Franchise Potential in Food Industry Expansion Strategies in East Kalimantan

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This study investigates the franchise potential in the food industry as part of expansion strategies in East Kalimantan, with a focus on the Wong Solo Group amid Indonesia’s capital relocation. Utilizing qualitative methods, including SWOT, PESTLE, Porter’s Five Forces, and the VRIO framework, the research provides a comprehensive analysis of strategic positions and opportunities for business expansion. The study reveals significant opportunities for growth driven by demographic changes, economic development, and increased consumer spending. Key findings indicate that Wong Solo Group’s established brand and operational expertise offer a strong foundation for expansion. However, challenges such as regulatory changes and intense competition need to be addressed. The SWOT analysis highlights internal strengths such as brand reputation and product innovation, while the PESTLE analysis underscores external opportunities and threats. Porter’s Five Forces analysis identifies competitive pressures within the food industry, and the VRIO framework assesses the group’s resources and capabilities. The study concludes with strategic recommendations for Wong Solo Group to leverage its strengths, address its weaknesses, capitalize on opportunities, and mitigate threats. These recommendations aim to ensure successful franchise expansion in the dynamic market environment of East Kalimantan, providing a roadmap for sustained growth and competitive advantage.

Analysis of Inventory Management System at Pharmacy of XYZ Hospital

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This research examines inventory management at the XYZ Hospital Pharmacy Installation in Bandung, with a special focus on medicines and medical devices. The background to this research is the significant increase in health costs and the importance of effective supply chain management to reduce unnecessary costs. Based on monthly stock and daily sales data from October 2023 to February 2024, this research uses quantitative methods to calculate optimal inventory levels, including Economic Order Quantity (EOQ), safety stock, and reorder point (ROP). This research also applies ABC analysis and cycle counting to prioritize inventory control. The research results show that the proposed inventory policy, especially the continuous review strategy, has the potential for significant cost savings for the XYZ Hospital Pharmacy Installation. For pharmaceutical products, achieving a 99% service level can result in savings of IDR 302,697,429, which is 48.17% of the average inventory level. For medical devices, potential savings reach IDR 70,602,064, which is 48.77% of the average inventory level. The total potential savings for all products is IDR 373,299,493. These findings highlight that hospitals currently do not have effective controls in managing inventory of single-use medical devices. Implementing strong inventory policies and procedures is critical to improving cost efficiency and optimizing inventory levels within an organization.

Improving Performance of Customer Relationship Management to Leverage Customer Loyalty (Case Study: MILKY CRM Loyalty Program)

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Customer Relationship Management (CRM) plays a crucial role for businesses as technology advances and consumer demands continue to rise. However, CRM implementation faces challenges from both external and internal factors within an organization. Ineffective CRM implementation can lead to customer dissatisfaction, decreased loyalty, reduced profitability, and missed business opportunities. This research aims to improve the MILKY CRM loyalty program by identifying the key root causes and proposing alternative solutions, ultimately determining the best alternative to enhance the program. The methodology includes in-depth interviews and analysis using the Kepner-Tregoe framework, which involves problem analysis, decision analysis, and potential problem analysis. Supported by external and internal analyses such as Porter’s Five Forces, Customer Journey Mapping, and an Integrated CRM Scorecard, the results are then utilized for a SWOT analysis.

The problem analysis identified 21 attributes as the root causes affecting MILKY CRM loyalty program performance. These attributes include Consumer Behaviour Change, Aggressiveness of Competitors, CRM Agency Capability, Healthcare Apps Strategic Partnership, Potential New Segments generated by New Entrants, CRM Differentiation, Strong Brand Reputation, Content Management, Ability Services Program, Customer Engagement, Customer Experience Improvement, Win Back Lapsed Customers, Incomplete metrics tracking on CRM scorecard, Financial Budget Constraints, Personalization Services & Rewards, Digital Acquisition Transition, Segmentation & Tiering Review, Balancing Strategy on Customer Acquisition & Retention, IT System Capabilities, and Human Capability on CRM. In the decision analysis section, alternative solutions were generated through TOWS analysis, and the best alternative was determined using the Analytical Hierarchy Process (AHP) tool. The top chosen strategy, Strategy #2: Optimizing CRM & Organizational Strategies for Enhanced Customer Engagement & Operational Efficiency (W/O Strategies), is recommended for future improvement. Focus areas include communication, resources, technology, and KPI metrics to mitigate potential problems. Overall, this research provides valuable insights and recommendations for enhancing the performance of the MILKY CRM loyalty program, ensuring its effectiveness in meeting customer needs and driving business success.

Evaluating Organizational Culture with the OCAI: Insights from the Competing Values Framework at PT. SGM

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This study analyzes the organizational culture of PT. SGM using the Organizational Culture Assessment Instrument (OCAI) based on the Competing Values Framework (CVF). The research employs a quantitative approach, distributing OCAI questionnaires to all employees to evaluate six cultural dimensions: dominant characteristics, organizational leadership, management of employees, organizational glue, strategic emphases, and criteria of success. The findings reveal that PT. SGM’s current culture is predominantly clan-oriented, emphasizing a collaborative and supportive environment, with significant hierarchical elements reflecting structure and control. However, employees prefer a shift towards a more competitive market-oriented culture, focusing on achievement and innovation. The study recommends adopting a bottom-up approach to enhance employee participation and innovation, as well as implementing transformational leadership to balance the current culture with desired competitive and innovative traits. This approach aims to align the organization’s culture with employee preferences and market demands, fostering a dynamic and innovative work environment for long-term success.

Translation of Outdoor Signs in Nusa Dua Beach Area

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This research was conducted to have a closer look at Linguistic Landscape in one of coastal areas of Bali, Indonesia. It specifically conducted with the aim of analyzing the translation of outdoor signs, in the form of notice or information boards. This research also examines translation shifts occur within those outdoor signs.

This research is a qualitative descriptive study. The method applied for this research is observation method and include image capture and also note-taking technique. The problem formulated in this research applies Linguistic Landscape theory by Landry and Bourhis and also Translation Shift theory by Catford and  Simatupang.

The result of the research found that the form of translation of the outdoor signs in Nusa Dua beach area can be seen in the form of Notice board, cemented sign, or colored banner which has function to give information or warning to the people who visit the area. It also can be found that the shift occurs in the translation of the outdoor signs consists of structure and meaning shift.

Vendor Selection in the Cosmetic Industry using Analytics Hierarchy Process (A Case Study of Saejiva Company)

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The Indonesian fragrance industry, under the cosmetic industry, is growing, with an increasing income per capita in the perfume category, despite a dip in 2020. The global natural fragrance market, growing at an estimated 9% CAGR from 2023 to 2032, shows a strong preference for essential oil-based fragrances. Essential oils, derived from natural plant parts, are costly to produce due to large-scale machinery, skilled labor, and environmental factors. Companies often outsource these aspects to reduce costs and focus on core competencies like marketing and sales. Saejiva, a natural fragrance brand, currently faces challenges in vendor selection, experiencing issues with inefficiency, delays, and poor product quality from previous vendors, has the effect of reducing potential profits and necessitating a reevaluation of their vendor choices. This study uses the Analytical Hierarchy Process (AHP) to help Saejiva select a new vendor by prioritizing criteria that meet the company’s requirements and recommending the best vendor. Data was collected through literature reviews to identify relevant criteria, Focus Group Discussions (FGD) to find essential criteria for the company, and AHP questionnaires. Saejiva’s C-level executives acted as experts in the FGDs and AHP questionnaires to determine criteria priorities and vendor alternatives. The results showed the importance levels of criteria as follows: capability (0.3668), quality (0.1848), cost (0.1382), service (0.1068), capacity (0.0654), delivery (0.0606), warranty (0.0525), and performance history (0.0249). The importance levels of vendor alternatives were SKI (3.1994), AVF (2.7415), and SHB (2.0591). Thus, the best vendor recommended for Saejiva is SKI as the next vendor.

 

Factors Influencing Intention to Adopt Generative AI Tools in Indonesian Enterprise Users

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Indonesian enterprises are in the early stage of adopting generative AI tools. A report from Forbes shows that AI companies around the world have raised around $354 billion for Generative AI technology. One of the key drivers of those funding is to capitalize on the growing market demand. Market demand in Indonesia for Generative AI technology is explored by studying the intention to adopt such tools among enterprise users. Quantitative study reveals that perceived ease of use is a factor influencing the user’s intention to adopt Generative AI Tools in Indonesian enterprises. Recommendations for further research includes exploring more predictive factors and reaching broader target audiences for the study.

Designing Social Media Marketing Strategies Targeting Generation Z for Subsidized Housing in Indonesia (A Case Study of Pt. Graha Putra Asido)

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PT. Graha Putra Asido, a housing company in Pematangsiantar, focuses on subsidized housing but lacks a targeted marketing strategy, with only 22.22% of their buyers being Generation Z despite this group dominating Indonesia’s subsidized housing program. To avoid market loss and capitalize on Gen Z’s significant social media usage, this research is done, aiming to propose appropriate marketing strategies tailored to Generation Z preferences and behaviors to enhance PT. Graha Putra Asido’s market reach and engagement, using the P.O.S.T method and a touch on P.O.E.M Strategies. Through a mixed-method approach, including a market survey and key informant interviews, the study explores Gen Z’s social media patterns, preferences, and the company’s current marketing strategies. The research concludes with a comprehensive plan, including a Gantt chart, to achieve three main objectives by implementing targeted social media strategies, such as optimized posting schedules, platform-focused content, engaging visuals, influencer partnerships, and interesting campaigns tailored to Generation Z preferences.

The Impact of Selected Financial Ratios on The Market Performance of Listed Companies on The Acceleration Board Indonesia Stock Exchange (Period 2020-2023)

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This research aims to analyze the impacts of selected financial ratios on the market performance of listed companies in the Acceleration Board IDX (Period 2020-2023) and find if IDX need  to add the financial requirements in IDX Listing Regulations no. I-V to increase the company’s market performance in Acceleration Board IDX. The data of selected financial ratios and market performance were collected from the publication of listed companies’ financial reports and market trading data in 2020-2023 that can be accessed publicly on IDX’s official website. The population in this research is the whole Acceleration Board listed companies that were listed in IDX from 1st January 2020 – 31st December 2023. The samples used are limited to companies listed in Acceleration Board IDX period 2020-2023. Multiple regression analysis is used in this research to examine the relationship between the dependent variable and two or more independent variables. From five independent variables, partially, only the Net Profit Margin has a significant impact on the company’s market performance (stock price). From the results of the ANOVA test, there is a simultaneous significant effect of the independent variables ROA, ROE, DER, NPM, and Cash Flow from Operation on the dependent variable Market Performance (stock price).

Unlocking Hidden Demand: Utilizing Computer Vision for Street-Hailing Optimization in a Taxi Company in Jakarta

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Despite the technology disruption from online ride-hailing, street-hailing is still popular among certain people in Jakarta, the capital city of Indonesia. However, the traditional street-hailing faces several challenges for the taxi operators. Unlike ride-hailing apps where customers and drivers are matched and recorded digitally, street-hailing often lack visibility into street demand that is not always successfully picked up, which can lead to inefficiencies in fleet utilization, highlighting a significant operational gap between traditional taxi services and modern ride-hailing platforms.

Artificial Intelligence (AI) and Computer vision (CV) technologies offer a transformational approach to improve visibility and identify the unmet demand for street-hailing within urban transportation in Jakarta. Prior to its implementation, it is important to assess the potential business impact from deploying this digital innovation. This research highlights inference statistics combined with qualitative analysis to evaluate the potential demand that can be captured through CV systems. By leveraging historical taxi trajectory data and interviewing drivers and customers, we aim to uncover patterns and estimate unmet demand to ensure the system development will impact the taxi business and improve the service efficiency and customer satisfaction. This preliminary analysis serves as a foundation for strategic planning of CV system for street-hailing detection implementation.