Perbandingan SVM dan IndoBERT untuk Deteksi Intent Chatbot Lembur dalam Bahasa Indonesia

Digital transformation in higher education requires the development of intelligent and adaptive information systems, including services such as overtime submission for university staff. Chatbots offer a promising solution to enhance user interaction with the E-LEMBUR system. However, developing chatbots in academic settings poses challenges, including limited training data, complex overtime policies, and diverse institutional terminology. This study compares two intent classification approaches: Support Vector Machine (SVM), a traditional machine learning method, and IndoBERT, a transformer-based model designed for the Indonesian language. The dataset comprises 250 real user queries from the overtime system at Institut Teknologi Sepuluh Nopember (ITS). Experimental results show IndoBERT achieves 87% accuracy, slightly outperforming SVM at 85%. While IndoBERT offers better accuracy, it demands higher computational resources, presenting a trade-off between performance and efficiency. This study contributes by validating IndoBERT’s effectiveness on a limited dataset, establishing an initial benchmark for intent classification in overtime chatbots, and offering implementation recommendations aligned with university IT infrastructure. These findings lay the groundwork for developing context-aware information systems for staff services in Indonesian higher education.Transformasi digital di pendidikan tinggi menuntut pengembangan sistem informasi yang cerdas dan adaptif, termasuk layanan seperti pengajuan lembur bagi tenaga kependidikan. Chatbot menawarkan solusi yang menjanjikan untuk meningkatkan interaksi pengguna dengan sistem E-LEMBUR. Namun, pengembangan chatbot dalam lingkungan akademik menghadapi tantangan, seperti keterbatasan data pelatihan, kompleksitas kebijakan lembur, dan keragaman terminologi institusional. Studi ini membandingkan dua pendekatan klasifikasi intent: Support Vector Machine (SVM), metode pembelajaran mesin tradisional, dan IndoBERT, model berbasis transformer yang dirancang khusus untuk bahasa Indonesia. Dataset terdiri dari 250 pertanyaan nyata dari pengguna sistem lembur di Institut Teknologi Sepuluh Nopember (ITS). Hasil eksperimen menunjukkan bahwa IndoBERT mencapai akurasi 87%, sedikit lebih tinggi dibandingkan SVM yang mencapai 85%. Meskipun IndoBERT menawarkan akurasi yang lebih baik, model ini membutuhkan sumber daya komputasi yang lebih besar, sehingga menimbulkan trade-off antara kinerja dan efisiensi. Studi ini berkontribusi dengan memvalidasi efektivitas IndoBERT pada dataset terbatas, menetapkan tolok ukur awal untuk klasifikasi intent pada chatbot lembur, serta memberikan rekomendasi implementasi yang selaras dengan infrastruktur TI kampus. Temuan ini menjadi dasar untuk pengembangan sistem informasi kontekstual bagi layanan staf di lingkungan pendidikan tinggi Indonesia

The Impact of Using the Pregnancy and Baby Tracker Application on Anxiety Among Pregnant Mothers

In today's digital era, information technology has great potential to help reduce anxiety in pregnant women by providing accurate and easily accessible information. One of the innovations that has been developed is a mobile application specifically designed to support the health of pregnant women and babies. The purpose of this study was to analyze the effect of using the pregnancy and baby tracer application on the anxiety of pregnant women in the Pangkajene Health Center work area, Sidenreng Rappang Regency. The type of research used was a quasi-experimental study. The design used was a pretest-posttest with control group design. The population was all pregnant women who made pregnancy visits at the Pangkajene Health Center and a sample of 52 pregnant women with a classification of 26 pregnant women who were given pregnancy and baby tracer application intervention and 26 pregnant women only received ANC services. Anxiety was measured using the HARS questionnaire. Data analysis used Paired T-Test and Mann Whitney. The results of this study showed a decrease in anxiety scores after receiving pregnancy and baby tracer application intervention. The conclusion of the study is that there is an influence of the use of the pregnancy and baby tracer application on the anxiety of pregnant women in the Pangkajene Health Center work area

ARIMA Method Implementation for Electricity Demand Forecasting with MAPE Evaluation

Electricity demand forecasting is critical for efficient energy management and planning. This study focuses on the development and implementation of the Autoregressive Integrated Moving Average (ARIMA) method for forecasting electricity demand in South Sulawesi's power system. The evaluation of forecasting accuracy was conducted using the Mean Absolute Percentage Error (MAPE), which measures the percentage error between predicted and actual values. Two experiments were conducted with different ARIMA models: ARIMA(5,1,0) and ARIMA(2,0,1). Results showed that the ARIMA(5,1,0) model achieved a MAPE of 2.15%, while the ARIMA(2,0,1) model performed slightly better with a MAPE of 1.91%, indicating highly accurate predictions. The findings highlight the effectiveness of the ARIMA method in forecasting electricity demand, providing a reliable tool for energy providers to optimize resource allocation and enhance operational efficiency. Future research may explore integrating ARIMA with other advanced methods to further improve forecasting performance

Automated Medical Image Processing for Lung Pneumonia Diagnosis Based on LS-SVM

Pneumonia is an inflammation of the lungs that causes pain when breathing and limits oxygen intake. Pneumonia can be caused by bacteria, viruses, and fungi. Image processing, a branch of informatics or computer science, is a field highly related to the manipulation and analysis of digital images. This study aims to design a medical image processing system as an alternative to support the diagnosis of Pneumonia in the lungs using the LS-SVM method. LS-SVM (Least Square Support Vector Machine) is a simpler and modified model of the SVM method. HoG (Histogram of Gradient) is a commonly used feature extraction method in image processing and object detection. The objective of this study is to improve the quality of healthcare services and assist in faster and more accurate clinical decision-making. The results show that lung image analysis using the LS-SVM method has a good accuracy level in the image classification process, with 2000 training data inputs processed in the preprocessing stage, consisting of 1000 Pneumonia images and 1000 normal lung images, while the testing data used consisted of 500 images, with 250 Pneumonia images and 250 normal lung images. Based on the tested data, the system achieved an accuracy of 81% for 1300 tests, proving that the LS-SVM method is effective in image processing with satisfactory results.Pneumonia adalah peradangan pada paru-paru yang menyebabkan rasa sakit saat bernapas dan membatasi asupan oksigen. Pneumonia dapat disebabkan oleh bakteri, virus, dan jamur. Pemrosesan citra, yang merupakan cabang dari informatika atau ilmu komputer, adalah bidang yang sangat terkait dengan manipulasi dan analisis gambar digital. Penelitian ini bertujuan untuk merancang sistem pemrosesan citra medis sebagai alternatif untuk mendukung diagnosis Pneumonia pada paru-paru menggunakan metode LS-SVM. LS-SVM (Least Square Support Vector Machine) adalah model yang lebih sederhana dan telah dimodifikasi dari metode SVM. HoG (Histogram of Gradient) merupakan metode ekstraksi fitur yang sering digunakan dalam pemrosesan citra dan deteksi objek. Tujuan penelitian ini adalah meningkatkan kualitas layanan kesehatan dan membantu pengambilan keputusan klinis yang lebih cepat dan akurat. Hasil penelitian menunjukkan bahwa analisis citra paru-paru menggunakan metode LS-SVM memiliki tingkat akurasi yang baik dalam proses klasifikasi gambar. Data pelatihan terdiri dari 2000 input yang diproses pada tahap praproses, dengan 1000 gambar Pneumonia dan 1000 gambar paru-paru normal, sedangkan data pengujian terdiri dari 500 gambar, yaitu 250 gambar Pneumonia dan 250 gambar paru-paru normal. Berdasarkan data yang diuji, sistem ini mencapai tingkat akurasi sebesar 81% untuk 1300 pengujian, membuktikan bahwa metode LS-SVM efektif dalam pemrosesan citra dengan hasil yang memuaskan

Time Series Forecasting of Ship Departure Health Inspections for Strengthening Quarantine Surveillance Using the ARIMA Model

ARIMA (Autoregressive Integrated Moving Average) is a time series analysis method used to evaluate data based on temporal patterns. The number of ship departure inspections conducted by the Probolinggo Class I Health Quarantine Center has shown fluctuations over time. These inspections are part of disease prevention efforts as regulated in the Indonesian Minister of Health Regulation No. 10 of 2023 concerning the Organization and Work Procedures of the Quarantine Technical Implementation Unit. This study aims to forecast the number of ship departure inspections at the Probolinggo Class I Health Quarantine Center. This research employed a non-reactive design using secondary data from 2020 to 2023, sourced from the Health Quarantine Information System (SINKARKES). The ARIMA (2,0,2) model provided the best fit, with good accuracy (MSE 685,277; MAPE 7.311). Forecasting results show an upward trend in ship departure inspections throughout 2024. This increase is highly relevant for public health, as stronger inspection activity supports quarantine surveillance, helps detect potential disease risks early, and improves preparedness against cross-border health threats

Improving Organizational Citizenship Behavior through Organizational Competence and Commitment as a Mediation Variable

Research on performance management-based views has been the main framework of many human resource management research, the literature shows that much of the research is conducted with a major emphasis on performance management-based views in exploring the improvement of organizational citizenship behavior through employee competence and organizational commitment as a mediating variable. This study aims to analyze the influence of employee competencies on Organizational Citizenship Behavior (OCB) behavior with organizational commitment as a mediating variable. OCB is the voluntary behavior of employees that goes beyond their formal duties and contributes to the effectiveness of the organization. Employee competencies, which include knowledge, skills, and attitudes, are considered an important factor in driving OCB behavior. However, the relationship between competence and OCB can be influenced by the level of organizational commitment that employees have. This study uses a quantitative approach with a survey method on a number of employees at the Makassar City Regional Drinking Water Company. The sample determination technique uses a simple random sampling technique, so that a sample of 86 people was obtained. The data analysis technique used multiple linear regression analysis using the help of Smart PLS 4 software. The results of the analysis show that competence has a significant effect on organizational citizenship behavior, organizational commitment has a significant effect on organizational citizenship behavior, competence has a significant effect on organizational commitment and, competence has a significant effect on organizational citizenship behavior through organizational commitment. This research provides practical implications for organizational management in designing competency development programs that are integrated with efforts to increase organizational commitment, in order to encourage Organizational Citizenship Behavior that contributes to overall organizational performance

The Influence of Teamwork and Work Discipline on Employee Performance: A Quantitative Study at Ananda Maternity and Children's Hospital, Makassar

Human resources are a critical component that every organization must prioritize, as they play a vital role in determining the success of the organization in achieving its goals. This study aims to examine and analyze the influence of teamwork and work discipline on employee performance at RSIA Ananda in Makassar City. A quantitative research approach was employed, with data collected through the use of questionnaires. The population of the study consisted of 317 employees at RSIA Ananda Makassar. Using purposive sampling, a total of 177 respondents were selected as the sample. Data testing included both validity and reliability tests to ensure the quality of the instrument. The data were analyzed using multiple linear regression, with hypothesis testing conducted through the F-test. The results of the F-test showed that the calculated F value was 228.477, which exceeds the critical F value of 3.05, and the significance level was 0.000, which is below the threshold of 0.05. These findings indicate that teamwork and work discipline have a statistically significant simultaneous effect on employee performance. Moreover, the results demonstrate that both teamwork and work discipline contribute to employee performance at RSIA Ananda Makassar, with work discipline emerging as the dominant influencing factor

Pengaruh E-Booklet Terhadap Pengetahuan dan Sikap Calon Pengantin Tentang Persiapan Kehamilan Sehat

Persiapan kehamilan yang optimal merupakan aspek krusial bagi calon pengantin dalam upaya meningkatkan kesehatan ibu dan anak. Salah satu cara untuk mencegah tingginya angka kematian ibu adalah dengan mempersiapkan kehamilan sejak masa prakonsepsi. Untuk mendukung peningkatan pengetahuan dan sikap calon pengantin, diperlukan media edukasi yang efektif, salah satunya adalah melalui E-Booklet. Penelitian ini bertujuan untuk menganalisis pengaruh E-Booklet terhadap peningkatan pengetahuan dan sikap calon pengantin tentang persiapan kehamilan sehat di Puskesmas Nipah. Desain penelitian yang digunakan adalah pra-eksperimental dengan pendekatan one group pre-test dan post-test. Sampel berjumlah 45 orang dipilih menggunakan teknik purposive sampling, dengan populasi berupa calon pengantin yang telah mendaftar di KUA Kecamatan Pemenang serta menjalani pemeriksaan kesehatan di Puskesmas Nipah. Analisis data dilakukan menggunakan uji Wilcoxon. Hasil penelitian menunjukkan adanya peningkatan signifikan dalam pengetahuan dan sikap calon pengantin setelah mendapatkan edukasi melalui E-Booklet, dengan nilai p=0,000. Hal ini membuktikan bahwa media E-Booklet berpengaruh terhadap peningkatan pemahaman dan sikap calon pengantin mengenai persiapan kehamilan sehat. Diharapkan dengan adanya edukasi ini, calon pengantin lebih siap secara fisik dan mental dalam menghadapi kehamilan melalui peningkatan pengetahuan dan sikap yang positif

Uji Analgesik Ekstrak Rumput Belang (Zebrina pendula Schnizl.) Pada Mencit (Mus musculus) Dengan Parameter Geliat

This research was conducted to determine the effect and concentration of the extract of Striped Grass (Zebrina pendula Schnizl.) which is productive as an analgesic against mice. The research was conducted by extracting samples with ethanol as a solvent using the maceration method. The striped grass extract was used for analgesia test on male mice at concentrations of 0.5% w/v, 1% w/v and 1.5% w/v. The results of the study showed Striped Grass Extract 0.5%, 1% and 1.5% w/v showed an analgesic effect in mice with an average percentage decrease in the number of stretches of 22.82%, 52.88%, and 68.51.97%, respectively. Striped Grass Extract at a concentration of 1.5% w/v showed the most effective analgesic effect, but the effect was still lower than the comparison given mefenamic acid 0.2% w/v at the statistical calculation level 0.05 Penelitian ini dilakukan dengan tujuan untuk mengetahui efek dan konsentrasi ekstrak Rumput Belang (Zebrina pendula Schnizl.) yang berkhasiat sebagai analgesik terhadap mencit. Penelitian dilakukan dengan mengekstraksi sampel dengan pelarut etanol dengan metode maserasi. Ekstrak Rumput Belang yang diperoleh digunakan untuk uji analgesik terhadap mencit jantan  konsentrasi 0,5% b/v, 1% b/v dan 1,5% b/v.. Hasil dari penelitian menunjukkan Ekstrak Rumput Belang 0,5%, 1% dan 1,5% b/v menunjukkan efek analgesik pada mencit dengan rata-rata persentase penurunan jumlah geliat sebesar 22,82%, 52,88%, dan 68,51,97 %,  Ekstrak Rumput Belang pada konsentrasi 1,5% b/v menunjukkan efek analgesik paling efektif, tetapi efeknya masih lebih rendah dibandingkan pemberian pembanding asam Mefenamat 0,2% b/v pada perhitungan statistik  taraf α 0,05 menunjukkan signifika

Hubungan Perilaku Merokok Dengan Kepercayaan Diri Mitra di BPS Kabupaten Aceh Tengah

Salah satu alasan yang sering dikemukakan oleh perokok adalah bahwa merokok dapat meningkatkan rasa percaya diri, terutama dalam situasi sosial. Namun, fenomena ini masih menjadi perdebatan, apakah kepercayaan diri yang meningkat pada perokok merupakan efek psikologis yang nyata atau sekadar sugesti akibat kecanduan nikotin. Tujuan penelitian ini untuk mengidentifikasi hubungan perilaku merokok dengan kepercayaan diri pada Mitra di BPS Kabupaten Aceh Tengah. Penelitian ini menggunakan metode analitik observasional dengan desain cross sectional study. Sampel penelitian berjumlah 52 Mitra laki-laki di BPS Kabupaten Aceh Tengah yang diperoleh dengan teknik total sampling. Alat ukur yang digunakan adalah kusioner. Analisis data mengunakan uji statistic Chi square. Hasil penelitian diperoleh nilai ρ-value = 0,237 yang menunjukkan bahwa tidak ada hubungan perilaku merokok dengan kepercayaan diri pada Mitra di BPS Kabupaten Aceh Tengah. Diharapkan BPS Kabupaten Aceh Tengah untuk mengingatkan kepada Mitra kerja tentang bahaya merokok bagi kesehatan