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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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Model game edukasi pembelajaran bahasa arab berbasis android untuk anak-anak Sandy Ilham Hakim Syasri; Nazruddin Safaat H; Muhammad Irsyad; Febi Yanto
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.6428

Abstract

In the era of globalization, understanding Arabic is becoming increasingly important, and starting language learning early provides an invaluable competitive advantage. Games as learning media can increase students' motivation and interest in learning. This educational game is designed in an interesting way, such as quiz and puzzle and this game is built based on android with high flexibility allowing children to learn anytime and anywhere, using devices such as smartphones and tablets. With the approach of playing while learning, children are believed to be able to understand Arabic without feeling burdened. The development of this game uses the MDLC (Multimedia Development Life Cycle) method with 6 stages including concept, design, material collecting, assembly, testing, distribution, and testing the effectiveness of the game by running tests using black box and User Acceptance Test (UAT) and using Unity software in building games that can be run on android smartphones. The results of Black box Testing obtained test results from the learning mode function, play mode, settings and all buttons in the game run well without any errors. From the results of UAT testing by giving the game to 13 respondents and getting a score of 90% with a very good category which means that the Android-based Arabic Language Introduction Game is feasible as a new learning media innovation and can increase children's interest.
Perancangan user interface pada game edukasi bahasa arab menggunakan metode design thinking Fajri Fahreza Azeta; Nazruddin Safaat H; Muhammad Irsyad; Febi Yanto
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.6432

Abstract

Technology is developing rapidly, providing convenient access to information, and sparking interest in technological developments. The growth of technology influences children's learning. The integration of technology creates new and exciting learning experiences, especially in early childhood education. The use of smartphones as innovative learning media offers interactivity and attraction. In game development, attention to the User Interface (UI) is crucial to ensure a suitable gaming experience that supports the overall game experience. The research methodology used in conducting this research is the "Design Thinking" method, this method uses a process of combining designer thinking and techniques to meet the need to find a way out and look for alternative solutions. Sampling was carried out deliberately from respondents who had criteria that were in accordance with the research. The samples used in this research were children who were introduced to Arabic. After asking questions from respondents consisting of 16 people from general public backgrounds, students and university students representing the results of the System Usability Scale calculation, there were interpretation results of the average SUS Score, namely 76.09375. So the User Interface design prototype of "Arabic Educational Game" is included in the Good scale. Based on the results of the research, it is concluded that the User Interface has completed the design of the Design Thinking method with the Arabic Educational game to make it more interesting and easier to use, so that it can meet needs and provide interesting gaming experience for users.
RANCANG BANGUN APLIKASI SIMULASI MINING PADA JARINGAN BLOCKCHAIN BITCOIN Sugandi, Hatami Karsa; Harahap, Nazruddin Safaat; Cynthia, Eka Pandu; Yanto, Febi; Sanjaya, Suwanto
Sebatik Vol. 26 No. 1 (2022): Juni 2022
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v26i1.1875

Abstract

Bitcoin merupakan salah satu dari mata uang digital yang dalam regulasinya tidak diatur oleh siapa pun seperti lembaga, organisasi maupun pemerintahan. Bitcoin menggunakan teknologi kriptografi atau yang biasa dikenal dengan teknologi Blockchain. Teknologi ini merupakan teknologi penyimpanan data atau transaksi kedalam sebuah block, dimana setiap proses penambahan block baru harus melalui proses validasi oleh sistem sesuai dengan konsensus yang berlaku. Untuk mengamankan jaringan Blockchain miliknya, bitcoin menggunakan algoritma konsensus Proof of Work (PoW). Proses validasi block inilah yang dinamakan dengan proses mining. Mining dilakukan untuk menambahkan transaksi kedalam Block dengan cara memecahkan teka-teki matematika dari algoritma PoW dengan cara memberikan komputasi power dari GPU oleh miner. Dikarenakan membutuhkan power yang besar, para miner diberi imbalan berupa bitcoin. Besaran bitcoin yang diterima tergantung dari hash power miner. Fenomena mining bitcoin menjadi trend bisnis pada masa kini karena menjanjikan keuntungan. Fenomena ini membuat banyak orang awam untuk ikut melakukan mining, tanpa mengetahui apa yang sebenarnya akan dilakukan. Maka dari itu simulasi ini dibuat dengan tujuan untuk mengedukasi bagaimana proses yang terjadi pada mining Bitcoin dengan cara visualisasi melalui Aplikasi web yang nantinya akan dibangun menggunakan bahasa pemrograman javascript dan diharapkan dapat menggambarkan proses mining pada blockchain dengan menerapkan algoritma konsensus Proof of Work di dalamnya.
SISTEM TANYA JAWAB ILMU KEISLAMAN DENGAN MODEL LARGE LANGUAGE MODELS Aprilia, Risma; Nazruddin Safaat Harahap; Febi Yanto; Yusra
Jurnal Informatika dan Rekayasa Elektronik Vol. 7 No. 1 (2024): JIRE APRIL 2024
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v7i1.1156

Abstract

Tantangan serius dalam pemahaman Ilmu Keislaman oleh masyarakat menyoroti kebutuhan akan solusi inovatif untuk mendukung pengembangan spiritual dan budaya. Meskipun teknologi terus maju, pencarian informasi terpercaya terkait Ilmu Keislaman masih terhambat oleh keterbatasan teknik pencarian internet saat ini. Maraknya penggunaan kecerdasan buatan, seperti Chat GPT, menawarkan potensi besar dalam mendukung proses pembelajaran Ilmu Keislaman. Dalam konteks ini, teknologi Large Language Models (LLM), seperti model GPT yang dikembangkan oleh OpenAI, menjadi kunci dalam pembuatan sistem tanya jawab Ilmu Keislaman, dengan parameter yang besar, LLM dirancang untuk memahami bahasa manusia dengan lebih baik. Pada penerapannya sistem tanya jawab ilmu keislaman ini menghasilkan akurasi sebesar 82%. Hal ini didasarkan oleh pengujian dengan partisipasi dari para mahasiswa tafsir dan hadits, dalam memberikan jawaban yang sesuai dengan konteks Ilmu Keislaman yang diberikan. Hal ini bermakna, penggunaan teknologi LLMS dalam konteks Ilmu Keislaman berpotensi untuk memperluas akses dan meningkatkan pemahaman masyarakat terhadap aspek-aspek kunci, namun diperlukan dimodifikasi untuk mendapat hasil yang maksimal.
Implementasi Algoritma Convolutional Neural Network (Resnet-50) untuk Klasifikasi Kanker Kulit Benign dan Malignant: Implementation of Convolutional Neural Network Algorithm (ResNet-50) for Benign and Malignant Skin Cancer Classification Gusti, Gogor Putra Hafi Puja; Haerani, Elin; Syafria, Fadhillah; Yanto, Febi; Gusti, Siska Kurnia
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1398

Abstract

Kulit sebagai organ terluar yang menutupi seluruh bagian tubuh manusia rentan terhadap berbagi penyakit, salah satunya kanker kulit. Penggunaan teknologi malignant, khususnya Convolutional Neural Network (CNN) diangkat menjadi topik penelitian karena kemampuan CNN untuk secara otomatis mengenali fitur penting dalam klasifikasi citra medis kanker kulit. Oleh karena itu dilakukan penelitian pengklasifikasian penyakit kanker kulit benign (jinak) dan malignant (ganas) menggunakan algoritma CNN arsitektur ResNet-50 dengan dataset berupa 5000 data latih kanker kulit benign dan 4600 data latih kanker kulit malignant.Model CNN yang telah dirancang dengan epoch 50 menggunakan optimizer Adam dan batch size sebesar 54 serta melibatkan beberapa teknik augmentasi data guna meningkatkan keragaman dataset untuk kemudian model hasil perancangan diimplementasikan ke dalam tampilan sebuah website dengan menggunakan Flask sebagai kerangka kerja yang menghubungkan antara model deep learning dan website agar bisa diakses oleh pengguna. Metode pengujian blackbox dilakukan demi memastikan sistem dapat melakukan klasifikasi kanker kulit melalui input berupa citra medis kedalam 2 kelas yaitu benign dan malignant dengan baik serta didapatkan hasil akurasi model sebesar 94,88 % dan loss sebesar 13,24%.
Analisis Sentimen Terhadap Sebuah Figur Publik di Twitter Menggunakan Metode K-Nearest Neighbor Yenggi Putra Dinata; Yusra; Fikry, Muhammad; Yanto, Febi; Cynthia, Eka Pandu
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1904

Abstract

The development of online media, particularly through social media platforms like Twitter, has created a vast stage for various activities, including political campaigns and public opinion on public figures. When information technology advances rapidly, public opinion can be conveyed without time constraints through social media. Twitter, with its character limitations and the use of hashtags by users, is considered easier to gather information about existing opinions and sentiments. Currently, social media is widely used for communication and making friends, but also for other activities. Advertising products, buying and selling anything, including advertising political parties and campaigning for members of Congress or presidential candidates. This research focuses on sentiment analysis towards Puan Maharani, the Speaker of the Indonesian House of Representatives (DPR RI), using data from the social media platform Twitter. Twitter, as a platform that allows users to express opinions in a concise format, is used as the main source of information in this research. The K-Nearest Neighbor algorithm for sentiment analysis technique is utilized to classify individual tweets into positive or negative categories regarding views on Puan Maharani. The methods used in this research include data crawling, labeling, and data preprocessing, which involve case folding, cleaning, tokenizing, negation handling, normalization, stopword removal, and stemming. For the classification process, the K-Nearest Neighbor method, feature weighting (TF-IDF), and feature selection (thresholding) are employed, with a threshold value of 0.001. The data used comprises 9,000 tweets in the Indonesian language. The results of the testing conducted in the K-Nearest Neighbor method, using confusion matrices, with 6 different values of K (3, 5, 7, 9, 11, 13), with comparison mechanisms of 90:10, 80:20, and 70:30 achieved the highest accuracy of 90.00% with K = 11 from the comparison using the 90:10 ratio
Classification of Palm Oil Ripeness Level using DenseNet201 and Rotational Data Augmentation Nabyl Alfahrez Ramadhan Amril; Yanto, Febi; Elvia Budianita; Suwanto Sanjaya; Fadhilah Syafria
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1937

Abstract

Indonesia is a country in Southeast Asia with the largest palm oil production in the world. Based on Indonesian Central Statistics Agency data, in 2022 Indonesia produced 46,8 million Tons of Crude Palm Oil (CPO). To produce a high-quality oil, palm oil fruit must be harvested in an optimal condition. But, even a experienced and trained person found it difficult to identify whether the fruit is ripe or raw. In this research theres two type of classification which is ripe and raw, this is because palm oil milling factory only accept pure ripe palm oil fruit and not half ripe or almost ripe. The data that is used in this reseacrh was collected from two sources, the first source is from https://www.kaggle.com/datasets/ahmadfathan/kematangansawit and the second source was collected manually by going to palm oil plantation. The total of data that is used for this research is 1000 data and 1000 augmented data. Dense Convolutional Network (DenseNet) that is used in this research is a CNN architecture that was first introduced in 2017. Compared to DenseNet121 and DenseNet169, DenseNet201 is proven to have a higher level of accuracy. The 90:10 data scheme succeeded in getting the highest accuracy with a total accuracy of 97.50% with a learning rate of 0.001 and a dropout of 0.01
Deep Learning Menggunakan Algoritma Xception dan Augmentasi Flip Pada Klasifikasi Kematangan Sawit Masaugi, Fathan Fanrita; Yanto, Febi; Budianita, Elvia; Sanjaya, Suwanto; Syafria, Fadhilah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1938

Abstract

Palm oil is an important commodity in Indonesia, especially as Indonesia is the highest palm oil exporting country in the world. Ripe palm fruit is marked by a change in color of the fruit from black to reddish yellow. Apart from that, immature palm fruit has a negative and significant effect on CPO production. The data collection process was carried out by directly taking pictures of palm fruit on oil palm plantations and data obtained from Kaggle. The total amount of data is 1000 images and 1000 data resulting from flip augmentation. The Xception algorithm is an algorithm in deep learning which stands for Extreme version of Inception. This combination was then proven to provide better accuracy in classifying images from a dataset. The optimizer used is the optimizer in TensorFlow, namely Adam (Adaptive Moment Estimation) using learning rate and dropout values. Images of mature and immature palm oil were classified using the Xception algorithm with augmented and without augmented data. In addition, experiments were carried out by changing the parameter values ??of learning rate to 0.1, 0.01, 0.001 and dropout to 0.1, 0.01, 0.001. It was found that the data division was (90;10) with the best accuracy reaching 95%. Test parameters carried out by trialling were proven to increase accuracy when compared to without using parameters and flip augmentation. The best accuracy of the Xception model is 95% on augmented data with a learning rate of 0.001 and a dropout of 0.1.
Implementasi VGG 16 dan Augmentasi Zoom Untuk Klasifikasi Kematangan Sawit Mazdavilaya, T Kaisyarendika; Yanto, Febi; Budianita, Elvia; Sanjaya, Suwanto; Syafria, Fadhilah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1940

Abstract

Indonesia is a country that has very abundant palm oil plantations and makes palm oil one of the largest export commodities in Indonesia. Fruit maturity on oil palms has a significant influence on palm oil and kernel production. The level of ripeness in palm oil fruit can affect several contents in it, such as tocopherol content, yield and FFA. The classification will be divided into 2 classes, namely between ripe and immature fruit with data on 500 images of ripe fruit and 500 images of immature fruit, data taken from the Kaggle site and private gardens taken using a cellphone camera. The data that has been obtained is augmented which is useful for enriching the data to make it more abundant. Data augmentation uses zoom augmentation and makes the original 1000 data increase to 2000 data. The model used is VGG 16 which is part of deep learning. The existing dataset is then preprocessed, resized and rescaled, then divides the data into 3, namely train, test and valid data. After dividing the data, then carry out the classification process with VGG 16 and set the hyperparameters after that the model will learn with 20 epochs. The model will learn with 57 schemes to compare and find highest accuracy. After the model has finished learning, it is evaluated using a confusion matrix. The results obtained were that the 90:10 data division using data augmentation with a learning rate of 0.01 and a dropout of 0.001 obtained the best accuracy, reaching 93.8%.
Desain Aplikasi Informasi Akademik UIN Suska (Suska Mobile) Menggunakan Metode Lean UX Muhammad Haiqal Dani; Reski Mai Candra; Muhammad Irsyad; Febi Yanto
SATIN - Sains dan Teknologi Informasi Vol 9 No 2 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33372/stn.v9i2.1048

Abstract

Pemanfaatan Teknologi Informasi dan Komunikasi (TIK) menjadi kunci dalam membantu Perguruan Tinggi dalam memberikan layanan kepada mahasiswanya. Salah satu bentuk pemanfaatan TIK yang khusus ditujukan untuk mahasiswa adalah sistem informasi akademik mahasiswa. Sistem informasi akademik merupakan elemen penting dalam sebuah instansi pendidikan. Sistem informasi akademik dimiliki semua instansi pendidikan terutama Universitas. Namun, dari hasil pengamatan sarana sistem informasi akademik di Universitas Islam Negeri Sultan Syarif Kasim Riau masih belum efektif dan efisien terutama dalam bentuk mobile. Kondisi ini mengakibatkan sistem informasi akademik tidak memberikan pengalaman pengguna yang optimal. Tujuan dari penelitian ini adalah untuk merancang desain prototype sistem informasi akademik UIN Ssuska (Suska Mobile) dengan memperhatikan aspek kebergunaan (user experience) dan aspek tampilan antarmuka (user interface). Penelitian ini menggunakan pendekatan metode Lean UX yang terdiri dari 4 tahapan Declare Assumptions yang menghasilkan asumsi permasalahan, Create an Minimum Viable Product yang menghasilkan rancangan prototype, Run an Experiment melakukan demonstrasi dan Feedback and Research yang menghasilkan hasil pengujian serta perbaikan dari rancangan prototype. Hasil akhir penelitian ini adalah prototype yang dibangun menggunakan aplikasi figma dan telah diuji kepada 8 responden menggunakan pengujian System Usability Scale (SUS) dengan nilai 83,75%.
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