Lendra, Abysal Bisma Adina (2026) Perbaikan Proses Pelaporan Harian Lalu Lintas Pengiriman Pesan Application-To-Person (A2P) dengan Robotic Process Automation (RPA) Berbasis Pendekatan Lean pada Perusahaan Telekomunikasi. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Proses pelaporan harian lalu lintas pengiriman pesan Application-to-Person (A2P) pada perusahaan objek amatan dilakukan secara manual dengan durasi rata-rata sekitar 40-50 menit per hari. Proses ini bersifat rule-based dan repetitif, yang meliputi pengambilan data dari web, pengolahan, interpretasi, hingga distribusi laporan. Proses ini membutuhkan keterlibatan penuh operator setiap hari sehingga menimbulkan inefisiensi waktu dan tenaga kerja, serta ketidakkonsistenan waktu pelaporan. Penelitian ini menganalisis proses eksisting melalui pendekatan lean untuk mengidentifikasi aliran proses, jenis aktivitas, dan waste, yang menjadi dasar perancangan dan implementasi Robotic Process Automation (RPA) berbasis Python sebagai solusi perbaikan. Hasil penelitian menunjukkan bahwa penerapan RPA mengurangi total waktu waste sebesar 90,47%, serta durasi proses pelaporan sebesar 97,13% menjadi sekitar 84 detik. Selain itu, variabilitas waktu pelaporan juga menurun secara signifikan, dengan penurunan MAD dari 81 detik menjadi 7 detik dan hasil Brown-Forsythe Test (W₅₀ = 5,3134 > F kritis = 4,414; p = 0,03328 < α = 0,05), yang mengindikasikan pelaporan berbasis RPA lebih stabil dibanding pelaporan secara manual. Validasi expert judgement mengenai kesesuaian luaran memperoleh skor 4,58 dari 5,00, sementara pengujian RPA selama 20 hari memiliki tingkat keberhasilan 90%. Kontribusi utama RPA tidak sekadar mempercepat proses, melainkan menghilangkan ketergantungan pada kehadiran operator dan menstabilkan waktu pelaporan sehingga laporan dapat dihasilkan secara konsisten dan tepat waktu. Sistem juga memiliki empat potensi kegagalan dengan dua di antaranya terjadi saat pengujian dan berhasil ditangani
sehingga sistem dapat berjalan secara berkelanjutan.
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The daily reporting process for Application-to-Person (A2P) messaging traffic at the observed company is done manually and takes an average of about 40-50 minutes per day. This process is rule-based and repetitive, encompassing data collection from the web, processing, interpretation, and report distribution. It requires the operator’s full involvement every day, leading to inefficiencies in time and labor, as well as inconsistent reporting times. This study analyzes the existing process using a lean approach to identify process flows, activity types, and waste, which serve as the basis for designing and implementing Python-based Robotic Process Automation (RPA) as an improvement solution. The results show that implementing RPA reduces total waste time by 90.47% and cuts the reporting process duration by 97.13% to approximately 84 seconds. In addition, the variability in reporting time also decreased significantly, with a reduction in MAD from 81 seconds to 7 seconds and a Brown-Forsythe Test result (W₅₀ = 5.3134 > critical F = 4.414; p = 0.03328 < α = 0.05), indicating that RPA-based reporting is more stable than manual reporting. Expert judgement validation regarding the accuracy of the output received a score of 4.58 out of 5.00, while the 20-day RPA testing period achieved a 90% success rate. The main contribution of RPA is not merely to speed up the process, but to eliminate dependence on operator presence and stabilize reporting times so that reports can be generated consistently and on time. The system also has four potential points of failure, two of which occurred during testing and were successfully addressed, allowing the system to operate continuously.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Robotic Process Automation, Lean Thinking, Time Study, Value Stream Mapping, Process Improvement, Application-to-Person messaging, Operational Reporting, Robotic Process Automation, Lean Thinking, Time Study, Value Stream Mapping, Process Improvement, Application-to-Person messaging, Operational Reporting |
| Subjects: | T Technology > T Technology (General) > T58.62 Decision support systems T Technology > T Technology (General) > T58.8 Productivity. Efficiency T Technology > TS Manufactures > TS183 Manufacturing processes. Lean manufacturing. |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | Abysal Bisma Adina Lendra |
| Date Deposited: | 03 Aug 2026 01:43 |
| Last Modified: | 03 Aug 2026 01:43 |
| URI: | http://repository.its.ac.id/id/eprint/141630 |
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