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Salah satu permasalahan utama yang sedang dihadapi oleh Kementrian Kelautan dan Perikanan Republik Indonesia (KKP) adalah maraknya kejadian Illegal, Unreported, and Unregulated (IUU) fishing yang terjadi pada perairan Indonesia. Kejadian ini menimbulkan banyak kerugian bagi Indonesia, terutama dalam aspek sosial, ekologi, dan ekonomi. Untuk mengatasi masalah ini, terutama unreported fishing, dirancanglah sebuah sistem yang dapat digunakan untuk memonitor penangkapan ikan, sekaligus melakukan deteksi dan klasifikasi terhadap jenis ikan hasil tangkapan di atas kapal. Sistem dirancang menggunakan konsep object detection dan instance segmentation, dua bidang dari machine learning, menggunakan model YOLOv5 dan varian-variannya yang merupakan salah satu model dari keluarga YOLO (You Only Look Once) yang paling baik dari segi kecepatan dan akurasi. Dengan adanya sistem tersebut, diharapkan bahwa hasil tangkapan kapal di perairan Indonesia dapat bersifat lebih legal, teratur, dan sesuai dengan yang dilaporkan kepada KKP. Sistem terbaik dari penelitian ini dihasilkan menggunakan model instance segmentation yang mendapatkan nilai mAP50 0,834, mAP50-95 0,544, F1-score 0,848, dan kecepatan inferensi 232,6 fps untuk partisi validation, dan mAP50 0,797, mAP50-95 0,531, F1-score 0,802, dan kecepatan inferensi 250,0 fps untuk partisi testing pada hasil bounding box, serta nilai mAP50 0,739, mAP50-95 0,36, F1-score 0,789, dan kecepatan inferensi 232,6 fps untuk partisi validation, dan mAP50 0,711, mAP50-95 0,335, F1-score 0,746, dan kecepatan inferensi 250,0 fps untuk partisi testing pada hasil segmentation mask. Selain itu, model tersebut juga mendapatkan akurasi 60% pada tahapan perbandingan dengan model object detection.

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One of the main problems the Indonesian Ministry of Marine Affairs and Fisheries (KKP) is currently facing is the abundance of Illegal, Unreported, and Unregulated (IUU) fishing instances happening in Indonesian waters. This phenomenon creates a lot of problems for Indonesia, mainly in the social, ecological, and economical aspects. To overcome these problems, mainly unreported fishing, a system that can be used to not only monitor the fishing process, but also to detect and classify the types of fish that are caught by that boat was created. This system is based on object detection and instance segmentation, both fields of machine learning, using the YOLOv5 model and its variants, which are some of the fastest and most accurate models from the YOLO (You Only Look Once) family. With this system, it is hoped that fish caught in Indonesian waters can be more legitimate, regulated, and reported correctly to the KKP. The best system from this research is created using an instance segmentation model with mAP50 0.834, mAP50-95 0.544, F1-score 0.848, and inference speed 232.6 fps for validation scores, and mAP50 0.797, mAP50- 95 0.531, F1-score 0.802, and inference speed 250.0 fps for testing scores on the bounding box results, as well as mAP50 0.739, mAP50-95 0.36, F1-score 0.789, and inference speed 232.6 fps for validation scores, and mAP50 0.711, mAP50-95 0.335, F1-score 0.746, and inference speed 250.0 fps on the segmentation mask results. The model also achieved an accuracy of 60% in the comparison phase against the object detection model.

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"Dengan iklim bisnis yang penuh persaingan, organisasi perlu melakukan inovasi dan bekerja secara cepat. Untuk memenuhi tuntutan tersebut, banyak organisasi yang menggunakan metodologi agile dalam melakukan pengembangan sistem. Metodologi ini diketahui fleksibel, sehingga mampu menghadapi perubahan mendadak. Masalahnya, dengan kecepatan yang dimiliki metodologi agile, banyak pengetahuan yang harus dikelola dengan benar dan cepat pula. Maka dari itu, diperlukan KM (Knowledge Management) untuk membuat pengelolaan pengetahuan dalam praktik agile menjadi efektif. Berdasarkan masalah tersebut, penelitian ini bertujuan untuk mengetahui bagaimana KM dan metodologi agile dapat mendukung proses pengembangan yang ada di organisasi. Penelitian ini menggunakan pendekatan kualitatif dengan melibatkan 16 narasumber yang berasal dari 14 perusahaan berbeda. Narasumber berlatar belakang sebagai engineer, quality assurance, project/product manager, dan UI/UX designer. Dari hasil wawancara yang dilakukan, tim peneliti memetakan agile practices dan cloud services dengan KM processes dan KM foundation menggunakan model teoritis. Selain itu, dibuat juga KMS yang berisikan 27 fitur yang berguna bagi proses pengembangan sistem dan dapat membantu aktivitas KM. Kesuksesan organisasi dalam menjalankan proses pengembangannya akan bergantung pada semua aspek yang telah disebutkan, yaitu KM foundation, KM processes, agile practices, dan cloud services.

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With a competitive business climate, organizations need to innovate and work quickly. To meet these demands, many organizations use agile methodologies in developing systems. This methodology is known to be flexible, so it can deal with sudden changes. The problem is, with the speed that agile methodology has, a lot of knowledge must be managed properly and quickly. Therefore, KM (Knowledge Management) is needed to manage knowledge in agile practices effectively. Based on these problems, this study aims to find out how KM and agile methodologies can support the development processes in organizations. This study used a qualitative approach involving 16 interviewees from 14 different companies. The resource persons have backgrounds as engineers, quality assurance, project/product managers, and UI/UX designers. From the results of interviews conducted, the research team mapped agile practices and cloud services with KM processes and KM foundation using a theoretical model. In addition, a KMS was also created which contained 27 features that were useful for the system development process and could assist KM activities. The success of an organization in carrying out its development process will depend on all the aspects mentioned, namely the KM foundation, KM processes, agile practices, and cloud services."

"This book provides foundations for software specification and formal software development from the perspective of work on algebraic specification, concentrating on developing basic concepts and studying their fundamental properties. This book contains five kinds of material: the requisite mathematical foundations; traditional algebraic specifications; elements of the theory of institutions; formal specification and development; and proof methods. "

"Dengan adanya revolusi Industri 4.0, pengembangan sistem monitoring menjadi tinggi dan sektor otomotif lah yang paling mendapatkan keuntungannya. Meskipun teknologi di bidang otomotif terus berkembang, ban tetap tidak tergantikan. Sebagai satu-satunya titik kontak dengan jalanan, kondisi ban hanya diawasi dengan tire pressure monitoring system, meskipun kondisi ban yang tidak optimal meningkatkan peluang terjadinya kecelakaan, ditambah hanya satu dari tiga pengemudi tidak mengetahui mengenai kapan sebuah ban harus diganti. Penelitian ini dilakukan dengan tujuan agar dapat membuat model matematis yang dapat mengestimasi sisa umur ban dengan baik. Untuk mendapatkan model matematis yang dapat digunakan, perlu melakukan eksperimen sebagai pembanding dan menggunakan data best practice sebagai acuan utama. Hasil analisa perbandingan akan dijadikan acuan untuk implementasi di perangkat lunak berbasis Python. Hasil penelitian yang didapatkan adalah tingginya efek dari perbedaan kecepatan dan percepatan dalam eksperimen maupun pembuatan model. Model matematis yang didapatkan memiliki akurasi rata-rata sebesar 15% saat dibandingkan dengan hasil eksperimen. Perbedaan dapat terjadi karena kurangnya perawatan kendaraan, kondisi eksperimen yang memiliki banyak kondisi, akurasi alat ukur, serta kondisi dari ban itu sendiri. Model matematis memiliki akurasi yang paling dekat terhadap eksperimen, maka perangkat lunak menggunakan model matematis sebagai dasar kalkulasi yang didapatkan.

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With the Industry 4.0 revolution, the development of monitoring system increases and automotive sector reaps most of the benefits. Despite the development in automotive technology, tires are still essential and unchangeable. As the only contact point with the road beneath, tires’ conditions are only monitored with tire pressure monitoring system and nothing else, but only one in three people knows when to change into new tires. The research’s purpose is to develop a mathematical model that can estimate the tire remaining life accurately. In order to obtain an accurate mathematical model, and experiment is required in order verify the mathematical model, with best practice data used as the reference. The analysis result will determine which model is the most accurate to be used as the mathematical model for a Python based application. The result when comparing the mathematical model with the experiment is Universitas Indonesia that there is a difference of about 15%. The difference may be caused by lack of maintenance, too many driving conditions, measuring tool accuracy, as well as the tires themselves. The initial mathematical model poses the most accurate result, hence why the application will use the mathematical model as its main function."

"Insiden cedera tertusuk jarum suntik CJS pada mahasiswa keperawatan masih tinggi. Penelitian ini bertujuan menghasilkan Model Pembelajaran berbasis Keselamatan MPbK untuk membentuk perilaku mencegah CJS mahasiswa keperawatan di wahana praktik. Desain penelitian ini adalah quasi experimental pre and post-test with control group. Penelitian terdiri dari dua tahapan yaitu penyusunan dan pengujian MPbK. Penyusunan MPbK dilakukan berdasarkan hasil systematic review dan focus group discussion pada 10 pembimbing klinik. Pengujian MPbK dilakukan pada 165 mahasiswa praktik profesi keperawatan dengan membandingkan perubahan pengetahuan, sikap, dan intensi perilaku. Responden dikelompokkan dalam 4 kelompok yaitu 26 mahasiswa mendapatkan MPbK 1 intervensi individu reedukasi pengingat harian, intervensi kelompok, dan organisasi ; 72 mahasiswa mendapat MPbK 2 intervensi individu reedukasi dan organisasi , 31 mahasiswa mendapat MPbK 3 intervensi kelompok dan organisasi , dan 36 mahasiswa tanpa intervensi. Intervensi individu meliputi reedukasi dan pengingat harian pencegahan CJS melalui pesan singkat teks dan video. Intervensi kelompok meliputi pengingat dan contoh peran dari pembimbing klinik yang telah dilatih pencegahan CJS. Intervensi organisasi meliputi kontrak program keselamatan dan penyediaan fasilitas penunjang pencegahan CJS. Penelitian tahap 1 menghasilkan MPbK yang diuji pada penelitian tahap 2. Hasil uji GLM-RM pada penelitian tahap 2 didapatkan bahwa pengetahuan dan sikap mencegah CJS dapat ditingkatkan secara signifikan menggunakan MPbK 1, 2, dan 3 p

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Needle Stick Injury NSI incident in nursing student is constantly high. This research aimed to develop Safety based Learning Models MPbK in Indonesia to shape preventive behaviors of NSI among nursing students during clinical practices. Quasi experimental pre and post test design with control group was employed in this study. The study comprised two stages MPbK development and testing stages. The during the first stage, systematic reviews and a focus group discussion with 10 clinical instructors were conducted to generate MPbK. While, the testing stage was performed to measure the changes in students rsquo knowledge, attitudes, and intention before and after the implementation of MPbK. A sample of 165 nursing professional program students was selected for the second stage, dividing into 4 main groups 26 students participated in MPbK1 individual, group, and organizational interventions , 72 students participated in MPbK2 individual and organizational interventions , 31 students participated in MPbK3 group and organizational interventions , and 36 students received no interventions. Individual interventions comprised re education and daily reminders through short message and video. Group interventions included role model clinical instructors whereas organizational interventions were safety programs contract between the university and hospitals, along with the provision of appropriate infrastructure and facilities to promote safety. Results of GLM RM analysis demonstrated the use of MPbK1, 2, and 3 significantly increased the knowledge and atitudes of students p 0,001 , the intention of student behavior to prevent NSI can be increased, but not yet significan p 0,110 0,993 . NSI incidents can be reduced using MPbK1 zero incident . The study suggested nursing educational institutions, hospitals and nursing professional organizations to use MPbK as a reference to develop policies of NSI prevention."

"The majority of 0D/1D knock models available today are known for their poor accuracy and the great effort needed for their calibration. Alexander Fandakov presents a novel, extensively validated phenomenological knock model for the development of future engine concepts within a 0D/1D simulation environment that has one engine-specific calibration parameter. Benchmarks against the models commonly used in the automotive industry reveal the huge gain in knock boundary prediction accuracy achieved with the approach proposed in this work. Thus, the new knock model contributes substantially to the efficient design of spark ignition engines employing technologies such as full-load exhaust gas recirculation, water injection, variable compression ratio or lean combustion.Contents: Experimental Investigations and Thermodynamic Analysis Unburnt Mixture Auto-Ignition PredictionKnock Occurrence CriterionKnock Model Validation"

"Telemedicine telah menjadi teknologi baru karena mereka menawarkan layanan kesehatan jarak jauh untuk pasien yang sakit atau mereka yang khawatir akan terkena penyakit. Lebih lanjut, telemedicine dapat memberikan perawatan rutin tanpa risiko tertular Covid-19. Meskipun pengobatan jarak jauh menawarkan banyak potensi manfaat, tantangannya adalah mendorong orang untuk menggunakannya. Penelitian terkait adopsi telemedicine di Indonesia masih terbatas, sehingga masih kurangnya pemahaman mengenai niat perilaku mereka dalam menggunakan telemedicine. Salah satu teori yang paling banyak digunakan untuk menjelaskan adopsi telemedicine adalah Unified Theory of Acceptance and Use of Technology (UTAUT). Namun, variabel jenis kelamin dan usia belum pernah diterapkan dalam model UTAUT untuk menganalisis perilaku penggunaan telemedicine, khususnya untuk kasus di Indonesia setelah masa wabah Covid-19. Selain itu, penelitian ini menunjukkan pentingnya kedua variabel dalam konteks perawatan kesehatan yang meningkat karena banyaknya kebutuhan. Survei dilakukan dengan menyebarkan kuesioner online melalui Google Forms kepada 139 responden Indonesia yang pernah menggunakan telemedicine. Hasil penelitian menunjukkan bahwa ekspektasi kinerja, pengaruh sosial, dan kondisi fasilitas berpengaruh signifikan terhadap niat perilaku menggunakan telemedicine. Ekspektasi usaha tidak berhubungan signifikan dengan niat perilaku karena gagal mewakili penilaian subyektif pengguna bahwa telemedicine akan mudah dan tanpa usaha. Selain itu, Ekspektasi Kinerja, Ekspektasi Upaya, Pengaruh Sosial, dan Kondisi Fasilitasi tidak dipengaruhi secara signifikan oleh variabel moderasi jenis kelamin dan usia. Untuk Implikasi Manajerial dapat menjadi sarana bagi pengembang aplikasi startup. Temuan ini juga menunjukkan bahwa penyedia telemedicine harus mengelola harapan kinerja penggunanya, memfasilitasi kondisi, dan terutama pengaruh sosial karena itu adalah nilai tertinggi untuk meningkatkan niat menggunakan telemedicine.

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Telemedicine has become an emerging technology since they offer remote healthcare services for infected patients or those who are worried about being infected. Furthermore, telemedicine can provide routine care without the risk of contracting Covid-19. Although telemedicine offers many potential benefits, the challenge was to encourage people to use them. Research related to telemedicine adoption in Indonesia is still limited, so there is still a lack of understanding regarding their behavior intentions in using telemedicine. One of the most widely used theories to explain telemedicine adoption is the Unified Theory of Acceptance and Use of Technology (UTAUT). However, gender and age variables have never been applied in the UTAUT model to analyze telemedicine use behavior, especially for cases in Indonesia after the Covid-19 outbreak. In addition, this research points out the importance of both variables in the healthcare context increasing the need for examining this feature. The survey was conducted by distributing online questionnaires via Google Forms to 139 Indonesian respondents who have used telemedicine. The results show that performance expectancy, social influence, and facilitating conditions significantly affect behavior intention to use telemedicine. Effort Expectancy is not significantly associated with behavioral intention since it fails to represent the user's subjective assessment that telemedicine will be easy and effortless. Moreover, Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions is not significantly affected by both gender and age moderating variables. For the Managerial Implication, it can be a means for startup application developers. The findings also suggest that telemedicine providers should manage their users’ performance expectancy, facilitating conditions, and mainly social influence since it was the highest value to increase the intention to use telemedicine."