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All Journal Semesta Teknika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL ILMIAH INFORMATIKA JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika Kaputama (JIK) Jurnal Mantik JIKA (Jurnal Informatika) Jurnal Abdimas Komunikasi dan Bahasa J-Intech (Journal of Information and Technology) Jurnal Ilmu Komputer JURNAL KESEHATAN, SAINS, DAN TEKNOLOGI (JAKASAKTI) Jurnal Pengabdian Masyarakat Bangsa Jurnal Manuhara: Pusat Penelitian Ilmu Manajemen Dan Bisnis
Antonius Yadi Kuntoro
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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PENERAPAN DATA MINING DALAM PENILAIAN KINERJA AKADEMIK SISWA/I SMP YPI PULOGADUNG DENGAN METODE K-MEANS CLUSTERING Nabilatul Adzra, Salsa; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10396

Abstract

Improving the quality of education requires an objective, systematic, and data-driven academic performance assessment system. One technological approach that can be used to support this is data mining, specifically the K-Means Clustering method. This studyaims to cluster student academic data based on report card grades for the odd semester of the 2024/2025 academic year using the K-Means algorithm. Data processing was performed using RapidMiner software, with the optimal number of clusters selected at three (K=3) based on the Davies Bouldin Index (DBI) of 0.077. The clustering results form three main categories: Cluster 0 contains 174 students with average academic performance, Cluster 1 contains only one student with the lowest performance, and Cluster 2 contains 107 students with high academic performance. This grouping provides more structured and useful information for schools in designing targeted academic development strategies. This study demonstrates the effectiveness of the K-Means Clustering method in identifying student academic patterns and classifications.
ANALISIS SENTIMEN PROGRAM MAKAN GRATIS PADA PLATFORM X MENGGUNAKAN AGORITMA NAÏVE BAYES Laia , Metodius Modianus; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL ILMIAH INFORMATIKA Vol 13 No 02 (2025): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v13i02.10427

Abstract

The Free Meal Program is one of the government’s strategic policies that has received various public responses, especially on social media Platform X (formerly Twitter). This study aims to analyze the level of public sentiment toward the Free Meal Program on Platform X. The classification method used is the Naïve Bayes algorithm, with model validation performed using the K-Fold Cross Validation technique. A total of 3,600 Indonesian-language tweets relevant to the Free Meal Program were collected through a web scraping process, followed by text preprocessing steps such as case folding, cleaning, tokenizing, stopword removal, and stemming. Data labeling was carried out semi-automatically using the IndoBERT model, and the tweets were then classified into two sentiment categories: positive and negative. The Naïve Bayes model was trained using the TF-IDF representation and tested on a test set comprising 20% of the total dataset. The evaluation results showed that the Naïve Bayes algorithm achieved an accuracy of 86.46%, precision of 86.55%, recall of 95.25%, and an F1-score of 90.77% on 458 test tweets. Validation using 10-fold cross-validation yielded an average accuracy of 86.74%. These results indicate that the Naïve Bayes algorithm demonstrates good classification performance and stable generalization in classifying public sentiment regarding the Free Meal Program. This research is expected to serve as a supporting tool in mapping public opinion based on social media
Implementation of Warehouse Inventory Management System at CV Cahaya Karunia Mulia Hermawan, Muhamad Taufik; Hasan, Fuad Nur; Kuntoro, Antonius Yadi
JURNAL KESEHATAN, SAINS, DAN TEKNOLOGI (JAKASAKTI) Vol. 4 No. 3 (2025): JURNAL KESEHATAN, SAINS, DAN TEKNOLOGI (JAKASAKTI)
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/js.v4i3.4804

Abstract

The development of information technology has driven efficiency in various aspects of company operations, including inventory management. CV Cahaya Karunia Mulia, a company engaged in marble distribution, still uses Google Spreadsheets as the main tool for warehouse inventory management. This condition creates the risk of data discrepancies and hinders operational efficiency. This research aims to analyze requirements, design, implement, and test a web-based warehouse inventory management system for the company. The method used is the Waterfall approach, consisting of requirement analysis, system design, implementation, testing, as well as deployment and maintenance. The results show that the developed system is able to meet the company’s functional and non-functional requirements, with key features such as master data management, inventory transactions, and stock monitoring. System testing indicates that all functions run as expected and are capable of improving efficiency, accuracy, and effectiveness in warehouse inventory management. Therefore, this system can serve as a solution that significantly supports smooth operational processes.
IMPLEMENTATION OF BCRYPT ALGORITHM ON WEBSITE-BASED HASHING GENERATOR USING LARAVEL FRAMEWORK Febrian, Dio; Christian, Yoel; Sutisna, Alifan Widad; Budiarto, Gunawan; Syukur, Muhammad; Ramadhan, Xena Hadi; Kuntoro, Antonius Yadi; Fahlapi, Riza
Journal of Information System, Informatics and Computing Vol 7 No 2 (2023): JISICOM (December 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v7i2.1130

Abstract

Implementation of the Bcrypt algorithm on a website-based hashing generator using the Laravel framework has been carried out in this study. The background of this research is based on the development of information technology which has affected many aspects of human life, where data and information are very important and need to be protected. Web-based information systems are vulnerable to security threats, such as wiretapping and intrusion by unauthorized parties. Therefore, the implementation of information security aims to overcome these problems and provide solutions both technically and non-technically. This research uses the Laravel framework, an open-source PHP framework that enables the development of web applications with modules that optimize PHP performance. Bcrypt and salt algorithms are used in the hashing process to protect user data. The results of the research show that using Laravel as the right framework for making hashing generators. The result of the hashing process produces a constant value of 60 characters, even if the input text is more than 60 characters with random text. The cost factor, which is a factor that regulates hashing power, affects the time required for the hashing process and hash verification. Using the Bcrypt generator tool is useful in cross-browser testing, especially in tests involving hashed passwords. With this tool, many valid bcrypt password hashes can be generated for testing. This research makes an important contribution in improving the security of web-based information systems by applying the Bcrypt algorithm to the hashing process. This implementation can provide better data protection for users and improve overall system performance.
Mengenal Dan Memanfaatkan Teknologi Artificial Intelligence Pada Yayasan Yatim Piatu Dan Sosial IRMA Kuntoro, Antonius Yadi; Novianti, Deny; Fahlapi, Riza; Syarif, Mahmud
Jurnal Abdimas Komunikasi dan Bahasa Vol. 5 No. 1 (2025): Juni 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abdikom.v5i1.8916

Abstract

Pengembangan ilmu pengetahuan dan teknologi (IPTEK) memberikan peran yang sangat signifikan dalam meningkatkan kesejahteraan dan taraf hidup ekonomi masyarakat. Salah satu bidang yang dapat merasakan kehadiran teknologi yaitu bidang pendidikan organisasi kemasyarakatan, demikian juga dengan Yayasan Yatim Piatu dan Sosial IRMA yang berada di bilangan Tegal Parang, Jakarta Selatan. Untuk mengelola data maka organisasi diperlukan kemampuan administrasi yang baik, juga dengan anggotanya dalam mengerjakan tugas sekolah yang juga memerlukan kecapakan dalam membuat tulisan, sehingga data dan materi bisa tertata dengan baik dan harmonis bagi kegiatan organisasi. Dalam rangka menunaikan salah satu Tri Dharma Perguruan Tinggi, maka Universitas Bina Saran Informatika melaksanakan Pengabdian Masyarakat berupa Pelatihan untuk mengenalkan konsep dasar dan memberikan pelatihan beberapa aplikasi Artificial Intelligence atau AI secara ringan dan menyenangkan. Aplikasi AI ini dapat digunakan untuk memudahkan proses belajar dalam mengerjakan tugas sekolah dan juga sebagai media belajar dalam pengembangan kemampuan dalam memaparkan program kerja Yayasan, seperti digunakan sebagai media promosi dan publikasi organisasi. Metode pengabdian masyarakat terdiri dari 3 tahapan, yaitu tahap persiapan, tahap pelaksanaan, dan juga tahap yang terahir adalah monitoring dan evaluasi. Adapun peserta kegiatan ini adalah pengurus dan anggota Yayasan Yatim Piatu dan Sosial IRMA yang mengikuti pelatihan komputer secara offline. Dengan adanya pelatihan ini, peserta merasakan manfaat kehadiran teknologi dimana dapat membantu kegiatan sosial, pendidikan dan keagamaan bagi organisasi. Pemanfaatan AI dalam mengerjakan tugas sekolah bagi anggota dan sebagai alat kerja bagi pengurus organisasi yang bisa digunakan untuk membuat presentasi yang menarik dalam slide yang bisa dimodifikasi sesuai kebutuhan. Science and technology development (IPTEK) plays a very significant role in improving the welfare and economic standard of living of the community. One of the fields that can feel the presence of technology is the field of education, community organizations, as well as the IRMA Orphan and Social Foundation which is located in Tegal Parang, South Jakarta. To manage data, the organization needs good administrative skills, as well as with its members in doing school assignments which also require skill in making writing, so that data and materials can be well organized and harmonious for organizational activities. In order to full fill one of the Tri Dharma of Higher Education, Bina Saran Informatics University carries out Community Service in the form of Training to introduce basic concepts and provide training on several Artificial Intelligence )AI) applications in a light and fun way. This AI application can be used to facilitate the learning process in doing schoolwork and also as a learning medium in developing skills in explaining the Foundation's work programs, such as being used as a promotional media and organizational publication. The community service method consists of 3 stages, namely the preparation stage, the implementation stage, and also the last stage is monitoring and evaluation. The participants of this activity were administrators and members of the IRMA Orphan and Social Foundation who participated in offline computer training. With this training, participants feel the benefits of the presence of technology which can help social, educational and religious activities for organizations. The use of AI in doing schoolwork for members and as a work tool for organizational administrators that can be used to make interesting presentations on slides that can be modified as needed.
TREN PUBLIKASI ANALISIS KEBIJAKAN PEMERINTAH MELALUI MEDIA SOSIAL: TINJAUAN LITERATUR SISTEMATIS Kuntoro, Antonius Yadi; Fahlapi, Riza; Saputra, Dedi Dwi; Hermanto, Hermanto; Asra, Taufik; Aditya, Tommy; Adiputra, Mahesa; Rachimsah, Wildan; Nanjaya, Ahmad Fadhil
Jurnal Ilmu Komputer (JUIK) Vol 6, No 1 (2026): February 2026
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/juik.v6i1.4620

Abstract

Penelitian ini berfokus pada pemetaan perkembangan dan tren terkini dalam analisis sentimen berbasis machine learning (ML), khususnya dalam konteks evaluasi kebijakan pemerintah. Dengan menggunakan pendekatan Systematic Literature Review (SLR), sebanyak 634 artikel ilmiah yang terindeks di Scopus dan Web of Science dalam periode 2021–2025 dianalisis untuk mengidentifikasi tren terkini dalam penggunaan machine learning untuk analisis sentimen, serta aplikasinya dalam evaluasi kebijakan pemerintah. Analisis dilakukan menggunakan alat pemetaan bibliometrik Vosviewer dan CiteSpace, yang memungkinkan identifikasi dan pemetaan klaster-topik yang dominan dalam bidang ini. Hasil penelitian menunjukkan bahwa terdapat sembilan klaster utama dalam kajian analisis sentimen, di antaranya deep learning models, transformer-based models (BERT, GPT), dan real-time sentiment analysis. Di antara klaster-klaster tersebut, deep learning models menjadi pendekatan yang paling dominan, menandakan peningkatan signifikan dalam akurasi dan efisiensi analisis sentimen, yang sangat relevan untuk evaluasi kebijakan pemerintah, terutama dalam menangkap respons publik secara real-time. Penelitian ini memberikan kontribusi penting dengan memperluas pemahaman tentang perkembangan teknologi dalam analisis sentimen serta aplikasinya yang semakin berkembang dalam konteks politik dan kebijakan publik. Namun, penelitian ini juga memiliki keterbatasan terkait dengan cakupan sumber data yang terbatas hanya pada dua database utama, yakni Scopus dan Web of Science, yang mungkin tidak mencakup keseluruhan literatur terkait. Oleh karena itu, penelitian selanjutnya disarankan untuk memperluas cakupan dengan memasukkan database lain seperti EBSCO dan IEEE Xplore guna mencapai pemahaman yang lebih komprehensif dan mendalam terkait tren perkembangan analisis sentimen dalam kajian kebijakan pemerintah.
ANALISIS LINIER BERGANDA PENGARUH HARGA DAN RATING PRODUK TERHADAP VOLUME PENJUALAN PADA PLATFORM E-COMMERCE SHOPEE Kuntoro, Antonius Yadi; Fahlapi, Riza; Saputra, Dedi Dwi; Hermanto, Hermanto; Asra, Taufik; Aditya, Tommy; Adiputra, Mahesa; Rachimsah, Wildan; Nanjaya, Ahmad Fadhil
Jurnal Ilmu Komputer (JUIK) Vol 6, No 1 (2026): February 2026
Publisher : Universitas Muhammadiyah Gorontalo

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

Abstract

Perkembangan e-commerce di Indonesia mendorong pelaku usaha untuk bersaing dalam menawarkan produk yang tidak hanya berkualitas, tetapi juga kompetitif dari segi harga dan ulasan konsumen. Penelitian ini bertujuan untuk menganalisis pengaruh harga dan rating produk terhadap volume penjualan pada platform Shopee, dengan studi kasus pada toko Sista Footwear. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan analisis regresi linier berganda berdasarkan data dari 100 produk selama Januari hingga Maret 2025. Teknik pengumpulan data menggunakan teknik pengumpulan data dilakukan melalui metode dokumentasi, dengan mencatat data sekunder secara manual dari halaman produk di toko Sista Footwear di platform Shopee meliputi harga produk, rating produk (skala 1–5), jumlah produk yang terjual untuk menjamin validitas data, proses pencatatan dilakukan berulang (cross-check) pada waktu yang berbeda guna mengantisipasi perubahan dinamis pada platform e-commerce. Teknik analisis data dilakukan dengan menggunakan model regresi linier berganda untuk mengetahui pengaruh harga (X₁) dan rating (X₂) terhadap volume penjualan (Y) dengan melakukan analisis regresi, dilakukan uji asumsi klasik yang meliputi uji normalitas, uji multikolinearitas, dan uji heteroskedastisitas, untuk memastikan tidak adanya varians residual yang tidak konstan,. Berdasarkan model regresi diketahui hasil analisis menunjukkan bahwa harga memiliki pengaruh negatif signifikan terhadap volume penjualan karena setiap kenaikan harga Rp 1 menurunkan penjualan sebesar 0,000175 unit, sedangkan rating produk berpengaruh positif signifikan karena setiap kenaikan 1 poin rating meningkatkan penjualan sebesar 18,57 unit, serta model menjelaskan 5,9% bahwa variabel harga dan rating secara simultan menjelaskan variasi penjualan. Temuan ini menekankan pentingnya strategi penetapan harga yang tepat serta upaya peningkatan kepuasan pelanggan melalui rating yang tinggi untuk meningkatkan penjualan di e-commerce.
Co-Authors Adiputra, Mahesa Aditya, Tommy Ali Mustopa, Ali Anasanti, Mila Desi Ani Nuriska Safitri Budiarto, Gunawan Christian, Yoel Dedi Dwi Saputra Dedi Dwi Saputra Dwiza Riana Fahlapi, Riza Febrian, Dio Ferry Syukmana Hasan , Fuad Nur Hasan, Fuad Nur Hasanah, Riyan Latifahul Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Hermanto Wahono Hermawan, Muhamad Taufik Khiyarana Fayziyah Laia , Metodius Modianus Lasman Effendi M. Rangga Ramadhan Saelan Mahmud Syarif Mawalda Azharah Moh. Arie Hasan Muhammad Syukur Nabilatul Adzra, Salsa Nadia Septia Aisyah Nanjaya, Ahmad Fadhil Nitra, Ridatu Oca Novianti, Deny Nurajijah, Nurajijah Rachimsah, Wildan Ramadhan, Xena Hadi Ramanda, Dea Rianto, Yan Ridatu Oca Nitra Ridatu Oca Nitra Ridatu Ocanitra Riza Fahlapi Riza Fahlapi RIZA FAHLAPI Saputra, Dedi Dwi Siti Nurlela siti nurlela Sugiarto, Hady Sukmawati, Alfiani Sutisna, Alifan Widad Taufik Asra Usnah, Asmaul Wahono, Hermanto