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All Journal Jurnal Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer OPERATION EXCELLENCE: Journal of Applied Industrial Engineering WIDYAKALA JOURNAL Jurnal INTECH Teknik Industri Universitas Serang Raya JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Abdimas UNWAHAS : Jurnal Pengabdian Masyarakat UNWAHAS Mitra Akademia: Jurnal Pengabdian Masyarakat Indonesian Journal of Industrial Engineering & Management Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Konstelasi: Konvergensi Teknologi dan Sistem Informasi Journal Physical Therapy UNISA
Novi Purnama Sari
Program Studi S1 Perpajakan Fakultas Ilmu Administrasi Universitas Brawijaya
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Designing Secondary Packaging for Skincare Products Using the Kansei Engineering Method Faizi, Isnaini; Aprilia, Ika Riswi; Wati, Rahma; Sari, Novi Purnama
WIDYAKALA JOURNAL : JOURNAL OF PEMBANGUNAN JAYA UNIVERSITY Vol 12, No 2 (2025): Urban Lifestyle and Urban Development
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat UPJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36262/widyakala.v12i2.1198

Abstract

The use of secondary packaging in skincare product bundles is essential for the shipping process. Relying solely on bubble wrap presents drawbacks, as it is non-reusable and lacks aesthetic value. The absence of optimal secondary packaging increases the risk of product damage during distribution and reduces visual appeal, ultimately affecting consumer perceptions of quality and brand credibility. Therefore, the design and development of suitable secondary packaging is necessary. This study aims to identify appropriate design elements based on user perceptions using the Kansei Engineering method, which has proven effective in product development. A total of 43 Kansei words were extracted from 39 packaging samples, resulting in two primary design concepts: “Practical-Modern” and “User Friendly- Untenable” The selected design elements include: leather and plastic materials (X1.6), pouch shape (X2.7), leather handle with divider (X3.7), four-sided flip-top closure (X4.9), modern design style (X5.1), and transparent red color (X6.10). The highest correlation value (PCC = 0.8963) was found in the “shape” element, indicating its strong influence on consumer perception. The final design was implemented as a physical mockup. Evaluation results showed that 59.4% of respondents preferred the design concept reflecting ease of use. Fuzzy Logic analysis confirmed these findings, placing the design in a neutral category leaning toward user-friendliness. These findings offer valuable insights into how emotional consumer preferences can inform secondary packaging strategies for skincare products.
Aplikasi Fuzzy Logic dalam Evaluasi Kemasan Siomay Gondrong Sari, Novi Purnama; Nursya'bani, Jauhariah; Sandjaja, Shafa Aisyah Pasha; Satriaji, Tegar Bayu
Jurnal SENOPATI : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Vol 7, No 1 (2025): Jurnal SENOPATI Vol 7, No 1
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.senopati.2025.v7i1.7010

Abstract

Permasalahan utama dalam evaluasi kemasan Siomay Gondrong adalah memastikan desain kemasan yang efektif untuk menarik konsumen sekaligus menjaga kualitas produk. Faktor-faktor seperti estetika, fungsionalitas, dan daya tarik visual sering kali sulit diukur secara kuantitatif. Penelitian ini bertujuan untuk menerapkan logika fuzzy sebagai alat evaluasi yang mampu menangani ketidakpastian dan subjektivitas dalam penilaian. Metode yang digunakan melibatkan pengumpulan data melalui kuesioner dari konsumen dan ahli desain, yang kemudian diolah menggunakan sistem logika fuzzy berbasis aturan. Sistem ini mengintegrasikan variabel seperti estetika, daya tahan, dan keberlanjutan dalam menghasilkan skor evaluasi akhir. Hasil riset penelitian menunjukkan sistem fuzzy logic memberikan hasil jawaban netral. Kesimpulannya, sistem logika fuzzy belum sepenuhnya memberikan hasil yang efektif dan fleksibel untuk mengevaluasi desain kemasan.
Integrasi Kansei Engineering dan Data Mining dengan Particle Swarm Optimization pada K-Means untuk Penentuan Konsep Desain Kemasan Dodol Faizi, Isnaini; Sari, Novi Purnama
KONSTELASI: Konvergensi Teknologi dan Sistem Informasi Vol. 5 No. 1 (2025): Juni 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/konstelasi.v5i1.11407

Abstract

Rasa Dewa merupakan salah satu UMKM yang memproduksi dodol belimbing khas Kota Depok. Produk ini memiliki potensi besar sebagai produk unggulan, namun kemasan yang digunakan masih kurang menarik, tidak praktis, dan belum mencerminkan identitas lokal. Hasil survei menunjukkan bahwa 93,5% responden merekomendasikan perbaikan kemasan. Oleh karena itu, pengembangan kemasan perlu dioptimalkan dengan memahami konsep desain berdasarkan aspek emosional konsumen. Penelitian ini bertujuan untuk menentukan konsep desain kemasan dodol belimbing berdasarkan preferensi konsumen menggunakan pendekatan Kansei Engineering. Proses pengolahan data dilakukan dengan teknik data mining menggunakan algoritma K-Means PSO untuk mengelompokkan kata Kansei dalam merumuskan konsep desain. Dari hasil penelitian, diperoleh 26 kata Kansei dan 53 sampel sebagai acuan. Berdasarkan uji validitas, hanya 18 kata Kansei yang dinyatakan relevan. Dua konsep utama diperoleh dari dua klaster dominan hasil pengelompokan K-Means PSO, dengan nilai k optimal = 2 berdasarkan Silhouette Score. Klaster 1 mewakili konsep estetika, sedangkan Klaster 2 mewakili konsep fungsionalitas. Nilai gbest sebesar -0,65909 (Klaster 1) dan 0,48952 (Klaster 2) menunjukkan solusi terbaik yang digunakan sebagai acuan centroid awal dalam proses K-Means, sehingga menghasilkan klasterisasi yang lebih terstruktur.
Determination of Packaging Design Elements of Baby Fish Crispy MSMEs Using Kansei Engineering Method Sari, Novi Purnama; Fatah, Abdillah Nur; Amir, Anneke Hazima Putri; Rasyid, Akbar Fikri
IJIEM - Indonesian Journal of Industrial Engineering and Management Vol 6, No 3: October 2025
Publisher : Program Pascasarjana Magister Teknik Industri Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijiem.v6i3.31466

Abstract

The current packaging of baby fish crispy has problems, namely packaging design elements such as not having an identity on the packaging and the packaging becomes less attractive, making it difficult to compete with similar products. The research objective is to identify packaging design elements that are in accordance with consumer perspectives. The research method uses Kansei Engineering with the supporting method used is Quantification Theory Type-1 (QTT1), to analysis the interaction between design elements and design concepts by converting independent variable categories (design elements) into quantitative data in KE. The research results obtained 7 categories of design elements based on 42 predetermined samples. The selected concept ‘Standard - Protection’ obtained the highest R-Square value of 0.9909 with design elements namely: aluminum (X1.7), tall tube (X2.2), lift-off lid (X3.2), corporation & window (X4.9), modern (X5.1), large (X6.3), and direct printing (X7.2). The results of the priority of design elements obtained from the Partial Correlation Coefficient (PCC) value with the highest value on the concept of ‘Standard - Protection’ are the type of body design element (X2) with a value of 0.98598.
Development of Concealer X Packaging Using Kansei Engineering Sari, Novi Purnama; Sinur, Valeri Vela; Suharto, Nurlita Pratiwi; Amri, Aulia
IJIEM - Indonesian Journal of Industrial Engineering and Management Vol 6, No 3: October 2025
Publisher : Program Pascasarjana Magister Teknik Industri Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijiem.v6i3.30961

Abstract

Concealer x packaging still has shortcomings in its packaging from the applicator which makes it difficult to use, the packaging design is uncomfortable for consumers, and the visual design is less informative. This is a challenge in developing concealer x packaging by considering consumer preferences. The purpose of this study is to identify the concept and elements of packaging design according to consumer preferences. Kansei Engineering is one of the methods used to optimize the identification of consumer preferences. This method can capture consumer emotions in the form of Kansei words which are translated into concepts and elements of packaging design. Other supporting methods used are Principal Component Analysis (PCA) and Quantification Theory Type 1 (QTT1). The results obtained were 61 selected samples and 35 Kansei words. The samples and Kansei words were then evaluated by creating a semantic differential questionnaire for 30 respondents by purpose judgment sampling. The results of the concept obtained by the PCA method were 4 PCs with PC 2 selected as the practical standard because it had the highest R-square value of 0.911. The results of the packaging design elements obtained are X1.1 Strew X2.9 Concave X3.6 Jug X4.3 Half Tube X5.4 Heptagon X6.2 Brush and Sponge X7.5 Silicon X8.1 Fun X9.1 Small 1 - 5 gr X10.1 Under. The conclusion of the packaging design obtained has described practical packaging following the design concept and meets consumer preferences.
Forecasting Persediaan Kemasan Folding Box untuk Mitigasi Risiko Stock Out: Pendekatan Sarima, Prophet, Xgboost, dan Random Forest Prastiwinarti, Wiwi; Muliati, Sukma Ambar; Sari, Novi Purnama
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 3: Juni 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026133

Abstract

Ketepatan peramalan kebutuhan persediaan folding box menjadi faktor krusial dalam menjaga kelancaran produksi industri kosmetik, khususnya bagi perusahaan maklon dengan sistem produksi Make to Order (MTO). PT X sebagai salah satu perusahaan maklon menghadapi tantangan dalam pengelolaan persediaan kemasan folding box, yang selama ini masih dilakukan secara manual. Ketidakakuratan dalam perencanaan persediaan folding box berpotensi menimbulkan risiko stock out dan keterlambatan produksi. Penelitian ini bertujuan untuk membandingkan kinerja empat metode peramalan, yaitu SARIMA, Prophet, XGBoost, dan Random Forest, dalam memprediksi kebutuhan folding box berdasarkan data historis periode Januari 2023 hingga Desember 2024. Evaluasi kinerja model dilakukan menggunakan dua metrik utama, yaitu Root Mean Squared Error (RMSE) dan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan bahwa model Random Forest memberikan performa terbaik dengan RMSE sebesar 14.375,29 dan MAPE sebesar 0,66%, diikuti oleh XGBoost dan Prophet. Temuan ini memperlihatkan bahwa pendekatan machine learning lebih unggul dalam menangani pola data persediaan yang fluktuatif dibandingkan model statistik. Penerapan model prediktif ini diharapkan dapat mendukung PT X dalam menyusun strategi pengadaan folding box secara lebih tepat guna meminimalkan risiko stock out dan meningkatkan efisiensi produksi. Penelitian ini juga membuka peluang pengembangan metode lanjutan berbasis hybrid atau ensemble untuk meningkatkan akurasi prediksi di masa mendatang.   Abstract The accuracy of folding box inventory demand forecasting is a crucial factor in maintaining the smooth operation of the cosmetics industry, especially for contract manufacturing companies with a Make to Order (MTO) production system. PT X, as one of the contract manufacturing companies, faces challenges in managing folding box packaging inventory, which has been done manually until now. Inaccuracies in folding box inventory planning have the potential to cause stock-out risks and production delays. This study aims to compare the performance of four forecasting methods—SARIMA, Prophet, XGBoost, and Random Forest—in predicting folding box demand based on historical data from January 2023 to December 2024. Model performance evaluation was conducted using two primary metrics: Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The results indicate that the Random Forest model performed best with an RMSE of 14.375.29 and a MAPE of 0,66%, followed by XGBoost and Prophet. These findings indicate that machine learning approaches are more effective in handling fluctuating inventory data patterns compared to statistical models. The implementation of these predictive models is expected to support PT X in developing more effective procurement strategies for folding boxes, thereby minimizing the risk of stockouts and improving production efficiency. This research also opens up opportunities for the development of advanced hybrid or ensemble-based methods to enhance prediction accuracy in the future.
Co-Authors Aditia Ginantaka Amir, Anneke Hazima Putri Amri, Aulia Aprilia, Ika Riswi Araminta, Shafa Fadhillah, Fahri Faizi, Isnaini Fatah, Abdillah Nur Hilmi Zadah Faidlullah Indriany, Dita Febrian Isna, Ade Kautsar, Alfa Giffari Luna, Zahira Ersa Maharani, Devyta Moh. Ali Imron, Moh. Muliati, Sukma Ambar Muryeti Muryeti, Muryeti Napitupulu, Yesaya Firdaus Nursya'bani, Jauhariah Rahma Wati Rahmadianto, Muhammad Athariq Rahmawati, Chintya Dwi Ramadhan, Raihan Thoriq Rasyid, Akbar Fikri Rina Ningtyas, Rina Saeful Imam, Saeful Sandjaja, Shafa Aisyah Pasha Satriaji, Tegar Bayu Silvia, Deli Sinur, Valeri Vela Suharto, Nurlita Pratiwi Wiguna, Nada Nabilla Wiwi Prastiwinarti Yunisyah, Fadilah Zelvi, Mustika Zelvi, Mustika