PREDICTION OF SHARE OF VISUAL INVENTORY USING STORE DISPLAY, CHANNEL, AND PRODUCT VARIABLES

The purpose of this study is to predict the share of visual inventory (SOVI), which is defined as the number of stock-keeping units (SKUs) of a company’s products, calculated as a percentage of the total SKUs on the display of all products. Research studies in the past have focused mainly on the impact of inventory, which includes back end and visual inventory, on sales but less attention has been given to the impact of SOVI on sales. To address this research gap, this study attempted to create an analytics model to predict SOVI at the category of soft drinks level using four predictor variables namely point of purchase display, channel/sub-channel, package group, product category, and derived variable gross national income (GNI). The results were encouraging confirming the effectiveness of such a model. The researchers utilized a data set collected over a period of 18 months (February 2016 to July 2017) by a soft drink firm headquartered in the United States. Based on the findings, it is suggested that this prediction model can be utilized by other researchers and practitioners to predict SOVI of other soft drinks, fast-moving consumer goods (FMCG), and food and beverage companies.

Marketing Innovation Through Integrated Social Media in Small Bussiness Wood Artists by Karya Langit Mangunan Bantul

This study aims to design a way of marketing wooden handicraft products in the 'Karya Langit' Craftsmen Group. Product marketing originally relied on word of mouth (WOM). In this research, marketing is done using integrated social media. Marketing through integrated social media is assumed to expand the market and allow craftsmen to communicate with consumers without the constraints of distance or pandemic situations. The method used by the researcher is a qualitative method that is exploratory in nature. Exploration here is in the context of extracting material to create social media content, both images, and product creation processes. The steps taken are (1) Exploring material that will be used as content on social media; (2) Processing the material to be used as content on social media; (3) Creating promotional applications on social media; (4) Training on content creation and uploading to social media. The results showed that 'Karya Langit' woodcraft products have strength in the types of kitchen utensils and health accessories. As for the type of decoration they bring from outside. It still takes time to educate the craftsmen to promote on social media because the process, according to them, is not instant.

Pengembangan Buku Cerita Rakyat Berbahasa Jawa untuk Siswa SD Kelas IV Berkultur Madura

The purpose of this research and development produce book Javanese folklore for student with Madura culture, the criteria is valid and practical according to (1) specialist subject matter, (2) spesialist product, (3) specialist learning and (4) small group product trials and (5) large group trials. The model used is an adaptation of Sugiyono,s research and development. Validation subject matter done with a lecturer literatur Indonesia, validation product design done with lecturer KSDP and lecturer TEP, validation specialist learning done with a IV grade teacher SD Negeri Kotalama 1 Malang. Small group product trials done with 12 students, and large group trials done with 25 IV grade students SD Negeri Kotalama 1 Malang. Overall average validation results are 94,55 percent, small group product trials result 99,16 percent and large group trials result 98,4 percent. Based on that research and development book Javanese folklore for students with Madura culture which is considered very valid and very practical. Abstrak: Tujuan penelitian dan pengembangan ini adalah menghasilkan media buku cerita rakyat Madura berbahasa jawa yang valid dan praktis menurut (1) ahli materi, (2) ahli media, (3) ahli pembelajaran, (4) uji coba kelompok kecil, dan (5) uji coba kelompok besar. Model yang digunakan merupakan adaptasi dari model penelitian dan pengembangan sugiyono. Validasi materi dilakukan oleh 1 orang dosen sastra Indonesia, validasi media dilakukan oleh 1 orang dosen KSDP dan 1 orang dosen TEP, serta validasi pembelajaran dilakukan oleh guru kelas IV SD Negeri Kotalama 1 Malang. Uji coba kelompok kecil dilakukan pada 12 siswa dan uji coba kelompok besar dilakukan pada 25 siswa kelas IV SD Negeri Kotalama 1 Malang. Keseluruhan rata-rata hasil uji validasi dengan persentase sebesar 94,55 persen, hasil uji coba kelompok kecil dengan persentase 99,16 persen dan uji kelompok besar dengan persentase 98,4 persen. Berdasarkan hal tersebut, maka media buku cerita rakyat Madura berbahasa jawa yang dikembangkan termasuk kriteria sangat valid dan sangat praktis.

Development of Snakes and Ladders Game for Physical Fitness Employees of PT Best Profit Medan 2020

This research was conducted at PT Best Profit Medan. The research treatment was carried out by adjusting the schedule during work holidays. The time of this research was carried out from October 2020 to November 2020. Subjects or users targeted in research on the development of the snake and ladder game on physical fitness for employees of PT Best Profit Medan. The issues in the small group in this study were 20 employees of PT Best Profit Medan, and the subjects in the large group in this study were 40 employees of PT Best Profit Medan. The research subjects were taken based on the purposive sampling technique with the following criteria: 1) for women in healthy body condition and not in a state of pregnancy, 2) for men whose body condition was healthy and did not suffer from internal diseases. This research method is a development method. The study results are small group product trials. From the value obtained, it is known that the empirical score obtained is 78.87% (Appropriate to Use), so it can be stated that the snake and ladder game product is effective. Large group trial, the results above are the results of the questionnaire distributed to the experts attached in the attachment and then calculated. The acquisition of the expert revision in the small group trial is 98.44% (Very Appropriate to Use), but in extensive group trial studies, it has been no revisions from experts.

Quality Prediction and Control of Assembly and Welding Process for Ship Group Product Based on Digital Twin

In view of the problems of lagging and poor predictability for ship assembly and welding quality control, the digital twin technology is applied to realize the quality prediction and control of ship group product. Based on the analysis of internal and external quality factors, a digital twin-based quality prediction and control process was proposed. Furthermore, the digital twin model of quality prediction and control was established, including physical assembly and welding entity, virtual assembly and welding model, the quality prediction and control system, and twin data. Next, the real-time data collection based on the Internet of Things and the twin data organization based on XML were used to create a virtual-real mapping mechanism. Then, the machine learning technology is applied to predict the process quality of ship group products. Finally, a small group is taken as an example to verify the proposed method. The results show that the established prediction model can accurately evaluate the welding angular deformation of group products and also provide a new idea for the quality control of shipbuilding.

ANALISIS TINGKAT KECACATAN DENGAN METODE SIX SIGMA PADA LINE TGSW

This study aims to defect analysis on the TGSW line. Research data the monthly report period Mei 2018 to April 2018. By using the six sigma method for the T4N-Case Group type in the DMAIC concept and what factors cause defect T4N-Case Group product type. The resulting number of production from Mei 2018 to April 2019 amounted to 838.519 pcs with the number of defect products that occurred in production amounted to 2.106 pcs. Based on the calculation, the TGSW line is at a sigma level of 4,32 with the possibility of damage to the level of 3.401 for one million productions (DPMO). Abstrak Pada penelitian ini bertujuan untuk analisis defect pada line TGSW. Data yang digunakan dalam penelitian ini periode Mei 2018 sampai dengan April 2019. Dengan menggunakan metode six sigma untuk type T4N-Case Group dalam konsep DMAIC dan faktor-faktor apa saja yang menyebabkan terjadinya produk cacat pada type T4N-Case Group. Hasil penelitian jumlah produksi dari bulan Mei 2018 sampai bulan April 2019 adalah sebesar 838.519 pcs dengan jumlah produk cacat yang terjadi dalam produksi sebesar 2.106 pcs. Berdasarkan perhitungan, line TGSW berada pada tingkat sigma 4,32 dengan kemungkinan kerusakan sebasar 3.401 untuk sejuta produksi (DPMO).

Organizational Parasites

The efficient work of the employees is important for the adaptation of the business to the rapidly changing environmental conditions. Businesses should identify the factors that affect employee productivity and emerging threats because the efficient level of performance and the measurability of this output lead to rational use of the resources. Employees who do not fulfill their duties and responsibilities in the organization and take a share from the group product may lead to deviations in reaching the targets set by the organization. Justice in the organization, trust, the deterioration in the values may adversely affect the process. The existence of such employees is the indicator of parasitic relations in organizations. In literature, the number of applied studies is limited. The strength of the study is to provide a detailed evaluation and measurement tool in the subject of parasitism in organizations. The scale of parasitism was developed with self-directed and community-directed dimensions consisting of 20 statements and was validated by EFA, CFA, and reliability analysis.

Uber: Applying Machine Learning to Improve the Customer Pickup Experience

Uber had pioneered the growth and delivery of modern ridesharing services by leveraging the explosive growth of technology, GPS navigation, and smartphones. Ridesharing services had expanded across the world, growing rapidly in the United States, China, India, Europe, and Southeast Asia. Even as these services expanded and gained popularity, however, the pickup experience for drivers and riders did not always meet the expectations of either party. Pickups were complicated by traffic congestion, faulty GPS signals, and crowded pickup venues. Flawed pickups resulted in rider dissatisfaction and in lost revenues for drivers. Uber had identified the pickup experience as a top strategic priority, and a team at Uber, led by group product manager Birju Shah, was tasked with designing an automated solution to improve the pickup experience. This involved three steps. First, the team needed to analyze the pickup experience for various rider personas to identify problems at different stages in the pickup process. Next, it needed to create a model for predicting the best rider location for a pickup. The team also needed to develop a quantitative metric that would determine the quality of the pickup experience. These models and metrics would be used as inputs for a machine learning.