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All Journal Pro Bisnis Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Bina Insani ICT Journal Jurnal Teknoinfo AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi MULTINETICS EVOLUSI : Jurnal Sains dan Manajemen Madani : Indonesian Journal of Civil Society Simpatik: Jurnal sistem Informasi dan Informatika Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Teknik Informatika
Husni Faqih
Universitas Bina Sarana Informatika
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences

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KLASIFIKASI SAMPAH PLASTIK BERDASARKAN DETEKSI WARNA RGB DENGAN METODE K-NEAREST NEIGHBOR Suseno, Kheri Agus; Faqih, Husni
Indonesian Journal on Software Engineering Vol 10, No 2 (2024): IJSE 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v10i2.25671

Abstract

Pengelolaan sampah plastik merupakan sebuah langkah yang sangat dibutuhkan kalangan masyarakat saat ini dalam menentukan penanganan yang tepat terutama pada sampah plastik. Mengelompokkan beberapa jenis plastik atau klasifikasi jenis plastik PET, HDPE, PP, LDPE PVC dan Other akan sangat membantu dalam pengelolaan sampah plastik terutama ketepatan dalam menentukkan jenis-jenis plastik tersebut agar lebih mudah dalam penanganannya. Dari jenis plastik pada umumnya dibagi menurut sifat khusus dan jenis bahannya sebagai pembeda sesuai kategori plastik tersebut. Dari jenis masing-masing plastik dapat diklasifikasikan dari beberapa fitur warna, berat dan sifat kimia yang terkandung didalamnya[2]. Penentuan warna dari jenis plastik ditentukan dengan menggunakan alat deteksi warna RGB dan T (Red Green Blue Temperatur Warna). Sensor Warna yang menghasilkan gelombang frekuensi pantulan sehingga didapatkan berupa data numerik tertentu sehingga dapat dijadikan sebagai penentu sifat, dan warna serta kualitas plastik tersebut. Nilai dari hasil deteksi ini akan dikumpulkan menjadi sebuah datasheet private yang akan digunakan sebagai penentu dari jenis-jenis plastik yang ada. Metode yang digunakan untuk menentukkan jenis plastik ini menggunakan metode K-nearest neighbor (KNN).               Kata kunci: Klasifikasi Pengelolaan sampah plastik, PET, HDPE, PP, LDPE PVC dan Other, Artivicial K-nearest neighbor (KNN).
Studi Komparatif Metode Naive Bayes dan Support Vector Machine dalam Menganalisis Sentimen Ulasan Ask-AI Faqih, Husni; Aji, Sopian; Suseno, Kheri Agus
MULTINETICS Vol. 11 No. 1 (2025): MULTINETICS Mei (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i1.7534

Abstract

The development of Artificial Intelligence (AI) has brought significant changes in the field of information and communication. The Ask-AI application is popular and has many reviews on the Google Play Store platform. The purpose of this study is to analyze user review sentiments towards the Ask-AI application and compare the performance of two text classification algorithms, namely Naive Bayes and Support Vector Machine (SVM) in classifying reviews into positive and negative sentiment categories. A total of 628 reviews were used as a dataset consisting of 314 positive reviews and 314 negative reviews. The dataset has gone through a text preprocessing stage including letter transformation (transform cases), tokenize, common word removal (stopword removal), and dictionary-based stemming. Data analysis using RapidMiner software and for model performance evaluation using the k-fold cross-validation approach which can provide more stable and representative results for the entire data. The evaluation results produce a performance value of the SVM algorithm which has very good performance. SVM produces an accuracy of 94.08%, a precision of 96.23%, a recall of 92.31%, and an Area Under Curve (AUC) value of 0.981. Meanwhile, the Naive Bayes algorithm provides an accuracy of 78%, a precision of 85.23%, a recall of 68.37%, and an AUC of 0.801. The results of the study indicate that the SVM method is superior to Naïve Bayes in classifying the sentiment of Ask-AI application user reviews because it can provide more accurate, consistent, and more sensitive classification results to variations in text data. It is hoped that this study can be a reference for choosing the optimal sentiment classification algorithm for AI-based application user review data.
Pengembangan Aplikasi Koperasi Simpan Pinjam Menggunakan Metode Waterfall Aji, Sopian; Fandhilah , Fandhilah; Faqih, Husni; Rousyati, Rousyati
JEKIN - Jurnal Teknik Informatika Vol. 4 No. 2 (2024)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v4i2.706

Abstract

Penerapan teknologi informasi dalam pengelolaan koperasi simpan pinjam menjadi krusial untuk meningkatkan efisiensi dan aksesibilitas layanan keuangan mikro. Tulisan ini membahas implementasi sistem aplikasi koperasi simpan pinjam menggunakan metode Waterfall sebagai pendekatan pengembangan perangkat lunak. Fokus utama adalah pada pengelolaan data yang melibatkan dua peran utama, yaitu Admin dan Super Admin. Admin memiliki kewenangan untuk mengelola data anggota, data tabungan, data pinjaman, dan menghasilkan laporan transaksi. Sementara itu, Super Admin memiliki kontrol penuh atas semua fungsi yang dimiliki Admin, ditambah dengan kemampuan untuk mengelola data administrator. Melalui analisis penggunaan metode Waterfall dalam pengembangan sistem aplikasi, penelitian ini mengidentifikasi manfaat dan tantangan yang terkait dengan pendekatan tersebut. Hasilnya memberikan wawasan yang berharga bagi pengembang sistem dalam merancang, mengimplementasikan, dan memelihara aplikasi koperasi simpan pinjam yang efisien dan andal. Diharapkan penelitian ini dapat memberikan kontribusi signifikan dalam pemahaman tentang penerapan teknologi informasi dalam konteks koperasi simpan pinjam serta memberikan dasar untuk pengembangan lebih lanjut di masa mendatang.
“Seeker” Platform LMS Pengembangan dan Penyediaan Tenaga Kerja Kompeten Hasirun; Prakosa, Herjuna Ardi; Rachindratama, Joda; Zahbika, Putra Maulana; Rifai, Zanuar; Faqih, Husni; Nur Afiana, Fiby
MULTINETICS Vol. 11 No. 02 (2025): MULTINETICS Nopember (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i02.7882

Abstract

The Industrial Revolution 4.0 is estimated to eliminate 23 million jobs but create 46 million new types of jobs based on technology such as IoT, AI, and Big Data. This change demands the readiness of human resources, including in the MSME sector, as well as increased digital competency. Many companies now require skills certification in addition to formal diplomas. LMS (Learning Management Systems) are present as digital learning solutions that manage materials, assignments, and online learning interactions. However, most LMSs still focus on formal education, not on developing skills for high school/vocational school or university graduates. The aim of this research is to combine elements of LMS and job seekers in an effort to strengthen the advantages of future generations through competitive qualifications, skills, and technology in the industry. This platform allows collaboration with educational institutions, industry, and MSMEs to build a strong cooperative ecosystem in the socio-environmental field. Using the Prototype method as a software development method to support the success of the research. The LMS "Seeker" is present as a platform for providing competent workers through certified skills classes at affordable prices. Its advantages are a curriculum relevant to industry needs, increased workforce competitiveness, and access to broad job opportunities
Transformasi Digital Berkelanjutan UMKM Kuliner melalui Sistem Informasi E-Commerce Berbasis Web dalam Ekosistem Cerdas Husni Faqih; Fandhilah Fandhilah; Mawadatul Maulidah; Nadiyah Hidayati; Nafisah Muazarah; Asna Mauhibah Maurani
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 6 No. 1 (2026): Juni 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v6i1.12788

Abstract

Sustainable digital transformation has become a strategic necessity for UMKM to improve efficiency and competitiveness in the digital economy era. This study aims to examine the implementation of a web-based e-commerce information system as part of digital transformation efforts at Bakehouse, a bakery and pastry UMKM. The main problems faced by the partner include manual sales and transaction recording, unintegrated order data, a high risk of recording errors, and limitations in generating accurate and timely sales reports. The research method used is a system development approach with the Waterfall model, which includes requirements analysis, system design, implementation, and testing stages. The system was developed using the Laravel framework and MySQL database and is equipped with features for managing products, categories, customers, order transactions, and periodic sales reports. The results show that the implementation of the web-based e-commerce information system improves operational efficiency, increases data recording accuracy, and facilitates monitoring and information-based decision making. The system functions not only as an online sales platform but also as an initial foundation for building a smarter business ecosystem and supporting sustainable digital transformation in culinary UMKM    
Co-Authors ., Supriyanta Aditya Syaiful Islam Agung Baitul Hikmah Aji, Sopian Akbar, Muhammad Taufan Asna Mauhibah Maurani Ayu Amarcia A.S.W Bernadette Cahya Putri Utami Diah Raka Siwi Dwi Iswahyuni Dwi Meiliana Ery Suryanti Fahlepi Roma Doni Fandhilah , Fandhilah Fandhilah Fandhilah Hasirun Hendra Lesmana Hilda Faiqoturrohmah Husni Mubarok Husni Mubarok Jamal Maulana Hudin Lis Saumi Ramdhani Mawadatul Maulidah Nadiyah Hidayati Nafisah Muazarah Nani Purwati Nur Afiana, Fiby Oktafiandy Risqi Fadhlurrahman Pangestu, Andika Tulus Prakosa, Herjuna Ardi Puspa Fortuna Zulfa Rachindratama, Joda Raka Siwi, Diah Ratnawati . Ratnawati . Rifai, Zanuar Rousyati Rousyati Rousyati, Rousyati Sri Kiswati Suci, Adillah Bulan Suleman Suleman Suseno, Kheri Agus Tika Dian Avisha Tika Dian Avisha Tri Wahyudi Wafiq Azizah Warjiyono Warjiyono Yani Sri Mulyani Yulia, Erika Zahbika, Putra Maulana Zanuar Rifai Zanuar Rifai