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All Journal Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Innovative: Journal Of Social Science Research Journal of Information System Exploration and Research
Ayub Prasetyo
Gunadarma University
Humanities Computer Science & IT Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Other

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Perancangan Aplikasi Sistem Penjualan Berbasis Microsoft Access Pada Distributor Mutiara Cosmetic Prasetyo, Ayub; Hasanah, Ina Siti; Amalia, Firda
Innovative: Journal Of Social Science Research Vol. 4 No. 4 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i4.9955

Abstract

Proses penjualan yang terkomputerisasi memainkan peran penting dalam kelancaran dan efisiensi operasi penjualan. Sistem komputerisasi menjadi faktor utama dalam upaya tersebut. Pada penelitian ini dibahas tentang komputerisasi proses penjualan. Selama ini, proses penjualan distributor Mutiara Cosmetic masih manual. Tujuan penelitian ini adalah merancang aplikasi berbasis Microsoft Access. Pendekatan waterfall dilakukan untuk memastikan perancangan aplikasi berjalan terstruktur dan sistematis, sementara Microsoft Access digunakan untuk membangun basis data dan antarmuka aplikasi, serta black box testing digunakan untuk menguji fungsionalitas aplikasi dari perspektif pengguna akhir. Hasil perancangan aplikasi terdiri dari beberapa tahapan. Pertama, dilakukan analisis sistem penjualan lama dimana pembuatan nota penjualan dan pencatatan stok produk dilakukan secara manual. Kedua, pemodelan sistem menggunakan diagram konteks, DFD, dan ERD. Diagram konteks menghasilkan empat entitas, yaitu pegawai stok, pegawai kasir, pemilik, dan pembeli. DFD menjelaskan proses berupa pendataan produk, transaksi, pemasukkan, dan pembaharuan stok. ERD menggambarkan hubungan antar data pada sistem. Ketiga, perancangan aplikasi untuk menggantikan sistem lama menjadi terkomputerisasi, meliputi tampilan Splash Screen, menu Login, tampilan Halaman Utama, menu Input Produk, menu Input Stok Produk, menu Transaksi, Laporan Transaksi, Laporan Penjualan, dan Laporan Stok Akhir. Keempat, aplikasi diuji menggunakan black box testing dimana semua kasus uji dan tahapannya berhasil sesuai harapan.
Employees’ Satisfaction and Sentiment Analysis toward BERSATU Application Ayub Prasetyo; Hotniar Siringoringo; Firda Amalia
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 27 No. 1 (2025): June 2025
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.27.1.21-32

Abstract

The era of digitalization has boosted companies to adopt innovative technology in seizing competitive superiority. However, adaptation to the change often deals with constraints, affecting operational efficiency and effectiveness. In this regard, PT Beiersdorf Indonesia faces issues regarding the impact of digital transformation of the sales process from manual to digital using Beiersdorf Sales Activity Tracking Routine (BERSATU) application, such as the difficulty of technology adaption by employees, accustomed to manual method, limitations of internet access in some areas, and technical constraints on application as well as insufficient technical support. Therefore, the research aims to analyze sentiment of user review on “BERSATU” application, using various algorithm classification and modeling topic. A total of 600 user reviews had been collected and analyzed to know positive or negative sentiments. Of 600 reviews, 60.33% was positive and 39.67% was negative. Based on the evaluated five algorithms classification, SVM and Naïve Bayes were superior with accuracy above 97% with better F1-Score. Regression Logistics had 96% accuracy, but it had low recall. Random Forest had 94% accuracy with a better F1-Score, but low recall was received. KNN has 93% accuracy, but low recall was obtained. SVM and Naïve Bayes were the recommended for further analysis. Modeling of LDA topics generated three topics with dominant keywords. Topic 1, such as “application,” “bersatu," “data,” “sales,” and “results,” covered 44.5% of the documents. Topic 2, including “application,” “good,” “visit,” and “order,” was relevant at 29.5%. Topic 3, comprising of “application,” “assistance,” “easy,” “sell,” and “store,” was relevant 26.1% of the documents.
Risk-Aware Multi-Capacity Routing for Shift-Feasible Cosmetic Distribution Ayub Prasetyo; Firda Amalia; Sarifuddin Madenda; Ernastuti; Murni
Journal of Information System Exploration and Research Vol. 4 No. 2: April 2026
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v4i2.62

Abstract

Urban cosmetic distribution requires routing decisions that satisfy delivery time windows, vehicle capacity, and working-hour constraints. Conventional routing models often rely on deterministic travel-time assumptions and single-capacity limits, which mayobscure lateness risk and volume overload. This study proposes a risk-aware multi-capacity routing framework for shift-feasible cosmetic distribution. Customer and depot coordinates were used to estimate distances with the Haversine formula, adjusted by acircuity factor and converted into travel time. The model applies split-delivery preprocessing for oversized records, enforces weight and volume capacities, and distinguishes delivery trips from vehicle requirements within a 09:00–17:00 shift.Three routing models were evaluated: deterministic single-capacity, distance-based multi-capacity, and risk-aware multi-capacity routing. Results show that oversized records were split, eliminating unserved and infeasible customers. The single-capacity model produced multiple over-volume cases, while the multi-capacity model removed capacity violations without significantly affecting lateness or resource needs. The risk-aware model reduced lateness and late customers but increased travel time, delivery trips, and vehicle requirements. Sensitivity analysis confirmed stable conclusions across key assumptions. These findings highlight improved delivery reliability alongside trade-offs between service performance and resource usage.
Co-Authors Ernastuti Firda Amalia Hotniar Siringoringo Ina Siti Hasanah Murni Sarifuddin Madenda