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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 a Web-Based Financial Management System in the AER Konveksi Embroidery Business Mutiara Nur Aini; 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.v5i03.716

Abstract

Manual financial management in MSMEs has the potential to cause recording errors, delays in report preparation, and difficulties in obtaining accurate financial information. These problems are experienced by AER Konveksi, which operates in the embroidery and garment industry. This study aims to implement a web-based financial management system to support effective, efficient, and integrated financial data management. The system development method used is Waterfall, which includes needs analysis, design, implementation, testing, and maintenance. The system was developed using PHP, HTML, CSS, JavaScript, and MySQL as the database, while testing was conducted using the Black Box Testing method. The results of the study indicate that the system is able to manage customer data, orders, payments, income, expenses, cash accounts, and generate financial reports in an integrated manner. In addition, the system provides a feature for printing Work Orders (SPK) and transaction receipts to support operational processes. The test results show that all system functions run according to user needs, so the system can improve the effectiveness of financial management and assist in the preparation of financial reports at AER Konveksi.
Web-Based Healthcare Personnel Scheduling Information System at Hidayah General Hospital, Boyolali Ubaid Syaiful Anwar
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.v5i03.789

Abstract

The manual scheduling of healthcare workers at Hidayah Boyolali General Hospital (RSU Hidayah Boyolali) presents challenges in accessing schedule information and potentially leads to shift errors. This study aims to identify and describe the scheduling system, as well as to design and build a web-based healthcare worker scheduling information system. The study employed a descriptive method with a cross-sectional approach. Subjects included the head of the medical records room, the head of the nursing room, and the head of the midwife room. The instruments consisted of observation guidelines, interviews, and documentation, while the data were analyzed descriptively. The development procedure used the Software Development Life Cycle (SDLC) stages. The results showed that the system provides features for managing staff data, monitoring and inputting schedules, daily and monthly schedules, printing reports, and submitting and approving shift changes. In conclusion, the system can support more structured healthcare worker schedule management and facilitate access to schedule information
Sentiment Analysis of Customer Reviews to Determine Favorite Perfume Scents Using the Naive Bayes Method Yoshida Sary; Eka Maulana Putra
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.v5i03.800

Abstract

This study is motivated by the large number of customer reviews regarding perfume fragrances that are still evaluated manually, making it difficult to objectively identify the most preferred fragrance. This study aims to develop a sentiment analysis system to classify customer reviews into positive, neutral, and negative sentiments using the Naïve Bayes method and to determine the favorite perfume fragrance. The study employed a quantitative approach using sentiment analysis. The population consisted of all customer reviews at the perfume store under study, while the sample comprised reviews containing information about fragrance and review content. The research instrument consisted of customer review data collected through online questionnaires and direct interactions. Data analysis involved preprocessing, TF-IDF weighting, an 80:20 training-testing split, Naïve Bayes classification, and evaluation using a confusion matrix, accuracy, precision, recall, and F1-score. The results showed that the model achieved 71.43% accuracy on 42 testing data, with 30 correctly classified instances. Of the 36 reviews, positive sentiment accounted for 58.33%. CHRISTIAN DIOR - SAUVAGE obtained the highest positive sentiment, with 7 of 10 reviews or 70.00%. The conclusion indicates that Naïve Bayes can effectively be applied to classify customer sentiment and support the identification of favorite perfume fragrances for store decision-making
SAPA LABUKTI : Information Access System for Visiting and Integration Services at Bukittinggi Prison Irfan Fauzi Hasan; Naniek Pangestuti; Denny Nazaria Rifani
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.v5i03.874

Abstract

Public access to clear correctional service information is essential because visitation and integration services involve procedures, schedules, security rules, and administrative requirements that must be understood before people arrive at a correctional institution. This community service article describes the development and implementation of SAPA LABUKTI, a digital information access system for visitation and integration services at Class IIA Bukittinggi Correctional Institution. The activity was conducted from 19 June to 9 August 2026 using a descriptive-evaluative community service approach. The stages included observation of service problems, identification of information needs, preparation and validation of content with service officers, development of a responsive website, integration of a Quick Response Code, functional testing, staff socialization, and handover of the administrator account. The resulting website provides visitation schedules and procedures, visitor rules, security provisions, conditional release and conditional leave information, frequently asked questions, contact information, and a direct link to the institution's information service. Functional testing reported that the menus, access, device compatibility, and displayed information operated as intended. Qualitatively, the program expanded self-service access to information, reduced the need to repeat general explanations, supported information transparency, and enabled officers to independently update the website after handover. The program demonstrates a practical and sustainable model for strengthening digital public information services in correctional settings.
Analysis of Changes in Customer Sentiment in the Period Before and After the Google Review-Based Digital Promotion Program as a Basis for Managerial Decision Making at Kopi Kenangan Haikal Yudistira Simarmata
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.v5i03.893

Abstract

Customer reviews on Google Reviews can be a valuable source of information for understanding consumer response trends toward Kopi Kenangan products and services. However, the large number of reviews and the unstructured text data require computational processing for systematic analysis. This study aims to determine the distribution of customer sentiment before and after the digital promotion program and apply Multinomial Naive Bayes to classify reviews. The study used sentiment analysis and text mining on 500 reviews from 15 Kopi Kenangan outlets in North Sumatra, consisting of 250 reviews before the promotion and 250 reviews after the promotion. Data were obtained from Google Reviews with ratings and review text as analysis instruments. Data underwent preprocessing, TF-IDF unigram and bigram weighting, 80:20 training and testing split, and oversampling of the training data. The results showed an accuracy of 71.00% and a macro F1-score of 61.48%. The distribution of positive sentiment increased from 48.40% to 63.20%, while negative sentiment decreased from 31.60% to 20.40%. In conclusion, there was a change in the distribution of sentiment towards a more positive direction in the period after the promotion, but this change cannot yet be stated as a direct impact of the digital promotion.
INCREASING PUBLIC KNOWLEDGE THROUGH THE GEMA CERMAT AND DAGUSIBU PROGRAMS IN THE MANAGEMENT OF ANTIHYPERTENSION DRUGS Eky Meiracella Susanty; Febrina Novannisa; Hadnad Syiah Manggabarani; Sa’idatun Nisa’; Rudy Mardianto
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.v5i03.894

Abstract

Hypertension is one of the most prevalent non-communicable diseases in Indonesia and a major risk factor for cardiovascular diseases. Limited public knowledge regarding antihypertensive medication management may reduce treatment effectiveness, highlighting the need for continuous health education. This community service program aims to improve the knowledge of participants in the Chronic Disease Management Program (Prolanis) regarding antihypertensive medication management through GEMA CERMAT (Smart Community Movement in the Use of Medicines) and DAGUSIBU (Get, Use, Store, and Dispose of Medicines Properly) education. The program was conducted in Mangunrejo Village, Kepanjen District, Malang Regency, involving 31 Prolanis participants. The intervention was delivered through health education using leaflets and evaluated using pre-test and post-test questionnaires. The results demonstrated that the educational intervention improved participants' understanding of proper antihypertensive medication management, including obtaining, using, storing, and disposing of medications according to the principles of GEMA CERMAT and DAGUSIBU. The educational activity also supported the implementation of the Prolanis program by enhancing participants' ability to manage hypertension therapy independently. Therefore, GEMA CERMAT and DAGUSIBU education can serve as an effective educational strategy to support hypertension control in the community.
Value at Risk Estimation for Life Insurance Using Monte Carlo Simulation Based on an ARIMA Model with a Generalized Error Distribution (GED) Assumption Andreas Timothy; Dwi Susanti; Kankan Parmikanti
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.v5i03.895

Abstract

Extreme increases in life insurance claims can threaten an insurer’s solvency and liquidity. This study estimates the Value at Risk (VaR) of monthly life insurance claims in Indonesia using an Autoregressive Integrated Moving Average (ARIMA) model with a Generalized Error Distribution (GED) innovation, combined with Monte Carlo simulation. Monthly aggregate claims data from the Financial Services Authority (OJK), comprising 107 log-return observations, were used. A three-stage procedure (parameter significance, residual white-noise, and minimum AIC) selected ARIMA(0,0,1) as the best mean model, with no remaining autocorrelation or conditional heteroscedasticity. Maximum Likelihood Estimation yielded a GED shape parameter of ν̂ = 0.731368, indicating heavier tails than the normal distribution. Because the relevant risk for an insurer is a surge in claims, VaR was estimated on the upper tail of the one-month-ahead return distribution through 110,000 Monte Carlo replications. At the 99% confidence level, the estimated VaR was 0.91646 in log-return terms, equivalent to a potential increase of approximately IDR 21.07 trillion above the reference month’s claim value. Kupiec’s backtest confirmed the model’s validity (LR = 2.1508, p = 0.1425). The ARIMA-GED model with Monte Carlo simulation thus provides a statistically valid basis for estimating extreme claim-surge risk in Indonesian life insurance.
Comparison of Machine Learning Algorithms for Polycystic Ovary Syndrome (PCOS) Classification Sabila Sulistyani; Sumanto; Rizal Amegia Saputra
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.v5i03.897

Abstract

Polycystic Ovary Syndrome (PCOS) is a hormonal disorder in women of reproductive age that poses challenges in diagnosis and early detection. This study aims to compare the performance of the K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Logistic Regression algorithms in classifying PCOS under consistent testing conditions. This study employs a quantitative approach and machine learning methods using secondary data from the PCOS Diagnosis dataset. The study population and sample consisted of 1,000 patient medical records, all of which were used, with 800 for training and 200 for testing. Altair AI Studio was used as the research tool, while analysis was conducted using confusion matrices, accuracy, precision, recall, and F1-score. The results show that KNN achieved an accuracy of 96.00%, precision of 90.91%, recall of 90.91%, and an F1-score of 90.91%, while SVM and Logistic Regression produced lower performance. In conclusion, KNN provided the most consistent classification performance on the research dataset and has the potential to be used as a supporting approach for PCOS classification based on clinical data.
An Expert System for Recommendation of Elementary School Readiness Levels for Kindergarten Students Under 7 Years of Age Using the Mamdani Fuzzy Method Muhammad Arfan Tarigan; Yohanni Syahra
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.v5i03.900

Abstract

The readiness of Kindergarten (TK) students under 7 years old to enter Elementary School (SD) needs to be assessed based on various developmental aspects, while the assessment process can face limitations in objectivity and standardized tools. This study aims to build an expert system for recommendations on the level of readiness to enter elementary school using the Fuzzy Mamdani method. The study uses an exploratory quantitative approach with a population of 300 kindergarten student data and 50 data as a test sample. The research instrument is a student development dataset with four indicators, namely writing, reading, communication, and independence. Data are analyzed through fuzzification, IF-THEN rule base, MIN-MAX inference, Centroid defuzzification, and confusion matrix. The results show that the Fuzzy Mamdani baseline obtains an accuracy of 82.00%, a weighted precision of 80.65%, and a weighted recall of 82.00%. The DNN model achieved 92.00% accuracy, while the Hybrid Fuzzy-DNN achieved 94.00% accuracy, 93.80% weighted precision, and 94.00% weighted recall. In conclusion, the Mamdani Fuzzy system can be used as a measurable tool in providing recommendations for student readiness to enter elementary school, while further development is needed to improve classification accuracy in adjacent categories.
OPTIMIZATION OF OVERBURDEN BLASTING GEOMETRY BASED ON THE EFFECT OF BLASTHOLE DEPTH ON POWDER FACTOR AND EXPLOSIVES COSTS TO MEET PRODUCTION TARGET Natasya Rosiana Maharani; Supardi Razak; A. Silvan Erusani
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.v5i03.903

Abstract

Blasting in overburden stripping strongly influences whether production targets are met and is also one of the largest operating cost items. This study examines how strongly blasthole depth affects powder factor (PF) and explosive cost, and then formulates an improved blast geometry so that the target of 200,000 BCM per cycle can be achieved more cost-efficiently. A quantitative approach with descriptive and comparative analysis was applied to one overburden blasting cycle at a coal mine in South Kalimantan, consisting of 334 blastholes 6.0–9.0 m deep drilled on an actual 7 m burden and 8 m spacing. Simple linear regression shows that hole depth is very strongly related to explosive charge (R² = 0.989), PF (R² = 0.957), and specific blasting cost (R² = 0.951). The actual geometry broke only 75.31% of the target at a PF of 0.341 kg/BCM. Three alternative geometries were designed using ICI Explosives criteria, all of which meet the target. The 8 m burden and 10 m spacing alternative performed best, giving a PF of 0.237 kg/BCM and a specific cost of Rp. 4,589.82/BCM, about 30% lower than the actual condition while requiring fewer holes. The findings indicate that increasing blasted volume is more effectively achieved by enlarging burden and spacing than by deepening the holes.

Page 12 of 13 | Total Record : 123

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