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Ambidextrous : Journal of Innovation, Efficiency and Technology in Organization
Published by PT. Takaza Innovatix Labs
ISSN : -     EISSN : 30317002     DOI : https://doi.org/10.61536/ambidextrous
Core Subject : Economy, Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering
Focus: The primary focus of Ambidextrous is to explore and advance the intersection of innovation, efficiency, and technology within organizational contexts. The journal aims to contribute to the understanding and enhancement of organizational capabilities by examining how innovation strategies, efficiency measures, and technological advancements collectively shape the dynamics of modern organizations. Scope : Alternative Energy Information Technology Artificial Intelligent/Neural Network Innovation Management Change Management and Organizational Adaptability Logistics and Supply Chain Management Efficiency in Operations Manufacturing System Enterprise and Material Resource Planning Occupational Safety and Health Electrical Efficiency Product Design and Development Human Resource Management Quality and Reliability Management Industrial Engineering Sustainability Industrial Ergonomics and Work System Design Technology Management Industrial Management Workforce Well-being and Productivity
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 123 Documents
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Implementation of Arcface in Employee Attendance System Face Recognition Based Rifky Andika Fajrul Falah; Ronny Makhfuddin Akbar; Ahmad Syaifuddin
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.646

Abstract

The employee attendance process is still largely done manually, potentially leading to recording errors, attendance misuse, and low efficiency in attendance data management. This study aims to implement a facial recognition-based employee attendance system using the ArcFace method through the InsightFace framework combined with location validation using geofencing. The system was developed web-based using FastAPI as the backend, Bootstrap 5 and JavaScript as the frontend, MySQL as the database, and SCRFD for face detection. System testing was conducted using the Black Box Testing method to test the system's main functions, while user evaluation was conducted using a questionnaire with a Likert scale. The test results showed that all system functions run according to the established functional requirements. In addition, the results of the user evaluation showed that all respondents gave a positive assessment of the system, indicating that the system is easy to use and well-received by users. Thus, the developed system is able to support the employee attendance process more effectively through the implementation of facial recognition, location validation, and web-based attendance data management.
Comparison of IndoBERT and Naive Bayes Performance on Sentiment Analysis of Indonesian-Language E-Commerce Reviews Tony Kurniawan; Soffa Zahara; Yanuarini Nur Sukmaningtyas
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.648

Abstract

The growth of e-commerce platforms in Indonesia has generated a large number of user reviews containing important information about service quality and user satisfaction. Manual analysis of these reviews is inefficient, necessitating a Natural Language Processing (NLP)-based approach. This study aims to compare the performance of Naive Bayes and IndoBERT in sentiment classification of Indonesian-language e-commerce reviews. The dataset consists of 26,103 reviews of Tokopedia, Shopee, and Lazada apps obtained from the Google Play Store. The research stages include sentiment labeling based on ratings, preprocessing, Term Frequency–Inverse Document Frequency (TF-IDF) weighting on Naive Bayes, fine-tuning IndoBERT, and evaluation using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results show that Naive Bayes achieved an accuracy of 80.53%, while IndoBERT achieved 86.48% with a Macro F1-Score of 0.6515 and a Weighted F1-Score of 0.8723. These results show that IndoBERT is more effective in understanding the context of Indonesian text, resulting in better sentiment classification performance.
Website-Based Honey Sales and Production Management Information System Rifki Hidayat; Ronny Makhfuddin Akbar; Ahmad Syaifuddin
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.651

Abstract

The development of information technology provides opportunities for MSMEs to improve business management, including honey production and sales. MSME Madu Sukeri still records production, stock, customers, and transactions manually, which is ineffective and risky for errors. This study aims to develop a website-based honey sales and production management application that integrates production, stock, and sales management and facilitates online ordering for customers. The Waterfall method used includes needs analysis, design, implementation, and testing. The system was developed using PHP, MySQL, and Tailwind CSS with features for managing products, production, stock, customers, orders, payments, and sales reports. Customers can register, place orders, upload proof of payment, and view order status and history. Testing using Black Box Testing showed that all system functions run as required. The results show that the application is able to improve the effectiveness of production and sales management and facilitate the online ordering process.
IoT Based Flood Warning Monitoring System with Using the Telegram Application Muhammad Mirza Safaraz; Soffa Zahara; Yanuarini Nur Sukmaningtyas
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.658

Abstract

Floods often occur suddenly and cause losses due to the limited availability of real-time early warning systems that are easily accessible to the public. This study aims to develop an Internet of Things (IoT)-based flood warning monitoring system with notifications using the Telegram application. The system was developed using the Research and Development (R&D) method with a prototyping approach consisting of a sensor module, a data processing module, and a notification module. The implementation was carried out using an ESP32 microcontroller integrated with an ultrasonic sensor to detect water levels and a rain sensor, and utilized the Telegram Bot API for automatic warning delivery. Evaluation of 20 respondents in flood-prone areas was carried out based on notification response speed, reading accuracy, ease of use, and user satisfaction. The results showed that the system was able to send warning notifications with an average time of 1.82 seconds from the detected condition and a sensor reading accuracy level of 98.50%. In addition, the system obtained an ease of use score of 3.42 and a user satisfaction score of 3.35 on a 4-point Likert scale. These results indicate that the IoT-based monitoring approach with Telegram integration is effective in helping the public obtain flood warning information more quickly and easily
Implementation of Internet of Things (IoT) Technology in Monitoring Food Quality and Temperature in Nutrition Fulfillment Service Units (SPPG) Achmad Fadlil Athoriq; Soffa Zahara; Yanuarini Nur Sukmaningtyas
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.660

Abstract

Food quality and safety declines often occur undetected and pose a risk to patients due to the limited availability of real-time food temperature and quality monitoring systems that are easily accessible to staff. This study aims to develop an Internet of Things (IoT)-based food quality and temperature monitoring system with notifications using the Telegram application at the Nutrition Fulfillment Service Unit (SPPG). The system was developed using the Research and Development (R&D) method with a prototyping approach consisting of a sensor module, a data processing module, and a notification module. Implementation was carried out using an ESP32 microcontroller integrated with a DS18B20 temperature sensor to detect food temperature and an MQ-135 gas sensor to detect food quality (freshness), and utilizing the Telegram Bot API for automatic alert delivery. Evaluation of 20 nutrition officer respondents at SPPG was carried out based on notification response speed, reading accuracy, ease of use, and user satisfaction. The results showed that the system was able to send warning notifications with an average time of 1.82 seconds from the detected condition and a sensor reading accuracy rate of 98.50%. Additionally, the system received a user-friendliness score of 3.42 and a user satisfaction score of 3.35 on a 4-point Likert scale. These results demonstrate that the IoT-based monitoring approach with Telegram integration effectively helps SPPG officers obtain food quality and temperature monitoring information more quickly and easily.
Smart Drip Irrigation Monitoring and Control System for Melon Cultivation Based on ESP32 and Using Blynk Application Muhammad Dzikri Idham Surya; Soffa Zahara; Yanuarini Nur Sukmaningtyas
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 02 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i02.661

Abstract

Melon cultivation often faces obstacles in maintaining optimal soil moisture and efficient water use due to conventional irrigation methods which tend to be manual, imprecise, and time-consuming. This research aims to develop an intelligent drip irrigation monitoring and control system to automate watering and optimize soil moisture in melon cultivation. The system was developed using the Research and Development (R&D) method with an Internet of Things (IoT) approach consisting of a soil moisture sensor as input, an ESP32 microcontroller as the control center, and a water pump as an actuator. Implementation was carried out by integrating a capacitive sensor to read soil conditions in real-time, which was then processed by the ESP32 to automatically activate the water pump through a relay module based on a specified threshold, and utilizing the Blynk application as a remote monitoring and control interface. System evaluation was carried out based on sensor reading accuracy, control response speed, and water use efficiency. The results showed that the system was able to maintain soil moisture in the optimal range of 60-80% for melon plants with a sensor reading accuracy reaching 97.5%. Furthermore, the system successfully increased water efficiency by 45% compared to manual watering methods, and achieved an average response time of 2.5 seconds for sending data to the Blynk application. These results demonstrate that the ESP32- and Blynk-based IoT approach effectively helps farmers optimize melon cultivation with greater efficiency, precision, and remote monitoring.
Strategi Pemerintah Daerah dalam Mengatasi Disparitas Akses Pendidikan Melalui Sistem Penerimaan Murid Baru (SPMB) Sekolah Dasar di Kota Tanjungpinang Tahun 2025 Aditya Rizal Ramadhan
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 03 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i03.671

Abstract

Disparities in access to elementary education in Tanjungpinang City are reflected in unequal student enrollment across schools. Schools in denser areas face capacity pressure, while SD Negeri 001 Tanjungpinang Barat experiences low enrollment. Previous studies have mainly examined zoning implementation, public perceptions, or policy impacts, but few have analyzed local government strategy after the 2025 shift to the New Student Admission System through the dimensions of goals, plans, programs, decisions, and effects. This study aims to analyze the strategy of the Tanjungpinang City Government in reducing disparities in access to elementary education through SPMB. A descriptive qualitative approach was applied. Data were collected through purposive interviews with six informants and documentation of policies, school records, and population data. Data analysis involved reduction, display, and conclusion drawing. The findings show that the government has established equity goals, planned school capacity, conducted socialization and coordination, implemented SPMB, and issued technical rules. Student distribution nevertheless remains unequal because of population distribution, family mobility, and school preferences. The findings imply that SPMB evaluation should integrate demographic data, school capacity, service quality, and public trust when designing enrollment strategies.
Design and Construction of a Rice Drying System Using Microcontroller-Based Canopy Control Muhammad Dwi Indra Saputra; Soffa Zahara; Yanuarini Nur Sukmaningtyas
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 03 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i03.673

Abstract

The rice drying process is an important post-harvest stage to produce good quality grain, but conventional methods that rely on sun drying and manual canopy operation are still vulnerable to unpredictable weather changes, so the grain is at risk of being exposed to rain and decreasing its quality. This study aims to design and build a rice drying system with automatic canopy control based on a microcontroller that can work without continuous manual supervision and can be monitored remotely. The method used is Research and Development (R&D) with the stages of needs identification, design, implementation, testing, and evaluation. The system is built using an ESP32 microcontroller as the main control unit integrated with a DHT22 sensor, Light Dependent Resistor (LDR), and an FC-37 rain sensor to detect temperature, air humidity, light intensity, and rain; a servo motor as a canopy driver; a DC blower to help air circulation; an I2C LCD as a local monitoring medium; and a Telegram Bot as a real-time remote monitoring medium. The test results showed that the DHT22 sensor had a temperature reading error of 0.98%–1.38% and humidity of 1.33%–1.54% compared to the benchmark, while the LDR sensor and FC-37 rain sensor were able to control the canopy position and blower status precisely in all test scenarios. The system successfully opened and closed the canopy automatically according to environmental conditions, kept the blower active at night as long as the grain was not dry, stopped its operation when rain was detected or the grain was dry, and sent the system status to Telegram in real-time. These results indicate that the integration of environmental sensors, actuators, and IoT connectivity based on Telegram Bot can be an effective alternative solution to reduce reliance on manual supervision and the risk of grain damage due to unpredictable weather.
Regional Government Strategy to Address Disparities in Access to Education Through the Elementary School New Student Admission System (SPMB) in Tanjungpinang City in 2025 Aditya Rizal Ramadhan; Novi Winarti; Khairi Rahmi
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 03 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i03.682

Abstract

Disparities in access to elementary education in Tanjungpinang City are reflected in unequal student enrollment across schools. Schools in denser areas face capacity pressure, while SD Negeri 001 Tanjungpinang Barat experiences low enrollment. Previous studies have mainly examined zoning implementation, public perceptions, or policy impacts, but few have analyzed local government strategy after the 2025 shift to the New Student Admission System through the dimensions of goals, plans, programs, decisions, and effects. This study aims to analyze the strategy of the Tanjungpinang City Government in reducing disparities in access to elementary education through SPMB. A qualitative descriptive approach was applied. Data were collected through purposive interviews with six informants and documentation of policies, school records, and population data. Data analysis involved reduction, display, and conclusion drawing. The findings show that the government has established equity goals, planned school capacity, conducted socialization and coordination, implemented SPMB, and issued technical rules. Student distribution nevertheless remains unequal because of population distribution, family mobility, and school preferences. The findings imply that SPMB evaluation should integrate demographic data, school capacity, service quality, and public trust when designing enrollment strategies.
Implementation of the Yolov8 Model for Component Detection and Image-Based Free Nutritional Food Nutrition Ovan Pramana Putra; Ronny Makhfuddin Akbar; Ahmad Syaifuddin
Ambidextrous Journal of Innovation Efficiency and Technology in Organization Vol. 5 No. 03 (2026): Ambidextrous: Journal of Innovation, Efficiency and Technology in Organization
Publisher : Takaza Innovatix Labs Ltd.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61536/ambidextrous.v5i03.698

Abstract

The Free Nutritional Food Program (MBG) is a government effort to improve the nutritional status of students by providing balanced nutritious meals. However, the process of verifying food components and evaluating nutritional content is still done manually, which is time-consuming, subjective, and inefficient. Previous studies have applied the YOLO algorithm for food detection and calorie estimation, but generally focused on individual consumption or only produced energy estimates. This study proposes the implementation of the YOLOv8 model integrated with a nutrition database to detect food components and estimate energy, protein, fat, and carbohydrates in the image-based Free Nutritional Food package. The dataset was obtained by extracting videos from the MBG package into 400 images consisting of 19 food classes. The dataset was annotated using bounding boxes, preprocessed, augmented, and divided into training, validation, and testing data. The model was trained using Roboflow with GPU support, then the detection results were integrated with the nutrition API and implemented in a web application to automatically present nutritional information. System performance was evaluated using precision, recall, and mean Average Precision (mAP) metrics. The contribution of this research is the development of an integrated system based on YOLOv8 to support monitoring of MBG nutritional quality objectively, efficiently, accurately, adaptively, sustainably, and support artificial intelligence-based decision making.

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