Tenri Ola Salsabila, Azizah Sanatang Soeharto Soeharto Sulmadani, Fitriah Syahbani, Dimas Syair, Andi Irfandiari Syair Syukur, Pramudya Asoka Tahir, Muhlis Taufiq, Muhammad Aqsha Tenriola, Andi Udin, Alvin Mas Wahyuni , Maya Sari Wardani, Ayu Tri Wardani, Ayu Tri Wardani WULANDARI