bluuebunny/crossref_metadata_2025 huggingface dataset:
Agotamientos del no-objeto = Beckett
Authors: Badal Casas Laia
Published: July 2024

En este articulo analizamos el texto de L’épuisé, de Gilles Deleuze, desde la hermenéutica. Partimos de su definición de la figura del “agotado” en tanto que ser que desestabiliza la lógica hegemónica de las estructuras del lenguaje, y generamos un diálogo rizomático entre esta figura y el pensamiento de Deleuze convocando varias de las publicaciones y reflexiones de todo su recorrido. La reflexión sobre el lenguaje, sobre la literatura y el arte como espacios de détournement y de algunas bases del posestructuralismo abren paso finalmente al análisis de cuatro obras filmadas de Samuel Beckett, que ayudan a poner en práctica las teorías formuladas por Deleuze a la vez que friccionan con ellas desde su singularidad, y desde sus fórmulas particulares de agotamiento del lenguaje.
Central Valley, California y otros modos del tercer paisaje
Authors: Valls Boix Juan Evaristo
Published: July 2024

El propósito del presente artículo consiste en explorar una forma de lectura comparada en clave materialista que denominamos lectura de la (y desde la) infraestructura. Esta forma de lectura es pertinente porque permite valorar el alcance político de la literatura, que aquí se comprenderá desde una reflexión híbrida entre biopolítica (Agamben) y estética (Rancière). De todas las infraestructuras, este artículo abordará la del acceso al suelo, esto es, nuestra relación con el espacio, la habitabilidad de las ciudades. La precariedad de esta infraestructura se estudiará a través de una resignificación del concepto de “tercer paisaje” de Gilles Clément, un concepto espacial que se mostrará operativo para analizar diversas muestras de narrativa breve estadounidense de los últimos años. Este análisis nos permitirá delimitar una tendencia del cuento contemporáneo habitualmente tachada de “realismo” que aquí se denominará “Escuela de la Banalidad” en oposición a la tradición estadounidense de novela posmoderna y sus sucesores.
Meningkatkan Kemampuan Berpikir Kritis Siswa Kelas VII Melalui Media Monotangray Produk Ecoenzyme
Authors: Nugroho Ervan
Published: July 2024

Penelitian ini dilatarbelakangi oleh rendahnya kemampuan berpikir kritis siswa kelas VII A Sekolah Menengah Pertama SMART Ekselensia pada materi pencemaran lingkungan. Data awal menunjukkan bahwa terdapat sebelas orang atau enam puluh sembilan persen kesulitan memiliki kemampuan berpikir kritis dengan skor 60.0 dalam pembelajaran. Salah satu upaya untuk mengatasi permasalahan tersebut dengan menggunakan media pembelajaran yang diperkirakan dapat mendorong dan menjembatani kemampuan berpikir kritis. Tujuan penelitian ini adalah meningkatkan kemampuan berpikir kritis dengan menggunakan media pembelajaran monotangray produk ecoenzyme. Penelitian dilakukan melalui tindakan kelas yang terdiri dari dua siklus, masing-masing terdiri dari dua pertemuan. Metode pengumpulan data menggunakan tes, pengamatan dan kuesioner. Instrumen penelitian yang digunakan adalah lembar tes tulis, lembar pengamatan observasi aktivitas belajar siswa, observasi aktivitas mengajar guru. Data tersebut dianalisis secara deskriptif kuantitatif. Hasil penelitian menunjukkan meningkatnya kemampuan berpikir kritis sebesar 18 angka dari 68 pada siklus 1 menjadi 86 pada siklus 2, dengan demikian dapat disimpulkan bahwa pembelajaran dengan media pembelajaran monotangray produk pembuatan ecoenzyme dapat meningkatkan kemampuan berpikir kritis siswa. Berdasarkan hasil penelitian ini disarankan kepada guru IPA lainnya untuk menggunakan media pembelajaran monotangray produk pembuatan ecoenzyme dalam pembelajaran topik pencemaran lingkungan yang disesuaikan dengan kondisi dan karakter kelasnya.
Liberating Learning: Insights into the Merdeka Curriculum Implementation
Authors: Trisna Nina , Arafat Yasir , Furkan Nuril
Published: July 2024

The Merdeka Curriculum is a key component of the Ministry of Education, Culture, Research, and Technology's Merdeka Belajar policy, aimed at enhancing the quality of education in Indonesia. This study investigates the implementation of the Merdeka Curriculum in educational institutions, specifically describing and analyzing its execution, impact on teacher performance, and the factors that either hinder or support its implementation. The research was conducted at SMA Negeri 3 Prabumulih, utilizing a qualitative research approach with data collected through interviews, observations, and document analysis. Data were analyzed using the interactive model analysis technique from Miles and Huberman. The findings revealed that: (1) The implementation of the Merdeka Curriculum has been effectively carried out, transitioning from an independent choice model to a shared independent implementation model; (2) The successful implementation is supported by the roles of the principal, teachers, educational staff, and other stakeholders; (3) The Merdeka Curriculum is applied in grades X and XI, while grade XII continues to follow the 2013 Curriculum due to the transitional period; (4) The implementation process involves the planning of operational curriculum documents, organizing resources, mobilizing learning activities, and monitoring through direction, guidance, and assistance.
The Effectiveness of Fisherman Community Empowerment Programs Through Fisheries Actor Business Cards
Authors: Gazali Gazali , Kurra Sudiarti Dewi , Saguni Dewi Sulfa , Arifai Muhammad , Yus Abd. Rahman
Published: July 2024

This study aims to determine the effectiveness of the Fisherman Community Empowerment Program through Fisheries Actor Business Cards in Landolia Village, Ranteangin District, North Kolaka Regency. This type of research was conducted with qualitative research methods, data collected from primary data and secondary data. Primary data sourced from interviews with informants totaling 11 people and from observations. As for secondary data by collecting data through literature studies and other supporting literature. The data analysis technique used is qualitative data analysis using data collection, data reduction, data presentation, and drawing conclusions put forward by Miles and Hubberman. Based on the results of the study indicate that the effectiveness of the Fisher Community Empowerment Program through the Fisheries Actor Business Card (KUSUKA) Landolia Village, Ranteangin District, North Kolaka Regency through 4 indicators to measure the effectiveness of the program, namely: 1) the accuracy of the program targets, the effectiveness of the Fisherman Community Empowerment Program through the Kusuka Card in the village. Landolia, Ranteangin District, North Kolaka Regency has not been effective because the target accuracy indicator has not been effective because the target achievement is less than all program targets, 2) Program socialization on program socialization indicators in the fishermen community empowerment program through Kusuka is still not effective because of the low interest of the community to participate in socialization. 3) program objectives, with the Kusuka program for fishermen groups in Landolia Village, it is said to be quite effective because it really helps the community in meeting their daily needs. 4) Program Monitoring Based on the explanation above, the authors conducted further searches and saw data on the members of the fishing group who received the assistance provided through the Kusuka program, which is still not considered effective because not all members of the fishermen use the assistance programs properly.
Construcción de una genealogía: el erotismo lésbico en la novela Amora de Rosamaría Roffiel
Authors: Anguiano Treviño Karime Aylen
Published: July 2024

Este trabajo es enmarcado dentro de la crítica literaria feminista y lesbiana, con la intención de mostrar como se desarrolla el erotismo lésbico en la novela Amora de Rosamaría Roffiel, publicada por Editorial Planeta en 1989, así como identificar los recursos literarios que emplean en ella y, principalmente, el por qué se le considera como la primera novela lésbica en México y un punto de partida para la conformación de un canon literario lésbico. Partiendo de la hipótesis de que esto es debido a que propone un discurso de completa libertad femenina, tanto en su narrativa como en sus personajas, alejado del sistema hegemónico imperante masculino que crea y define a la mujer a partir del hombre.
La Poética de Efraín Huerta de los años setenta
Authors: Leyva Ortiz Jesús Alberto
Published: July 2024

Los años setenta en la poética de Efraín Huerta es relevante por dos acontecimientos ligados entre sí: el primero es de carácter biográfico, haber padecido cáncer de laringe y sobrevivido con el coste de la pérdida de la voz. El segundo es de carácter literario, esa década representó la mayor producción literaria del escritor en relación a otras pasadas y futuras, caracterizada por ser su etapa más irónica, lúdica y desinhibida. Este documento sostiene que, tanto los sucesos de salud en el escritor como el cambio de estructura versal fueron factores que influyeron en el cambio del estado anímico reflejado en su poesía.
DEMAND OF ILLUSTRATED PHOTOGRAPHY IN CONTEMPORARY ART
Authors: Rani Mamta
Published: July 2024

Photography is a widely known and celebrated art across the globe that gained even more popularity with the advancement in technology that provided every individual with a camera in their hands. The art of Photography has been used for ages for several purposes such as recording events, taking portraits, sometimes discovering the new world, selling and buying products through advertisement, etc. The advancement in technology has revolutionized the art of clicking pictures into an entirely different skill called ‘Illustrated photography’. This new art has thus transformed ancient photography. Unlike other photographers, professionals here use photos to illustrate any action, story, or any other product in a better form i.e., with some form of visualization that not only makes the product more interesting but also provides customers with a virtual tour of whatever product they are considering for their purchase. Therefore, they are ideally creating a fantastic and more realistic scene that would be impossible to photograph. As a consequence, illustrated photography gained acceptance as it offered all those opportunities that photography couldn’t. As both photography and illustrated photography is a means of visual communication and expression; sharing a common foundation of aesthetics; this study endeavours to understand and study the history, evolution, and characteristics of illustrated photography. Further, it focuses on drawing distinction between photography and illustrated photography along with its emergence. Moreover, the research endeavours to investigate the major illustrators along with the pioneers in the field of illustrated photography with their contributions. The study also attempts to trace the difference in the function of both photographers and illustrators and the contribution of newly skilled illustrators in the field of art and aesthetics.
Business Development Strategy of Lumindai Palm Sugar Home Industry with BMC and SWOT Approach
Authors: Zain Elvita Putri , Azrifirwan  , Permata Deivy Andhika
Published: July 2024

This study aims to analyze and develop a business strategy of the lumindai palm sugar industry in Sawahlunto City, Indonesia by combining BMC and SWOT approaches. To identify the industry, a BMC mapping is initially performed. The results from the BMC serve as inputs for categorizing business development elements. These elements are then divided into four SWOT categories: Strengths, Weaknesses, Opportunities, and Threats. Each factor within these categories is evaluated and assigned a value, followed by an analysis using IFE and EFE. The IFE analysis yields a score of 3.045, indicating strong internal capital for industry development. Conversely, the EFE score of 2.636 suggests that the industry's external conditions are moderate. The IFE and EFE results then serve as a basis for formulating relevant strategies using the IE matrix. According to the IE matrix, the industry falls into cell IV, placing it in the Grow and Build position. This position is used to develop detailed strategic specifications in the SWOT matrix, which provides actionable insights for industry growth.
Karies Mencapai Pulpa Merupakan Faktor Risiko Stunting Pada Anak Prasekolah di Daerah Lokus
Authors: Rahmadi Antun , Purnomowati Ratnasari Dyah , Prasetiowati Lies Elina , Wijaya Sofyan Musyabiq
Published: July 2024

Pendahuluan: Karies gigi dan stunting merupakan masalah yang umum dijumpai pada anak prasekolah. Di Kabupaten Tulang Bawang Barat diperkirakan 84% anak prasekolah mengalami karies gigi dan 32% diantaranya merupakan karies pulpa. Demikian juga stunting yang masih menjadi masalah kesehatan masyarakat karena prevalensinya masih 16,4%.   Tujuan: menilai tingkat keparahan karies gigi dan hubungannya dengan status gizi anak prasekolah di desa lokus. Jenis penelitian ini adalah analitik observasional dengan disain penelitian yang dipilih adalah cross sectional. Populasi adalah semua siswa TK/PAUD usia 3-5 tahun di 3 kecamatan Kabupaten Tulang Bawang Barat. Data dikumpulkan dengan pemeriksaan, pengukuran dan wawancara. Data diolah secara univariat dan bivariat dengan uji statistik Chi square. Hasil: penelitian menunjukkan prevalensi karies sebesar 77,5% dan 25,2% diantaranya adalah karies pulpa. Diketahui juga angka prevalensi stunting sebesar 13,3%. Kesimpulan: ada hubungan yang bermakna secara statistik (p-value = 0,02) antara karies dan stunting.  Anak dengan karies mencapai pulpa berisiko 4,7 kali menjadi stunting dibandingkan dengan yang tidak.
Pengaruh Penyuluhan Menggunakan Flipchart Terhadap Pengetahuan Kehilangan Gigi dan Motivasi Penggunaan Gigi Tiruan pada Pra Lansia
Authors: Lestari Kurnia Dwi , Taadi  , Widayati Aryani
Published: July 2024

Pendahuluan: Masyarakat Indonesia mengalami kehilangan gigi karena dicabut dan tanggal, dan data jenis tindakan yang diterima untuk mengatasi masalah gigi dan mulut menunjukkan bahwa pada rentang usia 45-54 tahun hanya 2,5 % yang telah melakukan pemasangan gigi tiruan. Kecilnya prevalensi penggunaan gigi tiruan salah satunya dipengaruhi oleh kurangnya pengetahuan masyarakat tentang kehilangan gigi dan manfaat penggunaan gigi tiruan. Media flipchart dapat menjadi salah satu alternatif untuk meningkatkan pengetahuan masyarakat karena praktis dalam penggunaannya. Tujuan: Mengetahui manfaat penggunaan flipchart untuk meningkatkan pengetahuan dan motivasi penggunaan gigi tiruan pada pra lansia. Metode: Desain penelitian ini adalah Quasi Experiment dengan menggunakan rancangan Pre test-post test with control. Pengambilan sampel menggunakan teknik purposive sampling dengan jumlah sampel 68 responden, analisis data menggunakan uji Wilcoxon Signed Rank Test dan uji Mann Whitney. Hasil: Hasil uji wilcoxon menunjukkan adanya peningkatan pengetahuan dan motivasi sebelum dan sesudah dilakukannya penyuluhan menggunakan flipchart yaitu pengetahuan kehilangan gigi dari kriteria cukup 50% menjadi 94,1%  kategori baik dan peningkatan motivasi penggunaan gigi tiruan dari kriteria motivasi sedang 47,1% menjadi 88,2% kriteria tinggi (p = 0,000). Hasil uji Mann-Whitney didapatkan skor rata-rata pada kelompok eksperimen lebih besar daripada kelompok kontrol, dengan nilai variabel pengetahuan (p=0,045) dan variabel motivasi (p = 0,008). Kesimpulan: Flipchart meningkatkan pengetahuan kehilangan gigi dan motivasi penggunaan gigi tiruan pada pra lansia.
Cardiotoxic effects of antitumor therapy for colorectal cancer
Authors: Klimkin P. , Shalenkova M. , Ovchinnikova E.
Published: July 2024

Fluoropyrimidines (5-fluorouracil, capecitabine) are the main chemotherapeutic agents in the treatment of gastrointestinal oncologic pathology. However, therapy with these drugs may be associated with the development of cardiotoxic effects. The article discusses risk factors, the main proven mechanisms of cardiotoxic effects development; possible measures of primary and secondary prevention, peculiarities of fluoropyrimidines cardiotoxicity treatment are outlined. Clinical cases are presented that demonstrate the complexity of the pathophysiological mechanisms of development of fluoropyrimidine (capecitabine) cardiotoxicity and the difficulties of its prediction. In this case, drugs with a vasodilating effect can be effectively used as part of secondary prevention.
Analysis of Preservice Teachers' Ability to Develop TPACK Integrated Learning Tools
Authors: Sridana Nyoman , Novitasari Dwi , Magfirah Nurul
Published: July 2024

This study aims to analyze the ability of preservice mathematics teachers at University of Mataram to develop learning tools such as powerpoint presentations and student worksheets integrated with TPACK to foster 21st-century skills. The study was conducted in Micro Teaching courses with 14 students as research subjects. Data collection techniques included assessment sheets and interviews. The results shows that the learning tools created by preservice teachers are quite capable of supporting 21st-century skills. The ability of preservice mathematics teachers to develop TPACK-integrated powerpoint presentations overall has an average score of 2.43, which is categorized as moderate. The ability of preservice mathematics teachers to develop worksheets integrated with TPACK overall has an average score of 3.59, which is categorized as high. Based on interview results, it was found that applying the TPACK approach in learning tools is very important, as it can create engaging, interactive learning and facilitate students' understanding of the material.
Stevia como edulcorante en postres y su efecto sobre la glicemia en pacientes con diabetes mellitus
Authors: Sánchez Cabrera Diana Estefanía , Martínez Villegas Richard Antonio , Orquera Tello Ana Cristina , Padilla Palacios María Fernanda , Maldonado Yépez Rafael Mauricio
Published: July 2024

La diabetes mellitus es una enfermedad metabólica crónica caracterizada por altos niveles de glucosa en la sangre, a menudo llevando a restricciones alimenticias. Por lo tanto, el objetivo se centra en evaluar la variabilidad de los niveles de glucosa antes y después del consumo de postres endulzados con Stevia, además de su aceptación organoléptica. Este estudio adoptó un enfoque mixto y transversal, no experimental. La parte cuantitativa utilizó un glucómetro para medir los niveles de glucosa, mientras que la parte cualitativa empleó una escala hedónica de cinco puntos para evaluar atributos organolépticos como color, aroma, sabor y textura. Se realizó un análisis de varianza (ANOVA), una prueba de normalidad Anderson-Darling (AD) y un método comparativo de medias de Tukey. Obteniendo que los análisis revelaron que no hay una variación significativa en los niveles de glucosa después de consumir tres distintos postres en 55 (21 + 34) participantes. La aceptabilidad organoléptica fue alta, con una puntuación media de 4.6/5. Concluyendo en el uso de Stevia en proporción del 8% en comparación con la sacarosa es viable en productos elaborados, sin afectar significativamente los niveles de glucosa en personas con diabetes.
Tea (Camellia sinensis) leaves accumulate higher levels of Aluminum: Potential Health Risk- Alzheimer’s disease (AD): An updated review of evidence
Authors: Ravindra B. Malabadi  , Sadiya MR  , Kiran P. Kolkar  , Raju K. Chalannavar  , Simuzar S. Mammadova  , Himansu Baijnath  , Antonia Neidilê Ribeiro Munhoz  , Gholamreza Abdi
Published: July 2024

This review paper of literature highlights the role of accumulation of aluminum in tea leaves and its toxic effects on human health. Tea is the most consumed beverage in the world after water and contains heavy metals and trace elements that may cause potential negative effects on health. Tea is known to be a metal accumulator. However, drinking even a very high dietary amount of black tea or green tea would be unlikely to cause these adverse effects in humans. Thus, for the majority of heavy tea drinkers around the world, tea is likely to be the largest single source of aluminum intake. Addition of milk to tea can decrease or completely inhibit tea antioxidant properties. According to the literature survey, it is well known that the tea plant accumulates aluminum in its leaves to a greater extent than most other edible plants, and would be a potentially important source of dietary aluminum. Aluminum can be transferred into tea infusions through brewing tea, then enter the human body via tea drinking, thereby causing potential harm to human health. On the basis of literature survey, even though some epidemiological reports were contradictory, there was mounting scientific evidence suggesting a relationship between the neurotoxicity of aluminum and the pathogenesis of Alzheimer’s disease. In particular, the link between aluminum and Alzheimer’s disease has been the subject of scientific debate for several decades. The literature survey confirmed that aluminum hypothesis has been the subject of much debate and criticism for several decades. Evidence from human clinical trials suggested that moderate (1–6 cups/day) rather than excessive consumption of tea could bring diverse health benefits. The relationship between tea consumption and dementia has not been well established yet and other studies reported no significant association. The cause of Alzheimer's disease and any association with aluminum is still unknown. There have been conflicting findings in the scientific literature.
Dampak Penggunaan Media Berbasis Android terhadap Self-efficacy Ibu dalam Merawat Neonatus
Authors: Sukoco Bekti , Kartika Esa , Yugistyowati Anafrin
Published: July 2024

Latar belakang: Bayi baru lahir (neonatus) sangat rentan terhadap penyakit. Kualitas perawatan yang baik, terutama dari ibu, sangat penting. Salah satu cara meningkatkan kualitas perawatan adalah dengan meningkatkan kepercayaan diri ibu dalam merawat bayinya (self-efficacy). Pendidikan yang tepat, terutama melalui media yang mudah diakses seperti smartphone, dapat membantu meningkatkan kepercayaan diri ibu. Tujuan: untuk mengevaluasi dampak penggunaan media berbasis android terhadap self-efficacy ibu dalam merawat neonatus. Metode: Jenis penelitian ini adalah quasi experiment dengan pendekatan non equivalent control group. Responden berjumlah 62 ibu hamil trimester III yang melakukan ANC di Puskesmas yang dibagi menjadi kelompok eksperimen menggunakan media android (n=31) dan kelompok kontrol menggunakan booklet (n=31). Instrumen yang digunakan untuk pengumpulan data adalah kuesioner Perceived Maternal Parenting Self-efficacy Scale (PMP-SE). Analisis yang digunakan adalah independent samples t-test dan paired t-test. Hasil: penggunaan media berbasis android dapat meningkatkan faktor prosedur perawatan pada self efficacy ibu dalam merawat neonatus (p=0,032) dan ditemukan adanya perbedaan faktor keyakinan situasional di antara kedua kelompok (p=0,002). Kesimpulan: Penggunaan media berbasis android dapat meningkatkan faktor prosedur perawatan pada self-efficacy ibu dalam merawat neonatus, sehingga berpotensi sebagai media edukasi untuk ibu yang berada jauh dari pusat layanan kesehatan agar memperoleh informasi secara rutin.
Implementasi Algoritma Knuth Morris Pratt Dalam Pencocokan String Pada Kamus Indonesia–Korea
Authors: Kurniawan R Rakhmat , Lubis Aidil Halim , Hadisa Siti Ayu
Published: July 2024

Currently, South Korean culture is very popular with many Indonesians, and the rapid development of Korean culture in Indonesia is currently very widespread and very popular. Many Indonesians even learn Korean to keep up with current trends, but due to the different structure of the language, learning Korean becomes more difficult for most people. The dictionary is an effective guide for translating foreign languages/terms. Conceptually, dictionaries are arranged alphabetically, along with explanations of definitions, uses or translations. This is also required for Indonesian to Hangul Korean translation. Many Indonesian-Korean dictionaries are currently published in printed form, but it is still difficult to use because users have to look up the meanings manually. We need practical and effective new media such as smartphone media. There are many algorithmic methods that can be used to create dictionary applications, one of which is using the Knuth Morris Pratt (KMP) algorithm. With this algorithm, every text to be translated is checked for word search and then a match is found with the appropriate word from the desired word. In this study, the final results of the study found differences in the use of the word hangul in formal and informal forms. In this study, the authors tested the application of the algorithm on an Android-based Indonesian-Korean dictionary application.
Penerapan Seleksi Fitur Untuk Klasifikasi Penerima Bantuan Sosial Pangkalan Sesai Menggunakan Metode K-Nearest Neighbor
Authors: Fauzan Muhammad , Gusti Siska Kurnia , Jasril Jasril , Pizaini Pizaini
Published: July 2024

The inability to fulfill basic human needs is how poverty is defined. To address this issue, the indonesian goverment implements various social assistance programs, one of which is Kartu Indonesia Pintar (KIP), aimed at providing free education to children aged 7-18 who are economically disadvantaged. However, in the distribution of aid in the Pangkalan sesai sub-district, distributing officers often face challenges due to the high number of eligible recipients applying, complex data requierements, and limited time for the officers. Distributing this social assistance accurately is crusial. Therefore, this research aims to determine the accuracy value for the data of potential recipients of the Kartu Indonesia Pintar (KIP to enhance the data verification process’s outcomes. To tackle this issue, the research employs the K-Nearest Neighbor (K-NN) algoritm and also employs feature selection using Information Gain to reduce less influential attributes. The data used consists of 1998 records of KIP beneficiaries from the 2023 in excel format, with 33 attributes. After performing data cleaning an Information Gain-based feature selection, the dataset is reduced to 1675 records, with 5 selected attributes. The best classification result in this study is achieved with ratios of 7:3 and 8:2, and a value of k = 5, yielding the highest accuracy of 98,21%. The lowest accuracy is obtained using a ratio of 9:1 with the same k value when not using Information Gain, resulting in an accuracy of 89,82%.
Pemilihan Auditor Internal dalam Mengimplementasikan Pendekatan Metode Multi Attribute Utility Theory (MAUT) dan Menerapkan Pembobotan Rank Order Centroid (ROC)
Authors: Abdullah Mohammad Aldinugroho , Aldisa Rima Tamara
Published: July 2024

The Internal Auditor of a company is a professional responsible for evaluating, overseeing, and providing independent assessments of the effectiveness of internal controls, accounting systems, and business processes of a company. The primary task of the internal auditor is to assist the company's management in ensuring that its operations adhere to applicable standards, policies, and regulations. The presence of an internal auditor helps the company maintain integrity, accountability, and compliance with relevant standards and regulations. They provide an independent view of the company's performance and aid in enhancing operational efficiency and effectiveness. In the complex business world, selecting a candidate for the role of Internal Auditor poses a challenge. Diverse selection criteria, such as auditing skills, industry knowledge, and integrity, often prove difficult to objectively assess. Decision-making based solely on experience can lead to inconsistent outcomes. The importance of accuracy and objectivity in selecting an Internal Auditor demands a scientific approach. The Multi-Attribute Utility Theory (MAUT) analysis method is employed to address the complexity of criteria. Meanwhile, the Rank Order Centroid (ROC) method is used to assign weights to each criterion. By combining MAUT and ROC in a support system, companies have a more structured and measurable way to select potential Internal Auditors. This approach is expected to help overcome issues in candidate selection that often do not align with the company's needs, and to provide more accurate and objective decisions. The ultimate result obtained by applying the MAUT method is a value of 0.794, which is the highest ranking among the 7 selected alternatives. The highest ranking result associated the seventh alternative, named Poppy Rosana.
Penerapan Metode EXPROM II Dalam Menentukan Tempat Wisata Pantai Terbaik
Authors: Mesran Mesran , Triayudi Agung , Nofrisa Dini , Fadillah Rizkah
Published: July 2024

Tourism is an activity or activity carried out by humans in order to find pleasure or provide space for themselves to rest themselves from daily fatigue. The word tourism describes the expression of pleasure for someone who will enjoy a holiday by going somewhere. Many beaches in Indonesia in various regions make people confused in choosing which place to visit while on vacation. To assist visitors in choosing which beaches should be visited, a system is needed. A good system used in this problem is a decision support system. A decision support system is a system that has the same working procedures as a computer system. DSS requires a method. The method used in this study is the EXPORM II method. The EXPORM II method is a modified method of the PROMITHE II method. Where the EXPORM II method is easier than the PROMITHE II method. However, it has the same accurate results as the PROMITHE ll method. The results of this study are that the best alternative is Cemara Kembar Beach as an alternative to A7 with a value of 0.69889 which in the end is suggested to be the best beach resort.
Sistem Pendukung Keputusan Pemilihan Wi-Fi Extender dengan Pendekatan Complex Proportional Assessment dan Rank Reciprocal
Authors: Nugroho Nurhasan , Fatmayati Fryda , Alexander Allan Desi , Tonggiroh Mursalim
Published: July 2024

A Wi-Fi Extender is a device needed to expand the range and improve the quality of the Wi-Fi signal. To determine the choice, decision makers must know one by one the specifications of the existing products. This results in making decisions difficult and requiring a long time. So the aim of this research is to develop a decision support system for choosing a Wi-Fi Extender using the Rank Reciprocal and COPRAS (Complex Proportional Assessment) weighting approach to make it easier to make decisions in a relatively short time. The Rank Reciprocal approach is used to rank or weight the criteria given by decision makers. Meanwhile, the COPRAS approach is used to obtain the best alternative which is evaluated by calculating the effectiveness index directly proportional to the criteria considered to provide benefits and costs. Based on the case study that was carried out, the highest utility result was obtained, namely the Mercusys MW300RE (A4) which obtained a score of 100. The output produced by the decision support system in the case study that was carried out obtained the same score as manual calculations. Apart from that, the usability testing results obtained an average value of 88.75%. This shows that the system is declared suitable for use because it is in accordance with its function and use.
Sistem Pendukung Keputusan Penerimaan Dosen Tetap Menggunakan Metode MOORA dan MOSRA
Authors: Mesran Mesran , Aldisa Rima Tamara , Rangkuti Wanda Tofani Devi , Sari Cindy Nanda
Published: July 2024

Lecturers are the forerunners and places to gain knowledge for the nation's children, good lecturers will produce good students too, and good students will become successors to the progress of the nation to be even better, the large number of lecturers at Budi Darma University results in a density of lecturers, it is important to do acceptance of permanent lecturers to provide rewards to lecturers who have worked diligently and earnestly, each lecturer has their own quality but permanent lecturers are lecturers who have a safer position and are trusted by the campus, the importance of selecting permanent lecturers using a system decision support to prevent fraud in the election process. In this study, the MOORA (Multi-Objective Optimization on the Basis Of Ratio Analysis) and MOOSRA (Multi-objective Optimization on the basis of Simple Ratio Analysis) methods are used to assist the selection process in a logical, systemic manner and can produce a decision value on the ranking value. which are different from each formula or algorithm, but these values are equally real and fair without any cheating. In this study the authors also used the ROC (Rank Order Centroid) value to obtain an effective and correct weighting value to perform calculations on the criteria values that had been set by the campus or college of the Budi Darma Medan University. The results in this study based on the calculation of the MOORA method, the highest result was achieved by A1, which is worth 0.4742 and in the MOOSRA method, the highest alternative result was achieved by A1, which is worth 28.1366.
Penerapan Data Mining Untuk Clustering Kualitas Udara
Authors: Rifqi Ahmad , Aldisa Rima Tamara
Published: July 2024

Human health at this time is the key to the continuity of life. Human health is very necessary in the process of development of human life. Environmental health is related to the circumstances or conditions that exist in the surrounding area where you live, whether in a small environment or a large environment. Air quality is the condition of the surrounding air. Air quality is very important for human life because air is what helps humans to live by breathing. With the availability of good air quality, it will certainly be an important factor for an area, not only for health but also for other sectors that interact directly in open areas. The important role of air quality for humans means that more attention needs to be paid and special treatment is given to areas exposed to bad air. The above is a very important problem that must be resolved immediately, if the problem is not resolved immediately it will have an impact on health. The process of solving problems requires a way to resolve them. Where the process of measuring air quality can be seen based on certain conditions or criteria that occur in an area. Data mining is a method used to carry out the problem solving process by processing data. In the process carried out in data mining, there are various ways of solving it. One thing that can be used is clustering. In clustering itself there are various kinds of algorithms such as DBSCAN, K-Means and K-Medoids. In this research, the solution process will use the three algorithms K-Means, K-Medoids and DBSCAN. The purpose of using these three algorithms is to compare the results obtained. In the process carried out in completing data mining, clustering techniques are used using 3 (three) algorithms, namely K-Means, K-Medoids and DBSCAN. The results obtained were that the K-Means algorithm had the highest accuracy value obtained at K=4 with a value of 0.843, for the K-Medoids algorithm the highest value was obtained at K=5 with a value of 0.896 and for the DBSCAN algorithm the highest value was obtained at K=2 with a value of 0.885.
Klasifikasi Sinyal EEG Untuk Mengenali Jenis Emosi Menggunakan Deep Learning
Authors: Rosemari Pita , Rini Dian Palupi , Sari Winda Kurnia
Published: July 2024

This research focuses on in-depth exploration and analysis of the application of three types of deep learning, namely Convolutional Neural Networks (CNN), Bidirectional LSTM (BI-LSTM) and Deep Neural Network (DNN). The three models are trained with the same parameters, consisting of three layers, using the Relu activation function, and applying 1 dropout level. In order to compare the performance of the three, experiments were carried out using three dataset groups for training and evaluation of performance. The evaluation includes metrics such as accuracy, recall, F1-Score, and areas under the curve (AUC). The dataset used is EEG Emotion which consists of 2458 unique variables. In terms of performance, BI-LSTM succeeded in outperformed the performance of CNN and DNN in the task of classification of emotional data based on EEG signals. On the other hand, CNN and DNN show excess in the acceleration of the training process compared to BI-LSTM. Although the accuracy of the two methods is almost similar in all data distribution, but in the evaluation of the ROC curve, the BI-LSTM model demonstrates superior with a more optimal curve than CNN and DNN.
Implementasi Data Mining Dalam Memprediksi Penjualan Parfum Terlaris Menggunakan Metode K-Nearest Neighbor
Authors: Sabda Mhd Angga , Suhardi Suhardi
Published: July 2024

Ahlinyaparfum is a perfume shop that provides various kinds of fragrance oils. To run his business, Ahlinyaparfum must send perfume variants to his shop from the place where the perfume is made, which requires shipping costs. Often, the perfume variants offered by Ahlinyaparfum do not match the wishes of customers, which has a negative impact on the number of store sales. The best-selling prediction process is needed based on previous sales data to help stores know which perfumes are most popular with customers and the level of best-selling in the future. By applying data mining using the K-Nearest Neighbor method, this research aims to overcome this problem. This method was tested using perfume sales data from January to June 2023 with a total of 215 data. To test and ensure its performance with the help of the Jupyter Notebook application with Python. The process of predicting perfume sales for the next month uses the parameter k = 3 with Euclidean distance calculations. The best-selling result predicted for the 7th month is Aigner Blue Emotion with total sales of 153 ml. Based on the evaluation algorithm, the overall average value of MSE is 0.52, which shows that the results are very good in determining next month's perfume sales. This is due to the fact that the calculation results are closer to the actual value the lower the MSE value.
Penerapan Algoritma Naïve Bayes Terhadap Klasifikasi Penerima Bantuan Program Keluarga Harapan (PKH)
Authors: Irsyada Amelia , Haerani Elin , Irsyad Muhammad , Wulandari Fitri , Afriyanti Liza
Published: July 2024

Poverty in Indonesia is one of the complex social issues. As a manifestation of the government's concern about poverty in the country, various assistance programs have been established to target the impoverished population. One such program aimed at alleviating poverty in Indonesia is the Family Hope Program (Program Keluarga Harapan or PKH). PKH is a conditional cash transfer program provided to the impoverished community. The manual selection process for aid recipients is considered less than ideal, leading to issues of improper distribution. In this study, the Naïve Bayes algorithm is applied to classify PKH aid recipients in the Bungaraya Subdistrict, Siak Regency, as part of the government's efforts to tackle poverty. The dataset used consists of 560 records, including data on existing PKH aid recipients and potential recipients from various villages in the Bungaraya Subdistrict for the year 2022. The attributes considered in this research include age, income, number of dependents, dependents attending school, dependents with disabilities, housing status, floor type, and wall type. The highest accuracy obtained through calculations on Google Colab is 99% for an 80:20 ratio, while the accuracy obtained using RapidMiner is 94%.
Pengelompokan Hasil Survei MBKM Menggunakan K-Mean dan K-Medoids Clustering
Authors: Mayadi Mayadi , Setiawati Siti , Priatna Wowon
Published: July 2024

In order to categorize data from the findings of the MBKM survey using machine learning, the goal of this research is to determine how well the implementation of MBKM has been comprehended by Education staff, lecturers, and students at the university level. Artificial intelligence, which is frequently employed to address a variety of issues, includes machine learning. K-Mean and K-Medoids clustering algorithm models were used to group the data for suggestions on how to apply MBKM at Bhayangkara Jakarta Raya University. This study uses databases and machine learning approaches to categorize MBKM survey data at the level of the relevant study program. In order to examine the machine in accordance with the learning algorithm, the K-Mean and K-Medoids clustering algorithms will be utilized. This research will train a machine or system using filtered data that can predict the outcomes of the MBKM survey, which was constructed using machine learning. The study's findings come from the application of MBKM into two groups, with cluster 1 showing a high degree of comprehension and cluster 2 showing a low level of understanding, as produced by K-Mean. In the meantime, K-Medoids created cluster 2 for high comprehension of MBKM and cluster 1 for low understanding of MBKM implementation. The results of the comparison evaluation of clustering between K-Mean and K-Medoids obtained cluster evaluation values using the Davies Bouldin Index by conducting trials starting from K=2, K=3, K=4 and K=5 showing lower K-Mean values compared to K-Medoids, so that K-Mean is recommended as a clustering algorithm for grouping the results of the MBKM survey implementation in Higher Education.
Perbandingan Metode Klasifikasi Untuk Deteksi Stress Pada Mahasiswa di Perguruan Tinggi
Authors: Wibowo Merlinda , Djafar Muh. Rizieq Fazlulrahman
Published: July 2024

The outbreak of the COVID-19 pandemic is increasingly affecting the high level of stress in humans. Stress due to this pandemic has also occurred, especially for students. This stress is caused by students spending too much time studying online. Using student data can act as a tool to identify student stress by processing it through various machine-learning methods. This method can extract information and find patterns and information from the data. Classification techniques are used as data groupings based on mapping data into sample data. This study used several classification methods: Naïve Bayes, Decision Tree, Support Vector Machine (SVM), Neural Network, Random Tree, Random Forest, and K Nearest Neighbor (KNN). These methods were successfully compared to determine which is the best for detecting stress precisely and accurately based on the classification performance results of each method. Random Tree and Decision tree were chosen as the best methods for the results of this performance comparison with an 80:20 split reaching up to 100%.
Implementasi Metode Convolutional Neural Network untuk Klasifikasi Breast Cancer pada Citra Histopatologi
Authors: Amrustian Muhammad Afrizal , Wibowo Merlinda
Published: July 2024

Breast cancer is a tumor that manifests as an abnormal lump in the breast of a woman. The occurrence of breast cancer in women can be triggered by genetic and lifestyle factors. According to Global Cancer Statistics, 600,000 out of 2.3 million occurrences of breast cancer result in death. The death rate from breast cancer in Indonesia is likewise relatively high, reaching 17% for every 100,000 female inhabitants. Using histological pictures to diagnose breast cancer is one technique. The patient will capture an image of her breast cells, which will be examined and diagnosed by medical personnel. Even if histopathological scans are utilized as a baseline for the detection of breast cancer, the death rate associated with this disease remains rather high. One of the causes for the high mortality rate associated with breast cancer is the late detection of the disease, which results in patients being treated when the disease is in a severe state, and sometimes a misdiagnosis. The authors propose creating a breast cancer classification model utilizing the convolutional neural network (CNN) method in order to address the described issues. The study's findings indicate that CNN can classify breast cancer patients with an accuracy of 85 percent. Moreover, by calculating the loss function, the constructed model prevents overfitting.
Penerapan Data Mining untuk Klasifikasi Hasil Panen Jamur Tiram Menggunakan Algoritma K-Nearest Neighbor
Authors: Mandala Eka Praja Wiyata , Putri Dewi Eka , Permana Randy
Published: July 2024

Oyster mushroom is a type of mushroom that can be consumed by humans. Lots of food products are made from processed oyster mushrooms. This makes mushroom farmers intensively cultivate oyster mushrooms because they see good economic prospects. However, not all mushroom cultivation processes can be successful so it will have an impact on the yield of the oyster mushrooms. So it is necessary to classify so that it is easier for mushroom farmers to determine the amount of yield from the oyster mushroom. The classification was carried out because of the difficulty of mushroom farmers in determining the amount of harvest by looking at the width of the mushroom caps, the number of mushroom caps to the mushroom harvest time. This study proposes a data mining technique to classify oyster mushroom yields using the K-Nearest Neighbors algorithm so that it can help mushroom farmers in determining the yield of oyster mushrooms being cultivated. This study used a dataset of 42 mushrooms as training data and 1 mushroom data to determine the classification of the crops. From the results of testing on 1 mushroom with a cap width of 8 cm, the number of caps is 14 pieces and the harvest time is 49 days, the results of classification results obtained from this mushroom are Less with a Mean absolute error of 0.1419, Root mean squared error of 0.2111, Relative absolute error of 36.2177% and Root relative squared error of 48.002%. The results of this research can help mushroom farmers in classifying oyster mushroom yields.
Comparison of IndoBERTweet and Support Vector Machine on Sentiment Analysis of Racing Circuit Construction in Indonesia
Authors: Lee Hanvito Michael , Sibaroni Yuliant
Published: July 2024

The construction of the circuit is one of the policies made by the Indonesian government to advance the tourism sector and improve the national economy. This policy triggers various opinions given by the public, primarily through social media Twitter, both in the form of positive and negative opinions. This study compares machine learning and deep learning algorithms, Support Vector Machine and IndoBERTweet, that will be used as a model to predict the sentiment of racing circuit construction tweets. These models are built with K-Fold cross-validation to obtain the overall model’s performance for the entire dataset. Based on the experiments that have been carried out, it shows that IndoBERTweet performs better than the Support Vector Machine, with an overall accuracy score of 86%, a precision score of 88.2%, a recall score of 88.6%, and an f1-score of 88.4% for the entire dataset. Meanwhile, the Support Vector Machine model only achieves 82% for the accuracy score, 87.3% for the precision score, 84.3% for the recall score, and 85.8% for the f1-score. In addition, the best accuracy value from each iteration for IndoBERTweet is 94%, and the Support Vector Machine is 93%.