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DETERMINATION OF THE BEST FORECASTING METHOD FROM MOVING AVERAGE, EXPONENTIAL SMOOTHING, LINEAR REGRESSION, CYCLIC, QUADRATIC, DECOMPOSITION AND ARTIFICIAL NEURAL NETWORK AT PACKAGING COMPANY Lina Gozali; Sharin Candra; Andres Andres; Natalia Velany Putri; Frans Jusuf Daywin; Carla Olyvia Doaly; Vivi Triyanti
Jurnal Ilmiah Teknik Industri Vol 9, No 2 (2021): Jurnal Ilmiah Teknik Industri : Jurnal Keilmuan Teknik dan Manajemen Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jitiuntar.v9i2.13377

PT. Peace Industrial Packaging is a company that produces Styrofoam and plastic bottles that are used as containers or places or commonly referred to as packaging used by other companies to place their finished products. After getting data on the number of requests and production results obtained every month then the data will be processed using several forecasting methods such as Single Moving Average; Double Moving Average; Weight Moving Average; Single Exponential Smoothing; Double Exponential Smoothing; Linear Regression; Quadratic Method, Method Cyclic; Decomposition Method; and Artificial Neural Network (ANN) Method. After conducting the research calculation, the following conclusions can be drawn. The right forecasting method used for the HBL 100 ML product is the ANN (Artificial Neural Network) method because it has the smallest error value, namely the MAD error method of 760.583554, the MSE error method of 863,032.834043, the SDE error method of 970.304264, the MAPE error method is 0.112530, and the MPE error method is 0.112530

PENENTUAN JUMLAH TENAGA KERJA DENGAN METODE KESEIMBANGAN LINI PADA DIVISI PLASTIC PAINTING PT. XYZ Lina Gozali; Andres .; Feriyatis .
Jurnal Ilmiah Teknik Industri Vol 3, No 1 (2015): Jurnal Ilmiah Teknik Industri (Jurnal Keilmuan Teknik dan Manajemen Industri)
Publisher : Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jitiuntar.v3i1.505

PT. XYZ merupakan perusahaan yang bergerak di bidang industri manufaktur bagian otomotif. Adanya bottleneck pada suatu stasiun kerja dikarenakan jumlah operator yang tidak ideal akan menyebabkan efisiensi produksi rendah. Dengan adanya keseimbangan lini dalam suatu sistem produksi akan meningkatkan efisiensi produksi perusahaan. Metode keseimbangan lini yang akan digunakan untuk menyelesaikan permasalahan tersebut yaitu metode Kilbridge-Wester, metode Helgeson-Birnie, metode Moodie Young, dan metode J-Wagon. Efisiensi awal yaitu sebesar 62,27%, dengan menggunakan metode Kilbridge-Wester, metode Helgeson-Birnie, dan metode J-Wagon didapatkan hasil efisiensi lini yang sama yaitu sebesar 76,24%, dan efisiensi lini dengan metode Moodie Young yaitu sebesar 80,06%. Metode Moodie Young merupakan metode terbaik untuk PT. XYZ karena memiliki hasil yang paling baik dalam efisiensi lini, balance delay, smoothness index, waktu siklus, waktu menganggur, dan jumlah stasiun kerja. Waktu siklus yang diperoleh yaitu sebesar 31 detik dengan balance delay sebesar 19,94%, smoothness index sebesar 29,08 waktu menganggur 86,52 detik, dan 14 stasiun kerja. Kata kunci: Keseimbangan Lini, Waktu Siklus, Efisiensi Lini, Balance Delay, Smoothness Index

DETERMINATION OF THE BEST FORECASTING METHOD FROM MOVING AVERAGE, EXPONENTIAL SMOOTHING, LINEAR REGRESSION, CYCLIC, QUADRATIC, DECOMPOSITION AND ARTIFICIAL NEURAL NETWORK AT PACKAGING COMPANY Lina Gozali; Sharin Candra; Andres Andres; Natalia Velany Putri; Frans Jusuf Daywin; Carla Olyvia Doaly; Vivi Triyanti
Jurnal Ilmiah Teknik Industri Vol. 9 No. 2 (2021): Jurnal Ilmiah Teknik Industri : Jurnal Keilmuan Teknik dan Manajemen Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jitiuntar.v9i2.13377

PT. Peace Industrial Packaging is a company that produces Styrofoam and plastic bottles that are used as containers or places or commonly referred to as packaging used by other companies to place their finished products. After getting data on the number of requests and production results obtained every month then the data will be processed using several forecasting methods such as Single Moving Average; Double Moving Average; Weight Moving Average; Single Exponential Smoothing; Double Exponential Smoothing; Linear Regression; Quadratic Method, Method Cyclic; Decomposition Method; and Artificial Neural Network (ANN) Method. After conducting the research calculation, the following conclusions can be drawn. The right forecasting method used for the HBL 100 ML product is the ANN (Artificial Neural Network) method because it has the smallest error value, namely the MAD error method of 760.583554, the MSE error method of 863,032.834043, the SDE error method of 970.304264, the MAPE error method is 0.112530, and the MPE error method is 0.112530

MODIFIKASI PRODUK NEBULIZER UNTUK MEMBANTU PENANGANAN PENDERITA COVID-19 YANG BERMASALAH DENGAN PERNAFASAN DENGAN METODE VDI 2221 DAN REVERSE ENGINEERING Samuel .; Frans Jusuf Daywin; Lina Gozali
Jurnal Mitra Teknik Industri Vol. 1 No. 1 (2022): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jmti.v1i1.18751

Dengan terdapatnya pandemik Covid-19 pada masa saat ini tentu juga memiliki keterkaitan dengan bahasan khusus yang dipilih oleh penulis. Bahasan khusus yang dipilih oleh penulis adalah modifikasi produk nebulizer dengan implementasi metode VDI 2221 dan reverse engineering. Produk nebulizer merupakan suatu produk yang sudah tersebar luas di pasar. Selain tersebar luas, produk ini juga dapat mendukung para manusia yang mengalami permasalahan dalam hal bernapas. Menurut penulis produk ini juga merupakan salah satu produk kebutuhan manusia apalagi jika dilihat kondisi dunia saat ini. Produk nebulizer juga dapat membantu para penderita virus covid-19 khususnya dalam hal permasalahan pernapasan. Dasar penulis melakukan modifikasi terhadap produk nebulizer adalah mengacu pada kebutuhan pasar di masa pandemik Covid-19 ini ataupun mengupayakan melakukan peningkatkan kualitas kinerja produk dan pembaharuan inovasi. Kata kunci: Nebulizer, Modifikasi, Reverse Engineering, VDI 2221

The Entrepreneurship Curriculum Development and Implementation from Tarumanegara University to Students of SMK Triguna, South Jakarta, Indonesia Lina Gozali; Evera Olivia; Jennifer Juyanto; Laurencia Tiffany; Vanecia Marchella Hardinanerl; Meiluseano Bramnas Hede; Fithri Mawartini
Journal of Innovation and Community Engagement Vol. 3 No. 3 (2022)
Publisher : Faculty of Smart Technology and Engineering, Universitas Kristen Maranatha, Bandung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/ice.v3i3.4696

It is essential in obtaining and developing a business so as to increase company profits to ensure the sustainability of the next business world. Business is usually identified with obtaining the maximum profit or as much as possible so as to be able to continue to develop the business world that is occupied. The concept of selling itself is not only focused on selling goods and services. The new concept emphasized the ability of business actors to meet consumer needs so that they can achieve a good level of customer satisfaction. Therefore, it takes the ability, knowledge, motivation, confidence, and skills needed to achieve the goals of the business world. The educational model was chosen during the implementation of Inquiry Learning and Problem Based Learning. The students were carried out in 1 hour 15 minutes to understand the mathematical model of the business world forecasting, and there were games and questions and answers. Management skills should also be obtained from mathematical analysis of a simple framework or problem. From this introduction to consumer needs, a conclusion can be drawn to understand existing customer demand patterns. This can develop business startups to capture patterns of customer demand in meeting customer satisfaction.

ANALISIS PENGARUH MOBIL LISTRIK TERHADAP PENJUALAN MOBIL INTERNAL COMBUSTION ENGINE (ICE) BERDASAR UJI ANOVA Wilson Patrick Tirtamidjaja; Anjerina Hartanto Widjaya; Claudia Glory Marchatmyna; Lina Gozali; Meirista Wulandari
Jurnal Mitra Teknik Industri Vol. 5 No. 1 (2026): Jurnal Mitra Teknik Industri
Publisher : Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jmti.v5i1.38039

The purpose of this paper was to determine whether Indonesian sales of internal combustion engine (ICE) vehicles are impacted by the growth in electric vehicle sales. The Association of Indonesian Automotive Industries' (GAIKINDO) publicly available wholesales reports for the years 2020–2024 provided the data used in the analysis. The association between the sales of the electric vehicle (X variable) dan the sales of the ICE vehicle (Y variable) was investigated quantitatively using simple regression analysis dan the F-test. The test results show that the significance value is greater than 0.05, with a value of 0.729. Therefore, it can be stated that the data distribution is normal. Then, the Spearman's Rank Correlation Test was performed, yielding a correlation coefficient value of -0.545, which means the two variables have a strong negative relationship; when one variable increases, the other will decrease. The significance value of the Spearman's rank correlation test performed was 0.067, which is below 0.1 as the P-Value. Next, the F-test was performed, resulting in an F-statistic value of 5.026, which, when compared to the F-table, is 4.96 (F-statistic ≥ F-table). From the 3 tests conducted, it can be concluded that H0 is accepted, meaning that the sale of electric cars significantly affects the sale of ICE (Internal Combustion Engine) cars.

Forecasting Demand for Cardboard Boxes Using Some Forecasting Method at PT XYZ Lina Gozali; Wildan; I Wayan Sukania; Ahad Ali; Sani Susanto
Jurnal Sistem Teknik Industri Vol. 28 No. 1 (2026): JSTI Volume 28 Number 1 January 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i1.22252

In the manufacturing sector, accurate demand forecasting is essential for effective material planning and inventory management. PT. XYZ, a company specialising in the production of corrugated carton boxes, currently faces challenges aligning raw material procurement with market demand due to the use of subjective, non-systematic forecasting methods. This research proposes applying statistical forecasting techniques to develop a more reliable and automated forecasting system. The study utilises historical monthly sales data collected over a one-year period, which are analysed using time series forecasting methods. The models are assessed based on key forecasting error metrics, including mean absolute deviation, mean squared error, and mean absolute percentage error. The model construction, data processing, and visualisation, thereby improving efficiency and reducing manual intervention. The findings reveal that combining seasonal statistical models with programming tools enhances forecast accuracy and supports data-driven decision-making within the organisation. This forecasting system can assist the planning division of PT. XYZ is optimising raw material allocation, reducing excess inventory, and preventing material shortages. In conclusion, the study recommends that PT. XYZ implements the decomposition forecasting model as a practical solution for improving the quality of its sales data. The research contributes to the development of forecasting systems tailored for industrial environments with fluctuating, seasonal demand.

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