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All Journal Jurnal Teknologi Industri Pertanian Jurnal Pendidikan Kimia Undiksha Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Penelitian Pendidikan IPA (JPPIPA) Biosfer: Jurnal Pendidikan Biologi IJCER (International Journal of Chemistry Education Research) Pendas : Jurnah Ilmiah Pendidikan Dasar JSiI (Jurnal Sistem Informasi) Jurnal Pelita PAUD Jurnal Riset Pendidikan Kimia (JRPK) Mandalika Mathematics and Educations Journal Journal of Educational Chemistry (JEC) Quantitative Economics and Management Studies Griya Journal of Mathematics Education and Application ARRUS Journal of Mathematics and Applied Science Parameter: Journal of Statistics Jurnal Ipteks Terapan : research of applied science and education Cakrawala: Jurnal Pendidikan VARIANSI: Journal of Statistics and Its Application on Teaching and Research KHIDMAH: Jurnal Pengabdian kepada Masyarakat ARRUS Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan Anak Usia Dini Journal of Physics Education and Science Indonesian Science Education Journal (ISEJ) Indonesian Journal of Chemical Science TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang Jurnal Pelita PAUD Jurnal Inovasi Pendidikan Kimia
Sudarmin
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Analisis Sentimen Ulasan Game Simulator Indonesia di Google Play Store Menggunakan Algoritma Naive Bayes Meliyana R, sitti Masyitah; Sudarmin; Sabrina Effendy, Yuni
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 2 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm336

Abstract

Sentiment analysis is the process of text data to understand the opinion contained in a sentence. The commonly used algorithm in this analysis is the Naïve Bayes Classifier. Naive Bayes Classifier (NBC) is a classification that uses statistical and probabilistic methods to group texts into several categories of sentiments such as positive and negative. The Indonesian simulator game analyzed is Angkot d Game. This algorithm is used to understand users' perceptions of the game and to identify the factors that affect user sentiment. The results show that the Naive Bayes Classifier has a high level of accuracy in classifying the sentiments of simulator game reviews. The findings of this analysis are also expected to provide insights to game developers about user preferences and complaints, allowing them to adjust features or aspects of the game to better meet user needs. This enables game developers to make significant changes to the games they develop, potentially increasing revenue in the Indonesian gaming industry and focusing more on games created by local developers. Keywords: Simulator Game, Sentiment analysis, Naive Bayes Classifier.
Penerapan Metode Support Vector Regression (SVR) dalam Memprediksi Indeks Standar Pencemar Udara (ISPU) di Kota Makassar Sudarmin; Ruliana; Sasa Arisa, Sasa Arisa
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 2 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm400

Abstract

Air quality is a comprehensive indicator that reflects air pollution. The air quality index is defined as a description or value of the transformation of individual parameters of interrelated air pollution, such as PM10, SO2, CO, O3, NO2 into one value or a set of values ​​so that it is easy to understand for the general public. Therefore, predictions of the Air Pollutant Standard Index in the future are needed for future policy decision making. SVR is a development of Support Vector Machine (SVM) for regression cases. The aim of this study is to predict the Air Pollutant Standard Index (ISPU) in the future using the SVR method. In the SVR method, the best kernel is used as an aid in solving non-linear problems, the Min-Max Normalization method for data normalization, division of training and testing data, selection of the best model with Grid Search Optimization. The best prediction results were obtained using a radial kernel with values with parameters ​​ε = 0.1, C = 10, and γ = 1 with the smallest error of 0.0086, with an RMSE of 0.0894. The RMSE value indicates that the model's ability to follow data patterns well. From the model on the radial kernel, the predicted results of the Air Pollution Standard Index from January 1, 2025 to July 31, 2025 were obtained which were not constant or fluctuating with an interval range of 41,14 – 58,69 and based on the Air Pollution Standard Index category, it was in the fairly good category index.
TECHNO-ECONOMIC ANALYSIS OF CHILI SAUCE PRODUCTION USING FERMENTED CASSAVA FLOUR Rahim, Abdul; Adi, Qadaruddin Fajri; Adelina, Fitrah; Sudarmin
Jurnal Teknologi Industri Pertanian Vol. 35 No. 3 (2025): Jurnal Teknologi Industri Pertanian
Publisher : Department of Agroindustrial Technology, Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24961/j.tek.ind.pert.2025.35.3.244

Abstract

This study performs a techno-economic analysis to assess the feasibility of developing chili sauce products incorporating fermented cassava flour as a local food ingredient. The evaluation covers both technical/technological and economic aspects. Technologically, the product exhibits favorable characteristics with a mean moisture content of 72% and pH of 4.01, supported by positive organoleptic test results. Economically, financial analysis indicates strong viability, with a Net Present Value (NPV) of IDR 40,138,730 an Internal Rate of Return (IRR) of 34.53%, a Benefit-Cost (B/C) Ratio of 2.25, and a Payback Period (PP) of 2 years and 1 months. The integrated findings from both technical and economic evaluations confirm that chili sauce formulated with fermented cassava flour is technically sound and economically feasible for commercial development. This product has significant potential to enhance added value, create new business opportunities, and support sustainable local food security. keywords: chili sauce, techno-economic, cassava
The Application of Ethno-ESD as a Strategy to Strengthen Sustainable Environmental Attitudes in Chemistry Education Students Ariyatun; Sudarmin; Sri Wardani; , Woro Sumarni; Maria Paristiowati
Journal of Educational Chemistry (JEC) Vol. 7 No. 2 (2025)
Publisher : Department of Chemistry Education, Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze the effectiveness of the Engineering Design Project learning model based on Ethno-ESD in actualizing sustainable environmental literacy in Chemistry Education students. The method used was a quasi-experiment with the design of the One-Shot Case Study involving 46 fifth-semester students. The environmental literacy measurement instrument which includes the aspects of Sustainability Environmental, Sustainability Social, and Sustainability Economic was validated using Aiken's V analysis. After Ethno-ESD learning was applied, the test result data was analyzed through normality, homogeneity, and one-way ANOVA tests to determine the effectiveness of the treatment. The results show that all data are distributed normally and homogeneously, thus qualifying parametric analysis. The ANOVA test produced a value of F = 20.365 with a significance of 0.000, which indicates that the Ethno-ESD learning model has a significant effect on improving students' sustainable environmental literacy. This finding confirms that the integration of local wisdom with the principles of Education for Sustainable Development is able to improve students' knowledge, attitudes, and sustainable behaviors in the context of environmental chemistry learning. The Ethno-ESD model is recommended as an innovative approach to strengthen sustainable environmental literacy in higher education.
Content Validity Analysis of AKM Reading Literacy Test Instruments on Acid–Base Theory and Equilibrium Using the Aiken’s V Method Dian Pratiwi; Sudarmin; Sri Yamtinah
Jurnal Inovasi Pendidikan Kimia Vol. 19 No. 2 (2025): Jurnal Inovasi Pendidikan Kimia
Publisher : Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jipk.v19i2.6046

Abstract

The quality of educational assessment plays a crucial role in measuring students’ competencies in the 21st century, particularly reading literacy as assessed through the Minimum Competency Assessment (AKM). This study aimed to analyze the content validity of an AKM reading literacy test instrument on acid–base theory and equilibrium using Aiken’s V method. The instrument was developed in accordance with the AKM framework, covering various item formats and cognitive levels, and consisted of 30 test items supported by six contextual reading passages. Content validity was evaluated through expert judgment involving nine validators, comprising five university lecturers and four senior high school chemistry teachers. The validators assessed each item based on six criteria: relevance to content, clarity of item formulation, functionality of answer options, alignment with AKM reading literacy components, appropriateness of completion time, and language accuracy. Quantitative data were analyzed using Aiken’s V formula, while qualitative feedback was used to refine the test items. The results showed that all 30 items obtained Aiken’s V values equal to or exceeding the critical value of 0.71, indicating acceptable content validity. One item demonstrated high validity, while the remaining items exhibited moderate validity. Expert feedback further contributed to improving clarity, contextual accuracy, and alignment with acid–base equilibrium concepts. Overall, the findings confirm that the developed instrument is content-valid and suitable for measuring students’ reading literacy in chemistry. Future research should focus on empirical validation to assess reliability and construct validity.
APPLICATION OF THE COPULA FRANK FOR ESTIMATING VALUE AT RISK (VAR) IN TELECOMMUNICATION SUB SECTOR STOCKS Mutiara; Sudarmin; Hafid, Hardianti
Parameter: Journal of Statistics Vol. 5 No. 2 (2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2025.v5.i2.17823

Abstract

Investment is investing capital with the aim of getting money or additional profits. When investing, you need to pay attention to risks that can cause losses for investors. One method that is widely used to measure investment risk is Value at Risk (VaR). VaR often has limitations, especially in capturing non-linear dependencies between variables, so a copula function is needed that can handle moderate to strong dependencies. One of the copulas used is the Archimedian copula with Frank subcopula. This article aims to estimate investment risk using the Value at Risk (VaR) method based on the Frank copula approach and to analyze the dependency structure between stock returns. The main steps in estimating VaR using the Frank copula are calculating the return of each stock, estimating the parameters of the Frank copula, carrying out data simulations using Frank copula parameters, calculating the VaR value using Frank copula. The data used in this research comes from shares of PT. Telkom Indonesia Tbk and shares PT. Indosat Ooredoo Hutchison Tbk. These two stocks have a positive correlation of 0.136. However, such a low correlation may still indicate for non-linear dependencies or tail dependencies that cannot be captured by linear correlations, so additional analysis, namely Frank copula, is required. The estimated Frank copula parameter value is 0.825. From the VaR estimation results, the risk obtained at a 90% confidence level is -0.0222, at a 95% confidence level it is -0.0281 and at a 99% confidence level it is -0.0383.
DEVELOPMENT OF A WEB-BASED ELECTRONIC CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM FOR IMPROVING CUSTOMER SERVICE IN RETAIL BUSINESSES Puspita Rini; Masitah Handayani; Sudarmin
Jurnal Sistem Informasi Vol. 13 No. 1 (2026)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/1zfhhv60

Abstract

The development of information technology encourages businesses to adopt digital systems to improve customer service and operational efficiency. Small retail businesses often face challenges in managing customer data and transactions due to manual processes, which can lead to inefficiencies and data inconsistencies. This study aims to design and implement a web-based Electronic Customer Relationship Management (E-CRM) system to support customer data management and enhance service quality. The research method used is the Software Development Life Cycle (SDLC) with the Waterfall model, which includes requirement analysis, system design, implementation, testing, and evaluation. Data were collected through observation, interviews, and documentation. The system was tested using Black Box Testing to ensure that all functionalities operate as expected. The results show that the developed system is able to integrate customer data, transaction records, order monitoring, and customer feedback into a unified platform, thereby improving service efficiency and reducing data recording errors. The implementation of the system also enables faster transaction processing and more structured customer data management. This study contributes to the field of information systems by providing an integrated E-CRM model tailored for small retail businesses, emphasizing the use of customer interaction features and data-driven service strategies. The findings also imply that the adoption of E-CRM can enhance service effectiveness and support better decision-making in small-scale business environments.   Keywords: E-CRM; Information System; Web-Based System; Customer Service.
Comparison of Geographically Weighted Regression (GWR) and Mixed Geographically Weighted Regression (MGWR) Models (Case Study: Crime in South Sulawesi) Ridwan, Indi Nur; Sudarmin; Mar'ah, Zakiyah
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 8 No. 1 (2026)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm503

Abstract

The Geographically Weighted Regression (GWR) model operates by taking into account how the relationships between different factors change across geographic space. Meanwhile, the Mixed Geographically Weighted Regression (MGWR) model permits certain variables to exhibit spatially varying (local) effects, while other variables are assumed to have constant effects across all locations. Both models are relevant to be applied in crime studies influenced by variations in regional conditions. The objective of this study is to evaluate the GWR and MGWR approaches in selecting the best model to explain factors associated with crime cases in South Sulawesi. The data used include the number of crime cases in South Sulawesi in 2024 along with factors presumed to influence them. The investigation's outcomes suggest the GWR model demonstrates higher appropriateness compared to the MGWR model, evidenced by its reduced Akaike Information Criterion (AIC) score and a 98.44% coefficient of determination . Based on the best-fitting model, population density and the number of poor residents were identified as the main factors influencing criminality in South Sulawesi in 2024.
Development of AR Comics for Differentiated Chemistry Learning: Catalyzing Students' Critical Thinking Prasetiyani, Nabila; Priatmoko, Sigit; Sudarmin; Cahyono, Edy
IJCER (International Journal of Chemistry Education Research) VOLUME 10, ISSUE 1, APRIL 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ijcer.vol10.iss1.art1

Abstract

To bridge the gap in visualization and interactivity found in traditional chemistry tools, this study developed an AR-powered comic using differentiated instruction to help students navigate the spatial complexities of molecular geometry while sharpening their critical thinking.The product was developed using the 4D model (Define, Design, Develop, Disseminate) and integrated visual storytelling, interactive 3D molecular visualisations, and an instructional song to support multimodal learning. Five experts validated the media and content, indicating high validity (media = 89.5%; content = 91%). Effectiveness was examined using a one-group pretest-posttest design with 30 Grade 11 students. Shapiro–Wilk results confirmed normal distributions for pretest and posttest scores (p = 0.278; p = 0.324). A paired-samples t-test showed a significant improvement in students’ critical thinking after the intervention (t(29) = -11.524, p < 0.001). Learning gains were moderate (n-gain = 0.40), with the strongest improvements in supposition and integration but inference and decision-making require further reinforcement through targeted scaffolding, such as the inclusion of guided inquiry prompts or interactive decision-making tasks within the AR interface that direct students to evaluate electron pair repulsions and conclude molecular properties based on their 3D observations. Overall, the AR differentiated comic is a promising medium for strengthening critical thinking in chemistry differentiated learning.
Co-Authors , Woro Sumarni Abdul Rahim Adi Nur Cahyono Agung Tri Prasetya Ahmad Farham Majid Alfairus, Muh. Qodri Amin, Badaruddin Amiruddin Hambali Andi Kusumayanti, Andi Anjarsari, Irna Arif Widiyatmoko, Arif Ariyatun, Ariyatun Ayu Pebriyanti Azqia Noviatun Nisa Baharuddin Baharuddin Abbas, Baharuddin Bambang Subali BENI SETIAWAN Budoyo, Joto Desi Utami Dian Pratiwi Edy Cahyono Ellianawati Ermina Sari Fathiyah Marsya Tilawah Febriyanto, Hendra Fitrah Adelina Fredy Supriadi Hardianti Hafid Harianingsih Helmiah, Fauriatun Hendra Febriyanto Ibrahim Ike Yunia Meka Jum’anil Agustini Kristanto, Tan Kevin Kurotul Aeni Luky Hidayat Mar'ah, Zakiyah Maria Paristiowati Martalasari Masitah Handayani Masnaeni Meliyana R, Sitti Masyitah Mita, Ermita Khoirumminsani Muhammad Naufal, Muhammad Muhammad Nur Hidayat Muhammad Rizki Muhammad Saefudin Mutiara Nanik Wijayati Neli Syahida Ni'ma Noening Andrijati Norma Eralia Norma Eralita Nurman, Sulaeman Nurul Rezky Nusrang, Muhammad Nyi Mas Ayu Ratna Gumilar Prasetiyani, Nabila Purbawati, Sih Yunika puspita rini Putut Marwoto Qadaruddin Fajri Adi Rahmat Hidayat Rais, Zulkifli Raudhah Awal Ricky Rizaldi Ridwan, Indi Nur Risa Dwita Hardianti Ruliana Sabrina Effendy, Yuni Safitriani, Indah Sarwi Sasa Arisa, Sasa Arisa Sigit Priatmoko Siti Anisah Siti Suhartini Sitti Masyitah Meliyana R. Sri Anggini Wahyuningsih Sri Endang Pujiastuti, Rr Sri Haryani Sri Sukasih SRI WARDANI Sri Yamtinah Sriwidiastuty, Asi Sukniasih Sunardi Syahputra, Akbar Tri Joko Raharjo Wahyu Lestari Woro Sumarni