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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab SMARTICS Journal Syntax Literate: Jurnal Ilmiah Indonesia JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Edukasi Islami: Jurnal Pendidikan Islam JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research METIK JURNAL Jurnal Informatika Kaputama (JIK) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Ilmu Komputer dan Bisnis Jurnal Teknologi Informasi dan Multimedia Jurnal Ekonomi Manajemen Sistem Informasi Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Computer and Information System (IJCIS) International Journal of Engineering, Science and Information Technology Djtechno: Jurnal Teknologi Informasi Jurnal Tika Instal : Jurnal Komputer Dirgamaya: Jurnal Manajemen dan Sistem Informasi Jurnal Minfo Polgan (JMP) Jurnal Teknik Mesin Mechanical Xplore Abdimas Jurnal Sistem Informasi STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Jitu: Jurnal Informatika Utama VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Hananto, Agustia
Fakultas Ilmu Komputer, Program Studi Sistem Informasi, Universitas Buana Perjuangan Karawang, Karawang, Indonesia
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Analisis Sentimen Ulasan Pengguna Alikasi Traveloka Pada Google Play Store Menggunakan Algoritma Naive Bayes Ikhsan, Muhammad Daffa; Huda, Baenil; Hananto, Agustia; Nurapriani, Fitria
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30444

Abstract

The advancement of the digital era has driven increased usage of online reservation applications, including Traveloka. The abundance of user feedback available on the Google Play Store platform has the potential to become a valuable database for development teams in improving service quality. However, the characteristics of unstructured and spontaneous reviews pose challenges in conventional data processing.This research aims to explore sentiment in Traveloka application user comments using the Multinomial Naïve Bayes algorithm. The dataset used consists of 1,500 review samples obtained through web scraping techniques from the Google Play Store. The research methodology includes several data preprocessing stages, including data cleaning, case normalization, word tokenization (tokenizing), stopword removal, and word stemming to their base forms (stemming). Subsequent processes include data categorization, feature extraction using the Term Frequency–Inverse Document Frequency (TF-IDF) approach, and building a classification model with the Multinomial Naïve Bayes algorithm.Test results show that the model is capable of classifying sentiment with an accuracy rate of 79%. The model demonstrates high recall values in identifying negative reviews (0.97), but the recall value for positive reviews remains limited (0.64). This indicates that the model has higher sensitivity to negative expressions. From a total of 1,500 review data, there were 461 positive reviews and 543 negative reviews that were successfully categorized clearly.The findings in this study prove that the implementation of the Multinomial Naïve Bayes algorithm is quite efficient in sentiment classification of user reviews, and is capable of providing strategic insights that can be utilized by development teams to improve application service quality
The Advanced Analysis of Deep Drawing Processes for 1-Inch Diameter Dop-Pipe Caps: Simulation and Experimental Insights Pratama, Tito Chaerul; Sukarman; Tikamori, Ghazi; Mulyadi, Dodi; Supriyanto, Agus; Amir, Amir; Khoirudin, Khoirudin; Hananto, Agus
Jurnal Teknik Mesin Mechanical Xplore Vol. 5 No. 1 (2024): Jurnal Teknik Mesin Mechanical Xplore (JTMMX)
Publisher : Mechanical Engineering Department Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jtmmx.v5i1.7269

Abstract

This article investigates the challenges and solutions within the deep drawing process, focusing on issues like cracks and deviations from standard thickness dimensions. Utilizing both experimental methods with a 40-ton power press machine and numerical simulations via ABAQUS software, the study uses SPCC-SD steel to produce a Dop-pipe 1-inch diameter pipe cap. Key findings reveal significant correlations in elements E-90 and E-91, with minimal disparities of around 4.5% between experimental and numerical approaches, showcasing the accuracy of numerical predictions. Notably, the numerical simulations identify potential issues such as increased thickness due to higher axial forces, providing valuable insights for process optimization and defect reduction. By advancing the deep drawing process and extending its applicability to broader material-forming applications, this research contributes significantly to enhancing production efficiency and improving manufacturing practices, emphasizing the importance of simulation-driven approaches in achieving precision and quality enhancement in complex manufacturing processes.
Taguchi-Based Optimization of TIG Welding for Joining Low-Carbon Steel (ST37) and Stainless Steel (SUS 304) Khoirudin; Karyadi, Karyadi; Kusnadi, Akhmad; Amir, Amir; Abdulah, Amri; Hananto, Agus; Taufik Ulhakim, Muhamad
Jurnal Teknik Mesin Mechanical Xplore Vol. 5 No. 2 (2024): Jurnal Teknik Mesin Mechanical Xplore (JTMMX)
Publisher : Mechanical Engineering Department Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jtmmx.v5i2.9043

Abstract

This study investigates the optimization of tungsten inert gas (TIG) welding parameters for joining dissimilar metals, specifically ST37 low-carbon steel and SUS 304 stainless steel, using the Taguchi L9 experimental design. The welding parameters evaluated include welding current (45-65 A), tungsten electrode diameter (1.6-2.4 mm), and shielding gas flow rate (12-18 LPM). The aim is to enhance joint integrity and mechanical properties by systematically analyzing the influence of these parameters on hardness and tensile load (TS loads). Hardness testing revealed that the weld zone exhibited the highest hardness, followed by the heat-affected zone and base metal. Tensile testing showed that the highest TS loads of 341 kgf were achieved at 45 A, 1.6 mm electrode diameter, and 12 LPM gas flow rate. Signal-to-noise ratio analysis and analysis of variance (ANOVA) indicated that welding current had the most significant influence on hardness and TS loads, with contributions of 39% and 41.27%, respectively, followed by electrode diameter (17% and 36.42%). In comparison, the gas flow rate had the least impact (45% and 22.31%). However, ANOVA results showed that none of the factors exhibited statistical significance (P > 0.05). The findings contribute to the field of welding engineering by providing optimized TIG welding parameters for ST37-SUS 304 joints, enhancing their reliability in various industrial applications such as automotive manufacturing, oil and gas, and power generation, where durable and corrosion-resistant welds are crucial.
Determination of Training Participants in Community Work Training Centers Using the Naïve Bayes Classifier Algorithm Hananto, April Lia; Hananto, Agustia; Huda, Baenil; Rahman, Aviv Yuniar; Novalia, Elfina; Priyatna, Bayu
JOIV : International Journal on Informatics Visualization Vol 8, No 3 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3.1995

Abstract

Community work training centers are skills training institutions that aim to improve the skills of the surrounding community by providing training programs that align with industry needs. Registration of training participants at the Al-Ikhwan Islamic Boarding School community work training centers often faces obstacles, namely, the selection process is still manual, so it takes a long time, and there is a possibility of errors. This study aims to apply the Naive Bayes Classifier Algorithm to determine whether applicants pass training at the Al-Ikhwan Islamic Boarding School community work training centers. This classification method is used to help optimize the applicant selection process by considering administrative factors, income, and training quotas. RapidMiner software is used as a tool to implement the algorithm. This study found that the Naive Bayes Classifier Algorithm can provide good accuracy results in determining applicants who pass the training selection. The test results show that the resulting model has an accuracy of 90.00% in determining passing training participants with data that has the highest chance of passing, namely data that has the attributes of the female gender, age 20 years, last education Senior High School/Vocational High School, student work/student, income 364,912, father's work as laborer, father's income 3912,280, mother's work as an IRT, and mother's income 885,964. This research increases efficiency and accuracy in determining training applicants at the Al-Ikhwan Islamic Boarding School community work training centers.
RANCANG BANGUN SISTEM INFORMASI E-COMMERCE AYAMSEGAR.ID MENGGUNAKAN METODE PROTOTYPE PADA UMKM Atmaja, Rashelin Zahra; Hananto, Agustia; Huda, Baenil; Hananto, Aprilia
Jurnal Informatika Vol 9, No 4 (2025): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v9i4.14469

Abstract

Transformasi digital telah menjadi kebutuhan mendesak bagi UMKM di era industri 4.0, terutama dalam aspek pemasaran dan layanan pelanggan. Penelitian ini bertujuan untuk merancang sistem informasi e-commerce berbasis website pada UMKM Kurnia Farms dengan menggunakan metode prototype. Proses pengembangan dilakukan secara iteratif, dimulai dari identifikasi kebutuhan, perancangan sistem, implementasi prototype, hingga evaluasi oleh pengguna. Pengumpulan data dilakukan melalui observasi, wawancara, studi pustaka, dan pengujian usability menggunakan System Usability Scale (SUS). Hasil implementasi menunjukkan bahwa sistem berhasil memenuhi kebutuhan pengguna dalam pengelolaan produk dan transaksi secara digital. Evaluasi usability menghasilkan skor SUS sebesar 87.5 yang termasuk dalam kategori Excellent Usability, menandakan bahwa sistem mudah digunakan dan sesuai dengan ekspektasi pengguna. Sistem ini dinilai dapat menjadi solusi digitalisasi yang efektif dan terjangkau bagi UMKM serupa.
Klasifikasi Kenyamanan Produk Hijab Kaos Rayon Menggunakan Algoritma Naïve Bayes Berdasarkan Ulasan Konsumen di Shopee Zein, Selmia Aulia; Paryono, Tukino; Hananto, Agustia; priyatna, bayu
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i6.59532

Abstract

Industri fashion muslimah di Indonesia mengalami pertumbuhan yang pesat, dengan produk hijab kaos rayon menjadi pilihan populer karena kenyamanannya yang sesuai dengan iklim tropis. Shopee, sebagai platform e-commerce terbesar di Indonesia, menjadi tempat utama bagi konsumen untuk membeli produk ini. Namun, dengan banyaknya ulasan yang tersedia, penilaian manual terhadap kenyamanan produk menjadi tidak efisien. Penelitian ini bertujuan untuk mengembangkan model klasifikasi sentimen menggunakan algoritma Naïve Bayes untuk menilai tingkat kenyamanan produk hijab kaos rayon berdasarkan ulasan konsumen di Shopee. Data ulasan dikumpulkan melalui teknik web scraping, kemudian diproses menggunakan tahapan preprocessing seperti case folding, tokenization, stopword removal, dan stemming. Selanjutnya, data diberi label berdasarkan tingkat kenyamanan: sangat nyaman, nyaman, cukup nyaman, dan tidak nyaman. Model Naïve Bayes diimplementasikan untuk mengklasifikasikan ulasan tersebut, menghasilkan tingkat akurasi 71,56%, dengan presisi, recall, dan f1-score masing-masing 72%. Hasil klasifikasi menunjukkan bahwa kategori "Cukup Nyaman" mendominasi, diikuti oleh kategori "Nyaman", "Sangat Nyaman", dan "Tidak Nyaman". Analisis ini memberikan gambaran yang lebih cepat dan akurat bagi konsumen dalam memilih produk hijab kaos rayon yang sesuai dengan preferensinya.
Klasterisasi Tingkat Penjualan Kedai Kopi Hallo Burjois Menggunakan Algoritma K-Medoids Sebagai Evaluasi Pradana Rizki Maulana; April Lia Hananto; Agustia Hananto; Bayu Priyatna
JURNAL FASILKOM Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6912

Abstract

Kedai Hallo Burjois yang sedang mengalami tantangan untuk memperluas jangkauan produk menu produk, penelitian ini menerapkan algoritma K-Medoids Clustering untuk meningkatkan strategi promosi dengan mengidentifikasi menu-menu yang memiliki tingkat minat pembeli rendah. Proses tersebut melibatkan pengolahan data penjualan harian yang diubah menjadi format bulanan, di mana algoritma K-Medoids digunakan untuk membentuk tiga kluster yang mewakili tingkat penjualan tinggi, sedang, dan rendah. Hasil klasterisasi menunjukkan adanya menu-menu dengan penjualan rendah sebanyak 6 item, antara lain Americano, Caffe Latte, Dark Choco Caramel, Dimsum, Hazelnut Latte, dan Pasta Carbonara. Lalu kami mengadopsi prinsip 4P (Product, Price, Place & Promotion) untuk mengevaluasi produk dengan tingkat penjualan terendah. Uji validitas dilakukan menggunakan Davies Boulding Index (DBI), menunjukkan keakuratan dan konsistensi hasil klasteriasasi sebesar 0,95 pada tiga kluster.
Implementasi Metode Agile Development Dalam Perancangan Sistem Informasi Pendaftaran KB MKJP Berbasis Website Handayani, Citra; Priyatna, Bayu; Hananto, Agustia; Tukino, Tukino
Jurnal Ilmu Komputer dan Bisnis Vol. 16 No. 1 (2025): Vol. 16 No. 1 Mei (2025)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v16i1.1039

Abstract

Program Keluarga Berencana (KB) merupakan salah satu upaya pemerintah Indonesia dalam mengendalikan pertumbuhan penduduk dan meningkatkan kesejahteraan masyarakat. Salah satu metode yang dianjurkan dalam program ini adalah Kontrasepsi Jangka Panjang (MKJP), seperti implan, IUD, dan sterilisasi. Namun, partisipasi masyarakat, terutama di daerah pedesaan seperti Kecamatan Karang Bahagia, Kabupaten Bekasi, masih tergolong rendah. Proses pencatatan dan pengelolaan data di BKKBN Kecamatan Karang Bahagia masih dilakukan secara manual, sehingga rawan mengalami kesalahan, kerusakan, atau kehilangan data. Untuk menjawab permasalahan tersebut, penelitian ini mengembangkan sistem informasi pendaftaran KB MKJP berbasis web dengan menggunakan metode Agile Development yang memungkinkan pengembangan dilakukan secara bertahap dan fleksibel. Sistem ini dirancang untuk meningkatkan efisiensi dalam proses pendaftaran, validasi data, serta pelaporan secara real-time. Berdasarkan hasil pengujian black box, seluruh fitur dalam sistem berfungsi sesuai dengan harapan. Diharapkan dengan adanya sistem ini, tingkat partisipasi masyarakat terhadap program MKJP dapat meningkat dan pengelolaan data menjadi lebih akurat serta terintegrasi.
Perancangan Sistem Rekomendasi Produk pada E-Commerce Toko Sendal Grosir Menggunakan Algoritma Content-Based Filtering Novalia, Elfina; Awal, Elsa Elvira; Hananto, Agustia; Tarmuji, Tarmuji; Setiawan, Pratama Wahyu
Journal of Information System, Applied, Management, Accounting and Research Vol 9 No 4 (2025): JISAMAR (Journal of Information System, Applied, Management, Accounting and Resea
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v9i4.2130

Abstract

Perkembangan teknologi informasi memberikan pengaruh besar terhadap persaingan bisnis, khususnya di sektor penjualan grosir. Toko sendal grosir sebagai usaha berskala kecil hingga menengah seringkali menghadapi tantangan dalam mengelola transaksi, inventaris, dan promosi produk secara efektif. Penelitian ini bertujuan untuk merancang dan membangun sistem e-commerce menggunakan Laravel dan Nuxt.js yang dilengkapi dengan fitur rekomendasi produk berbasis algoritma Content-Based Filtering. Laravel digunakan di sisi backend karena struktur arsitektur MVC yang terorganisir, keamanan data, serta kemudahan pengembangan. Sementara itu, Nuxt.js digunakan di sisi frontend untuk menghadirkan antarmuka pengguna yang responsif dan interaktif melalui dukungan server-side rendering (SSR). Proses perancangan meliputi analisis kebutuhan, desain antarmuka, dan implementasi modul seperti halaman utama, detail produk, checkout, serta logika rekomendasi. Sistem rekomendasi memanfaatkan atribut produk seperti kategori, warna, ukuran, dan harga, dengan perhitungan kemiripan menggunakan metode cosine similarity. Meskipun sistem rekomendasi masih dalam tahap perancangan, integrasinya bertujuan untuk meningkatkan personalisasi dan pengalaman belanja pengguna. Sistem ini juga dirancang agar skalabel dan mudah dikembangkan di masa depan.
RECONSTRUCTION OF ISLAMIC EDUCATION CURRICULUM MANAGEMENT BASED ON DEEP LEARNING IN THE ERA OF DIGITAL TRANSFORMATION Masruroh, Siti; Rahmatiani, Lusiana; Hananto, Agustia; Utomo, Ainur Alam Budi; Ali, Agus
Edukasi Islami: Jurnal Pendidikan Islam Vol. 14 No. 04 (2025): Edukasi Islami: Jurnal Pendidikan Islam
Publisher : Sekolah Tinggi Agama Islam Al Hidayah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30868/ei.v14i04.9293

Abstract

Background: The reconstruction of the Islamic Education (PAI) curriculum is essential in responding to the changes brought by the digital era. Purpose: This article proposes a deep learning–based curriculum management model for Islamic education as a form of digital transformation within Islamic educational institutions. The approach emphasizes the development of deep understanding, spiritual reflection, and the integration of Islamic values into all aspects of the curriculum. Method: The research employs a conceptual-theoretical (library research) approach with a comparative analysis of literature on curriculum management, deep learning theory, and best practices in contemporary Islamic education. Result: The findings reveal key components of deep learning–based curriculum management, including adaptive curriculum design, data-driven teacher training, longitudinal evaluation, and managerial-technological synergy. Conclusion: Practical recommendations are directed toward transforming curriculum policies in madrasahs and Islamic schools.
Co-Authors Abdul Hafiz Adila Rahmawati Afif Hakim Afra, Alfina Fadhilah Agneresa Agneresa Agus Supriyanto Alfiansyah, Muhammad Rindra ali, agus alzahra, alika aziza Amir Amir Amri Abdulah Anggi Octa Fadilah Angraeni, Rahmah Nur Annam, Dyno Syaiful Apriade Voutama Apriani, Fitria April Lia Hananto Arief Wibowo Arip Solehudin Asep Permana atikah, dwi Atmaja, Rashelin Zahra Aulia, Aldi Aviv Yuniar Rahman Aviv Yuniar Rahman Awal, Elsa Elvira Azizah, Fathin Putri Baenil Huda Baenil Huda Baenil Huda Baenil Huda Bayu Priyatna Bayu Yoga Astario Cepi Budiansyah, Ade Deva Defrina Aldeana Difa Prakoso Fuadi, Muhammad Dodi Mulyadi Dodi Mulyadi Dyno Syaiful Annam Eko Pramono Elfina Novalia Elfinanovalia , Elfinanovalia Emilia Sukmawati, Cici Erlyta Hares Fatmanisa Mumpuni Delta Maharani Fauzi Ahmad Muda Ferdiansyah, Indra FIKRI HAIKAL Fitria Nur Apriani Fitria Nurapriani Fitria Nurapriani Fizra Firdaus Nillan Goenawan Brotosaputro Handayani, Citra Herda Andriana Heryana, Nono Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Huban Kabir Huda , Baenil Huda, Baenil Ikhsan, Muhammad Daffa Ilham Fariz Asya Mubarok Indra Kurniawan Indra, Jamaludin Jasmine Dina Sabila Karyadi Karyadi Khoirudin Khoirudin Khoirudin, Khoirudin Kusnadi, Akhmad Maharina, Maharina Melisa Mubarok, Piky Muhamad Mammun Muhamad Rizky Arfani Muhamad Rizky Arfani Muhammad Khaerudin Novalia, Elfina Nur Widyartha, Yogi Nur ‘Azah Nurafriani, Fitria Nurajizah, Dhea Nurapriani, Fitria Nurfajria, Dera Nurhayati Nurlaelasari, Euis Paryono, Tukino Pradana Rizki Maulana Pratama, Tito Chaerul Priyatna, Bayu Priyatna, Bayu Puspita Sari, Desti Rahdiana, Nana Rahmatiani, Lusiana Ramadanti, Anita Khansa Rati Ratnasari Ratna Juwita, Ayu Reswara, Hadaya Abhista Rini Mayasari Rosalina, Elsa Sabrina Amanda Salsabila Saefil Aripiyanto Salsabila, Nasya Setiawan, Pratama Wahyu Setiawan, Pratama Wahyu Shofa Shofia Hilab Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Sifa, Sifa Rismawati Sigit Budi Nugroho Silvana Nazuah Siti Masruroh Sri Wahyuni Suhara, Ade Sukarman Sukarman Sukarman Sukarman Sunarya, Edwin Yohanes Supriyanto, Danang Susilo, Hendri Tamala, Evi TARMUJI TARMUJI, TARMUJI Taufik Ulhakim, Muhamad Thoyib, Imam Nurhuda Tikamori, Ghazi Tukino Tukino , Tukino Tukino Tukino Tukino Tukino, Tukino Tukino, Tukino Tukino, Tukino Utomo, Ainur Alam Budi Wahyu, Pratama Widyanti, Tyas Witulas Ambang Cahyati Yoga Astario, Bayu Zein, Selmia Aulia