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Seleksi Penerimaan Bantuan Internet Gratis dengan Menggunakan Metode AHP Tukino Paryono; Muhamad Rizky Arfani; Agustia Hananto; Baenil Huda
INTERNAL (Information System Journal) Vol. 6 No. 1 (2023)
Publisher : Masoem University

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Abstract

The internet is an information technology that is able to provide benefits for life and is a major requirement as a means of communication, entertainment or business. Covid 19 spreads throughout the City or Regency to villages in all regions in Indonesia which has a broad impact on the world of Education, especially Elementary and Middle School Education. Seeing the change in learning patterns from face-to-face to online learning, there are obstacles that are felt by students, especially in learning that requires the teaching and learning process between teachers and students to be carried out remotely (online). To support online learning, adequate internet facilities are needed. Provision of internet packages can be provided free of charge with due observance of predetermined requirements. To support the provision of free internet packages, a decision support system is needed to determine the selection of receiving free internet assistance so that it is right on target by using the Analytical Hierarchy Process (AHP) solving procedure. This method is used to make rankings for selecting free internet recipients, where the highest score is generated based on the best criteria. The results of calculations with this method. Where to make a decision support system in order to prevent errors in determining the criteria that deserve free internet assistance.
Penerapan Software Testing Life Cycle Pada Pengujian Otomatisasi Platform Dzikra Ruliansyah Ruliansyah; Tukino; Baenil Huda; April Lia Hananto
Computer Science Research and Its Development Journal Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.15.1.2023.01-11

Abstract

PT Bejana Investidata Globalindo (BIGIO), as an IT consultant and software development company, develops an in-house product called Dzikra which is a platform to help users build good habits in worship. In order to develop this system, the company requires a daily worship content management system known as the Dzikra web admin. The Software Development Life Cycle (SDLC) has several stages, one of the important stages is the testing stage which has the goal of evaluating whether the software has been created in accordance with the specifications and detects bugs or errors. Black box testing automation with Robot Framework can provide good testing documentation and can reduce human errors during the testing process. The implementation of the Software Testing Life Cycle (STLC) in the testing process can also make the testing flow more structured and provide a better focus on each testing stage. The results of the testing show that of the six features tested, they have run as expected. It is hoped that this research will provide support to PT Bejana Investidata Globalindo (BIGIO) in automating software testing process.
Analisis Sentimen User Experience Menggunakan Naive Bayes dan Design Thinking pada Aplikasi SIPT Muhamad Helmi Fauzi; Baenil Huda; Elfina Novalia
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 2 (2025): Volume 9 Nomor 2 April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i2.14712

Abstract

Sistem Informasi Perguruan Tinggi Universitas Buana Perjuangan Karawang (SIPT UBP Karawang) merupakan aplikasi yang dirancang untuk mempermudah mahasiswa dalam mengelola administrasi akademik, seperti melihat nilai, pembayaran UKT, dan informasi perkuliahan. Berdasarkan pengalaman pengguna ditemukan permasalahan pada tampilan antarmuka, khususnya halaman dashboard yang dinilai kurang intuitif. Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap aplikasi SIPT UBP Karawang menggunakan algoritma Naive Bayes, serta merancang solusi perbaikan antarmuka dengan pendekatan Design Thinking. Data yang dikumpulkan sebanyak 502 komentar pengguna aplikasi, setelah tahap preprocessing menjadi 406 data set komentar aplikasi. Hasil dari klasifikasi sentimen terdapat 236 sentimen positif dan 170 sentimen negatif. Visualisasi WordCloud pada komentar negatif menunjukan kata “dashboard” paling sering muncul, mengindikasikan titik masalah utama pada antarmuka. Proses klasifikasi menggunakan algoritma Naive Bayes menghasilkan akurasi sebesar 0.89% . Tampilan antarmuka didesain ulang agar lebih ramah pengguna menggunakan metode Design Thinking. Pengujian dilakukan menggunakan instrumen System Usability Scale (SUS), dan teknik Usability Testing. Skor rata-rata yang diperoleh adalah 81, jadi termasuk nilai A atau predikat sangat bagus. Penelitian ini menunjukkan bahwa hasil klasifikasi sentimen dengan metode Naive Bayes dan pendekatan Design Thinking efektif dalam melakukan identifikasi masalah dan menghasilkan solusi desain yang meningkatkan kepuasan pengguna terhadap aplikasi SIPT UBP Karawang.
Classification of Traffic Accident Levels in West Java Using the K-Means Algorithm Gusti Musyaffa Razan; Baenil Huda; Shofa Shofiah Hilabi
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 5 No. 04 (2026): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), April 2026
Publisher : Sean Institute

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Abstract

Traffic accidents are an important factor in improving public safety in West Java Province, because the population movement rate there is very high. The high number of accidents is directly related to increased deaths and material losses, but the use of historical data is still limited to administrative archiving tasks without any process of identifying regional vulnerability patterns. This study aims to classify accident-prone areas using Data Mining techniques and the K-Means Clustering algorithm, as well as applying the CRISP-DM framework approach. The analyzed dataset comes from the Indonesian National Police Traffic Accident Database (Pusiknas Polri) for the period 2020 to 2025, consisting of 552 observations with indicator variables covering the number of fatalities, serious injuries, and minor injuries. The determination of the most appropriate number of clusters was tested using the Silhouette method to ensure more accurate and objective modeling results. The analysis shows that the number of clusters (k=3) is the most appropriate, with a Silhouette metric value of 0.398. The application of the model produces three levels of risk: the red zone, which indicates high risk with 51 cases and the highest mortality rate; the yellow zone, which indicates moderate risk with 189 cases; and the green zone, which indicates low risk with 312 cases. The visualization of these mapping results is expected to be an important tool for the police and local governments in formulating mitigation policies, improving patrol efficiency, and accelerating infrastructure improvements in high-risk areas, thereby reducing the number of accidents in the future.
Implementasi Algoritma K-Means Clustering untuk Mengelompokkan Wilayah Produksi Kopi di Jawa Barat Jingga Pratama; Baenil Huda; Shofa Shofiah Hilabi; Elvina Novalia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 2 (2026): April 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i2.3622

Abstract

Regional disparities in Arabica coffee output across West Java Province underscore the necessity of evidence-based analytical approaches to systematically map production distribution. This study applies K-means clustering to segment Arabica coffee-producing districts and cities based on their production volumes. The analytical pipeline encompasses data preprocessing, cluster modeling, performance evaluation, and result visualization. Three distinct production tiers emerged from the analysis: low, moderate, and high. A silhouette score of 0.883 confirmed excellent cluster cohesion and separation quality. The novelty of this research lies in its territory-level, data-driven segmentation approach paired with interpretable visualization to inform regional policy. The findings reveal pronounced inter-regional production disparities and offer an empirical foundation for crafting targeted, data-informed, and sustainable development strategies to improve the equity and competitiveness of Arabica coffee production at the regional level.Keywords: K-Means clustering; Arabica coffee; Coffee production; Regional clustering; Data analysisAbstrakKesenjangan tingkat produksi kopi Arabika antar daerah di Provinsi Jawa Barat mengindikasikan perlunya pendekatan analitis berbasis data untuk memetakan pola sebaran produksi secara sistematis. Penelitian ini menerapkan metode K-means clustering guna mengelompokkan daerah penghasil kopi Arabika berdasarkan volume produksinya. Rangkaian analisis mencakup pra-pemrosesan data, pemodelan cluster, evaluasi performa, dan visualisasi hasil. Tiga kelompok wilayah berhasil terbentuk, yakni kategori produksi rendah, menengah, dan tinggi. Nilai silhouette score sebesar 0,883 mengonfirmasi kualitas pengelompokan yang sangat baik dengan separasi antar cluster yang tegas. Kebaruan penelitian terletak pada penerapan segmentasi berbasis wilayah yang bersifat data-driven serta penyajian visual yang informatif sebagai fondasi pengambilan kebijakan. Temuan ini mengungkap adanya ketimpangan produksi yang nyata antar wilayah sekaligus menyediakan landasan empiris untuk merancang strategi pengembangan kopi Arabika yang lebih tepat sasaran, berbasis data, dan berkelanjutan ditingkat daerah. 
Design and Implementation of a Manpower Distribution Information System at PT Gokko Mirai Indonesia Ani Ani; Baenil Huda; Elfina Novalia; Bayu Priyatna
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 3 (2026): Juni 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i3.3618

Abstract

At PT Gokko Mirai Indonesia, workforce deployment is still done manually, which makes the process inefficient, time-consuming, and potentially leads to data processing errors and unclear application status. The purpose of this research is to create and implement an integrated information system for web-based workforce distribution that improves process efficiency and transparency. The waterfall method is used for system design, testing, implementation, and needs analysis. PHP is used in the construction of this system. and utilizes the Laravel framework and MySQL database. The main features are applicant data control, vacancy data, application submission process, and real-time application status monitoring. Black box testing results show that every system feature operates as intended, according to requirements. The new system can improve data processing efficiency and provide information transparency to applicantsKeywords: Information system; Recruitment; Web; Waterfall; Black box testing AbstrakDi PT Gokko Mirai Indonesia, penyebaran tenaga kerja masih dilakukan secara manual, yang membuat proses tidak efisien, memakan waktu lama, dan berpotensi menyebabkan kesalahan pengolahan data dan ketidakjelasan tentang status lamaran. Tujuan dari penelitian ini adalah untuk mengembangkan dan menerapkan sistem informasi yang terintegrasi untuk penyaluran tenaga kerja yang berbasis web yang akan meningkatkan efisiensi dan transparansi proses. Metode Waterfall yang digunakan meliputi analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Sistemnya ini dibuat menggunakan PHP dan menggunakan framework Laravel serta database MySQL. Pengendalian data pelamar, data lowongan, proses pengajuan lamaran, dan pemantauan status lamaran secara real-time adalah fitur utama. Hasil pengujian metode black box menunjukkan bahwa semua fitur sistem bekerja dengan baik sesuai dengan kebutuhan. Sistem baru dapat meningkatkan efisiensi pengolahan data.serta memberikan transparansi informasi kepada pelamar. 
DIGITALISASI LAYANAN TOKO LARIS MOTOR DENGAN TEKNOLOGI CHATBOT OTOMATIS BERBASIS AI Gefira Rahmaifha; April Lia Hananto; Elfina Novalia; Baenil Huda
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7374

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem chatbot otomatis berbasis Artificial Intelligence (AI) menggunakan workflow automation N8N sebagai solusi digitalisasi layanan pelanggan pada Toko Laris Motor. Permasalahan yang dihadapi meliputi keterlambatan respons, penumpukan pesan WhatsApp, serta ketidakkonsistenan informasi akibat proses pelayanan yang masih dilakukan secara manual. Penelitian ini menggunakan pendekatan Research and Development (R&D) yang mencakup tahapan analisis kebutuhan, perancangan sistem, pengembangan, pengujian, dan evaluasi. Sistem chatbot dikembangkan dengan memanfaatkan AI Agent untuk memahami konteks percakapan, serta diintegrasikan dengan WhatsApp API dan Google Sheets guna menyediakan informasi produk, harga, dan ketersediaan stok secara real-time. Proses pengujian sistem dilakukan menggunakan metode Blackbox Testing untuk memastikan setiap fungsi sistem berjalan sesuai dengan kebutuhan pengguna tanpa melihat struktur kode program. Hasil pengujian menunjukkan bahwa sistem mampu meningkatkan kecepatan respons layanan, menjaga konsistensi informasi, serta mengurangi beban kerja administratif. Implementasi chatbot ini mendukung transformasi digital pada sektor UMKM ritel otomotif dan menunjukkan bahwa otomatisasi layanan berbasis AI dapat meningkatkan efektivitas operasional serta kualitas interaksi pelanggan secara berkelanjutan.