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Copyright of Journal of Social & Technology / Jurnal Sosial dan Teknologi (SOSTECH) is the property of Green Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Jembatan Jalan Bromo terletak pada Desa Mojounggul, Kecamatan Bareng, Kabupaten Jombang dengan bentang yang direncanakan 10 meter. Jembatan ini awalnya menggunakan struktur pelengkung yang dibangun masa Belanda sehingga harus dilakukan perencanaan struktur jembatan. Di sini peneliti memodifikasi desain jembatan menggunakan balok-T (T-Beam Structure). jembatan Jalan Bromo digunakan sebagai objek penelitian untuk memodifikasi desain struktur jembatan bagian atas yang meliputi: balok-T jembatan dan bangunan bawah meliputi: abutmen, pondasi, dan diafragma dengan menghitung aspek pembebanan mengacu pada SNI 1275-2016, aspek penulangan dan dimensi penulangan pada balok-T, selanjutnya kontrol kekuatan terhadap abutmen dan daya dukung pada tiang pancang. Hasil perhitungan pada redesign jembatan didapatkan hasil momen ultimit (MU) pada balok 116 kNm dan gaya geser ultimit (VU) 598 kN dengan tulangan yang digunakan pada balok tulangan lentur 12 D 32 mm, tulangan bagi 2 D 13 mm tulangan geser D 16-150 mm. Stabilitas guling pada abutmen 12,4 arah x, 4,8 arah y. stabilitas geser pada abutmen didapatkan nilai 14 arah x, dan 432 arah y. Daya dukung tiang pancang 31.899 ton lebih besar dari beban aksial 5.272,2 ton.

Self Compacting Concrete (SCC) adalah inovasi beton berupa beton cair memadat mandiri tanpa adanya bantuan alat penggetar berupa vibrator. Karakteristiknya yang cair memudahkan pada proses pengadukan. Dalam penelitian ini dilakukan pengujian kuat tekan, kuat tarik belah, dan kuat lentur beton SCC. Bahan yang ditambahkan ke dalam adukan adalah limbah serat kenaf dengan persentase 0%, 0,25%, 0,5%, 0,75%, dan 1% serta superplasticizer consol N11 LN dengan persentase 1,25%. Masing-masing pengujian dibuat 4 sampel benda uji dengan pengujian pada umur 28 hari. Dari hasil pengujian kuat tekan beton SCC mengalami penurunan kuat tekan seiring dengan ditambahkannya variasi limbah serat kenaf. Pada pengujian kuat tarik belah dan kuat lentur beton SCC mengalami kenaikan seiring ditambahkannya variasi limbah serat kenaf. Pada penambahan LSK 1 tidak memenuhi syarat sebagai beton SCC dikarenakan diperoleh nilai slump flow 52,71 cm. Limbah serat kenaf pada kuat tekan beton SCC maksimum yaitu pada LSK 0,25 mencapai 27,61 MPa akan tetapi beton tanpa serat tetap yang mencapai kuat tekan tertinggi sebesar 28,69 MPa, sedangkan penggunaan limbah serat kenaf pada kuat tarik belah beton SCC maksimum yaitu pada LSK 0,75 mencapai 2,77 MPa, sedangkan penggunaan limbah serat kenaf pada kuat lentur beton SCC maksimum yaitu pada LSK 0,75 mencapai 4,29 MPa.

The escalating daily demand for electricity, propelled by technological advancements and the pervasive use of electronic devices, accentuates the imperative for a dependable and sustainable power generation system. Renewable energy sources emerge as a viable solution to address the electricity needs in Indonesia, particularly in remote areas where access to the main grid is challenging. Tasikmalaya Regency, situated in West Java Province and defined by its geographical coordinates between 7°02' 29" - 7°49' 08" South Latitude and 107°54' 10" - 108°25' 52" East Longitude, presents a promising setting for the implementation of such sustainable energy solutions. The coastal area of Tasikmalaya, specifically Cipatujah Subdistrict, exhibits substantial renewable energy potential, including wind, solar radiation, and ocean waves. This research endeavors to design an efficient hybrid power generation system in Cipatujah Subdistrict using HomerPro software. The methodology involves crafting various models to determine the most economically efficient generation strategy. The study utilizes electricity consumption data sourced from the Karangnunggal Tasikmalaya Substation, situated in the southern coastal region of Tasikmalaya, particularly in Cipatujah Subdistrict, with a daily consumption of 20.6917 MW. By addressing the specific energy needs of the region, the research aims to make a positive contribution to the development of renewable energy and, concurrently, serve as a guiding framework for similar system designs in locations sharing comparable characteristics. This multifaceted approach underscores the significance of tailoring sustainable energy solutions to the unique requirements of diverse regions, fostering a broader transition towards a reliable and environmentally conscious energy future.

Banjir pada lapangan sepakbola Desa Selaganggeng, Kecamatan Mrebet, Kabupaten Purbalingga terjadi karena sistem drainase yang ada tidak baik. Air hujan yang jatuh di area lapangan tidak dapat segera diresapkan ke dalam tanah atau dialirkan ke saluran pembuang. Namun hal ini dapat diatasi dengan cara membuat sistem drainase bawah permukaan berupa pipa-pipa lateral di bawah tanah yang terhubung dengan saluran pembuang. Analisis hidrologi dilakukan untuk mendapatkan debit hujan sebagai dasar untuk merencanakan dimensi pipa dan jarak antar pipa terpasang. Hasil analisis hidrologi didapatkan bahwa debit hujan dengan kala ulang 5, 10, 15, dan 20 tahun berturut-turut adalah sebesar 4,432 x 10-2 m3/detik, 5,694 x 10-2 m3/detik, 6,289 x 10-2 m3/detik, dan 6,947 x 10-2 m3/detik. Banjir tidak terjadi jika pipa dipasang pada kedalaman 0,4 m dengan diameter Ø 4 inci dan jarak antar pipa adalah 3,30 m serta perlu pergantian lapisan tanah lapangan dengan yang lebih porus.

Mitigasi bencana alam banjir sangat diperlukan untuk mengurangi resiko akibat bahaya banjir. Dalam penelitian ini telah dibuat sistem untuk memantau tinggi permukaan air di bendungan Sungai Ijo. Sisem menggunakan sensor ultrasonik untuk mendeteksi tinggi permukaan air (water level sensor). Gelombang ultrasonik yang dipancar jika terkena permukaan air akan memantul dan akan diterima oleh bagian penerima ultrasonik. Hasil pembacaan sensor diproses oleh mikrokontroler untuk menentukan kondisi permukaan air (aman, siaga, darurat). Sistem yang berbasis IoT (Internet of Things) ini akan mengirimkan kondisi tinggi permukaan air dengan menggunakan aplikasi telegram setiap 5 menit ke beberapa nomor yang sudah terdaftar. Berdasarkan hasil uji coba di lapangan, sistem ini memiliki tingkat kesalahan yang kecil, yaitu 0,1 % untuk kondisi aman, 0,06 % untuk kondisi siaga, dan 0,05 % untuk kondisi darurat.

Polusi udara menjadi salah satu ancaman bagi lingkungan, khususnya di kawasan perkotaan yang memiliki tingkat emisi tinggi gas berbahaya seperti karbon dioksida (CO2) dan karbon monoksida (CO). Penelitian ini mengembangkan sistem pemantauan kualitas udara berbasis sensor MQ-135 yang berfokus pada deteksi gas CO2 dan CO secara real-time. Sensor ini diintegrasikan dengan mikrokontroler dan kalibrasi untuk meningkatkan akurasi pengukuran. Penelitian ini menawarkan pendekatan yang lebih efisien dan ekonomis dibandingkan dengan perangkat monitoring komersial. Hasil pengujian menunjukkan bahwa sistem yang dikembangkan mampu mendeteksi konsentrasi gas dengan presisi yang dapat diterima untuk aplikasi lingkungan. Pengujian menunjukkan bahwa sistem yang dikembangkan mampu mendeteksi konsentrasi CO2 hingga 520 ppm dan CO hingga 20 ppm dengan tingkat akurasi 2,21% untuk CO2 dan 0,26% untuk CO dibandingkan alat monitoring komersial. Studi ini berkontribusi terhadap pengembangan teknologi monitoring udara yang lebih terjangkau untuk aplikasi perkotaan.

Kota Banyumas memiliki BRT Trans-Banyumas sebagai salah satu transportasi massal yang diharapkan menjadi transportasi dengan pelayanan terbaik, nyaman, aman, dan cepat. Tujuan dari penelitian ini adalah untuk mengetahui bagaimana karakteristik penumpang Bus Trans Banyumas mempengaruhi karakteristik perilaku perjalanan pada koridor 1 menggunakan metode analisis statistik deskriptif. Karakteristik sosio ekonomi dan demografi penumpang terlihat dari hasil pengolahan data 250 responden yang di survey didapati bahwa dari jenis kelamin perempuan lebih banyak dengan tingkat usia terbanyak di umur 35-50 tahun dengan pendidikan terakhir mayoritas SMA. Terkait maksud perjalanan responden didominasi oleh rekreasi/belanja, untuk profesi didominasi oleh lainnya. Dengan mayoritas pendapatan rata-rata perbulan sebesar 1 jt – 2 jt. Karakteristik perilaku perjalanan dari data yang diperoleh dan diolah untuk moda sebelum beralih menngunakan bus trans banyumas didominasi menggunakan bus/angkot. Kemudian untuk moda perjalanan hubung dan moda transportasi yang digunakan baik dari rumah menuju shelter dan dari shelter menuju ketempat tujuan didominasi oleh jalan kaki. Kemudian untuk jarak perjalanan hubung dari rumah menuju shelter dan dari shelter menuju ketempat tujuan adalah > 400 m. Dengan pemilihan rekan berjalan mayoritas sendiri dengan mayoritas alasan sehat. Tidak semua kondisi demografi sosial ekonomi mempengaruhi karakteristik perilaku perjalanan.

Keamanan sistem informasi menjadi aspek kritis dalam lingkungan teknologi informasi yang terus berkembang. Penetration testing adalah salah satu metode yang efektif untuk mengidentifikasi dan menguji keamanan dalam sebuah simulasi serangan terhadap suatu sistem atau jaringan guna menemukan celah keamanan yang disebabkan oleh keamanan dari suatu sistem, konfigurasi yang tidak benar atau kelemahan operasional dalam proses teknik. Penelitian ini melakukan identifikasi kerentanan pada website SIPLO dengan metode penetration testing menggunakan framework ISSAF (Information System Securiry Assesment Framework) untuk mengukur keamanan sistem. Penetration testing dilakukan dengan menggunakan tiga jenis serangan teratas dari OWASP Top 10 yaitu, XSS, Brute-force attack, SQL injection, dan DDoS attack. Hasil identifikasi kerentanan pada website SIPLO menunjukkan bahwa terdapat 23 kerentanan pada SIPLO dengan dua kerentanan memiliki level tinggi, empat kerentanan memiliki level sedang, sebelas kerentanan memiliki level rendah, enam kerentanan memiliki level informational. Walaupun dengan kerentanan-kerentanan tersebut website SIPLO masih terlindungi dari serangan XSS dan SQL injection. Serangan brute-force attack hanya berhasil teridentifikasi satu username dan satu password. Sedangkan serangan DDoS tidak memiliki pengaruh yang signifikan terhadap SIPLO namun tercatat adanya perbedaan sebanyak 217,221 millisecond saat dilakukannya serangan DDoS tersebut.

Background: Schools are reluctant to adapt physical education to virtual as it would be challenging to do physical education via virtual learning. Objectives: This study aimed to assess the contemporary efficacy of virtual physical education and its contribution to raising learners' interest and engagement levels. Methods: This study employed an exploratory research design. The content was compiled using various printed and electronic textbooks, encyclopedias, reference materials, scholarly publications, and dissertations. Subsequently, the author assessed the multiple sources to ascertain the data's caliber. Results: Conventional education is obsolete; thus, schools should adopt virtual physical education due to its positive outcomes in education regarding learners' performance by increasing learners' interest and engagement. Conclusion: A properly planned and well-implemented virtual physical education, well-trained and experienced educators, well-guided learners, proper infrastructure, and supporting resources result in learners being interested and engaged, thus leading virtual physical education to success. This study bridges the gap between virtual physical education and learners' interest and engagement, adding to the existing corpus of information concerning virtual physical education.

The focus of 21st-century learning is on developing students' critical thinking, real-world application of knowledge, mastery of information technology, communication, and collaboration skills. Therefore, it is important to integrate information technology into the learning process and assessment of learning outcomes. This research aims to explore how Computer-Based Testing (CBT) can enhance the quality of cognitive assessment procedures based on literacy and improve learning evaluations for students at Islamic Elementary School. This study adopted a qualitative case study design and was conducted at Islamic Elementary School Al Wathoniyah 10 East Jakarta in the second semester of the 2023/2024 academic year. The researcher used interviews, observations, and documentation as data collection methods. The findings of this research show that literacy-based cognitive assessment using CBT can optimize the quality of learning evaluation. Teachers and students are accustomed to using information and communication technology devices in learning activities. There are five stages of the procedure in literacy-based cognitive assessment using CBT to optimize the quality of learning evaluation, including the planning stage, item question development stage, validation stage, implementation stage, and evaluation stage. The investigative conducting procedure truly optimizes the quality of learning evaluation. Islamic Elementary School Al Wathoniyah 10 utilizes CBT, which has literacy-based characteristics. CBT used in learning evaluation is equipped with meaningful stimuli and various forms of questions. The questions in CBT are made as similar as possible to the national assessment questions. The educational report results in the 2023 national assessment, especially in the cognitive domain, have shown improvement. The literacy and numeracy skills of students at Islamic Elementary School Al Wathoniyah 10 have achieved good and moderate results. Both have obtained top rankings nationally.

Stunting is a condition of failure to thrive in children under five (toddlers) which can hinder the child's physical and mental development. Data from the 2023 Indonesian Health Survey (SKI) shows that the number of stunted toddlers in West Nusa Tenggara (NTB) Province is still quite high, namely 24.6%. Stunting cannot be cured but can be prevented. One of the prevention efforts is to increase the knowledge of mothers or prospective mothers regarding stunting and preventing it by providing food with high nutrition. This Community Service Activity (PKM) was carried out with the aim of educating mothers and wives of home-based beef cattle farmers in Lando Village, East Lombok, NTB about preventing stunting by providing highly nutritious supplementary food (PMT) and stunting detection. The methods used were socialization and demonstration of making toddler food. The results of this PKM activity were that there was a significant increase in participants' knowledge regarding the material being socialized (p0.0001). The conclusion that can be drawn is that There had been an increase in knowledge among PKM participants regarding stunting and preventing stunting through providing food with high protein content.

Pliek-u is a specialty food product in Aceh with local wisdom values that should be preserved. The Program of Community Service Based Product (PKMBP) aimed to improve the pliek-u agro-industry by adapting simple processing technologies so that it could lighten work, produce quality products, and attract the interest of the younger generation as pliek-u entrepreneurs in future. The method applied consist of surveys, preparation of tools and materials, assembly of a solar tunnel dryer type Hohenheim Aceh and a hydraulic press, training and dissemination of technology through field schools, and evaluation of the program with pre-tests and post-tests. Data analysis was carried out using the Wilcoxon rank test with alpha of 5%. The results of the program were the construction of 1 unit of Hohenheim Aceh tunnel dryer, 1 unit of hydraulic press, and the implementation of training and dissemination activities which have been published in the form of videos on YouTube media and press releases through online media. The results of the Wilcoxon rank test also showed that of the 13 participants whose data were valid, 100% of participants received positive rankings and the pre-test scores were significantly different from the post-test scores. Thus, it can be concluded that the program carried out has contributed to increasing the knowledge, expertise capacity, and interest of participants in pliek-u processing technologies since the profile of conventional agroindustry can be transformed to be better agroindustry by the use of solar tunnel dryer type Hohenheim Aceh and hydraulic press. In addition, the use of technologies will ensure the halal requirement of pliek-u.

Farmers, especially those in Blang Krueng Village, Baitussalam Subdistrict, Aceh Besar District, have so far been raising livestock using traditional or semi-extensive patterns, where livestock are released in pastures or rice fields to find their own feed and in the afternoon given grass that has been cut into pieces. The purpose of the activity is to assist farmers in their livestock business, especially in the problem of feed needs that still cannot be met. This activity is carried out using the PRA (Participatory Rural Appraisal) approach. In this case the target audience participates in increasing and analyzing their knowledge about their own conditions so that they can make plans and actions, especially in efforts to raise cattle. The method of processing fermented straw, among others, the straw is aerated so that the moisture content is 40%, the straw is stacked with a length of 2.5 m, a width of 2.5 m and a thickness of 25 cm, on top of the straw layer watered with water that has been mixed with urea until evenly distributed, on top of the straw layer sprinkled with starter until evenly distributed, the straw is stacked again with a thickness of 25 cm trampled until solid, repeated watering of water mixed with urea until evenly distributed, repeated sowing of starter until evenly distributed, so repeated until the pile can reach 3 m, after completion the top is covered with dry leaves such as banana leaves, rice straw is left for at least 3-4 weeks and fermented rice straw is ready to be given to livestock. The results of the service that have been achieved are the availability of alternative feed from fermented straw and can be given to cattle, where the cattle also want to consume it.

Contingency Plan for Outbreak/Epidemic Disaster in Banda Aceh City is a document that contains the process of identifying and preparing future plans based on potential disaster conditions. The purpose of making a Contingency Plan document that becomes a reference in the disaster outbreak/epidemic of Infectious Diseases Caused by Viruses in the City of Banda Aceh. Method The preparation process involved all disaster management institutions and actors, both government and non-government. The scope of activities carried out are: Technical Team Meeting, Public Seminar, and Plan Finalization. The results obtained by the issuance of the Banda Aceh Mayor's Regulation for the Contingency Plan for the epidemic of infectious diseases caused by viruses in the city of Banda Aceh which is regulated in a Banda Aceh Mayor's Regulation No. 68 of 2021 concerning the Contingency Plan for the Epidemic of Infectious Diseases Caused by Viruses in the City of Banda Aceh. In conclusion, Banda Aceh City has realized preparedness for the threat of epidemics of diseases caused by viruses by involving multi-sectors. To improve the function and sustainability of the document, data updates and projections of resource needs are needed to support the implementation/activation of the contingency plan that has been prepared.

U-Neulheu, a traditional Acehnese cooking spice made from roasted grated coconut, is typically produced using simple and limited equipment, leading to an inefficient production process. As a result, both the quality and quantity of the final product are often suboptimal. The integration of technology into the production process remains far from ideal. The aim of this community service activity aims to enhance the quantity and quality of U-Neulheu produced by local partners through the implementation of Appropriate Technology, such as a roasted coconut grinder and dryer. These improvements are expected to increase the partner's income level and living standards. The partners involved in this activity are a group of housewives who produce U-Neulheu in Cot Preh Village, Kuta Baro Sub-District, Aceh Besar District. The methods of this community service activity include counseling, the implementation of technology in the form of a roasted coconut grinder and dryer, as well as technical guidance. The results of the activity show that the partners greatly benefited from the application of this Appropriate Technology. The use of the roasted coconut grinder and dryer in the U-Neulheu production process made it more effective and efficient in terms of both time and cost. In addition, the quantity and quality of U-Neulheu products have also increased. The quantity increase is measurable by the higher number of products produced (50%), while the quality improvement is evident in the smoother and more hygienic products.

Sentiment analysis is a technique to decipher textual views and feelings. This study assesses a model's performance in sentiment analysis of Google Play Store reviews for the Amikom One app. With more unfavorable ratings, the primary problem is the imbalance in classes. It was done using the Synthetic Minority Over-sampling Technique (SMOTE) to remedy this. The techniques used are preprocessing the data, using SMOTE, and classifying sentiment using an artificial neural network (ANN). F1-score, recall, accuracy, and precision are used in the model evaluation process. The outcomes demonstrate a great degree of accuracy improvement in the ANN model's performance following the use of SMOTE. On training data, the model successfully classified sentiment reviews with 100% accuracy, while on test data, it achieved 93.44% accuracy. Sentiment research shows that 54.10 percent of the evaluations are favorable to the application, with 45.90% being critical. This study Artificial Neural Networks' (ANN) potential in sentiment analysis of mobile application reviews, offering developers with useful insights into how to enhance program quality using user feedback.

The Knowledge Management System Application is an application that users can use to store and manage knowledge from the Community Of Practice (CoP) Marine Information Systems Study Program (SIK). CoP, known as the Expertise Group or KBK, consists of students and lecturers. The problem that exists based on the results of observations is that the Knowledge Management System Application called Asmape.Com application has not been utilized optimally; this can be seen from the use of the application, which is only used by three courses in the Marine Information Systems study program, namely knowledge management, business intelligence, and biodiversity. The successful implementation of an application depends on technological aspects and requires comprehensive attention to the existing dimensions of the information system. Therefore, it is necessary to model the utilization of knowledge management system applications (Asmape.com), which can be used as a systematic guide to understanding, analyzing, and improving performance. The methodology used is the information systems methodology from Hevner. One of the stages in the method is to determine the components using the Kitchenham systematic literature review. The study results show four layers in the model of utilizing knowledge management system applications: Infrastructure, Technology, Process, and Performance. The infrastructure consists of learning outcomes and technical skills components, and processes consist of Organization, People, Asmape Services, and Artifact Knowledge components. The performance consists of Pedagogic excellence, Digitalization Knowledge Management, and Openness Excellence.

Fulfilling nutritional needs with the Recommended Dietary Allowances (RDA) shows the average value of the number of vitamins, protein and other nutrients the body needs to function properly. Each person's nutritional needs are different, so the RDA can be calculated based on different age groups and gender. In general, there are still many people who do not know the nutritional value of food and consume food without considering whether it meets the body's needs. This usually happens because calculating the RDA value is not yet familiar to do. Efforts are needed to increase awareness about the importance of a balanced diet through RDA calculations. Calculation and determination of nutritional status using the RDA number serves as a measuring tool to monitor whether a person's nutritional intake is in accordance with daily needs. This research developed a web-based application to calculate RDA numbers and group RDA numbers into nutritional status of less, enough, or more. Determination of nutritional status is carried out using the fuzzy tahani method, by displaying the results in percentage form, so that users can easily see the proportion or percentage of nutritional status obtained. This application not only calculates nutritional values, but provides a food record feature to help users manage healthy eating patterns.

Breast cancer is one of the most common causes of death worldwide. Data mining can be utilized to detect breast cancer, where information is extracted from data to provide valuable insights. Clustering of breast cancer is conducted to assist medical professionals in grouping the characteristics of each cancer type. However, multicollinearity in breast cancer data can impact clustering results. To address this issue, dimensionality reduction through Principal Component Analysis (PCA) is employed. PCA can effectively handle multicollinearity issues and enhance computational efficiency. Additionally, the K-Means method has limitations in determining the optimal number of clusters. Therefore, the Gap Statistic method is employed to find the optimal K value suitable for breast cancer data. This study compares the evaluation results of the K-Means clustering model, the combined PCA-KMeans clustering model, and the combined PCA-GapStatistic-KMeans clustering model. The findings indicate that the evaluation results for the K-Means model with PCA dimensionality reduction and optimal Gap Statistic K are superior to the K-Means model without dimensionality reduction. The Gap Statistic suggests 2 clusters as the optimal number, with an evaluation result of 1.195513.

This study explores the use of Convolutional Neural Network to identify and classify regional batik motifs, a significant aspect of Indonesian cultural heritage. The CNN model was optimized with Adam optimizer and used to extract distinctive features from the batik patterns. Subsequently, a hierarchical clustering method was employed to construct a relationship tree depicting the link between batik motifs based on their region. The research findings demonstrate that the CNN model effectively classifies batik motifs with an accuracy of up to 88%. The study provides insights into the intricate connections between regional batik designs and contributes to the preservation and understanding of Indonesia's cultural heritage.

Magelang Regency, with a wealth of tourist destinations with a variety of things, such as Borobudur Temple and Nepal Van Java, has extraordinary tourism potential. With this diversity, it is a challenge for tourists to determine the best tourist objects that suit their preferences. This study aims to develop an intelligent system for recommending the selection of the best tourist attractions in Magelang Regency by integrating the Weighted Product and K-Means Clustering Methods. The system is designed to provide accurate recommendations based on tourist criteria such as location, facilities, tickets, and security, as well as group attractions based on their level of potential. The Weighted Product method is used to determine the best tourist attractions, while K-Means Clustering groups tourist destinations into high, medium, and low potential categories. In this study, several stages were carried out: literature study, data collection, system design, data analysis, implementation, and system testing to produce an effective and efficient recommendation system for tourists in Magelang Regency. The results of this research obtained the best tourism, namely at Borobudur Temple.

Game is a form of entertainment that is often used to refresh the mind from the fatigue of daily activities and routines. Honkai: Star Rail is a popular turn-based game from Hoyoverse available on Google Play Store. Several studies have proposed Sentiment Analysis with Naïve Bayes classification method. However, not many have identified the reviews of a game to the extent of identifying on its aspects. In aspect-based sentiment analysis, text is analyzed to identify various attributes or components, then the relevant sentiment (positive, negative, or neutral) for each of these attributes is determined. This research aims to analyze aspect-based sentiment using the Naïve Bayes Classifier method, as well as categorize sentiment into positive and negative, and classify reviews into certain aspects. The results obtained after 5-fold iteration obtained the best average accuracy of 79%, The evaluation results show that it is necessary to tune the model using Grid Search Hyperparameter Tuning. Optimization of smoothing parameters with alpha = 0.1 proved effective in improving model performance with the highest weighted average accuracy of 93%. The evaluation results show that Grid Search Hyperparameter Tuning optimization gives better performance to the Naive Bayes algorithm model in multi-label classification.

One of the topics that has been discussed on twitter is the rules regarding the removal of masks. However, there's a chance that the data from Twitter contains unequal data classes. An unequal amount of data can cause the classification process to malfunction. Combining under- and oversampling techniques is known as combine sampling, and it is a data-balancing strategy. The research's data consists of Indonesian tweets using the hashtag "The Policy of Removing Masks." In this study, the classification approach was K-Nearest Neighbor, while the oversampling and undersampling techniques were SMOTE and Tomek Links. The purpose of this research is to classify sentiment using the K-Nearest Neighbor algorithm and to use combine sampling to balance the amount of training data in the two classes that are not yet balanced. 234 training data with a positive sentiment and 652 training data with a negative sentiment were obtained after the data was divided. Due to an imbalance in the quantity of training data between the two classes, the positive class's data is minor and the negative class's data is major. The quantity of training data are 613 in the positive class and 613 in the negative class obtained following the combine sampling. Following the balancing of data between the two classes, sentiment classification was performed, yielding accuracy of 60.4%, precision of 78.5%, and recall of 65%. The reason for the accuracy number of 60.4% is because machine learning misinterpreted a tweet regarding Indonesia's mask removal policy, leading to incorrect classification.

Packaged food and beverages often pose a risk of increasing diabetes when consumed regularly. This study aims to classify these products based on their nutritional content listed on the labels, with a focus on identifying diabetes risk. The methods employed include K-Means and Fuzzy C-Means, K-Means is used to determine initial center of cluster, while Fuzzy C-Means enhances the clustering by assigning probabilistic memberships to each data point. These methods are applied to products sold in stores in Banyumas Regency, Central Java, Indonesia. This research is the first to combine these two methods in the context of product clustering based on nutritional labels. The results indicate that packaged food and beverage products can be classified into high-risk and low-risk clusters for diabetes. Consequently, this study provides important guidance for consumers in choosing healthier.

Weather is the atmospheric condition at a specific location and time that is variable and constantly changing. Many factors influence weather conditions, one of which is rainfall. Rainfall is a climatic parameter characterized by high variability due to climate anomalies. These anomalies make rainfall prediction very challenging. Specific factors can cause uneven distribution patterns of rainfall between different regions. The exact amount of rainfall that will occur cannot be determined precisely, but predictions or estimations can be made for future rainfall amounts. This study predicts rainfall in Tegal Regency using ETSFormer. Its aim is to provide useful information about future rainfall patterns for the community, especially in Tegal Regency, to facilitate daily activities. The results show that the ETSFormer model effectively predicts rainfall, achieving optimal results with an 8:2 data composition using univariate analysis, yielding the best MSE evaluation metric of 0.002925439039245248 and MAE of 0.036676984280347824.

In particular, stunting and being under the Red Line (BGM) are significant issues for society and the healthcare system. This research utilizes machine learning, particularly the K-Nearest Neighbor (KNN) and Naïve Bayes algorithms, for classifying the health of children experiencing stunting or BGM. The training data used comes from the Indonesian Posyandu website, serving as the foundation for classifying new data. This research not only identifies patterns in the data through KNN but also compares the prediction results between KNN and Naïve Bayes in assessing the probability of stunting or BGM in children. This issue reflects nutritional deficiencies and has the potential to cause developmental delays and long-term health impacts. This approach allows for the comparison of predictive outcomes, enhancing the accuracy of children's health assessments. By using the RapidMiner application, the accuracy result for KNN is 70.62% and for Naïve Bayes is 99.47%, providing a deeper understanding of the effectiveness of each algorithm in addressing child health challenges. The aim of this research is to classify new toddler data using the KNN and Naïve Bayes methods, implemented in the form of a Visual Basic application. It is hoped that this will help monitor children's health more effectively and be more easily accessible to interested parties.

Every year, the library must be buying books in order to increase the collection of books that are in the libraries. When purchasing books, it is necessary to make various considerations so that the books that will be used are relevant to the needs of students and lecturers in academic activities. The procurement of books in the library is still done manually with book selection carried out by the librarians is still one-on-one of the list of submissions of books that have been made by the lecturer. Therefore, there is a need to have a renewal of the system of book acquisition in the libraries one of which uses the decision support system in the process of the book acquisitions. In this study the decision support system used is the MOORA method in determining the rating of the recommendation book to be held. The alternative submission data will be obtained from the library's proposal with the book data from the publisher's book collection. The study uses five criteria for book acquisition, including book price, year of publication, book stock, number of book proposals, and availability of books. This decision support system will provide a recommendation for purchase of books from the alternative data for book submission that will be calculated using the MOORA method to obtain any book recommendation that matches the criteria and budget of the book procurement. Accuracy level testing using the Confusion Matrix by comparing the results of manual calculations with the system to obtain 100% accuracy.

The user interface (UI) design of software in the early stages of development is crucial to ensure the future success of the product and is key to creating an effective user experience (UX). This study aims to produce a UI design for software, namely an e-repository, and conduct a usability evaluation based on user satisfaction with the UX of the design. The resulting e-repository design is a prototype, where the research process implemented the design thinking method consisting of five main phases: empathize, define, ideate, prototype, and test. The evaluation is conducted in the test phase, where the evaluation uses the usability testing method by assigning a number of task scenarios, totaling 8 tasks, to respondents. Furthermore, to measure user satisfaction levels, a questionnaire based on the System Usability Scale (SUS) is used, consisting of 10 statements with both positive and negative orientations. The research results indicate that the UI design has addressed the issues and met the needs of users. Meanwhile, the analysis results from the usability evaluation show that the Adjective Ratings are categorized as Good. Additionally, in terms of Acceptability Ranges, the prototype is deemed Acceptable by users, with a Grade Scale obtained being B, where the evaluation results indicate that the scores obtained are above the average SUS score standard.

In today's rapidly evolving technological landscape, the successful implementation of IT projects is increasingly contingent upon effective organizational change management (OCM). This research paper explores the intersection of OCM and IT project delivery, proposing a comprehensive framework that integrates these two critical domains. Through a review of existing literature and analysis of case studies, we identify key challenges and best practices for synchronizing OCM strategies with IT project management processes. Our findings reveal that the alignment of OCM with IT project delivery not only enhances project success rates but also promotes sustainable organizational transformation. This integrated approach ensures that technological advancements are supported by a well-prepared workforce, thereby minimizing resistance and maximizing adoption. The paper concludes with practical recommendations for practitioners aiming to bridge the gap between OCM and IT project delivery, ultimately fostering a more agile and resilient organizational environment.

This Systematic Literature Review study discusses the factors that influence the adoption of e-government services with varsiability in the influence of these factors in various countries. The research confirms the importance of trust, performance expectancy, effort expectancy, social influence, and facilitating conditions in the acceptance and adoption of e-government services. Trust factors, especially related to information security and government transparency, were found to be key elements in driving e-government adoption. In addition, the expectation of benefits obtained, ease of use, and influence from the social environment also play an important role in people's decision to use the service. Suggested recommendations to increase e-government adoption involve improving technology infrastructure, supportive policies, technology training for government personnel, as well as an approach that considers local community conditions and factors. This study provides important insights for governments and agencies in improving e-government services and increasing the adoption of these technologies across various social and cultural environments.

At present, clove cultivation is increasingly in demand, especially by farmers because it is easy to maintain and the selling price is high. Researchers conducted observations in Tana Toa Village on how the processing of cloves after harvesting is drying them in the sun until they turn brown and shrink. After that, farmers select dried cloves and distinguish between good and bad quality. One way for farmers and traders to determine the quality of cloves is by visually inspecting the size and color. One of the disadvantages of this manual classification process is that each person can look at the same material in bulk in different ways depending on the situation or individual weak points. The aim of this research is to help farmers produce high quality cloves that will ultimately produce favorable results on their economy. With digital image-based methods and Naive Bayes, this process can be done quickly and efficiently, reducing operational costs and labor time. The Naive Bayes algorithm is able to process data more thoroughly than humans, especially if the image quality and features used for classification are optimized. This reduces human errors that may occur during manual processing. The results of this study are, Gaussian Naive Bayes testing has an accuracy of 0.82. Bernoulli naïve bayes has an accuracy of 0.69, Complement naïve bayes and multinomial naïve bayes each have an accuracy of 0.89. This shows that they affect the accuracy rate of clove quality effectively

The Surabaya City Government launched an application based on an internet site or web page in the form of a data collection system carried out by the local Kader Surabaya Hebat (KSH) to record various problems in the community related to poverty and health problems, the application was named the Sayang Warga Application (ASW). The application that was launched does not mean it has shortcomings because until now the application has never been maintained, causing ASW to be considered less than optimal and this clearly hinders the performance of users in conducting data collection. This study uses the right method to achieve a goal. From what can be traced and studied, the appropriate method is to use a quantitative method. This study uses the Partial Least Square-Structural Equation Model (PLS SEM) method. The results of 12 variable relationship paths, 4 variable path relationships were declared insignificant and rejected because the T-test and P-value values were below 1.96 and 0.05, while 8 variable path relationships were declared significant and accepted because the T-test and P-Value values were above the threshold, namely 1.96 and 0.05. Furthermore, the results of the analysis of factors that influence the success of use in ASW can be concluded, the results of the hypothesis test indicate that perceived ease of use has a positive and significant effect on perceived usefulness. Because the hypothesis path has the highest value with a T-test of 6,560 with a P-Value of 0.000

In order to handle student discipline infractions at school, this project intends to design a decision support system (DSS) based on the Simple Multi-Attribute Rating Technique (SMART) technique integrated with a graphical dashboard. A variety of visual tools, such as scatter plots, heatmaps, pie charts, bar charts, and line charts, are used to evaluate and display violation data. This integration's primary goals are to make monitoring and analysis faster and more efficient and to support decision-making with regard to student infractions. The findings demonstrate how the SMART approach and visualization dashboard can be used to manage violation data more effectively, provide a better knowledge, and speed up reactions to infractions. This technique makes it easier for schools to spot trends in infractions, choose the best course of action for corrective measures, and enhance overall student discipline. It is anticipated that this system will enable discipline management in a learning environment in an efficient manner.

Diabetic retinopathy is a serious complication of diabetes that can lead to blindness if not detected and treated early. Automated detection of diabetic retinopathy requires effective feature extraction techniques to enhance diagnostic accuracy. This study aims to develop a method for detecting diabetic retinopathy by utilizing Local Binary Pattern (LBP) combined with wavelet transform, and then classifying the extracted features using Support Vector Machine (SVM). The approach includes feature extraction from retinal images using LBP and wavelet transform. The extracted features are subsequently classified with SVM to evaluate performance in detecting diabetic retinopathy. Analysis results show that the dominant feature is found in the fifth row with a value of 0.57006, indicating the effectiveness of the LBP method in feature extraction. The developed model demonstrates high performance with an accuracy of 95.59%, precision of 96%, recall of 97.96%, and F1-score of 96.97%. The combination of feature extraction methods with SVM proves to be effective and reliable in detecting diabetic retinopathy, offering low error rates and high accuracy, thus potentially serving as a valuable tool in clinical diagnosis

Along with advances in digital technology, the ease of carrying out payment transaction processes via digital wallet applications is increasing. OVO is one of the leading digital wallet applications in Indonesia. However, there are several users who complain and report problems such as difficulties in upgrading, login problems, transaction failures, and applications that respond slowly. These reviews can be seen through the comments column in the OVO application on Google Playstore. Application representation can influence user perceptions of an application. This research aims to assess the user experience of the OVO application using the User Experience Questionnaire (UEQ) method, which involves six aspects of assessment: attractiveness, clarity, efficiency, stimulation and innovation. The research results obtained show that the overall user assessment of the evaluation that has been carried out on the OVO application is positive. This research is expected to be able to provide important insights and information regarding user satisfaction with digital wallet applications. Apart from that, it is also hoped that this research can become a reference for subsequent research and further development related to the OVO application, with the aim of improving the user experience.

PT. Telkom Akses (PTTA) has constraints in the employee leave application management system, this is because the employee leave application process is still done manually and difficulties in determining the level of importance for employees who apply for leave. Therefore, a web-based application was built using FMCDM and the SAW Method. This study aims to improve efficiency and effectiveness in managing the employee leave application system by utilizing the Fuzzy Multi-Criteria Decision Making (FMCDM) approach using the Simple Additive Weighting (SAW) method at PT. Telkom Akses (PTTA). In order to make it easier for employees to carry out the deduction process and obtain complete and detailed information and rules related to deductions, the personnel department is expected to be able to create an online information system. To help with this, one of the fields of technology that can be utilized is soft computing technology. There are various methods that can be used to solve problems, one of which is the Fuzzy Multi Criteria Decision Making (FMCDM) method and the Simple Additive Weighting (SAW) method. The results of the study indicate that the web-based application that has been designed can help solve the problems faced by PT. Telkom Akses Medan STO Simpang Limun in terms of managing the employee leave application system and helping to determine the level of importance and ranking for employees who apply for leave accurately and efficiently, and the results of the application of FMCDM and the SAW Method in determining employee leave permits are that out of 7 employees who apply for leave, 2 employees get the highest rating results. The conclusion of this study is to help decision makers in determining employees who get leave permits based on relevant and transparent assessments of each employee who applies for leave.

This research was conducted to analyze user satisfaction with the Netflix application using the UX Honeycomb method. The UX Honeycomb method is used to evaluate various aspects of user experience, such as usability, aesthetic value, sustainability, accessibility, satisfaction, and diversity. This study involved data collection through online surveys and interviews with active Netflix users. Data analysis was conducted using statistical techniques and qualitative interpretation. The UX Honeycomb method was employed to understand the essential aspects of user experience within the application. The results of this study are expected to provide valuable insights for other streaming service providers to enhance their service quality and create a better user experience. Additionally, the contribution of the UX Honeycomb methodology in assessing user satisfaction can serve as a foundation for further research in the context of digital entertainment applications.

BAPPEDA-LITBANG Tambrauw, a regional technical institution in Tambrauw Regency, Southwest Papua, faces challenges in data management related to data integration and access. This condition hampers the planning and decision-making process there. This research aims to design a web-based data management system that can integrate various types of data from multiple sources, making it easier to access and analyze data in the agency. The prototype method was used in developing this system through problem identification, needs analysis, system design, implementation, testing, and improvement and evaluation. The research results show that the proposed web-based data management information system can overcome the challenges of limited data access and lack of data integration and support regional development that is more structured and responsive to community needs. In addition, this system can be a reference for developing systems in other government institutions with similar characteristics and challenges.

Artificial ripening methods use calcium carbide (carbide) which often leaves harmful residues on the mango fruit. This research designs a classification tool for carbite and non-carbite mango fruit using the Android-based InceptionV3 Convolutional Neural Network method. The mango fruit image dataset consists of 1622 images (881 images of carbite mangoes and 811 images of non-carbite mangoes) used to train and test the model. The testing process is done by implementing the model on a Raspberry Pi B+ connected to a camera pi to take pictures of mangoes at a distance of 30 cm. The results showed that the CNN model developed achieved an average accuracy of 94.4% in classifying carbitan and non-carbitan mangoes. This result shows that the classification tool designed can provide significant benefits for farmers, traders, and consumers in ensuring marketed quality.

This research employs social media (Twitter) to apply sentiment analysis ascertain the degree of public satisfaction with the Bulukumba tourist attraction. Unstructured text data is a major challenge in sentiment analysis. For this reason, implementing the Naïve Bayes algorithm is an effective approach for conquering this challenge because of its ability to handle text data well. This study aims to evaluate the performance of multinomial Naïve Bayes by testing a combination of minimum document frequency (min-df) and maximum document frequency (max-df) parameter values in determining the level of accuracy. This analysis stage includes collecting data from Twitter related to the Bulukumba tourist attraction. Preprocessing carried out includes data cleaning, casefolding, text normalization, tokenization, stopword removal, and stemming. Feature extraction using Count Vectorizer and TF-IDF weighting. The process ends with 10-Fold Cross-Validation by separating the data into training data and test data for sentiment analysis classification, as well as evaluation using the Confusion Matrix. In this research, there are 10 test scenarios with various combinations of min-df and max-df. The values of employed min-df consists of 0.001, 0.002, 0.005, 0.01, 0.02 and max-df consists of 0.5 and 0.8. The results of implementing Multinomial Naïve Bayes in this test show that classification accuracy increases with effective min-df and max-df parameter settings. The greatest accuracy was 0.7910 in testing a combination of min-df parameter values of 0.001 and max-df 0.8. Meanwhile, the average accuracy for each test was obtained the highest value of 0.7272 with min-df of 0.002 and max-df of 0.5 and 0.8 respectively.

The school management information system (SIAHDU) is an application managed by the IT department of a Vocational High School in Salatiga City. This application is an application of SI/IT in the education sector which was created with the aim of making school business processes more effective and efficient, such as administrative activities for paying tuition fees, managing grades and report cards, violation points, attendance and student biodata that can be accessed by teachers and students. With the convenience provided, it cannot be denied that risks will always arise both internally and externally. Based on this, risk management activities need to be carried out to minimize risks that might hamper and stop the system's business processes. In this research, the ISO 31000:2018 framework is used as a risk analysis assessment guide. The stages used are divided into risk assessment and mitigation stages so that it is hoped that they can minimize and overcome existing risks. The aim of this research is to carry out risk assessments and risk mitigation in school management information system applications using ISO 31000:2018. The results of the day of research that was carried out contained 25 risk opportunities, three of which were at a high level, fourteen were at a medium level, eight were at a low level. It is hoped that the results of this risk management documentation will become a reference for schools to implement new policies to minimize risk opportunities Keywords: risk management, ISO 31000:2018, risk analysis

Health centers as health service providers have an important role in ensuring adequate drug availability for the community. However, drug management in health centers often faces obstacles, including the use of manual methods in stock monitoring, which can lead to unavailability or accumulation of unused drugs. This study aims to improve the efficiency of drug management in health centers through the application of the K-Means Clustering method. This method is used to group drug stocks into three main clusters: heavy drugs, moderate drugs, and light drugs. With this grouping, it is expected that pharmacists can more easily determine the type of drug, monitor drug availability in a timely manner, and manage drug procurement according to patient needs. Research methods include literature studies, data collection and analysis, system modeling design, and system testing and evaluation. The results of this study are expected to improve the efficiency of drug management in health centers, so that health services to the community can be more optimal. The results of testing using the Silhouette Coefficient (SC) method produced an average SC of 0.97 which means strong structure, so it can be concluded that it has a strong structure.

One of the activities that is routinely held during the learning process is filling out questionnaires by parents to determine the quality of Tadika CERIA education and services. The results of this questionnaire were then analyzed using the Spearman Rank Correlation method. This study aims to apply correlation analysis using Python to evaluate student satisfaction with the learning location at Tadika CERIA. Utilizing a dataset of survey responses that includes variables such as cleanliness, quality of teaching, and communication, analysis was conducted to identify key factors influencing student satisfaction. This approach not only shows the practical application of Python in data processing and statistical analysis, but also provides valuable insights for school administrators in improving the quality of the learning environment. The results show a positive correlation between certain aspects and student satisfaction, underscoring the importance of a deep understanding of student preferences and needs in the development of a conducive learning environment. This research makes an important contribution in the context of early childhood education, offering a foundation for further research in an effort to improve the holistic educational experience.

Technology that continues to develop indirectly forces people to adapt to these developments. The vital role of technology is becoming increasingly felt during the COVID-19 pandemic when all world activities are paralyzed and only allowed to communicate online. However, the enormous benefits of technology are also directly proportional to the risks that may occur. Therefore, IT Risk Management is needed to mitigate potential sources of threat. This research aims to analyze IT risk management by measuring the level of capability, gap analysis, and providing recommendations for improvement using the COBIT 2019 framework to support PT XYZ's work performance and IT security. Researchers used qualitative methods with data collection techniques through observation, interviews, and questionnaires. The results showed that the risk management domain that was the research focus EDM03, APO12, APO13, and DSS05 had a gap between the expected capabilities and what was happening in the company. Therefore, improvement recommendations are needed, such as determining the level of IT risk and socializing it with stakeholders, recording IT risk events, building an Information Security Management System (ISMS), implementing a network filtering mechanism, and regularly evaluating information about potential new threats by reviewing product security and vendor or third-party services.

Tsunamis have the potential to have a large impact on the environment, therefore early detection and preparation for tsunami need to be carried out to reduce the impact of casualties and losses incurred. This research aims to predict tsunami events due to large earthquakes in Indonesia as a form of early detection. The optimized neural network method is used in research to classify tsunami events in Indonesia in 2000-2023 for large earthquakes with strength more than 5 magnitudes. The research results show that the neural network structure formed consists of an input layer, a hidden layer, and an output layer. The results of the evaluation of the neural network model with SMOTE obtained an accuracy value of 99.43%, precision of 96.31%, and an F1 score of 97.86%, which means the resulting model is good. Therefore, an optimized neural networks can be applied as a warning system in various regions to detect potential tsunami events in the future.

The Wild Brain Workshop (TWBW) is a custom culture community in Medan that was founded in 2011. This community started from a custom workshop which then developed into a wider community with a focus on custom motorbikes, music and lifestyle. TWBW, as one of the well-known custom motorbike workshops in the city of Medan, of course gets lots of orders from various custom motorbike lovers. This research was created to create a mobile application for ordering custom motorbike packages by implementing CRM (Customer Relationship Management). The problem formulation in this research is designing an effective mobile application for ordering custom motorbike packages and implementing CRM to improve relationships with customers. The aim of creating this application is so that you can easily view the various custom motorbike packages available, see detailed specifications and prices, and place orders directly through the application. The implementation of CRM in this application is found in the chat feature and customer service menu. By implementing CRM (Customer Relationship Management), it is hoped that TWBW can manage relationships with customers, by utilizing technology to maximize communication and marketing. Through the development of this application, it is hoped that the use of this technology can effectively improve the ordering process.

A prescription is a written request from a doctor to a pharmacist, as not everyone can know the dosage or type of a particular drug, especially patients who need a prescription for the drug must be kept secret. Rapid technological advances can have an impact on all sectors, both private and government, including the medical field. One of the medical services that utilizes IT is to send prescription messages electronically to pharmacists in response to doctors' requests. The many misuse of prescription drugs by irresponsible people and misreading prescription drugs by pharmacists can be fatal for patients, so a solution is needed to overcome these problems. The purpose of this study is to create an encrypted electronic recipe application using the Hill Cipher method. This research method generally starts from data collection, data analysis and encryption model development. Applications designed with the Hill Cipher Algorithm are developed with modified algorithm keys using postal code patterns as the matrix keys, this aims to achieve the maximum level of security. The results of the system functionality test using the black box method obtained normal results for all system test scenarios. Validity testing yields valid results. The final test, through questionnaire testing, obtained a good level of system feasibility, namely an average level of Service of 83%, Features of 78% and Performance of 81%. Overall, the system has given a good performance score as the accuracy of the system is above 70%.

In the culinary and health fields, spices are known to play a significant role. However, differentiating and identifying spices can often be challenging, especially for students or individuals with impaired sense of smell and taste. Our research builds upon our previous study, which involved designing a spice classification model using the pre-trained EfficientNetB0 model, yielding a testing accuracy of 48%. This study designs and develops an application for classifying images of spices from the Zingiberaceae family using the Rapid Application Development (RAD) method, aimed at addressing the difficulties of manual spice identification. Testing results using a black box technique indicate that the designed application performs well in basic tasks such as opening the interface without significant errors, responding promptly to functional buttons, and displaying user-inputted image results. However, in one of the testing scenarios, the application struggled to accurately classify certain spice images, indicating the need for improvements in the model used for more precise spice image classification.