Implementasi Cloud Database Library Knowledge-Based Layanan Kos Untuk Chatbot WhatsApp Berbasis AI

Stevano, Frederic (2026) Implementasi Cloud Database Library Knowledge-Based Layanan Kos Untuk Chatbot WhatsApp Berbasis AI. S1 Teknik Informatika thesis, STMIK Widya Cipta Dharma.

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Abstract

ABSTRAK Frederic Willy Stevano, 2026, Implementasi Cloud Database Library Knowledge-Based Layanan Kos untuk Chatbot WhatsApp Berbasis AI. Skripsi Program Studi Teknik Informatika, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma. Pembimbing Utama Eka Arriyanti, S.Pd., M.Kom. dan Pembimbing Pendamping Siti Lailiyah, S.Kom., M.Kom. Kata Kunci: Layanan, Kos, Pemetaan, Pertanyaan, Sistem_Cerdas. Penelitian ini bertujuan memetakan pengetahuan pertanyaan dan jawaban (Question and Answer; QnA) layanan kos dalam kerangka struktur jaringan syaraf tiruan sehingga menjadi basis pengetahuan (knowledge-based) untuk chatbot layanan kos. Selanjutnya, penelitian ini juga bertujuan mengimplementasikan knowledge-based layanan kos pada cloud database library sehingga sistem chatbot WhatsApp berhasil diimplementasikan sebagai layanan informasi kos yang cerdas. Pemetaan QnA dilakukan melalui pengumpulan dan verifikasi data, pengelompokan pertanyaan Q1–Q8, penentuan topik, kondisi, dan aturan pemetaan, serta pengaitan dengan kode jawaban A1–A79. Hasil pemetaan diimplementasikan pada Google Sheets sebagai cloud database library. Sistem dikembangkan menggunakan metode Waterfall yang mencakup tahap analisis, perancangan, implementasi, pengujian, penerapan, dan pemeliharaan. Implementasi dilakukan melalui integrasi n8n, WhatsApp, Fonnte, Google Sheets, dan Gemini AI, kemudian diuji menggunakan Black Box Testing dan Basis Path Testing. Hasil penelitian menghasilkan delapan kelompok pertanyaan, 49 aturan pemetaan, 79 kode jawaban, dan 1.013 variasi pertanyaan. Sistem mampu memberikan informasi layanan, mengelola konteks percakapan dan pemesanan, menerima bukti pembayaran, menangani pengaduan, serta memperbarui status kamar. Black Box Testing terhadap 23 skenario memperoleh keberhasilan 100%, sedangkan Basis Path Testing menghasilkan kompleksitas siklomatik 8 dengan delapan jalur independen yang seluruhnya berhasil diuji. Dengan demikian, sistem cerdas layanan informasi kos berhasil diterapkan sebagai chatbot WhatsApp. ============================================================ ABSTRACT Frederic Willy Stevano, 2026, Implementation on Knowledge-based Cloud Database Library of A Room Rental Service for AI-based WhatsApp Chatbot. Undergraduate Thesis. Informatics Engineering Study Program, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma. Main Supervisor Eka Arriyanti, S.Pd., Co-Supervisor Siti Lailiyah, S.Kom., M.Kom. Keywords: Service, Room Rental, Mapping, Questions, Intelligent_System. This study aims to map Question and Answer (QnA) knowledge of room rental services within an artificial neural network structure to form a knowledge base for a room rental service chatbot. Furthermore, this study aims to implement the knowledge base in a cloud database library so that the WhatsApp chatbot can be successfully implemented as an intelligent room rental information service. The QnA mapping was conducted through data collection and verification, classification of questions into Q1–Q8, determination of topics, conditions, and mapping rules, and association with answer codes A1–A79. The mapping results were implemented in Google Sheets as a cloud database library. The system was developed using the Waterfall method, which includes analysis, design, implementation, testing, deployment, and maintenance. The implementation integrated n8n, WhatsApp, Fonnte, Google Sheets, and Gemini AI and was subsequently tested using Black Box Testing and Basis Path Testing. The study produced eight question groups, 49 mapping rules, 79 answer codes, and 1,013 question variations. The system can provide service information, manage conversation and booking contexts, receive proof of payment, handle complaints, and update room statuses. Black Box Testing of 23 scenarios achieved a 100% success rate, while Basis Path Testing produced a cyclomatic complexity value of 8, with all eight independent paths successfully tested. Therefore, the intelligent room rental information service system was successfully implemented as a WhatsApp chatbot.

Item Type: Thesis (S1 Teknik Informatika)
Additional Information: Pembimbing 1 : Eka Arriyanti, S.Pd., M.Kom Pembimbing 2 : Siti Lailiyah, S.Kom., M.Kom
Uncontrolled Keywords: Layanan, Kos, Pemetaan, Pertanyaan, Sistem_Cerdas.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Teknik Informatika
Depositing User: Mr Frederic Willy Stevano
Date Deposited: 07 Aug 2026 05:49
Last Modified: 07 Aug 2026 05:49
URI: http://repository.wicida.ac.id/id/eprint/6431

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