cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Rudito
Contact Email
admin.tepian@politanisamarinda.ac.id
Phone
+6285388729017
Journal Mail Official
admin.tepian@politanisamarinda.ac.id
Editorial Address
Jl. Samratulangi Samarinda 75131 Telepon. 0541 260421, 260680 Faximile. 0541 260680 email : info@politanisamarinda.ac.id dan politanismd@gmail.com
Location
Kota samarinda,
Kalimantan timur
INDONESIA
Buletin Poltanesa
Published by Politeknik Pertanian Negeri Samarinda
ISSN : 14120097     EISSN : 26148374     DOI : 10.51967/tanesa.v21i2.326
Core Subject : Science, Education, Agriculture,
Agriculture, Biological Sciences & Forestry Computer Science & IT Education
Buletin Poltanesa is a collection of research articles, scientific works, and dedication from all academic community in order to integrate information. Buletin Poltanesa provides open publication services for all members of the public, both in all tertiary educational and teacher environments and other research institutions, with the freedom to exchange information that is dedicated to facilitating collaboration between researchers, writers and readers through information exchange. Buletin Poltanesa was introduced and developed in Research Department of Politeknik Pertanian Negeri Samarinda Buletin Poltanesa is published periodically twice a year, in June and December, this bulletin contains the results of research activities, discoveries and ideas in the field all multidisciplinary sciences. Hopefully with the articles in cultivation researchers can share knowledge in order to advance Indonesia, especially East and North Borneo.
Arjuna Subject : Umum - Umum
Articles 645 Documents
 58   59   60   61   62 
Empowering Religious Leaders for Sustainable Prevention of Lifestyle-Related Diseases Elizabeth Sulastri Nugraheni; Hanna Tabita Hasianna Silitonga; Saskia Dyah Handari; Mellyanawati Mellyanawati; Stefani Nurhadi; Jennifer Tantadiputra; Rafkha Hakam Irsyad Maulana
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3715

Abstract

Promotive and preventive care represents the most meaningful contribution physicians can make within preventive medicine. However, this approach is often difficult to implement in clinical settings, where patients typically seek help only after illness has developed. Strengthening health literacy and promoting healthier lifestyles at the community level are therefore essential to preventing lifestyle-related non-communicable diseases before onset. This study explores the empowerment of religious leaders and Islamic scholars as key actors in community-based promotive and preventive health efforts. In Indonesia’s collectivist and high–power distance culture, religious figures hold influential positions, making them effective agents of change for health education and behavior transformation. A descriptive cross-sectional design was employed using secondary data from questionnaires administered during community engagement activities. Educational sessions addressed lifestyle and health issues across demographic groups. Twenty-three participants completed structured self-assessments, and program effectiveness was evaluated using pre- and post-test measures. Results demonstrated diverse demographic characteristics among participants. Post-intervention findings showed a 13.1% improvement in attitudes toward healthy lifestyle practices. Additionally, 47.82% of participants had a body mass index above the normal range. These findings highlight the potential of religious leaders as catalysts for sustainable, community-based preventive health practices.
Dynamics of Toxic Work Environments and Job Satisfaction: Analyzing the Mediating Role of Self-Efficacy and the Moderation of Social Support Mariano Firmansyah; David Manafe; Septiani Arbania
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3717

Abstract

This study aims to analyze in depth the influence of toxic work environments on employee job satisfaction in Kupang City, examining the role of self-efficacy as a mediating variable and social support as a moderating variable. While unhealthy work environments are often regarded as a primary factor in declining morale, this research explores the underlying psychological mechanisms behind such impacts. Employing a quantitative approach, data were collected via questionnaires from employees in Kupang City and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to test the structural relationships between variables.The results indicate that social support is a strong predictor that positively influences job satisfaction. Conversely, toxic work environments are confirmed to have a general negative impact on job satisfaction. However, a unique finding reveals that a toxic work environment actually enhances employee self-efficacy. Furthermore, self-efficacy is proven to act as a mediator that bridges the relationship between a toxic work environment and job satisfaction.Nonetheless, moderation testing demonstrates that social support is unable to weaken the negative influence of a toxic work environment on job satisfaction. This finding emphasizes that emotional support among colleagues has limitations in mitigating the effects of a destructive organizational culture. Therefore, systemic interventions to improve management and organizational culture are far more crucial than merely relying on internal social relations.
Influence of Chemical Activator (H₃PO₄ and NaOH) on the Characteristics of Coconut Shell-Derived Activated Carbon Rozalia Rozalia; Deivy Andhika Permata; Ayulian Sara
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3720

Abstract

Activated carbon is an adsorbent material widely utilized in various environmental applications, particularly in water and wastewater treatment due to its excellent adsorption properties. Coconut shell is recognized as a lignocellulosic biomass with significant potential for activated carbon production due to its abundant availability, renewable nature, and high carbon content. However, studies specifically comparing the effect of different chemical activating agents on the physicochemical characteristics of coconut shell-derived activated carbon remain limited. This study aims to compare the characteristics of activated carbon derived from coconut shells chemically activated using two different activating agents, namely phosphoric acid (H₃PO₄) and sodium hydroxide (NaOH). The production process was carried out through a carbonization stage at 700°C for 2 hours, followed by chemical activation using H₃PO₄ and NaOH at concentrations of 5%, 10%, and 15%, respectively. The characterization conducted included analysis of moisture content, ash content, volatile matter, fixed carbon content, and iodine adsorption capacity based on SNI 06-3730-1995 standards. The results indicate that chemical activation can reduce moisture content, ash content, and volatile matter while increasing fixed carbon content. In terms of iodine adsorption capacity, H₃PO₄ at a concentration of 5% was found to be the most effective activator, with a value of 1311.94 mg/g. Activated carbon derived from coconut shells using both H₃PO₄ and NaOH meets the quality standards of SNI 06-3730-1995, indicating its potential use as an adsorbent in water treatment and industrial waste management.  
Exploring the Role of Digital HR Analytics in Enhancing Human Resource Management Effectiveness Risza Putri Elburdah; Muhammad Ramdhan
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3721

Abstract

This study aims to explore the role of Digital HR Analytics in enhancing Human Resource Management (HRM) effectiveness. A qualitative research approach was employed to gain an in-depth understanding of how analytics is utilized in HR practices. Data were collected through semi-structured interviews with HR professionals and organizational leaders who are directly involved in HR decision-making processes. The data were then analyzed using thematic analysis to identify key patterns, themes, and insights. The findings indicate that Digital HR Analytics plays a significant role in improving HRM effectiveness through four major dimensions: data-driven decision-making, enhancement of HR functional effectiveness, strategic transformation of HR roles, and the identification of implementation challenges. The use of analytics allows organizations to make more accurate, objective, and timely decisions. It also enhances the efficiency and quality of core HR functions, including recruitment, training, and performance management. Furthermore, HR is increasingly positioned as a strategic partner that contributes to broader organizational decision-making and business outcomes. However, several challenges were identified, including limited analytical competencies among HR professionals, issues related to data quality, and organizational resistance to change, all of which may hinder effective implementation. This study contributes to the HRM literature by providing in-depth qualitative insights into the strategic value of Digital HR Analytics, while also emphasizing the need for developing analytical capabilities and robust digital infrastructure to maximize HR effectiveness in the digital era.
Sentiment Analysis and Topic Modeling of Danone Indonesia Product Brands on Social Media X Muhammad Sholahuddin Al Ayubi; Indra Budi
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3723

Abstract

Public opinion expressed on social media increasingly mirrors consumer perception of brands in the Fast-Moving Consumer Goods (FMCG) sector. This study builds and compares sentiment analysis models to objectively classify public opinion toward three Danone Indonesia brands, namely AQUA, Mizone, and SGM, based on conversations on X/Twitter, while identifying the topics that shape that opinion. Data were collected legally through the official X/Twitter API v2, yielding 5,813 Indonesian-language tweets posted between May 2025 and June 2026 after duplicate removal. Three annotators labeled relevance and sentiment, with reliability assessed using Fleiss' Kappa, and the text was represented through TF-IDF weighting. Four classifiers, namely Naive Bayes, Support Vector Machine (SVM), Decision Tree, and Logistic Regression, were compared using cross validation, while Latent Dirichlet Allocation modeled the topics. After hyperparameter tuning and stratified ten-fold validation, SVM was the most accurate and stable model, reaching 88.80% accuracy and 88.19% macro F1. AQUA was dominated by negative opinion driven by a water-source controversy, whereas Mizone and SGM leaned positive. Integrating sentiment analysis and topic modeling objectively measures and explains public opinion toward FMCG brands.
The Mediating Role of Shopping Lifestyle in the Effect of Financial Literacy and PayLater Usage on Impulsive Buying among Civil Servants Marna Marthen Rando; Lailani Silmina Kresida; Nurun Nida Nilhar; Rahmawati Rahmawati; Syarifah Hudayah; Sugeng Hariyadi
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3726

Abstract

This study aims to examine the effect of financial literacy and PayLater usage on impulsive buying, with shopping lifestyle as a mediating variable among civil servants in Samarinda City. The rapid growth of Buy Now Pay Later services has changed consumer payment behavior by offering instant credit, transaction convenience, and deferred payment options. Although PayLater provides financial flexibility, it may also reduce the psychological pain of paying and increase unplanned purchases. This research applies a quantitative approach using Partial Least Squares-Structural Equation Modeling with 350 civil servants who had used PayLater services within the last six months. The questionnaire consisted of 57 indicators measured using a five-point Likert scale. The findings show that financial literacy has a positive and significant effect on shopping lifestyle, but it does not directly influence impulsive buying. PayLater usage significantly affects both shopping lifestyle and impulsive buying. Shopping lifestyle also significantly influences impulsive buying and mediates the effects of financial literacy and PayLater usage. These findings indicate that impulsive buying is driven more strongly by shopping lifestyle and digital payment convenience than by financial knowledge alone.
Implementation of Text Mining for Service Quality Classification of Google Maps Reviews at Samarinda Civil Registry Office Using K-Nearest Neighbor Algorithm Abed Nego; Heny Pratiwi; Ivan Haristyawan
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3728

Abstract

This research aims to analyze public sentiment regarding services at the Department of Population and Civil Registration as an objective evaluation instrument for service quality through a series of methodological stages, beginning with text preprocessing including cleansing, folding, tokenizing, filtering, and stemming to reduce noise in the scraped textual data. Feature extraction was performed using Term Frequency-Inverse Document Frequency (TF-IDF) to determine the significance of each term within the documents, while the classification process was implemented using the K-Nearest Neighbor (KNN) algorithm by experimenting with various nearest neighbor (k) values to identify the most optimal model parameters. Based on a comprehensive evaluation using a confusion matrix, the model achieved peak performance at k=3 with an accuracy rate of 92.8%, although significant limitations were identified in predicting negative sentiments, only 6 of the 14 data points were correctly classified. This indicates a classification bias triggered by data imbalance, a common challenge in text mining is that the number of positive reviews far outnumbers the number of negative reviews. Qualitatively, although reviews were dominated by public appreciation, critical complaints were still found regarding perceived slow service duration and overlapping bureaucratic complexities. These findings emphasize that while the model possesses high quantitative accuracy, a thorough evaluation of service quality must focus on strategic transformations that improve system efficiency and information transparency to bridge the gap between community expectations and the reality of public service delivery.
Sentiment Analysis of Akutusocks Store Reviews Using Text Mining and K-Nearest Neighbor (KNN) Ade Maulana Anshari; Heny Pratiwi; Aisyah Fajrianti
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3732

Abstract

Akutusocks is a retail business that utilizes the TikTok platform for digital martaketing and as a vital two way communication channel with its consumers. The high intensity of interaction on this social media platform produces extensive review data containing various customer perceptions, complaints, and appreciation. However, this data remains largely unstructured, making it extremely difficult for the management team to analyze the information manually and efficiently. This study aims to implement advanced text mining techniques to classify the sentiment of Store Akutusocks reviews into positive and negative categories in order to provide an objective basis for evaluating the quality of product and service quality. The methodology applied in this study integrates the K-Nearest Neighbor (KNN) algorithm with a lexicon-based approach to streamline the initial data labeling process for thousands of user comments. The research stages began with rigorous text preprocessing, which is crucial for improving data quality. This process included case folding, cleansing, tokenization, and normalization to correct slang terms and abbreviations specific to TikTok, as well as stopword removal and stemming to reduce words to their base forms. Feature weighting was performed using the Term Frequency-Inverse Document Frequency (TF-IDF) method to extract dominant keywords representing user sentiment. This analysis is vital for Store Akutusocks in mitigating digital reputation risks and understanding market preferences. Through model testing using a Confusion Matrix, this study measures classification accuracy and provides deep insights into the effectiveness of the KNN algorithm
Supply Chain Success Analysis at Makeen Idea Store Muhammad Andrian; Heny Pratiwi; Rizky Zakaryya Rasyad
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3733

Abstract

This study aims to analyze the success of Supply Chain Management (SCM) implementation at Makeen Idea Store in improving operational performance and business competitiveness. This research employed a qualitative approach using a case study design, with data collected through direct observation, interviews with the store owner and employees, and documentation of operational activities. The findings indicate that the success of SCM implementation at Makeen Idea Store is influenced by several key factors, including strong information flow integration, strategic partnerships with suppliers, and demand-based inventory management. In addition, the implementation of an organized inventory recording system helps minimize errors and improve distribution efficiency. Effective SCM implementation has contributed to reducing operational costs, accelerating product distribution, and increasing customer satisfaction through stable product availability. However, several challenges remain, particularly limited digital technology adoption and dependence on certain suppliers, which may hinder sustainable supply chain performance improvement. Therefore, it is recommended that Makeen Idea Store further develop a digital-based SCM system and expand its supplier network to enhance supply chain flexibility and resilience in the future.
Macro Nutrient Content Of Combined Vermicompost Fertilizer And Tofu Drainage Waste Using Lumbricus Rubellus Worm Marselinus Banu; Josua Sahala; Wolfhardhus Vinansius Feka; Jefrianus Neonnub; Agustinus Agung Dethan; Ernanda Sofi; Maria Selfiana Pasi; Maria Magdalena Kapitan; Maria Metriana Seran
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3735

Abstract

This research was conducted to identify the macro-nutrient levels contained in vermicompost produced from a combination of Bio-slurry and tofu waste processed with Lumbricus rubellus. The study applied a single-factor experimental design focusing on the proportion of Bio-slurry mixed with tofu dregs, which served as an additional energy supply for the worms during vermicomposting. The experiment was carried out from June to July 2025 at the Animal Husbandry Laboratory, Faculty of Agriculture, Science, and Health, Timor University, Sasi Village, Kefamenanu. A Completely Randomized Design (CRD) consisting of four treatments and four replications was used, totaling 16 experimental units. The treatments included: P0 = 5 kg Bio-slurry + 250 g worms; P1 = 5 kg Bio-slurry + 200 g tofu dregs + 250 g worms; P2 = 5 kg Bio-slurry + 400 g tofu dregs + 250 g worms; and P3 = 5 kg Bio-slurry + 600 g tofu dregs + 250 g worms. The results revealed significant differences (P < 0.05) in Nitrogen, Phosphorus, and Potassium contents. Treatment P3 showed the highest levels of Nitrogen (2.15%), Phosphorus (0.95%), and Potassium (0.93%). Based on these findings, adding 600 g of tofu dregs produced the most optimal macro-nutrient composition in the resulting vermicompost.

Page 60 of 65 | Total Record : 645

 58   59   60   61   62 

Filter by Year

2019 2026


Reset
Filter By Issues
All Issue Vol 27 No 1 (2026): June 2026 Vol 26 No 2 (2025): December 2025 Vol 26 No 1 (2025): June 2025 Vol 25 No 2 (2024): December 2024 Vol 25 No 1 (2024): June 2024 Vol 24 No 2 (2023): December 2023 Vol 24 No 1 (2023): June 2023 Vol 23 No 2 (2022): Desember 2022 Vol 23 No 1 (2022): Juni 2022 Vol 22 No 2 (2021): Desember 2021 Vol 22 No 1 (2021): Juni 2021 Vol 21 No 2 (2020): Desember 2020 Vol 21 No 1 (2020): Juni 2020 Vol 20 No 2 (2019): Desember 2019 Vol 20 No 1 (2019): Juni 2019 More Issue