Jurnal Ilmiah Universitas Islam Balitar
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English Vocabulary Mastery Among Special Needs Students and Its Application in Lerning
No full textAbstract: This qualitative study explores the challenges and strategies associated with English vocabulary mastery among special needs students at SLB Mulatsarira Baturetno Wonogiri, a special education school in Indonesia. Focusing on students with diverse learning disabilities, including intellectual, physical, and sensory impairments, the research investigates how their vocabulary acquisition and application in both educational and daily contexts are influenced by teaching methodologies and environmental factors. Through in-depth interviews with educators, observations of classroom practices, and analysis of student interactions, the study identifies barriers such as cognitive limitations, motivation gaps, and limited contextual relevance of vocabulary. It also highlights effective pedagogical approaches, including multisensory instruction, visual aids, and personalized learning plans, which enhance retention and practical usage. Findings underscore the critical role of tailored instructional strategies and inclusive environments in fostering linguistic confidence and functional communication skills. The study concludes with recommendations for educators and policymakers to prioritize adaptive teaching frameworks and collaborative efforts between schools and communities to support the holistic development of special needs students. This research contributes to the understanding of inclusive education practices, emphasizing the need for context-specific interventions to bridge the gap between classroom learning and real-world application.
Venturimeter Booster Design In Irrigation Fertigation System Drops
No full textThe use of a venturimeter in a drip irrigation fertigation system is very helpful in the plant cultivation process. Apart from being effective and more efficient, providing nutrients to plants directly mixed with water media will facilitate the absorption of these nutrients. Fertilization in drip irrigation systems has obstacles, namely frequent clogging or crusting in the emitter, this is caused by the chemical solution flowing through a series of pipes that are not completely finished. Chemical nutrient solutions that are not smooth can cause the emitter to become easily clogged. The use of a venturimeter in the fertigation system or fertilization in the drip irrigation system is expected to help the homogeneity of the solution and the distribution of nutrients that are complete and not left in the hose, thereby reducing the risk of clogging the chemical solution in the emitter. The use of an appropriate venturimeter will facilitate the maintenance of the drip irrigation system series so that fertigation runs smoothly and precisely according to plant needs. The tools used in this study include grinders, hand drills, nipples, 1 inch HDPE hoses, 5 mm HDPE hoses, emitters, drip sticks, sandpaper, meters, manometers, 1 inch filters, 1 inch venturimers, scissors, measuring cups, drill bits, nails, 10 bar pressure gauges , flow controllers , sandpaper, manual saws, water pumps, NPK sensors. The materials used in this study were 1 inch PVC pipe, T pipe connector, L pipe connector, nutrient solution container, polyethylene (PE) plastic hose, pipe glue, stop valve, wooden batten, wooden rafters, PVC glue, red chili seeds, mulch, NPK, KNO3, SP36, manure, humic acid, trichoderma. The results showed that the average ventrumeter discharge was largest at valve opening 4 with an average of 695 ml / minute. The average venturimeter pressure was largest at valve opening 4 of 1.7 bar. The highest average output solubility level was obtained at valve opening 4 with a value of 590ppm. The larger the valve opening, the greater the discharge and nutrient solubility level.
LEVERAGE RISK ANALYSIS ON FINANCIAL PERFORMANCE PT. ANGKASA PURA I (Persero) and PT. ANGKASA PURA II (Persero)
No full textThe COVID-19 pandemic has significantly impacted financial stability across industries, including the aviation sector. PT Angkasa Pura I (Persero) and PT Angkasa Pura II (Persero) have faced increased debt levels, necessitating an analysis of leverage risk in their financial performance. This study aims to assess the companies\u27 leverage conditions and identify potential risk mitigation strategies using Debt to Asset Ratio (DAR) and Debt to Equity Ratio (DER) as analytical tools. A qualitative descriptive approach is employed, utilizing secondary data from 2017 to 2020. The analysis focuses on examining financial reports and relevant literature to understand the extent of leverage risk and its implications. The findings indicate that both companies exhibit high debt levels, placing them in an unhealthy financial state. This condition could lead to financial distress, limiting operational flexibility and increasing vulnerability to external economic shocks. Furthermore, the results suggest that excessive leverage poses significant risks, making it difficult for the companies to secure further funding from creditors or attract potential investors. To mitigate this issue, it is recommended that PT Angkasa Pura I and PT Angkasa Pura II explore alternative financial sources, such as increased equity financing through shareholders and investors or issuing new shares. Additionally, restructuring existing debt and optimizing cost management strategies could help improve financial resilience. This study highlights the critical need for effective debt management strategies to enhance financial sustainability and investor confidence. The insights from this research contribute to the broader understanding of leverage risk management in the aviation sector, especially in times of economic downturns and global crises
Web pembelajaran untuk meningkatkan pemahaman kalimat keterangan lampau bahasa Jepang
No full textJapanese, or Nihongo (日本語), is the primary language of Japan, spoken by more than 125 million people globally. It belongs to the Japonic language family and features a distinct writing system composed of Kanji, Hiragana, and Katakana. Kanji, derived from Chinese characters, while Hiragana and Katakana (referred to as Kana) are phonetic alphabets with 46 basic characters. Hiragana is used for native words and grammar, while Katakana is utilized for foreign words and emphasis. Japanese grammar follows a Subject-Object-Verb (SOV) structure, with social hierarchy reflected through the use of keigo, as well as past adverbial sentences and verb conjugations marked by formality. The global fascination with Japanese culture, including anime and manga, has sparked increased interest in the language. To facilitate learning, the author created a web-based learning platform using the Waterfall methodology, incorporating system engineering, requirement analysis, design, coding, testing, and maintenance phases. The platform is aimed at enhancing learners\u27 understanding of past tense adverbial sentences, with pilot tests indicating considerable improvements in users\u27 Japanese language abilities. Besides offering interactive content, the system also provides a well-organized and user-friendly learning experience. This study aims to positively impact Japanese language education and encourage broader adoption of educational technology, ultimately assisting learners in achieving higher Japanese proficiency in the digital ageBahasa Jepang, atau Nihongo (日本語), merupakan bahasa resmi Jepang yang digunakan oleh lebih dari 128 juta orang di seluruh dunia. Sebagai bagian dari keluarga bahasa Japonik, bahasa ini memiliki sistem penulisan yang khas, yang meliputi Kanji, Hiragana, dan Katakana. Kanji berasal dari bahasa Tiongkok, sementara Hiragana dan Katakana (dikenal sebagai Kana) adalah alfabet fonetik yang terdiri dari 46 karakter dasar; Hiragana digunakan untuk kata-kata asli Jepang dan elemen tata bahasa, sedangkan Katakana digunakan untuk kata asing dan penekanan. Struktur tata bahasa Jepang berbeda dengan bahasa Barat, mengikuti pola Subjek–Objek–Kata Kerja (SOV), dengan penggunaan keigo yang mencerminkan tingkatan sosial, serta kalimat keterangan lampau yang ditandai oleh partikel dan konjugasi kata kerja yang bergantung pada tingkat formalitas. Popularitas budaya Jepang, seperti anime dan manga, telah meningkatkan minat global terhadap bahasa ini. Untuk mendukung pembelajaran, penulis mengembangkan sistem pembelajaran berbasis web dengan metode Waterfall, yang meliputi tahapan System Engineering, Requirement Analysis, Design, Coding, Testing, dan Maintenance. Sistem ini bertujuan untuk memperdalam pemahaman pelajar mengenai kalimat keterangan lampau, dan hasil uji coba menunjukkan bahwa pengguna mengalami peningkatan signifikan dalam kemampuan berbahasa Jepang setelah menggunakan sistem ini. Selain menyediakan materi interaktif, sistem ini juga menawarkan pengalaman belajar yang terstruktur dan mudah diakses. Penelitian ini diharapkan dapat memberikan kontribusi positif terhadap metode pembelajaran bahasa Jepang dan mendukung penerapan teknologi pendidikan secara lebih luas, sehingga membantu pelajar dalam mencapai kompetensi bahasa Jepang yang lebih baik di era digital
APPLICATION OF NAÏVE BAYES ALGORITHM USING FORWARD SELECTION FEATURES IN DIABETES
No full textDiabetes merupakan salah satu penyakit kronis yang prevalensinya terus meningkat secara global, dan memerlukan diagnosis yang cepat dan akurat untuk mencegah komplikasi lebih lanjut. Dalam upaya meningkatkan akurasi diagnosis, penelitian ini menerapkan metode forward selection dengan algoritma Naive Bayes untuk klasifikasi data diabetes, Fitur forward selection digunakan dalam pemilihan fitur untuk menyaring atribut-atribut yang relevan sehingga dapat meningkatkan performa model. Teknik Analisis dari penelitian ini berdasarkan KDD yang diawali dengan pengumpulan data dari sumber dataset terbuka yang berisi informasi medis pasien diabetes. Data kemudian diolah dengan preprocessing yang meliputi penanganan missing value dan set role . Langkah selanjutnya adalah penerapan fitur forward selection untuk memilih fitur yang paling berpengaruh terhadap prediksi diabetes. Algoritma Naive Bayes kemudian diaplikasikan pada subset fitur yang terpilih. Performa model diukur menggunakan metrik akurasi, precision, dan recall. Hasil penelitian menunjukkan bahwa penggunaan fitur forward selection berhasil meningkatkan akurasi model Naive Bayes secara signifikan dibandingkan dengan model yang menggunakan seluruh fitur tanpa seleksi. Pada model yang diterapkan dengan seleksi fitur, akurasi yang diperoleh mencapai 75.01% , precision 76.10% , dan recall 90.00% , sementara model tanpa seleksi fitur hanya mencapai akurasi 67.32% , precision 63.84 % , dan recall 64.27% . Kesimpulan dari penelitian ini adalah bahwa fitur forward selection pada algoritma Naive Bayes mampu meningkatkan akurasi dalam diagnosis penyakit diabetes, serta dapat mengurangi kompleksitas komputasi dengan menggunakan fitur yang lebih sediki
BINARY CLASSIFICATION USING SINGLE LAYER PERCEPTRON ON COMPUTER LAB ASSISTANT APPLICANT QUESTIONNAIRE DATA
No full textStudents\u27 interest in becoming computer lab assistants needs to be analyzed to understand the factors that influence it. This research uses a Single Layer Perceptron (SLP) Neural Network to perform binary classification on the questionnaire data of lab assistant applicants collected through Google Forms. The SLP model was trained with initial weights and biases of zero, a learning rate of 0.1, and a threshold of 0.5. The results show that within two epochs, the model was able to recognize patterns with an accuracy of 75%. This model has a precision of 100%, but a recall of only 50%, resulting in an F1 Score of 67%. These findings indicate that SLP can process questionnaire data well and has the potential to be applied to larger datasets to improve model performance. Minat mahasiswa untuk menjadi asisten laboratorium komputer perlu dianalisis guna memahami faktor yang memengaruhinya. Penelitian ini menggunakan Jaringan Saraf Tiruan Single Layer Perceptron (SLP) untuk melakukan klasifikasi biner terhadap data kuesioner pelamar asisten lab yang dikumpulkan melalui Google Forms. Model SLP dilatih dengan bobot dan bias awal nol, laju pembelajaran 0,1, serta ambang batas 0,5. Hasil menunjukkan bahwa dalam dua epoch, model mampu mengenali pola dengan akurasi 75%. Model ini memiliki presisi 100%, namun recall hanya 50%, menghasilkan F1 Score sebesar 67%. Temuan ini menunjukkan bahwa SLP dapat mengolah data kuesioner dengan baik dan memiliki potensi untuk diterapkan pada dataset yang lebih besar guna meningkatkan kinerja model. 
The Correlation Between Listening to Dangdut Music and the Work Enthusiasm of Chili-Picking Laborers in Pojok Village, Ponggok District, Blitar Regency
No full textThis study aims to analyze the relationship between listening to dangdut music and the work enthusiasm of chili-picking laborers in Pojok Village, Ponggok District, Blitar Regency. The method used is quantitative with a correlational research design. The research population includes all chili-picking laborers in the village, and a random sample of 30 individuals was selected. Hypothesis testing was conducted using the product moment correlation test. The results show a positive relationship between listening to dangdut music and workers’ enthusiasm, with a correlation coefficient of r = 0.561, which is greater than the critical value of r table = 0.3061 at a 5% significance level. Given that the significance level of 0.000 is below the threshold of 0.05, the null hypothesis (H₀) is consequently rejected, and the alternative hypothesis (H₁) is accepted. This indicates that dangdut music influences the work enthusiasm of chili-picking laborers
ANALISIS ALGORITMA KNN DAN PENERAPAN SMOTE DALAM DETEKSI DINI KANKER PARUPARU
Get PDFLung cancer is one of the deadliest diseases and a major global health issue. Early detection is crucial to improving survival rates; however, challenges remain in prediction accuracy due to class imbalance in medical datasets. This study aims to analyze the implementation of the K-Nearest Neighbors (KNN) algorithm combined with the Synthetic Minority Oversampling Technique (SMOTE) for early detection of lung cancer. The dataset used was obtained from Kaggle.com and consists of 1000 patient records with 26 clinical and demographic features. The research process followed the CRISP-DM methodology, which includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment stages. In the modeling phase, the KNN algorithm was implemented with k=3 after applying SMOTE to balance the class distribution. Evaluation results showed excellent model performance with an accuracy of 99.50%, and precision, recall, and F1-score values that were nearly perfect. Therefore, the combination of the KNN algorithm and SMOTE has proven to be effective in enhancing the predictive capability for lung cancer severity levels, indicating its potential to be developed into a medical decision support system in the future.Kanker paru-paru merupakan salah satu penyakit paling mematikan dan masalah kesehatan global yang utama. Deteksi dini sangat penting untuk meningkatkan tingkat kelangsungan hidup; namun, tantangan tetap ada dalam akurasi prediksi karena ketidakseimbangan kelas dalam kumpulan data medis. Penelitian ini bertujuan untuk menganalisis implementasi algoritma K-Nearest Neighbors (KNN) yang dikombinasikan dengan Synthetic Minority Oversampling Technique (SMOTE) untuk deteksi dini kanker paru-paru. Kumpulan data yang digunakan diperoleh dari Kaggle.com dan terdiri dari 1000 catatan pasien dengan 26 fitur klinis dan demografis. Proses penelitian mengikuti metodologi CRISP-DM, yang meliputi pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi, dan tahap penyebaran. Pada fase pemodelan, algoritma KNN diimplementasikan dengan k=3 setelah menerapkan SMOTE untuk menyeimbangkan distribusi kelas. Hasil evaluasi menunjukkan kinerja model yang sangat baik dengan akurasi 99,50%, dan nilai presisi, recall, dan F1-score yang hampir sempurna. Oleh karena itu, kombinasi algoritma KNN dan SMOTE terbukti efektif dalam meningkatkan kemampuan prediktif tingkat keparahan kanker paru-paru, yang menunjukkan potensinya untuk dikembangkan menjadi sistem pendukung keputusan medis di masa mendatang
Gaya Penulisan Naskah Konten Video Hiburan Dalam Meningkatkan Engagement Instagram PT Lopokopi Digital Shankara
Get PDFInstagram has become a major platform in digital marketing strategies based on audiovisual content. This study aims to analyze the writing style of entertainment video content scripts used by PT Lopokopi Digital Shankara in increasing engagement on Instagram. The approach used is descriptive qualitative through observation, interviews, and document studies. This study uses Aristotle\u27s Three-Act Structure theory to analyze the alignment of writing style with storytelling patterns. The results of the study show that Lopokopi\u27s entertainment content script writing style consists of elements of a relaxed and humorous tone, slang and non-standard language diction, short sentence structure and storytelling, hyperbole, and is consistent with a narrative format in the form of hooks, storylines, and punchlines, and is supported by visual elements. This strategy is effective in building emotional engagement with the audience, especially young workers Gen Z and millennials, and increasing Lopokopi\u27s Instagram engagement rate.Instagram telah menjadi platform utama dalam strategi pemasaran digital berbasis konten audiovisual. Penelitian ini bertujuan untuk menganalisis gaya penulisan naskah konten video hiburan yang digunakan oleh PT Lopokopi Digital Shankara dalam meningkatkan engagement di Instagram. Pendekatan yang digunakan adalah kualitatif deskriptif melalui observasi, wawancara, dan studi dokumen. Penelitian ini menggunakan teori Struktur Tiga Babak Aristoteles untuk menganalisis keselarasan gaya penulisan dengan pola storytelling. Hasil penelitian menunjukkan bahwa gaya penulisan naskah konten hiburan Lopokopi terdiri dari unsur tone santai dan humoris, diksi bahasa gaul dan tidak baku, struktur kalimat pendek dan storytelling, majas hiperbola, dan konsisten dengan format naratif berupa hook, alur cerita, dan punchline, serta didukung elemen visual. Strategi ini efektif membangun keterlibatan emosional dengan audiens, terutama pekerja muda Gen Z dan milenial, serta meningkatkan engagement rate Instagram Lopokopi
Strategi Perencanaan Konten dalam Manajemen Media Sosial Instagram Klien @bikinwebsite.co di PT Lopokopi Digital Shankara
Get PDFThis research analyzes the content planning strategy implemented by PT Lopokopi Digital Shankara for client @bikinwebsite.co, in increasing brand awareness through Instagram social media. The purpose of this research is to find out the process of preparing content planning and the right strategy to use. This research uses a descriptive qualitative approach with data collection techniques through interviews with the CEO, Growth Specialist, and Head of Social Media of PT Lopokopi Digital Shankara, with Media Production Management Theory with the POAC approach (Planning, Organizing, Actuating, Controlling). The results showed that content planning is based on client needs, target audiences, and social media trends by prioritizing educational and interactive content. The strategy implemented is proven to increase engagement and strengthen the brand identity of @bikinwebsite.co. This research contributes to the understanding of content management in the context of digital agencies and the importance of a structured communication strategy.Penelitian ini menganalisis strategi perencanaan konten yang diterapkan oleh PT Lopokopi Digital Shankara untuk klien @bikinwebsite.co, dalam meningkatkan brand awareness melalui media sosial Instagram. Tujuan dari penelitian ini adalah untuk mengetahui proses penyusunan perencanaan konten serta strategi yang tepat digunakan. Penelitian ini menggunakan pendekatan deskriptif kualitatif dengan teknik pengumpulan data melalui wawancara kepada CEO, Growth Specialist, dan Head of Social Media PT Lopokopi Digital Shankara, dengan Teori Manajemen Produksi Media dengan pendekatan POAC (Planning, Organizing, Actuating, Controlling). Hasil penelitian menunjukkan bahwa perencanaan konten disusun berdasarkan kebutuhan klien, target audiens, dan tren media sosial dengan mengedepankan konten edukatif dan interaktif. Strategi yang diterapkan terbukti meningkatkan engagement dan memperkuat identitas merek @bikinwebsite.co. Penelitian ini memberikan kontribusi terhadap pemahaman tentang manajemen konten dalam konteks agensi digital dan pentingnya strategi komunikasi yang terstruktur