Publication Search

This community service activity aims to improve the competency of Regional Apparatus Work Unit (SKPD) personnel in preparing monthly, quarterly, and semi-annual financial statements in accordance with Government Accounting Standards (SAP). This activity uses a participatory approach through Focus Group Discussions (FGD) involving 95 participants consisting of Financial Administration Officers and expenditure treasurers from various SKPDs in the Semarang City Government. The evaluation indicators included participant participation, improvement of understanding, identification of reporting problems, and formulation of follow-up actions. The finding, based on the results of the post-test, an average of 80% of participants showed improvement, particularly in account classification, transaction recording, and periodic report preparation. The FGD identified four major issues: limited mastery of financial information systems, data input errors, insufficient competent human resources, and weak inter-unit coordination causing delays in report submission. As post-FGD outcomes, participants agreed on the need for continuous technical training, standardized operating procedures, optimization of information system integration, and the establishment of a reporting coordination forum. These results provide evidence that FGD was effective not only in evaluating participants’ competencies but also in generating practical solutions to enhance transparent and accountable regional financial governance.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

Psychological conflicts often arise intensely, as illustrated in Usmar Ismail’s play Ayahku Pulang. The character Gunarto experiences inner turmoil and trauma from family disputes, which trigger various defense mechanisms. This study aims to describe the forms of defense mechanisms exhibited by Gunarto and identify the factors behind their emergence.  Using a literacy  psychology approach, specifically Sigmund Freud’s psychoanalytic theory, the research elaborates on the character’s psychological dynamics. The qualitative method employed the read-and-record technique, with data analyzed through the Miles and Huberman model involving reduction, classification, and inference. Findings reveal eight defense mechanisms used by Gunarto: denial, repression, avoidance, compartmentalization, rationalization, displacement, sublimation, and identification with the aggressor. Their emergence is influenced by psychological factors such as past trauma, economic hardship, and disharmonious family relationships. In conclusion, Gunarto’s defense mechanisms reflect symptoms of individuals facing trauma and family disharmony. This study demonstrates how a literary-psychological approach enriches understanding of literature as a reflection of the human psyche and reveals more about a character’s inner world.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

This study aims to analyze the financial distress condition of PT Garuda Indonesia (Persero) Tbk during the period 2015–2024 using the Springate and Grover models. The research employs a quantitative descriptive approach with secondary data obtained from the company’s annual financial statements. Financial distress analysis is conducted by calculating financial ratios included in each model to describe the company’s financial condition over the observation period. The results indicate that PT Garuda Indonesia (Persero) Tbk experienced financial distress during several periods, particularly before and during the COVID-19 pandemic, which was reflected in weakened liquidity, declining profitability, and reduced efficiency in asset utilization. However, following the financial restructuring process after 2021, both the Springate and Grover models show an improvement in the company’s financial condition, indicating a transition toward a more stable non-distress status. Although the Springate and Grover models use different financial indicators and classification approaches, both are able to descriptively capture the dynamics of financial distress experienced by the company. The differences in classification results reflect the distinct focus of each model, where the Springate model is more sensitive to liquidity and operational performance, while the Grover model emphasizes asset profitability. Therefore, the combined use of both models provides a more comprehensive overview of the financial distress condition of PT Garuda Indonesia (Persero) Tbk during the research period.

Ibuprofen is an antipyretic and anti-inflammatory drug classified as Biopharmaceutics Classification System (BCS) class II, characterized by low water solubility and high permeability. Its limited solubility may reduce the dissolution rate and influence therapeutic effectiveness. This study aimed to formulate ibuprofen suppositories using cocoa butter (oleum cacao) as the suppository base through the melting method. Each suppository was prepared with a total weight of 2500 mg containing 125 mg ibuprofen, oleum cacao as the base, tween 80 as an emulsifier, and liquid paraffin as a mold lubricant. Before formulation, a displacement value test was performed to determine the exact amount of base required. The prepared suppositories were evaluated through organoleptic examination, weight uniformity, melting time, and dissolution testing. The evaluation results demonstrated that the suppositories possessed acceptable physical characteristics, uniform weight distribution, appropriate melting properties, and satisfactory dissolution behavior. Based on these findings, ibuprofen suppositories formulated with oleum cacao fulfilled pharmaceutical quality requirements in accordance with the Indonesian Pharmacopoeia standards.

Background: Acne vulgaris is a chronic inflammation of the pilosebaceous unit caused by multiple factors, characterized by the presence of comedones, papules, pustules, nodules, and cysts. This condition commonly affects adolescents and often leads to psychological impacts, particularly decreased self-confidence. During adolescence, sensitivity to physical appearance tends to increase, making facial changes such as acne influential on social interactions, self-esteem, and even academic performance. Objective: This study aims to determine the relationship between the severity of acne vulgaris and the level of self-confidence among students of SMA Al Irsyad Surabaya in 2025. Methods: The research employed an analytical design with a cross-sectional approach and involved a population of 90 students, from which 73 were selected as samples using purposive sampling based on inclusion and exclusion criteria. The severity of acne vulgaris was assessed using an observation sheet based on the Lehmann classification, while self-confidence levels were measured using the Rosenberg Self-Esteem Scale (RSES). Data were analyzed using the Spearman Rank correlation test. Results: The findings showed that most students experienced mild acne vulgaris (49.3%) and had a high level of self-confidence (64.4%). There was a significant relationship between acne severity and self-confidence (p = 0.008), indicating that the more severe the acne, the lower the level of self-confidence. Conclusion: This study is expected to serve as a basis for schools and healthcare providers in developing educational programs and psychological support for adolescents

Religious institutions such as mosques are part of non-profit public sector entities that manage public funds and therefore require accountable and transparent financial reporting standards. ISAK 335 is the applicable standard governing the presentation of financial statements for non-profit-oriented entities in Indonesia. This study aims to analyze the conformity of financial management practices in three mosques in Tanah Datar Regency, West Sumatra, namely Baiturrahman Mosque Sungayang, Nurul Huda Mosque Simpuruik, and Al-Amin Mosque Dobok Batusangkar, with the provisions of ISAK 335. The approach used in this research is a descriptive qualitative approach with data collection conducted through interviews and observations. The results of the study indicate that the three mosques have not implemented ISAK 335 in the preparation of their financial statements. Financial management practices are still limited to recording cash receipts and cash disbursements without the classification of net assets, statements of financial position, statements of activities, or notes to financial statements standardized in accordance with ISAK 335. The main inhibiting factors include limited human resources in the field of accounting, lack of standard dissemination, and minimal regulatory pressure. This study recommends the need for continuous training, technical assistance, and stronger regulations for mosque financial managers so that mosque financial statements can be prepared and presented in accordance with the applicable standards for non-profit organizations, namely ISAK 335.

This research is driven by the significance of examining language meaning, particularly connotative meaning which is often used to convey implicit messages in literary works. Folktales, as one type of oral literature, often utilize character names that carry specific meanings, such as Malin Kundang from Minangkabau. The aim of this research is to uncover the connotative meaning of the character name “Malin Kundang”, as well as its relationship with the moral and cultural values of the society. The methodology involves qualitative research using semantic analysis and a descriptive approach. Data were collected from the Malin Kundang folktale text thru library study and documentation techniques. Next, the processes of identification, classification, and interpretation of meaning were done in order to examine the data. The research result show that denotatively, the name Malin Kundang only functions as the identity of the character, but connotatively, it functions as a symbol of a disobedient child who does not respect their parents. The meaning is formed from the plot of the story and reinforced by the Minangkabau cultural values that uphold respect for parents. The implications of this research indicate that the naming of characters in folklore is not only linguistic but also reflects the moral and cultural values inherited by society.

The arrangement of inactive dynamic records is an important part of records management because it is related to storage organization and the ease of records retrieval. Inactive dynamic records are records whose frequency of use has decreased but still possess functional value, therefore they must be managed systematically. This study aims to analyze the arrangement of inactive dynamic records in supporting records retrieval. The study used a descriptive method with a library research approach. Data were collected through literature studies from books, scientific journals, and relevant regulations. Data analysis was conducted descriptively through data reduction, data presentation, and conclusion drawing. The results showed that systematic records arrangement through records classification, records retention schedules, storage systems, and retrieval aids can improve the effectiveness of records retrieval. The success of records retrieval is influenced by the storage system, the competence of human resources, and the availability of archival facilities and infrastructure. Therefore, proper management of inactive dynamic records plays an important role in supporting the effectiveness and efficiency of records management within an organization.

This study examines customer churn prediction in subscription-based telecommunications from a digital marketing perspective using machine learning. The analysis utilizes a secondary dataset of 7,043 customer records that simulate behavioral, contractual, and financial attributes commonly found in telecom services. Three classification algorithms Logistic Regression, Random Forest, and Gradient Boosting are applied to model churn behavior. Data preprocessing includes handling missing values, encoding categorical variables, and splitting data into training and testing sets. Model performance is evaluated using accuracy, recall, and ROC-AUC, with emphasis on recall due to its importance in identifying at-risk customers. The results show that Gradient Boosting achieves the highest overall performance with an ROC-AUC of 0.84, while Logistic Regression provides relatively higher recall. Key drivers of churn include short-term contracts, higher monthly charges, and lower service engagement. However, recall remains moderate, indicating limitations in capturing complex behavioral factors. These findings suggest the need to combine predictive models with behavioral insights and highlight the importance of early customer engagement and long-term retention strategies.

The development of modern armed conflicts shows the increasing involvement of civilians in hostilities, which has given rise to the phenomenon of civilian combatants and created ambiguity in the classification of subjects in International Humanitarian Law. This study aims to analyze the legal status of civilians involved in armed conflicts and the limits of legal protection inherent to them. The research method used is normative juridical with a legislative and conceptual approach, through an analysis of international legal instruments and relevant doctrines. The results show that civilian combatants are not explicitly recognized in international humanitarian law, thus creating uncertainty in determining their legal status. Furthermore, protection for civilians is conditional and can be temporarily lost when individuals engage in direct participation in hostilities, with limits determined by the principles of distinction and proportionality. These findings confirm that the limits of legal protection are dynamic and depend on individual actions in conflict. The implications of this study indicate the need for strengthened legal interpretation and more consistent implementation to ensure legal certainty and protection for civilians in modern armed conflicts.

This research is motivated by the existence of legal pluralism in marriage regulations in Indonesia before the enactment of Law Number 1 of 1974 concerning Marriage. During that period, marriage provisions were influenced by various legal systems, namely customary law, Islamic law, and colonial laws such as the Burgerlijk Wetboek, whose application was based on population classification. This condition gave rise to various problems, including legal uncertainty, differing standards for marriage validity, and weak protection of the rights of women and children. Based on these problems, this study aims to examine the development of marriage law in Indonesia, both before and after the enactment of the Marriage Law, and to assess the extent to which these regulations have been able to achieve legal unification and certainty within the national legal system. The method used is qualitative-normative research with a literature study approach through analysis of relevant laws and regulations, historical documents, and scientific literature. The results indicate that before 1974, the marriage legal system was complex and unintegrated, necessitating a comprehensive codification. The process of drafting this law was lengthy and marked by ideological debate and religious considerations. However, an agreement was ultimately reached that accommodated both religious values ​​and state interests. Subsequent developments, including amendments through Law Number 16 of 2019, confirm that marriage law in Indonesia is dynamic in responding to demands for justice, human rights, and gender equality.

The distribution of social assistance represents a key government strategy to enhance the welfare of low-income communities. Nevertheless, its implementation frequently faces challenges related to inaccurate targeting, often caused by uneven data collection and subjective decision-making processes in identifying eligible beneficiaries. This study aims to compare the performance of the K-Nearest Neighbors (KNN) and Naïve Bayes algorithms in determining eligibility for social assistance recipients in Banyuputih Kidul Village. Both models were evaluated using a confusion matrix with performance indicators including accuracy, precision, recall, and F1-score. The findings reveal that the KNN algorithm outperformed Naïve Bayes in identifying recipients of the PKH social assistance program, achieving an evaluation score of 99%, compared to 86% for Naïve Bayes. These results indicate that KNN provides higher predictive reliability for eligibility classification. This research is expected to support the development of an objective, data-driven decision support system that can assist village governments in distributing social assistance more accurately and transparently.

Background: Class II restoration according to the classification of Greene Vardiman Black is one of the procedures in dental conservation that often presents a challenge for operators or dentists during treatment. Class II restorations have their own level of difficulty, particularly during the placement of restorative materials into the cavity. One of the possible failures in Class II restorative treatment is marginal leakage, which can lead to microleakage at the restoration margins. Purpose: To report the success of class II restoration with composite resin using tofflmire matrix. Case report: A 23-year-old female patient came with a complaint of cavities, the complaint was felt since 1 year ago in the lower left back tooth, there was no pain and had never been treated. In the case, preparation and restoration were carried out using composite resin with isolation using tofflmire matrix, applied using an Incremental technique. Discussion: Class II posterior tooth restorations have challenges such as leakage due to the techniques and materials used. Composite resin is chosen because of its good adaptation, esthetics, and wear resistance. Incremental techniques are preferred because they reduce polymerization stress and provide optimal curing results. Tofflemire matrix is ​​used for stability and soft tissue protection.Conclusion: The selection of composite resin with an Incremental technique and the use of a Tofflemire matrix provides more optimal, aesthetic, and minimal risk of failure results for class II posterior tooth restorations.

With the advancement of technology, artificial intelligence tools have begun to emerge in the field of education, such as ChatGPT, which is now used by some teachers at Pondok Modern Darussalam Gontor to compare translations of Indonesian texts into Arabic. Although there are recognized reference books for correcting translations, there are discrepancies between machine translations, including errors in terminology selection and contradictions with the educational context. This raises questions about the accuracy of ChatGPT’s translations, making this study necessary to analyze and evaluate terminological errors. This study aims to analyze the translation errors made by ChatGPT when translating Indonesian articles into Arabic. This study also seeks to evaluate the quality of these translations based on the classification of terminological errors and Ali Al-Qasimi’s theory regarding the evaluation of terminology in terms of acceptance and rejection. This study employs a qualitative approach using content analysis, in which ChatGPT’s translations are compared with those in reference books, with reference to specialized Arabic dictionaries. Subsequently, the data was analyzed to identify error patterns and their acceptance levels within an educational context. The results indicate that translation errors can be classified into four main patterns: phonetic transfer, conceptual errors, semantic shifts, and inaccurate synonyms.

This research examines the practice of handling Factual Action (TF) cases at the State Administrative Court (PTUN) after the issuance of Supreme Court Regulation Number 2 of 2019 and the Job Creation Law, as well as the implications for the issuance of SEMA Number 2 of 2024. The main focus is on Factual Action (TF) cases which are preceded by a letter requesting the issuance of a certificate with a comparative study of Decision Number 93/G/TF/2023/PTUN.BDG and  41/G/TF/2024/PTUN.BDG.  This research aims to analyze whether TF cases that are preceded by an application for issuing a certificate are a form of smuggling in Negative Fictitious or Positive Fictitious cases, or whether they have their own classification because there are unique characteristics that differentiate them.  The research method used is a normative legal research method with a case study approach.  The research results show that there are two models for handling TF cases which are preceded by a request for certificate issuance.  The two are different because the first model can be considered as Positive Fictitious/Negative Fictitious legal smuggling, but the second model is not legal smuggling.  This means that the existence of factual action cases has produced various types of factual actions with their own unique characteristics.  These cases are not always smuggling Positive Fictitious or Negative Fictitious cases, but have unique characteristics that need to be recognized and accommodated in the practice of state administrative justice.

The objectives of the study are: 1) To analyze the level of vulnerability of agricultural land to flash floods in Nagari Pauh Kamang Mudiak, 2) To analyze the condition of agricultural land in Nagari Pauh Kamang Mudiak before and after the flash flood. The results of this study: 1) Analysis of the level of vulnerability of agricultural land to flash floods in Nagari Pauh Kamang Mudiak, namely in the safe class covering an area of 8.34 hectares, the non-vulnerable class covering an area of 12.01 hectares, the vulnerable class covering an area of 51.91 hectares and the very vulnerable class covering an area of 18.13 hectares. This shows that most of the research areas have a high level of vulnerability to flash floods. Furthermore, the analysis of flash flood risks with 4 risk classifications is an area with a low risk of 16.94 hectares, a moderate area of 30.60 hectares, a high area of 37.78 hectares, and a very high area of 5.07 hectares. Based on the results of this analysis, the agricultural land most affected by the flash flood in Nagari Pauh Kamang Mudiak is rice fields covering an area of 72.2 hectares, 2) Analysis of the condition of agricultural land vegetation in Nagari Pauh Kamang Mudiak before and after the flash flood, namely with 5 classes, namely the very low greenness class covering an area of 12.69 hectares, low covering an area of 29.69 hectares, medium covering an area of 13.22 hectares, and high covering an area of 34.84 hectares. The results of the accuracy test using overall accuracy reached a suitability of 89.58% and the kappa coefficient reached a suitability of 84.32%, meaning good accuracysuitability between the classification results and actual conditions in the field.

Carpal Tunnel Syndrome (CTS) merupakan gangguan muskuloskeletal pada ekstremitas atas akibat penekanan nervus medianus di terowongan karpal yang dapat menimbulkan nyeri, parestesia, penurunan kekuatan otot, serta keterbatasan fungsi aktivitas. Kondisi ini sering dijumpai pada individu dengan aktivitas tangan berulang dan berpotensi menurunkan kualitas hidup apabila tidak ditangani secara adekuat. Penelitian ini bertujuan untuk menggambarkan asuhan fisioterapi berbasis International Classification of Functioning, Disability and Health (ICF) pada pasien dengan Carpal Tunnel Syndrome unilateral. Penelitian menggunakan desain studi kasus pada seorang pasien perempuan berusia 55 tahun dengan keluhan nyeri dan kesemutan pada pergelangan tangan kiri selama ±2,5 bulan. Pemeriksaan meliputi asesmen nyeri menggunakan Numeric Rating Scale (NRS), lingkup gerak sendi (ROM), kekuatan otot menggunakan Manual Muscle Testing (MMT), serta fungsi aktivitas menggunakan Boston Carpal Tunnel Syndrome Questionnaire (BCTSQ). Intervensi fisioterapi diberikan selama tiga minggu dengan frekuensi dua kali per minggu, meliputi ultrasound terapeutik, terapi manual, latihan ROM aktif, latihan penguatan genggaman, stretching, nerve gliding, tendon gliding exercise, serta edukasi ergonomi dan home exercise program. Hasil evaluasi menunjukkan penurunan nyeri, peningkatan ROM palmar dan dorsal fleksi, peningkatan kekuatan otot fleksor dan ekstensor wrist, serta perbaikan fungsi aktivitas berdasarkan BCTSQ. Studi kasus ini menunjukkan bahwa asuhan fisioterapi berbasis ICF memberikan dampak positif terhadap perbaikan gejala dan fungsi pada pasien dengan Carpal Tunnel Syndrome unilateral.

The proliferation of online gambling promotional comments on Indonesian social media has become a serious issue requiring fast and accurate automated handling. This study aims to implement a Hybrid Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) method to classify online gambling comments and compare its performance with standalone RNN and LSTM models. The research utilized a dataset of 10,230 comments subjected to comprehensive preprocessing stages, including the normalization of non-standard language using a slang dictionary. Testing was conducted across three data-splitting scenarios: 90:10, 80:20, and 70:30. Experimental results demonstrate that the standalone LSTM model achieved the highest average accuracy of 97.45%. However, the Hybrid RNN–LSTM model showed significant superiority in terms of performance stability, yielding the lowest standard deviation (0.0027) and the smallest Coefficient of Variation (0.28%) across all scenarios. These findings indicate that while the LSTM architecture is highly effective at capturing short-text context, the Hybrid approach provides better robustness against fluctuations in data proportions, making it highly relevant for implementation as an automated detection system on social media.