Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID)

An Analysis of Goods Delivery Operations Management at Shopee Express in Palopo City

2026-09-02T16:31:43+00:00

The increasing volume of e-commerce transactions has created greater demand for fast, accurate, and reliable goods delivery, while delivery delays, shipment accumulation, system disruptions, and distribution barriers remain operational challenges. This study aims to analyze the operational management of goods delivery at Shopee Express in Palopo City and identify the factors supporting and hindering its implementation. This research employed a qualitative method with a descriptive case study approach. Data were collected through observation, semi-structured interviews, and documentation involving 25 informants selected using purposive sampling, consisting of supervisors or coordinators, couriers, sorting and warehouse staff, operational administrative staff, and customers. Data were analyzed using the interactive model of Miles, Huberman, and Saldaña, while data credibility was ensured through source, technique, and time triangulation. The findings indicate that operational management has been implemented relatively well through the functions of planning, organizing, actuating, and controlling. Planning is based on package volume, distribution areas, human resource requirements, and operational targets, while clear task division supports coordination among operational personnel. Delivery implementation is supported by digital systems and barcode scanning, and controlling is conducted through tracking systems, performance evaluation, and complaint handling. The main supporting factors are human resources, technology, fleet availability, tracking systems, and work coordination. Meanwhile, weather conditions, infrastructure limitations, system disruptions, high delivery volumes, and customer-related factors remain the main obstacles. The study concludes that effective delivery management requires the integration of human resources, technology, physical resources, and coordination, with continuous improvements in operational monitoring, resource capacity, and distribution optimization.

Sentiment Analysis of Google Maps Reviews of Hotel Grand Mansion Blitar Using Convolutional Neural Network Algorithm with Hyperparameter Optimization

2026-08-08T16:59:43+00:00

The development of digital platforms such as Google Maps has made customer reviews an important source of information for the hotel industry in evaluating service quality. However, the high volume of unstructured reviews and the presence of imbalanced sentiment classes make it difficult for management to identify problems and evaluate customer satisfaction quickly, accurately, and objectively. Therefore, this study aims to apply the Convolutional Neural Network (CNN-1D) algorithm to classify sentiments in Google Maps reviews of Hotel Grand Mansion Blitar, compare model performance before and after hyperparameter optimization using Grid Search based on Confusion Matrix evaluation (accuracy, precision, recall, F1-score), and map service priorities using Importance-Performance Analysis (IPA). The data were collected through web scraping using Webscraper.io, resulting in 1,580 raw reviews. After validation, text preprocessing, automatic sentiment labeling, tokenization, padding, and additional selection, 723 reviews were used in the modelling stage. Text representation was performed using Word2Vec. The results show that based on the Confusion Matrix evaluation, the baseline model achieved an accuracy of 66.21%, precision of 76.77%, recall of 66.21%, and F1-score of 70.45%. After optimization, the best model was obtained with 32 filters, kernel size of 3, dropout rate of 0.3, and learning rate of 0.001, achieving an increased accuracy of 81.38%, precision of 84.80%, recall of 81.38%, and F1-score of 82.92%. The IPA results indicate that the room condition (interior) attribute falls into Quadrant I, making it the main priority for improvement. Therefore, hyperparameter optimization significantly improved the sentiment classification performance, while IPA provided more focused service evaluation recommendations for hotel management.

The Effect of Employee Engagement and Work-Life Balance on Performance with The Mediation of Job Satisfaction of Employee in the Packing Division PT. Kao Indonesia Cikarang Pusat

2026-08-24T09:47:20+00:00

The phenomenon of consistently high performance among employees in the Packing Division of PT. Kao Indonesia Cikarang Pusat, despite the use of a traditional performance appraisal method, forms the background of this study. The research aims to analyze the effect of Employee Engagement and Work-Life Balance on Performance, with Job Satisfaction as a mediating variable. This study adopts a quantitative approach using a survey method, distributing questionnaires to 102 employees of the Packing Division at PT. Kao Indonesia Cikarang Pusat. Data were analyzed using Structural Equation Modeling (SEM) with LISREL 8.80 software. The results reveal that Employee Engagement and Work-Life Balance have a positive and significant effect on Performance; Employee Engagement has a positive and significant effect on Job Satisfaction; Work-Life Balance has no significant effect on Job Satisfaction; Job Satisfaction has a positive and significant effect on Performance; Job Satisfaction mediates the effect of Employee Engagement on Performance but does not mediate the effect of Work-Life Balance on Performance. These findings imply the importance of enhancing employee engagement and managing work-life balance appropriately to achieve optimal performance. The originality of this research lies in its focus on a division with fluctuating workloads and an attendance-based performance assessment based on targets and monthly production capacity, which is then converted to an annual basis, offering practical insights for similar organizations in managing human resources under such conditions.

Generative Artificial Intelligence for Supporting Scientific Writing Among Electrical Engineering Students: A Narrative Review

2026-09-12T15:21:17+00:00

The rapid development of Generative Artificial Intelligence (GenAI) has changed academic learning and writing practices in higher education. For electrical engineering students, scientific writing is a supporting competence because technical knowledge must be communicated through laboratory reports, project documentation, proposals, final projects, and scientific articles. This narrative review examines how GenAI can support scientific writing, identifies benefits relevant to electrical engineering students, analyzes risks, and formulates principles for responsible use. The review incorporated an updated search and verification of recent empirical studies, reviews, and policy guidance, with emphasis on publications from 2023–2026. The evidence indicates that GenAI can assist ideation, brainstorming, outlining, language revision, feedback, and exploratory learning. Engineering studies also report perceived gains in learning efficiency, initiative, creativity, and writing support. However, substantial concerns remain regarding inaccurate outputs, fabricated or erroneous references, overreliance, reduced metacognitive engagement, and academic-integrity risks. In electrical engineering, these risks are amplified because errors in equations, parameters, component specifications, standards, or simulation interpretations can propagate into technical conclusions. This review proposes a Human-Led, AI-Assisted, Evidence-Verified (H-A-E) conceptual model in which students retain responsibility for problem formulation, evidence selection, critical evaluation, technical verification, scientific argumentation, authorship, and final decisions. GenAI is positioned as a cognitive and linguistic assistant, not as a source of scientific evidence or a substitute for engineering judgment.

Design and Development of the Volunterr Corps at Samarinda State Polytechnic

2026-08-12T13:45:54+00:00

The Volunteer Corps of Samarinda State Polytechnic (KSR Polnes) faces challenges in managing personnel data, correspondence, inventory, and organizational information because these administrative activities were previously handled using conventional methods, resulting in limited accessibility and inefficient information management. This study aimed to design and develop a web based information system to support administrative management and facilitate the dissemination of organizational information within KSR Polnes. The research employed the Prototype method, with requirements identified through observation, interviews, and questionnaires. The system was developed using Laravel and MySQL, while system functionality was evaluated using Black Box Testing and user perceptions were assessed through a Likert scale questionnaire. The Black Box Testing results showed that all tested system functions operated according to the specified requirements without errors. The questionnaire results indicated positive user assessments, with an Information Quality score of 89.3%, a User Interface score of 88.4%, and a System Functionality score of 91.1%. These findings indicate that the developed website provides accessible organizational information and supports administrative activities within KSR Polnes. Therefore, the proposed system can serve as a digital platform for improving information management and supporting the delivery of organizational information to the Polytechnic community.

LLM Token Consumption Optimization Using BERT Pre-filtering and Retrieval-Augmented Generation (RAG)

2026-07-18T15:18:28+00:00

The adoption of Large Language Models (LLM) for software issue resolution causes token consumption inefficiency due to noisy and redundant context. This research proposes a hybrid system placing a BERT classification model as a context relevance pre-filter upstream of the Retrieval-Augmented Generation (RAG) pipeline, with hyperparameters optimized using Bayesian Optimization. A Design Science Research approach is applied through an ablation study of five scenarios (S0-S4) on GitHub Issues and SWE-bench datasets. The classification model achieves an F1-macro of 0.887, and BERT-based filtering (S2) reduces token consumption by 8.35% versus baseline, statistically significant (Wilcoxon, p<0.05). Bayesian Optimization yields a validation F1-macro of 0.889, higher than default hyperparameters. The main finding: token efficiency comes from the BERT pre-filter component, not from RAG which adds context.

Implementation of the DMAIC (Define, Measure, Analyze, Improve, Control), FTA (Fault Tree Analysis), and Poka-Yoke (Error-Proofing) Methods to Reduce Codification Defects in Gift Box Packaging at PT ASD

2026-07-25T17:06:25+00:00

The Gift Box packaging line at PT ASD experienced recurring codification defects, particularly Missing Code defects, which affected product traceability and process reliability. Historical quality control data showed that Missing Code was the dominant defect, accounting for 426,096 units or 92.7% of the recorded codification defects. This study aims to reduce codification defects on the Gift Box packaging line through the integrated implementation of DMAIC (Define, Measure, Analyze, Improve, Control), Fault Tree Analysis (FTA), and Poka-Yoke. The research followed the DMAIC framework, with the Measure phase evaluating process capability using DPMO and Sigma Level, the Analyze phase identifying root causes through Fishbone Diagram and FTA, and the Improve phase implementing Poka-Yoke-based corrective actions. The identified root causes included product accumulation at the guide rail, improper WIP input, uniform conveyor speed settings, and photoelectric sensor misalignment. The improvement actions consisted of installing a Guide Roll, applying a transparent acrylic cover, adjusting the conveyor speed ratio from 1:1:1 to 1:1.5:2, relocating the sensor, and implementing a timer-based automatic rejector. The results showed that the initial process capability was 77,296.44 DPMO with a Sigma Level of 2.93. Following the implementation of the improvements, the DPMO decreased to 257.20 and the Sigma Level increased to 4.98 based on post-improvement data collected from March to May 2026. The findings indicate that the integration of DMAIC, FTA, and Poka-Yoke improved the stability of the Gift Box coding process by addressing root causes and reducing reliance on manual error detection.

Implementation of a Web-Based Application System for Recommending Optimal Car Engine Oil Selection Using the AHP and TOPSIS Methods (Case Study: Astrido Daihatsu Serpong)

2026-07-28T16:33:46+00:00

Selecting the appropriate engine oil is an important factor in maintaining vehicle engine performance, efficiency, and durability. However, the wide variety of engine oil products with different characteristics often causes the selection process to be carried out manually, resulting in less objective decision-making. This study aims to design and implement a web-based engine oil recommendation system using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods at Astrido Daihatsu Serpong. The AHP method is applied to determine the priority weights of each decision criterion, while the TOPSIS method is used to rank engine oil alternatives based on their closeness to the positive ideal solution and distance from the negative ideal solution. The system was developed using the Laravel framework and MySQL database based on the system development method adopted in this research. The implementation results indicate that the proposed system is capable of providing objective, accurate, and efficient engine oil recommendations according to predefined criteria. Furthermore, the system improves the efficiency of the recommendation process, assists technicians in providing appropriate recommendations to customers, and supports more consistent decision-making at Astrido Daihatsu Serpong.

Product Innovation Management and Digital Technology Adoption in Indonesian Digital Startups: Model Development and Measurement Design

2026-08-24T09:47:51+00:00

Indonesia’s digital startup ecosystem requires firms to innovate products continuously while integrating digital technology into core business processes. This study develops a measurement model for examining Product Innovation Management, Digital Technology Adoption, and Digital Startup Performance in the Indonesian context. The study follows a quantitative research-development sequence combining literature synthesis, conceptual-model refinement, instrument operationalization, and internal focus-group review. The resulting instrument consists of 26 Likert-scale statements organized into three constructs: Product Innovation Management (9 items), Digital Technology Adoption (8 items), and Digital Startup Performance (9 items). The review process strengthened terminology consistency, item clarity, respondent-screening criteria, coding rules, and the alignment between constructs and the planned regression model. A complete empirical-analysis protocol was also specified, covering item validity, construct reliability, residual normality, multicollinearity, heteroscedasticity, and multiple linear regression. The study contributes a context-specific and empirically testable measurement architecture for research on innovation management and digital entrepreneurship in Indonesia. The framework is designed for field application among active startup founders, owners, managers, or other decision makers who understand product innovation and business performance.

Slope Stability Analysis Against Landslides Using the Bishop Method (Case Study: Katapop II, Salawati District, Sorong Regency)

2026-08-19T15:45:20+00:00

Sorong Regency has hilly and mountainous topography, making it prone to landslides, especially on steep slopes during periods of high rainfall. Landslides in this area can damage infrastructure and threaten human safety. These conditions highlight the importance of slope stability analysis to identify potential landslides and mitigation efforts to minimize disaster impacts. This study aims to analyze slope stability under saturated and unsaturated conditions and to determine the soil characteristics in Katapop II, Sorong Regency. The method used was the Bishop method utilizing GeoStudio software and manual calculations to validate the Safety Factor (SF) values. Based on the calculation results, the slopes in Katapop II were categorized as unstable under saturated conditions, with safety factors (SF) of 0.798 from the software analysis and 0.53 from manual calculations. Under unsaturated conditions, the safety factors (SF) were 2.69 from the software analysis and 2.70 from manual calculations, indicating stable conditions. The soil characteristics were identified as clay according to the AASHTO classification system, inorganic clay according to the USCS classification system, and silt loam according to the USDA classification system.

Reconstruction of Presidential Candidacy Following the Abolition of the Presidential Threshold (PT) under Law No. 7 of 2017: A Normative Analysis Based on Constitutional Democracy

2026-09-28T10:19:20+00:00

The abolition of the presidential threshold through Constitutional Court Decision No. 62/PUU-XXII/2024 has fundamentally altered the legal framework governing presidential and vice-presidential nominations in Indonesia. This study examines the normative problems embedded in the previous nomination system and formulates a legal reconstruction that is more consistent with the principles of constitutional democracy. The research employs normative legal research using statutory, conceptual, historical, and comparative approaches. Primary legal materials include the 1945 Constitution, Law No. 7 of 2017 on General Elections, and relevant Constitutional Court decisions, while secondary materials consist of legal scholarship and academic literature on constitutional democracy, political rights, and presidential systems. The findings show that the former presidential threshold created several normative tensions, particularly regarding political equality, popular sovereignty, electoral openness, the use of previous legislative election results, and the logic of simultaneous elections. Although the abolition of the threshold broadens access to presidential nomination, it also creates a need for a clearer and more coherent post-threshold regulatory framework. This study proposes an open nomination model that provides equal nomination opportunities for political parties participating in elections, supported by objective administrative requirements, transparent verification procedures, legal certainty, and non-restrictive mechanisms for maintaining presidential governability. The study concludes that post-threshold reform should not merely remove the previous numerical requirement but should reconstruct the broader architecture of presidential nomination in a manner that balances democratic openness, political equality, proportionality, and institutional effectiveness.