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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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Identifying Regional Patterns of Poverty in Indonesia: a Clustering Approach Using K-Means Wahyuni, Sri; Hananto, Agustia; Huda, Baenil; Apriani, Fitria; Tukino, Tukino
International Journal of Computer and Information System (IJCIS) Vol 6, No 1 (2025): IJCIS : Vol 6 - Issue 1 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i1.218

Abstract

Poverty in Indonesia remains a major challenge, with significant levels of inequality between provinces. This study applies the K-Means clustering method to analyze poverty distribution patterns in 38 provinces in Indonesia, using data on the percentage of poor people from 2010 to 2024. With this approach, provinces are grouped into three main clusters: low, medium, and high, based on the average poverty rate. The low cluster includes areas with poverty rates below 10%, while the medium and high clusters indicate poverty levels that require more specific policies. The evaluation results show a silhouette score of 0.613, indicating that this grouping is quite good but can still be improved. This study offers important insights to support more targeted and effective policies, especially in achieving Sustainable Development Goal (SDG) 1: Eradicating Poverty.
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.
Pelatihan Pengembangan Website Sistem Penjualan Online Berbasis Content Menagement System (CMS) Wordpress Novalia, Elfina; Hananto, Agustia; Emilia Sukmawati, Cici; Wahyu, Pratama; Voutama, Apriade
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i2.104

Abstract

This WordPress Content Management System (CMS) based website development training activity is designed to help digitize the helmet washing service business in Karawang. The purpose of this training is to equip business owners with skills in managing online sales platforms to expand market reach and make it easier for customers to order services. The training is carried out offline with a direct practice method, including a basic introduction to WordPress, theme and plugin installation, to optimizing online store features. Based on the evaluation, this training received a participant satisfaction rate of 85%. Participants felt helped by the material provided and were able to practice creating and managing websites independently to support their business operations. This training is expected to be able to increase the competitiveness of the helmet washing business in Karawang by utilizing an effective digital platform to reach customers more widely.
Klasifikasi Genre dan Rating Konten di Netflix : Wawasan dari Analisis Chi-Square dan Clustering alzahra, alika aziza; Hananto, April Lia; Hananto, Agustia; Priyatna, Bayu
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.11354

Abstract

Streaming platforms like Netflix rely on genre classification and content rating to enhance user experience and develop more effective marketing strategies. This study aims to analyze the relationship between genre and content rating on Netflix using Chi-Square analysis and clustering techniques to group genres based on rating distribution patterns. The Chi-Square test results indicate a significant relationship between genre and content rating (p-value < 0.05), suggesting that certain types of content tend to receive specific ratings. Furthermore, clustering analysis identifies three main groups: genres with high ratings suitable for a broad audience, genres with varied ratings that are more subjective, and genres with lower ratings that often include adult or less popular content. These findings provide insights that Netflix can leverage to optimize its content catalog, develop personalized recommendations, and tailor marketing strategies based on user consumption patterns.
Analisis Sentimen Pengguna terhadap Aplikasi Lalamove dengan Perbandingan Algoritma Support Vector Machine dan Naive Bayes Nurajizah, Dhea; Hilabi, Shofa Shofia; Hananto, Agustia; Huda, Baenil
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.7124

Abstract

The development of digital technology has brought significant changes to the logistics and transportation sector. On-demand delivery applications such as Lalamove are a solution for users who need fast and efficient services. However, the existence of various user reviews both positive and negative indicates a difference in experience that needs to be analyzed. This study aims to evaluate user perceptions of the Lalamove application by comparing the effectiveness of Support Vector Machine (SVM) and Naive Bayes algorithms in sentiment classification. The data used in this study includes 10,000 user reviews obtained through scraping techniques from the Google Play Store. After going through the data preprocessing stage, the analysis is performed using TF-IDF method as feature extraction and the model performance evaluation is performed based on accuracy, precision, recall, and F1-score metrics. Sentiment classification in this study was performed in two categories, namely positive and negative (binary) sentiment, without considering the neutral category. The results show that the SVM algorithm has a high accuracy of 87% compared to Naive Bayes which only reaches 83%. This research provides an understanding for application developers in improving service quality based on user sentiment analysis.
Sistem Monitoring Dan Visualisasi Data Konsumsi Energi Listrik Rumah Berbasis IoT Dengan Aplikasi Blynk Setiawan, Pratama Wahyu; Hananto, April Lia; Novalia, Elfina; Hananto, Agustia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2675

Abstract

Household electricity consumption continues to increase, but monitoring of electricity use is still limited to the KwH meter which only shows the total usage without real-time details. This research aims to design an Internet of Things (IoT)-based electrical energy consumption monitoring system with the Blynk application as a data visualization medium. The system is designed using a PZEM-004T sensor to measure voltage, current, and power, as well as a ESP8266 NodeMCU microcontroller to transmit data to the Blynk application over a WiFi connection. System testing is carried out using the black box method to evaluate the functionality of each feature without looking at internal processes. The test results showed that the system can display electricity consumption data in real-time, work stably, and allow remote monitoring via smartphone. The system also helps users recognize electricity usage patterns, supports decision-making in energy savings, and provides historical data for long-term usage evaluation.Keywords: Internet Of Things; Monitoring Listrik; NodeMCU ESP8266; Blynk; PZEM-004T AbstrakKonsumsi energi listrik rumah tangga terus meningkat, namun pemantauan penggunaan listrik masih terbatas pada KwH meter yang hanya menunjukkan total pemakaian tanpa detail real-time. Penelitian ini bertujuan merancang sistem monitoring konsumsi energi listrik berbasis Internet of Things (IoT) dengan aplikasi Blynk sebagai media visualisasi data. Sistem dirancang menggunakan sensor PZEM-004T untuk mengukur tegangan, arus, dan daya, serta mikrokontroler NodeMCU ESP8266 untuk mengirimkan data ke aplikasi Blynk melalui koneksi WiFi. Pengujian sistem dilakukan dengan metode Black box untuk mengevaluasi fungsionalitas tiap fitur tanpa melihat proses internal. Hasil pengujian menunjukkan bahwa sistem dapat menampilkan data konsumsi listrik secara real-time, bekerja dengan stabil, dan memungkinkan pemantauan jarak jauh melalui smartphone. Sistem ini juga membantu pengguna mengenali pola penggunaan listrik, mendukung pengambilan keputusan dalam penghematan energi, serta menyediakan data historis untuk evaluasi penggunaan jangka panjang. 
Perbandingan Algoritma K-Means dan Hierarchical Untuk Klasterisasi Data Kehadiran Karyawan Azizah, Fathin Putri; Hilabi, Shofa Shofiah; Tukino, Tukino; Hananto, Agustia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2644

Abstract

Employee attendance data analysis has an important role in human resource management to improve efficiency and productivity. This study compares the K-Means and Hierarchical methods for grouping employee attendance data to discover performance factors. The goal of this study is to compare the performance of the two algorithms utilizing the assessment metrics Silhouette Score, Calinski-Harabasz Index, and Dunn Index. The methods used include collecting employee attendance data, preprocessing data, applying clustering algorithms, and evaluating performance based on specified metrics. The evaluation results showed that K-Means produced a Silhouette Score of 0.46, a Calinski-Harabasz Index of 522.90, and a Dunn Index of 0.98, while Hierarchical obtained a score of 0.40, 452.85, and 0.86, respectively. These results indicate that K-Means is superior in forming clearer and separate clusters. Based on these findings, the K-Means technique is more recommended for employee attendance data analysis because it provides more optimal cluster separation.Keywords: Clustering; K-Means; Hierarchical; Attendance Data; Evaluation AbstrakAnalisis data kehadiran karyawan memiliki peran penting dalam manajemen sumber daya manusia untuk meningkatkan efisiensi dan produktivitas. Penelitian ini membahas perbandingan algoritma K-Means dan Hierarchical dalam klasterisasi data kehadiran karyawan guna mengidentifikasi karakteristik kinerja. Tujuan dari penelitian ini adalah mengevaluasi performa kedua algoritma menggunakan metrik evaluasi Silhouette Score, Calinski-Harabasz Index, dan Dunn Index. Metode yang digunakan meliputi pengumpulan data kehadiran karyawan, preprocessing data, penerapan algoritma klasterisasi, serta evaluasi performa berdasarkan metrik yang ditentukan. Hasil evaluasi menunjukkan bahwa K-Means menghasilkan Silhouette Score sebesar 0.46, Calinski-Harabasz Index sebesar 522.90, dan Dunn Index sebesar 0.98, sedangkan Hierarchical memperoleh nilai masing-masing sebesar 0.40, 452.85, dan 0.86. Hasil ini mengindikasikan bahwa K-Means lebih unggul dalam membentuk klaster yang lebih jelas dan terpisah. Berdasarkan temuan ini, algoritma K-Means lebih direkomendasikan untuk analisis data kehadiran karyawan karena memberikan pemisahan klaster yang lebih optimal. 
Pengenalan Enterpreunership Multimedia Pada Santri Pondok Pesantren At-Taubah Tirta Mulya Agustia Hananto; Elfina Novalia; Tukino Tukino
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 2 No. 2 (2025): Mei : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v2i2.1384

Abstract

This community service activity aims to introduce the concept of multimedia entrepreneurship to students of the At-Taubah Tirta Mulya Islamic Boarding School, Karawang, in order to improve their knowledge and skills in utilizing multimedia as a tool for entrepreneurship. Held on March 2, 2024, this activity involved 50 students who attended lecture sessions, discussions, and multimedia content creation practices. The research method used was participatory action research, which allowed participants to be actively involved in the learning process. Data were collected through observation, interviews, and questionnaires to measure changes in knowledge before and after the activity. The results of the analysis showed a significant increase in students' understanding and skills related to multimedia entrepreneurship. The implications of this activity highlight the importance of collaboration between higher education institutions and Islamic boarding schools to create a creative and independent generation in the digital era.
Komparasi Kinerja Model Naive Bayes, SVM, dan BERT dalam Klasifikasi Sentimen Ulasan Pada Aplikasi YUMMY Sabrina Amanda Salsabila; Bayu Priyatna; Agustia Hananto; Tukino
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 4 No. 2 (2025): Mei
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v4i2.5120

Abstract

Ulasan pada Google Play Store memainkan peran penting dalam membentuk persepsi publik terhadap sebuah aplikasi. Penelitian ini bertujuan untuk melakukan sentimen ulasan dengan mengklasifikasikan mejadi kategori positif dan negatif di aplikasi Yummy, serta membandingkan performa tiga metode klasifikasi teks: Naive Bayes, Support Vector Machine (SVM), dan Bidirectional Encoder Representations from Transformers (BERT). Sebanyak 6.773 data ulasan didapatkan melalui scraping dan diproses dengan tahapan pra-pemrosesan seperti pembersihan teks, tokenisasi, stopword removal, dan stemming. Representasi fitur dilakukan menggunakan TF-IDF untuk Naive Bayes dan SVM, sedangkan BERT memanfaatkan token embedding dari model pra-latih. Hasil eksperimen menunjukkan bahwa SVM menghasilkan performa sangat efektif dengan akurasi 94%, diikuti oleh Naive Bayes dan BERT yang keduanya mencapai akurasi 90%. SVM juga menunjukkan keseimbangan yang lebih baik dalam mengklasifikasikan teks sentimen positif dan negatif. Temuan ini menegaskan SVM direkomendasikan sebagai solusi yang stabil dan efisien dalam analisis sentimen teks berbahasa Indonesia.
IMPLEMENTASI USER INTERFACE PADA WEBSITE COMPANY PROFILE MENGGUNAKAN METODE DESIGN THINKING Tamala, Evi; Huda, Baenil; Novalia, Elfina; Hananto, Agustia
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 2 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode Mei 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/9pwc1780

Abstract

CV. Smart Motecare Mandiri bergerak di bidang penyedia perangkat teknologi informasi serta layanan instalasi dan perawatan peralatan tersebut. Seiring dengan pesatnya perkembangan teknologi informasi, perusahaan ini menyadari pentingnya keberadaan sebuah website sebagai sarana komunikasi dan promosi yang efektif. Website menjadi platform penting untuk menyampaikan informasi mengenai produk, layanan, serta profil perusahaan. Penelitian ini bertujuan untuk merancang website company profile CV. Smart Motecare Mandiri dengan memanfaatkan metode Design Thinking, yang mengarah pada pengetahuan yang komprehensif mengenai keperluan pengguna serta penyelesaian masalah yang dihadapi perusahaan. Proses perancangan mencakup tahapan Empathize, Define, Ideate, serta pembuatan desain dan prototype, yang kemudian diimplementasikan dalam pembuatan website menggunakan platform WordPress. Setelah website selesai dibuat, pengujian dilakukan dengan metode SUS untuk mengukur tingkat kegunaan website. Hasil pengujian menunjukkan skor akhir SUS sebesar 68,00, yang termasuk dalam kategori "marginal high" dan menunjukkan bahwa website yang dirancang efektif dalam memenuhi tujuan perusahaan. Website ini diharapkan dapat menjadi sarana promosi digital yang meningkatkan citra profesional perusahaan dan mempermudah calon pelanggan dalam memperoleh informasi.
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