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All Journal Teknika Journal of Economics, Business, & Accountancy Ventura SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Informatika dan Teknik Elektro Terapan JTT (Jurnal Teknologi Terpadu) Jurnal CoreIT Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Inotera Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi Krea-TIF: Jurnal Teknik Informatika Jurnal Riset Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika Ideguru: Jurnal Karya Ilmiah Guru Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) SINTA Journal (Science, Technology, and Agricultural) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer J-Intech (Journal of Information and Technology) Jurnal Indonesia Raya Knowbase : International Journal of Knowledge in Database Jurnal Dehasen Mengabdi SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Muhammad Fikry
Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Innovative funding solution for special projects: Crowd funding Wahjono, Sentot Imam; Marina, Anna; Fikry, Muhammad; ., Anggraeni
Journal of Economics, Business, and Accountancy Ventura Vol. 18 No. 1 (2015): April - July 2015
Publisher : Universitas Hayam Wuruk Perbanas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14414/jebav.v18i1.383

Abstract

The aim of this paper is to examine the influence of crowd funding knowledge, applica-tion, platform, and project initiator toward successful crowd funding. This study conducted by quantitative approach, data have been collected with web-based ques-tionnaires via Kickstarter.com direct message and e-mail to 200 successful crowd funding project initiators as a sample and as much 152 sets questionnaire returned by a complete answer and should be analyzed further. Deployment and data collection take 3 month from October to December 2013. This study found evidence that crowd funding knowledge, crowd funding application, crowd funding platform, and project initiator has positive and significant relationship toward the success of crowd funding. The implication from this research is crowd funding can be a source of capital to finance the projects, not just rely on traditional sources of financing just like banking and capital markets. Crowd funding can be innovative funding solution.
Klasifikasi Sentimen Tweet Masyarakat terhadap Kendaraan Listrik Menggunakan Support Vector Machine Ananda, Nuari; Fikry, Muhammad; Yusra, Yusra; Handayani, Lestari; Iskandar, Iwan
Jurnal Informatika Universitas Pamulang Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i4.36754

Abstract

Sentiment analysis involves using classification algorithms to analyze public opinions and feelings in text. Within the automobile industry, electric vehicles (EVs) stem from the circular economy and represent a novel technology under investigation in sentiment classification studies. The Support Vector Machine (SVM) algorithm is commonly used in this research due to its superior accuracy compared to other algorithms. The goal of this study is to apply SVM variable selection techniques to enhance sentiment analysis quality. Python is the programming language used to build the sentiment classification model, which involves feature selection using TF-IDF, training with cross-validation and grid search, evaluation using a confusion matrix, and storing the dataset in a MySQL database. The research focuses on the sentiment classification of 3000 public tweets about electric vehicles on Twitter. Through various scenarios, it was observed that the accuracy of sentiment classification varied depending on factors such as randomizing data, handling negation, and using different types of features like unigrams or bigrams. The highest accuracy achieved was 84% using a scenario with random data, negation handling, and unigram features. Overall, this research highlights the impact of randomizing data and selecting appropriate features on sentiment classification accuracy for electric vehicles on Twitter.
Penerapan Naïve Bayes Classifier dalam Klasifikasi Sentimen Publik di Twitter terhadap Puan Maharani Hidayat, Rizki; Fikry, Muhammad; Yusra, Yusra; Yanto, Febi; Cynthia, Eka Pandu
JUKI : Jurnal Komputer dan Informatika Vol. 6 No. 1 (2024): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v6i1.479

Abstract

Twitter adalah salah satu jejaring sosial terpopuler di Indonesia, dengan 18,45 juta pengguna aktif pada tahun 2022. Politisi berpengaruh Puan Maharani menjadi topik hangat di pesta ulang tahunnya di tengah protes harga bahan bakar. Analisis sentimen dapat membantu memahami keseluruhan sentimen yang diungkapkan di Twitter tentang Puan Maharani. Dua jenis dataset yang digunakan dalam penelitian ini, yaitu dataset tidak seimbang (9000 tweet: 7800 positif, 1200 negatif) dan dataset seimbang (2400 tweet: 1200 positif, 1200 negatif). Metode Naive Bayes classifier digunakan untuk klasifikasi sentimen, meliputi pengumpulan data, pelabelan, preprocessing, pembobotan TF-IDF, seleksi fitur, pembagian data, klasifikasi Naive Bayes, dan evaluasi dengan confusion matrix. Data dibagi dengan rasio 70:30, 80:20 dan 90:10 untuk data latih serta data uji. Feature selection menggunakan threshold 0,001. Merujuk hasil penelitian yang dilaksanakan, bisa disimpulkan bahwsanya analisis sentimen dapat menjadi alat yang efektif untuk memahami pendapat masyarakat khususnya netizen di platform Twitter terkait dengan persepsi terhadap Puan Maharani. Nilai akurasi tertinggi dari dataset tidak seimbang didapatkan yaitu sebesar 88.89% pada rasio pembagian data latih dan data uji 90:10 serta akurasi tertinggi dari dataset seimbang sebesar 81.0% pada rasio pembagian data 90:10.
Penerapan Chatbot pada Aplikasi Web Tanya Jawab Tentang Fiqih Jual Beli Islam Menggunakan LangChain Nurhapiza, Nurhapiza; Harahap, Nazaruddin Safaat; Fikry, Muhammad; Affandes, Muhammad
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5148

Abstract

Fiqh is the field that studies Islamic rules on how humans behave, both in speech and action. Islamic Fiqh of buying and selling is a branch of fiqh that concentrates on the laws and rules relating to transactions and social interactions that occur in the daily lives of Muslims. There are many sources of learning about the fiqh of buying and selling, including books and the internet. However, manual searches can take a long time and make it difficult for some people to gain in-depth understanding. The application of a chatbot to a question and answer web application can provide a solution to provide easier access. This research aims to provide an effective and efficient solution in understanding fiqh muamalah (Islamic buying and selling). This research develops a question and answer system about the fiqh of Islamic buying and selling to make it easier for users to understand, by utilizing a deep learning approach through technologies such as LangChain, OpenAI, Large Language Model, and ChatGPT 3.5 turbo. Implementation is done through a chatbot web application that provides an initial display and menu, allowing users to ask questions about the fiqh of Islamic buying and selling and see the answers and references. Testing was conducted by students of UIN Sultan Syarif Kasim Riau and an ustaz who has a good understanding of fiqh muamalah using ten questions that were tested through the question and answer web application as a guide. The test results showed an answer evaluation of 88.8% with a very suitable category regarding the correctness of the responses given.
Implementasi Data Mining Untuk Prediksi Stok Penjualan Keramik dengan Metode K-Means Dinata, Ferdian Arya; Nazir, Alwis; Fikry, Muhammad; Afrianty, Iis
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5200

Abstract

Ceramics has become one goods that consumers show interest in every year, so many companies are interested in selling ceramics. However, ceramic sales must meet and balance changing customer needs as well as problems found regarding ceramic products and customers, such as a lack of stock of ceramic products which results in customers not placing orders and product sales not meeting targets. So it is necessary to group ceramics to anticipate the risks that the company will accept by utilizing the data mining process using past data. This research uses the K-Means method found in data mining. The objective of this research is to group determine sales of brands that have potential for additional stock in the future and to test the data using the DBI (Davies Bouldin Index) which is carried out by testing the distance values between clusters through a series of experiments. This research uses data for the last 1 year from January 2022 to December 2022 with a total of 156 data using 9 attributes, namely brand, item code (FT, WT) and size (40x40, 25x25, 50x50, 25x40, 60x60, 20x40). The results of the research using the K-Means method, the best-selling brand is cluster 2, the best-selling brand is cluster 1 and the best-selling brand is cluster 0. The best-selling brand is HRM, the best-selling brand is VALENSIA and the best-selling brand is MCC. Test results using the DBI method with a validity of 01.013 show that the best cluster is obtained at k=3 using the elbow method. It is hoped that this research will contribute to related companies as support for decision making.
Pengembangan Media Monopoli dalam Meningkatkan Motivasi serta Minat pada Mata Pelajaran IPS Kelas 7 SMP Fikry, Muhammad; Arsyad, Muhammad Naharuddin; Sunuyeko, Nurcholis
Ideguru: Jurnal Karya Ilmiah Guru Vol 9 No 3 (2024): Edisi September 2024
Publisher : Dinas Pendidikan, Pemuda dan Olahraga Daerah Istimewa Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51169/ideguru.v9i3.987

Abstract

The inclusion of Hindu-Buddhist history in the Social Studies (IPS) curriculum plays a pivotal role in fostering historical thinking skills among students. However, the reality at SMP Sunan Ampel Poncokusumo Malang suggests that the IPS learning process on this subject matter often relies heavily on lecture-based methods, failing to engage students actively. While discussion methods have been introduced to address this issue, a comprehensive presentation of the historical material has yet to be achieved. Therefore, the researchers undertook the development of the IPS learning process at SMP Sunan Ampel Poncokusumo. This study aims (1) to elucidate the development of monopoly learning media in enhancing student motivation and interest in IPS subjects, and (2) to explain the evaluation results of the development of monopoly learning media in improving student motivation and interest in IPS subjects. The method used in this design is developmental research utilizing the ADDIE planning technique. The design process comprises five stages: analysis, design, development, implementation, and evaluation. Based on the validation results from subject matter experts and media experts, including IPS teachers from the school and experts from Insan Budi Utomo University in Malang, it can be concluded that the Monopoly media development received a final assessment of 87.5% from media and subject matter expert validation, falling under the "highly valid" category. Meanwhile, the student response questionnaire yielded a score of 88%, meeting the criteria of "excellent." The monopoly learning media that has been developed meets validity standards both in terms of media and material, so it can be concluded that the use of monopoly learning media can increase students' motivation and interest in learning in social studies learning.
Chatbot Berbasis Perintah untuk Membangkitkan Use Case Diagram Fikry, Muhammad; Yusra, Yusra
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2023: SNTIKI 15
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Chatbot dapat membantu pemodelan perangkat lunak sebelum perangkat lunak tersebut diimplementasikan. Untuk membangun model, Unified Modeling Language (UML) digunakan untuk mengkomunikasikan berbagai pandangan berbeda dari perangkat lunak yang dikembangkan. Dari 14 jenis diagram UML, penelitian-penelitian terkait hanya membangkitkan class diagram, state chart diagram, dan activity diagram. Pada penelitian ini, dirancang bangun chatbot untuk membangkitkan use case diagram. Hal ini dikarenakan use case diagram dibuat terlebih dahulu dalam fase analisis sebelum adanya diagram-diagram lain, sehingga berfungsi sebagai titik awal yang memberikan gambaran tingkat tinggi tentang fungsionalitas perangkat lunak. Untuk saat ini, chatbot hanya menerima masukan perintah, belum teks berbahasa alami. Analisa dilakukan untuk menspesifikasikan perintah yang dimasukkan oleh pengguna, dialog yang berlangsung antara pengguna dan chatbot, dan action yang dilakukan oleh chatbot. Setelah tahapan perancangan dan implementasi, dilakukan pengujian blackbox. Berdasarkan hasil pengujian blackbox terhadap seluruh fungsionalitas chatbot, diketahui bahwa chatbot telah sesuai dengan hasil analisa dan perancangan.
PENERAPAN METODE STRING MATCHING JARO WINKLER PADA SISTEM DETEKSI TINGKATAN HADITS Yani, Muhamamd; nurdin, nurdin; Fikry, Muhammad
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i1.5543

Abstract

Hadits memiliki data sanad, matan dan perawi yang pendeteksian hadits digunakan untuk menghasilkan tingkatan-tingkatan hadits yang selama ini banyak hadits diketahui oleh ummat tapi tidak mengetahui dasar haditsnya dan derajat hadits tersebut, untuk mengatasi masalah ini, maka penulis membuat aplikasi pengenalan tingkatan-tingkatan hadits menggunakan metode string matching jaro winkler dimana pendeteksian hadits telah dikatagorikan oleh penulis sehingga dapat menghasilkan derajat hadits yang dicari oleh pengguna yang telah disepakati oleh para ulama ulama hadits. Rancangan sistem ini adalah menggunakan database sistem yang akan menampung berbagai macam kategori tingktan-tingkatan hadits yang telah dipilih oleh penulis untuk dimasukkan kedalam database. Dengan merancang dan membangun aplikasi ini maka diharapkan dapat menghasilkan hasil yang optimal sehingga dapat digunakan untuk referensi mengamalkan hadits didalam pelaksanaan ibadah bagi ummat Islam khususnya bagi masyarakat awam yang tidak mempelajari ilmu hadits
End-to-End Text-to-Speech for Minangkabau Pariaman Dialect Using Variational Autoencoder with Adversarial Learning (VITS) Fakhrezi, Muhammad Dzaki; Yusra; Muhammad Fikry; Pizaini; Suwanto Sanjaya
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 1 (2025): June 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i1.9909

Abstract

Language serves as a medium of human communication to convey ideas, emotions, and information, both orally and in writing. Each language possesses vocabulary and grammar adapted to the local culture. One of the regional languages that enriches Indonesian as the national language is Minangkabau. This language has four main dialects, namely Tanah Datar, Lima Puluh Kota, Agam, and Pesisir. Within the Pesisir dialect, there are several variations, including the Padang Kota, Padang Luar Kota, Painan, Tapan, and Pariaman dialects. This study discusses the application of Text-to-Speech (TTS) technology to the Minangkabau language, specifically the Pariaman dialect, using the Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech (VITS) method. This dialect needs to be preserved to prevent extinction and supported through technological development that broadens its use. The VITS method was chosen because it is capable of producing natural and high-quality speech. The research stages include voice data collection and recording, VITS model training, and speech quality evaluation using the Mean Opinion Score (MOS). The final results show a score of 4.72 out of 5, indicating that the generated speech closely resembles the natural utterances of native speakers. This TTS technology is expected to support the preservation and development of the Minangkabau language in the Pariaman dialect, as well as enhance information accessibility for its speakers.
Klasifikasi Sentimen Terhadap Topik Pindah Ibu Kota Negara Pada Twitter Menggunakan Metode Naïve Bayes Classifier Dermawan, Jozu; Yusra, Yusra; Fikry, Muhammad; Agustian, Surya; Oktavia, Lola
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7475

Abstract

Towards the middle of 2019, President Joko Widodo announced plans to relocate Indonesia's capital city. This caused pros and cons in the community, which were widely observed in various social media. To quickly measure the level of public sentiment towards the policy of moving the National Capital City (IKN), whose construction is already underway, a classification system that has good performance is needed. This research proposes a classification of public sentiment on the topic using the Naïve Bayes Classifier method. The data used in this study amounted to 4000 tweets that have been classified into two classes, namely 2000 positive class data and 2000 negative class data. The purpose of this research is how to apply the Naïve Bayes Classifier method in classifying sentiment on the topic of moving the nation's capital and determine the accuracy level of the method. The application of the Naïve Bayes classification method using TF-IDF features to classify 10% of the data as testing data resulted in an accuracy of 77.00%, for a precision value of 77.06%, recall 77.08% and f1-score of 77.00%. Based on the results achieved, the Naïve Bayes Classifier method is good at text classification tasks, with a fairly good accuracy rate.
Co-Authors -, Yusra Abdillah, Rahmad Ahadi, Ridho Alwis Nazir Ananda, Nuari Andini, Nanda Anggraeni . Anggraeni, Ni Ketut Pertiwi Anna Marina Arnawan Hasibuan Asrianda Asrianda Ayu Fransiska Baehaqi Bahari, Bayu Dwi Prasetya Damayanti, Elok Dermawan, Jozu Detha Yurisna Dinata, Ferdian Arya Diqti, Fadillah Fauziah Eka Pandu Cynthia Eka Pandu Cynthia, Eka Pandu Eko Sumartono, Eko Elin Haerani Elin Haerani Elin Haerani Elvia Budianita Elvina Afriani Fadhilah Syafria Fakhrezi, Muhammad Dzaki Faresya, Natasya Febi Yanto Fitri Insani Fitri Insani Harahap, Nazaruddin Safaat Hasugian, Leonardo Hidayat, Rizki Husaini Ibnu Surya Iis Afrianty Inggih Permana Khaidar, Al kurnia, fitra Lestari Handayani Lola Oktavia Lola Oktavia Mei Lestari, Mei Muhammad Abdillah Muhammad Affandes Muhammad Dhuha, Teuku Nabil Muhammad Irsyad Muhammad Ravil Muhammad Yani, Muhammad Munadila, Aura Munirul Ula Naharuddin Naharuddin Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Ndruru, Arlan Joliansa Nurcholis Sunuyeko, Nurcholis Nurdin Nurdin Nurdin Nurhapiza, Nurhapiza Oktavia, Lola Pizaini Pizaini Prananda, Alga Putra, Wahyu Eka Putri Mardatillah Rahma Yunita, Rahma Rahmat Rizki Hidayat Rahmatillah, Siska Yuna Ramadanu Putra Reski Mai Candra Rinaldi Syarfianto Ritonga, Sinta Wahyuni Sagala, Ruflica Saputra, Ikhsan Dwi Sayed Omas Tutus Arifta Sayed Sentot Imam Wahjono Sofiah Surya Agustian Suwanto Sanjaya Taufik Hidayat Tiara Dwi Arista Wan Sobri Amin Wirdiani, Putri Syakira Yani, Muhamamd Yani, Susmi Syahfrida Yaskur Bearly Fernandes Yenggi Putra Dinata Yolanda, Khovifah Yossie Yumiati Yuda Zafitra Fadhlan Yusra Yusra Yusra . YUSRA YUSRA Yusra, Yusra Zukhruf, Muhammad Firmansyah