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"Bikunku adalah aplikasi untuk mendukung transportasi bus kuning di Universitas Indonesia, dibuat oleh Alamsyah et al. pada tahun 2022 yang melakukan tracking lokasi terhadap bikun secara real-time. Sistem awal dibuat dengan React, WebSocket, dan PostgreSQL, namun kurang optimal dalam mengirim data lokasi bikun yang banyak. Penelitian ini bertujuan meningkatkan performa sistem dengan teknologi baru, seperti gRPC dengan Kafka untuk komunikasi backend, Firebase Cloud Firestore untuk database real-time, dan Flutter untuk aplikasi mobile. Hasil pengetesan menunjukkan peningkatan performa sistem gRPC-Kafka sebesar 96% dalam response time dan 216% dalam throughput dibandingkan sistem lama. Sistem Firebase juga menunjukkan peningkatan, dengan response time lebih cepat 91% dan throughput 127% lebih baik. Sistem Flutter terintegrasi dengan gRPC-Kafka memberikan kinerja yang lebih baik pada Android, dengan peningkatan 27% dalam CPU usage, 18% max CPU usage, 42% memory usage, dan 33% rendering speed. Pada iOS, sistem juga lebih baik dalam memory usage (40%), FPS (28%), dan rendering speed (16%), meskipun CPU usage dan max CPU usage sistem lama unggul sedikit (9% dan 0,3%).

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Bikunku is an application to support the bus transportation at the University of Indonesia called bikun, created by Alamsyah et al. in 2022, which tracks the location of bikun in real-time. The initial system, built with React, WebSocket, and PostgreSQL, was less than optimal in handling the large volume of bus location data. This research aims to enhance system performance with new technologies such as gRPC with Kafka for backend communication, Firebase Cloud Firestore for real-time database, and Flutter for the mobile application. Testing results showed a performance increase in the gRPC-Kafka system of 96% in response time and 216% in throughput compared to the old system. The Firebase system also showed improvements, with a 91% faster response time and a 127% better throughput. The Flutter system integrated with gRPC-Kafka performed better on Android, with increases of 27% in CPU usage, 18% in max CPU usage, 42% in memory usage, and 33% in rendering speed. On iOS, the system also improved in memory usage (40%), FPS (28%), and rendering speed (16%), although the old system was slightly better in CPU usage and max CPU usage (9% and 0.3%)."

"Bikunku merupakan suatu aplikasi penunjang informasi bis kuning (bikun); sarana transportasi di lingkungan Universitas Indonesia; yang dibuat oleh Alamsyah et al. melalui penelitiannya pada tahun 2022. Salah satu fitur penting yang ditawarkan dalam aplikasi ini adalah tracking lokasi bikun yang sedang beroperasi secara real-time. Meskipun secara keseluruhan sistem ini dapat menjalankan tugas- nya melakukan tracking lokasi bikun, sistem yang menggunakan frontend React, komunikasi WebSocket, dan database PostgreSQL ini kurang optimal untuk menangani data lokasi yang dikirim oleh driver bikun dan dibaca oleh ribuan sivitas akademik Universitas Indonesia. Penelitian ini bertujuan melakukan improvement berupa peningkatan performa pada sistem tracking bikun pada aplikasi Bikunku yang meliputi pengukuran end-to-end response time, throughput, CPU usage, memory usage, FPS dan rendering speed. Penelitian terdiri dari pengembangan dari sisi backend protokol komunikasi menggunakan gRPC dengan Kafka, sisi database menggunakan Firebase Cloud Firestore sebagai Realtime Database pada backend, dan sisi frontend menggunakan Flutter sebagai aplikasi mobile. Implementasi frontend Flutter pada akhirnya diinkorporasikan dengan pilihan implementasi backend dengan hasil performa yang terbaik. Dengan pengembangan menggunakan teknologi tersebut, improvement yang dilakukan pada penelitian ini meliputi pengubahan cara penyaluran data lokasi tracking dan database dari sistem polling menjadi sistem pushing, pengubahan arsitektur sistem yang lebih performant, digunakannya protokol komunikasi yang lebih unggul, perbaikan implementasi pada autentikasi driver sebagai salah satu penyebab bottleneck, pengubahan aplikasi menjadi mobile app, dan digunakannya implementasi maps yang lebih siap untuk production. Pengetesan dilakukan dengan load testing membandingkan performa masing-masing sistem implementasi baru terhadap sistem terdahulu Alamsyah. Skenario pengetesan sistem backend dan database meliputi request pengiriman lokasi oleh 11 driver bikun, disertai 1800 concurrent user di sisi client untuk membaca simulasi data lokasi terbaru bikun yang beroperasi. Sementara pada sisi frontend dilakukan pengetesan dengan resource profiling dan observasi terhadap simulasi bikun yang berjalan di frontend. Hasil pengetesan menunjukkan sistem gRPC-Kafka lebih cepat sebesar 96% dengan throughput yang dihasilkan lebih baik 216% dibandingkan dengan sistem Alamsyah, sistem Firebase lebih cepat sebesar 91% dengan throughput yang dihasilkan lebih baik 127% dibandingkan sistem Alamsyah. Dari hasil yang didapat, sistem gRPC-Kafka kemudian dipilih sebagai sistem backend yang diinkorporasikan dengan implementasi Flutter. Hasil pengetesan sistem Flutter dengan gRPC-Kafka mendapatkan hasil yang lebih baik pada OS Android di semua skenario dengan peningkatan performa metrik CPU usage, max CPU usage, memory usage, dan rendering speed sebesar 27%, 18%, 42%, dan 33%. Sistem Flutter dengan gRPC-Kafka mayoritas lebih baik pada OS iOS di semua skenario, yakni pada metrik memory usage, FPS, dan rendering speed dengan peningkatan performa sebesar 40%, 28%, dan 16%. Sementara dari segi CPU usage dan max CPU usage, sistem Alamsyah lebih baik sebesar 9% dan 0,3% dari sistem Flutter dengan gRPC- Kafka.

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Bikunku is an information system application for bikun, a bus transportation facility within the University of Indonesia environment, developed by Alamsyah et al. through their research in 2022. One of the important features offered in this application is real-time tracking of the bikuns' location. Although the overall system is capable of tracking the bikun's location, the system, which utilizes React for the frontend, WebSocket for communication, and PostgreSQL for the database, it is not optimized to handle the location data sent by bikun drivers and accessed by thousands of University of Indonesia stakeholders.

This research aims to improve the performance of the bikun tracking system in the Bikunku application, including measuring end-to-end response time, throughput, CPU usage, memory usage, FPS, and rendering speed. The research consists of the development of backend communication protocol using gRPC with Kafka, development of backend using Firebase Cloud Firestore as Realtime Database, and development of the frontend mobile application using Flutter. The implementation of Flutter frontend is then integrated with the best performing backend implementation.

With the development using technologies listed, improvements made in this research include changing the method of location tracking data delivery and database from a polling system to a pushing system, modifying the system architecture for better performance, utilizing superior communication protocol, improving the implementation of driver authentication as one of the bottleneck causes, transforming the application into a mobile app, and utilizing a more production-ready maps implementation. Load testing is conducted to compare the performance of each new implementation with Alamsyah's previous system.

The testing scenarios for the backend and database systems involve location request submissions by 11 bikun drivers, along with 1800 concurrent users on the client side to simulate reading the latest location data of operating bikuns. On the frontend side, testing is performed using resource profiling and observation of the running bikun simulations.

The test results show that the gRPC-Kafka system is 96% faster with a 216% better throughput compared to Alamsyah's system, while the Firebase system is 91% faster with a 127% better throughput compared to Alamsyah's system. Based on these findings, the gRPC-Kafka system is then chosen as the backend system to be integrated with the Flutter implementation.

The testing results of Flutter with gRPC-Kafka demonstrate better performance on Android OS in all scenarios, with improvements in CPU usage, max CPU usage, memory usage, and rendering speed by 27%, 18%, 42%, and 33%, respectively. The Flutter with gRPC-Kafka system performs better on iOS OS in all scenarios for the majority, which are in terms of memory usage, FPS, and rendering speed, with performance improvements of 40%, 28%, and 16%, respectively. However, in terms of CPU usage and max CPU usage, the Alamsyah system performs better by 9% and 0.3% to the Flutter with gRPC-Kafka system."

"Bikunku merupakan suatu aplikasi penunjang informasi bis kuning (bikun); sarana transportasi di lingkungan Universitas Indonesia; yang dibuat oleh Alamsyah et al. melalui penelitiannya pada tahun 2022. Salah satu fitur penting yang ditawarkan dalam aplikasi ini adalah tracking lokasi bikun yang sedang beroperasi secara real-time. Meskipun secara keseluruhan sistem ini dapat menjalankan tugas- nya melakukan tracking lokasi bikun, sistem yang menggunakan frontend React, komunikasi WebSocket, dan database PostgreSQL ini kurang optimal untuk menangani data lokasi yang dikirim oleh driver bikun dan dibaca oleh ribuan sivitas akademik Universitas Indonesia. Penelitian ini bertujuan melakukan improvement berupa peningkatan performa pada sistem tracking bikun pada aplikasi Bikunku yang meliputi pengukuran end-to-end response time, throughput, CPU usage, memory usage, FPS dan rendering speed. Penelitian terdiri dari pengembangan dari sisi backend protokol komunikasi menggunakan gRPC dengan Kafka, sisi database menggunakan Firebase Cloud Firestore sebagai Realtime Database pada backend, dan sisi frontend menggunakan Flutter sebagai aplikasi mobile. Implementasi frontend Flutter pada akhirnya diinkorporasikan dengan pilihan implementasi backend dengan hasil performa yang terbaik. Dengan pengembangan menggunakan teknologi tersebut, improvement yang dilakukan pada penelitian ini meliputi pengubahan cara penyaluran data lokasi tracking dan database dari sistem polling menjadi sistem pushing, pengubahan arsitektur sistem yang lebih performant, digunakannya protokol komunikasi yang lebih unggul, perbaikan implementasi pada autentikasi driver sebagai salah satu penyebab bottleneck, pengubahan aplikasi menjadi mobile app, dan digunakannya implementasi maps yang lebih siap untuk production. Pengetesan dilakukan dengan load testing membandingkan performa masing-masing sistem implementasi baru terhadap sistem terdahulu Alamsyah. Skenario pengetesan sistem backend dan database meliputi request pengiriman lokasi oleh 11 driver bikun, disertai 1800 concurrent user di sisi client untuk membaca simulasi data lokasi terbaru bikun yang beroperasi. Sementara pada sisi frontend dilakukan pengetesan dengan resource profiling dan observasi terhadap simulasi bikun yang berjalan di frontend. Hasil pengetesan menunjukkan sistem gRPC-Kafka lebih cepat sebesar 96% dengan throughput yang dihasilkan lebih baik 216% dibandingkan dengan sistem Alamsyah, sistem Firebase lebih cepat sebesar 91% dengan throughput yang dihasilkan lebih baik 127% dibandingkan sistem Alamsyah. Dari hasil yang didapat, sistem gRPC-Kafka kemudian dipilih sebagai sistem backend yang diinkorporasikan dengan implementasi Flutter. Hasil pengetesan sistem Flutter dengan gRPC-Kafka mendapatkan hasil yang lebih baik pada OS Android di semua skenario dengan peningkatan performa metrik CPU usage, max CPU usage, memory usage, dan rendering speed sebesar 27%, 18%, 42%, dan 33%. Sistem Flutter dengan gRPC-Kafka mayoritas lebih baik pada OS iOS di semua skenario, yakni pada metrik memory usage, FPS, dan rendering speed dengan peningkatan performa sebesar 40%, 28%, dan 16%. Sementara dari segi CPU usage dan max CPU usage, sistem Alamsyah lebih baik sebesar 9% dan 0,3% dari sistem Flutter dengan gRPC- Kafka.

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Bikunku is an information system application for bikun, a bus transportation facility within the University of Indonesia environment, developed by Alamsyah et al. through their research in 2022. One of the important features offered in this application is real-time tracking of the bikuns’ location. Although the overall system is capable of tracking the bikun’s location, the system, which utilizes React for the frontend, WebSocket for communication, and PostgreSQL for the database, it is not optimized to handle the location data sent by bikun drivers and accessed by thousands of University of Indonesia stakeholders. This research aims to improve the performance of the bikun tracking system in the Bikunku application, including measuring end-to-end response time, throughput, CPU usage, memory usage, FPS, and rendering speed. The research consists of the development of backend communication protocol using gRPC with Kafka, development of backend using Firebase Cloud Firestore as Realtime Database, and development of the frontend mobile application using Flutter. The implementation of Flutter frontend is then integrated with the best performing backend implementation. With the development using technologies listed, improvements made in this research include changing the method of location tracking data delivery and database from a polling system to a pushing system, modifying the system architecture for better performance, utilizing superior communication protocol, improving the implementation of driver authentication as one of the bottleneck causes, transforming the application into a mobile app, and utilizing a more production-ready maps implementation. Load testing is conducted to compare the performance of each new implementation with Alamsyah’s previous system. The testing scenarios for the backend and database systems involve location request submissions by 11 bikun drivers, along with 1800 concurrent users on the client side to simulate reading the latest location data of operating bikuns. On the frontend side, testing is performed using resource profiling and observation of the running bikun simulations. The test results show that the gRPC-Kafka system is 96% faster with a 216% better throughput compared to Alamsyah’s system, while the Firebase system is 91% faster with a 127% better throughput compared to Alamsyah’s system. Based on these findings, the gRPC-Kafka system is then chosen as the backend system to be integrated with the Flutter implementation. The testing results of Flutter with gRPC-Kafka demonstrate better performance on Android OS in all scenarios, with improvements in CPU usage, max CPU usage, memory usage, and rendering speed by 27%, 18%, 42%, and 33%, respectively. The Flutter with gRPC-Kafka system performs better on iOS OS in all scenarios for the majority, which are in terms of memory usage, FPS, and rendering speed, with performance improvements of 40%, 28%, and 16%, respectively. However, in terms of CPU usage and max CPU usage, the Alamsyah system performs better by 9% and 0.3% to the Flutter with gRPC-Kafka system."

"ABSTRAKPenelitian ini bertujuan untuk menganalisis implementasi SIKP, menganalisis kinerja Ditjen Perbendaharaan dalam implementasi SIKP, serta meningkatkan kinerja SIKP dalam mendukung pelaksanaan kredit program pemerintah kepada sektor Usaha Mikro, Kecil, dan Menengah UMKM . Metode penelitian yang digunakan adalah deskriptif kualitatif dengan studi kasus pada Ditjen Perbendaharaan dengan melakukan analisis pengembangan sistem melalui pendekatan metode Framework for the Application of System Thinking FAST . Hasil penelitian menunjukkan bahwa implementasi SIKP pada tahun 2015 dan 2016 sudah mendukung kegiatan verifikasi terkait dengan fungsi ketepatan sasaran dan kebenaran tagihan, namun belum optimal dalam menjalankan fungsi percepatan pembayaran. Ditjen Perbendaharaan memiliki kinerja yang cukup baik sebagai Penyedia dan Pengelola SIKP. Namun demikian, masih diperlukan pengembangan sistem untuk meningkatkan kinerja SIKP dalam mendukung optimalisasi pelaksanaan kredit program pemerintah kepada UMKM, yaitu dengan meningkatkan keandalan sistem, mempermudah akses dan pengunggahan data, melakukan integrasi data untuk meningkatkan pengendalian internal, serta menciptakan fitur-fitur baru berupa komunikasi online dan penilaian perkembangan usaha/klasifikasi debitur yang dapat digunakan untuk mengukur keberhasilan kredit program pemerintah.

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ABSTRACTThis study aims to analyze the SIKP implementation, analyze the DG Treasury performance in the SIKP implementation, and improve the SIKP performance for supporting the implementation of government program credit to Micro, Small and Medium Enterprises MSMEs . This research used the descriptive qualitative method with case study on DG Treasury by Framework for the Application of System Thinking FAST method for the system development analysis. The results show that the SIKP implementation in 2015 and 2016 has supported the verification activities related to the function of target accuracy and correctness of the bill, but has not optimal in performing the acceleration of bill payment function. DG Treasury has good performance as a SIKP Provider and Manager. However, system development is needed to improve the performance of SIKP for supporting the optimization of government program credit implementation to MSMEs by improving system reliability, facilitating access and uploading data, integrating data to improve internal control, and creating new features of online communication and an assessment of business development debtor classification that can be used to measure the creditworthiness of government program credit."

"Penelitian ini berfokus pada peningkatan kinerja dalam kerangka 7'S Mc Kiney Satuan Tugas Airport Interdiction BNN yang berada di bandara udara internasional Soekarno-Hatta, Jakarta dalam melaksanakan pemberantasan penyalahgunaan dan peredaran gelap Narkoba Penelitian ini termasuk penelitian kualitatif dengan pendekatan deskriptif analitik. Model operasional menggunakan wawancara mendalam dengan informan pemangku kepentingan BNN, dan 19 orang anggota satgas yang mewakili masing-masing unit kerja. Satgas Airport Interdiction merupakan implementasi Keppres 17 tahun 2002 dan Perpes 83 tahun 2007 sebagai bentuk operasional pelaksanaan P4GN yang bertugas berkoordinasi dalam pengawasan pemberantasan, pencegahan peredaran gelap narkoba melalui bandara udara internasional. Penelitian ini didasari atas fokus masalah faktual karena masih ada kesenjangan antara mekanisme yang tertuang dalam aturan (Skep Ketua BNN) dengan implementasi di lapangan. Dari analisis terhadap hasil wawancara, disimpulkan bahwa : 1) Strategi yang digariskan oleh BNN dalam pembentuk Satgas Airport Interdiction adalah pengawasan terhadap penyalahgunaan dan peredaran gelap narkoba melalui bandara udara Internasional situasinya sangat mengkhawatirkan berkaitan dengan ketahanan nasional Indonesia. 2) Analisis Strategi, kurang dipedomaninya acuan pembentukan satgas atau Skep Ketua BNN untuk melaksanakan P4GN. 3) Analisis Struktur, menguatkan faktor komunikasi antara pimpinan dan barahan harus dieleminir. 4) Analisis Sistem, manajemen sistem harus memasukkan anggaran yang kuat untuk operasional dan unsur-unsur yang bersifat pengawasan melekat (waskat) pada setiap jenjang organisasi, diikuti dengan budaya organisasi dan nilai-nilai kepercayaan serta rasa memiliki yang tinggi. 5) Analisis Staf, bahwa pemenuhan petugas yang profesional didukung oleh struktur kerja dari anggota Satgas Airport Interdiction yang sesuai dengan bidang kerja dan kewenangannya. 6) Analisis Gaya/ Style, bahwa pimpinan dapat menerapkan penggunaan waktu dan berperilaku (behave) dalam mencapai tujuan dari satgas. 7) Analisis Keahlian/ Ketrampilan, ternyata banyak harapan dari anggota Satgas untuk dilakukan pelatihan dan keterampilan internasional, dengan memanfaatkan mitra kerja sama Satgas (instansi pemerintah maupun penyelenggara jasa angkutan bandara). 8) Analisis Nilai kersamaan, mewujudkan sikap profesionalisme dengan berbagai pengetahuan dan keterampilan yang dimiliki oleh masing-masing satuan anggota satgas akan mendukung analitik masing unit kerja

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This study focuses on improving performance within the 7'S Mc Kiney framework of the BNN Airport Interdiction Task Force located at Soekarno-Hatta international airport, Jakarta in carrying out the eradication of drug abuse and illicit trafficking. The operational model uses in-depth interviews with BNN stakeholder informants, and 19 members of the task force representing each work unit. The Airport Interdiction Task Force is an implementation of Presidential Decree 17 of 2002 and Perpes 83 of 2007 as an operational form of P4GN implementation which is tasked with coordinating the eradication and prevention of illicit drug trafficking through international airports. This research is based on the focus of factual problems because there is still a gap between the mechanisms contained in the rules (Skepticism of the Head of BNN) and implementation in the field.

From the analysis of the results of the interviews, it was concluded that: 1) The strategy outlined by BNN in forming the Airport Interdiction Task Force was the supervision of drug abuse and illicit trafficking through international airports, the situation was very worrying related to Indonesia's national security. 2) Strategy analysis, lack of guidelines for the formation of a task force or the Skep of the Head of the National Narcotics Agency to implement P4GN. 3) Structural analysis, strengthening the communication factor between the leadership and materials must be eliminated. 4) System Analysis, system management must include a strong budget for operations and elements that are inherent in supervision (waskat) at every level of the organization, followed by organizational culture and values of trust and a high sense of belonging. 5) Staff analysis, that the fulfillment of professional officers is supported by the work structure of members of the Airport Interdiction Task Force in accordance with their field of work and authority. 6) Analysis of Style / Style, that the leader can apply the use of time and behave (behave) in achieving the goals of the task force. 7) Expertise/Skills Analysis, it turns out that there are a lot of expectations from members of the Task Force for international training and skills, by utilizing the cooperation partners of the Task Force (government agencies and airport transportation service providers). 8) Analysis of the value of cooperation, realizing a professional attitude with various knowledge and skills possessed by each member of the task force will support the analysis of each work unit."

"Tren pendapatan pasar logistik meningkat secara signifikan karena didorong oleh peningkatan kebutuhan masyarakat saat pandemi dan tren berbelanja secara daring. Oleh karena itu, industri logistik dituntut untuk terus berinovasi agar performa perusahaannya tetap terjaga dan kepuasan pelanggan dapat terus terpenuhi. Pengiriman barang dalam waktu yang singkat dan barang yang tetap terjaga kualitasnya merupakan nilai utama dalam pemenuhan kepuasan pelanggan. Peningkatan permintaan jasa juga dialami oleh oleh PT X Indonesia sebagai industri jasa Courier, Express, and Parcel (CEP) sehingga perusahaan perlu untuk meningkatkan efisiensi proses dan kinerja proses pergudangannya. Hal ini dapat dicapai dengan mengurangi pemborosan yang ada pada proses dan mengeliminasi aktivitas yang tidak memberikan nilai (non value added activity). Value stream mapping sebagai metode penerapan konsep lean memiliki tujuan untuk memetakan aliran material dan informasi dalam suatu proses. Dalam penelitian ini, value stream mapping dapat membantu untuk menggambarkan proses secara menyeluruh dan mengidentifikasi pemborosan pada proses pergudangan. Kemudian dilakukan analisis akar masalah menggunakan ishikawa diagram dan analisis risiko yang ditimbulkan dengan tools FMEA untuk menemukan pemborosan kritis dan merancang usulan perbaikan untuk mengurangi pemborosan tersebut. Hasil penelitian ini menunjukkan bahwa lead time proses pergudangan berkurang 37,9%, processing time berkurang 12,5%, dan value added ratio proses pergudangan meningkat menjadi 21,95%.

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The trend of logistics market revenue increased significantly because it was driven by the increase in people's needs during the pandemic and the trend of shopping online. Therefore, the logistics industry is required to continue to innovate so that the company's performance is maintained and customer satisfaction can be continuously met. Delivery of goods in a short time and goods that are maintained in quality are the main values in fulfilling customer satisfaction. The increase in demand for services was also experienced by PT X Indonesia as a Courier, Express, and Parcel (CEP) service industry, so the company needed to improve process efficiency and warehousing process performance. This can be achieved by reducing waste in the process and eliminating non-value added activities. Value stream mapping as a method of applying the lean concept has the aim of mapping the flow of material and information in a process. In this study, value stream mapping can help to describe the overall process and identify waste in the warehousing process. Then the root problem analysis is carried out using Ishikawa diagrams and analysis of the risks posed by FMEA tools to find critical waste and design improvement proposals to reduce the waste. The results of this study indicate that the lead time of the warehousing process is reduced by 37.9%, the processing time is reduced by 12.5%, and the value added ratio of the warehousing process is increased to 21.95%."

"

Seiring dengan perkembangan bidang computer vision terdapat lebih banyak solusi yang dapat diimplementasikan untuk bidang sehari-hari. Salah satu bidang yang paling erat dengan kegiatan sehari-hari adalah kegiatan mengkonsumsi makanan. Dalam memperhatikan pola makan, penting dilakukan proses mengidentifikasi jenis makanan yang dikonsumsi. Dengan memanfaatkan perkembangan model machine learning deteksi objek yang bekerja secara waktu langsung, YOLOv5 dapat digunakan untuk melakukan deteksi objek untuk dapat mengidentifikasi berbagai jenis makanan dalam suatu gambar. Dengan menggunakan YOLOv5, deteksi terhadap makanan yang kerap kali dikonsumsi oleh masyarakat Indonesia dapat dilakukan dan ditingkatkan akurasinya dengan pemrosesan gambar hingga mencapai nilai mAP 94,3%. 

Penggunaan implementasi model ini dalam aktivitas sehari-hari dapat memberikan nilai tambah kepada orang-orang yang ingin lebih memahami jenis makanan yang dikonsumsinya. Dari hasil pengujian user experience yang dilakukan terhadap aplikasi, hasil perbandingan terhadap benchmark mengindikasikan bahwa aplikasi memiliki kualitas penggunaan di atas rata-rata dengan nilai 1,37 untuk daya tarik, 1,58 untuk kejelasan, 1,23 untuk efisiensi, 1,38 untuk ketepatan, 1,13 untuk stimulasi, dan 1,01 untuk kebaruan.

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With the advent of computer vision there are more solutions that can be implemented in everyday life. One of the areas most closely related to daily activities is the activity of consuming food. In paying attention to diet, it is important to identify the type of food consumed. By leveraging the development of object detection machine learning models that work in real time, YOLOv5 can be used to perform object detection to identify different foods within a single image. By using YOLOv5, detection of foods that are often consumed by Indonesian people can be carried out and the accuracy is increased by image processing up to a value of mAP 94.3%.

The use of this model's implementation in daily activities can provide added value to people who want to better understand the types of food they consume. From the results of user experience testing carried out on the object detection application, the results of comparisons against benchmarks indicate that the application has above average usage quality with a value of 1.37 for attractiveness, 1.58 for clarity, 1.23 for efficiency, 1.38 for accuracy, 1.13 for stimulation, and 1.01 for novelty."

"Pendidikan berbasis komputer telah menjadi elemen kunci dalam transformasi pendidikan modern. Penggunaan teknologi komputer dalam pembelajaran telah membawa manfaat signifikan, termasuk aksesibilitas yang lebih baik, fleksibilitas waktu, dan peningkatan interaktivitas. Meskipun demikian, tantangan dalam meningkatkan partisipasi pengguna dalam aplikasi pendidikan berbasis komputer masih menjadi isu yang signifikan. Tingkat partisipasi yang rendah dapat menghambat efektivitas pembelajaran dan mengurangi dampak positif teknologi dalam dunia pendidikan. Penelitian ini bertujuan untuk menganalisis dan mengimplementasikan teknik gamifikasi sebagai strategi untuk meningkatkan partisipasi pengguna dalam aplikasi pendidikan berbasis komputer. Kami menggabungkan elemen-elemen gamifikasi seperti penghargaan, poin, tantangan, dan level ke dalam aplikasi pendidikan yang ada untuk merangsang partisipasi dan motivasi pengguna. Penelitian ini menggunakan pendekatan eksperimental dengan mengukur partisipasi pengguna sebelum dan sesudah penerapan teknik gamifikasi, serta mengumpulkan data tentang perubahan pemahaman materi dengan menghitung metrix perilaku. Lalu didapatkan hasil dengan menghitung matrix korelasi dengan jangkauan nilai -1 hingga 1, dengan artian, semakin mendekati 1 atau -1 maka hubungan tersebut semakin kuat. Pada bagian materi, keseluruhan nilai matrix korelasi memiliki nilai sekitar 0,3 yang memengaruhi secara tidak langsung pada setiap hubungan perhitungan metriknya. Sedangkan pada bagian soal, Task ease dengan hasil nilai memiliki nilai matrix korelasi tertinggi dengan nilai 0.925. Pada keseluruhannya bahwa Duolingo memiliki hasil yang lebih baik dibandingkan dengan Kahoot.

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Computer-based education has become a key element in the transformation of modern education. The use of computer technology in learning has brought significant benefits, including improved accessibility, flexibility in scheduling, and increased interactivity. Nevertheless, the challenge of increasing user participation in computer-based educational applications remains a significant issue. Low participation rates can impede the effectiveness of learning and diminish the positive impact of technology in the field of education. This research aims to analyze and implement gamification techniques as a strategy to enhance user participation in computer-based educational applications. We incorporate gamification elements such as rewards, points, challenges, and levels into existing educational applications to stimulate user participation and motivation. The research employs an experimental approach by measuring user participation before and after the implementation of gamification techniques and collecting data on changes in understanding of the subject matter by calculating behavioral metrics. Then the results are obtained by calculating the correlation matrix with a value range of -1 to 1, meaning, the closer to 1 or -1, the stronger the relationship. In the material section, the overall correlation matrix value has a value of around 0.3 which indirectly influences each metric calculation relationship. Meanwhile, in the questions section, Task ease with results has the highest correlation matrix value with a value of 0.925. Overall, Duolingo has better results compared to Kahoot."

"Pandemi global COVID-19 mendorong digitalisasi di seluruh dunia. Digitalisasi di berbagai aktivitas memicu pertambahan pengguna internet dengan pesat. Penambahan pengguna meningkatkan kebutuhan akan aplikasi pengecekan performa layanan internet. Pada saat ini, terdapat beberapa aplikasi untuk melakukan pengukuran performa internet, misalnya aplikasi Speedtest. Aplikasi tersebut menguji parameter konektivitas internet, seperti ping, jitter, serta kecepatan download dan upload. Namun, aplikasi itu tidak menyediakan penjelasan terkait istilah teknis yang dapat dipahami pengguna awam. Aplikasi Network Checker berbasis Java yang penulis kembangkan menggunakan fitur pengukuran performa internet dari LibreSpeed. Penulis juga menyediakan penjelasan mengenai istilah-istilah teknis tersebut dalam halaman bantuan. Selain itu, aplikasi ini memiliki fitur untuk mendeteksi persentase throughput. Fitur tambahan tersebut diterapkan dengan basis packet sniffer TCPDUMP. Besar data hasil tangkapan TCPDUMP per detiknya diubah menjadi persentase terhadap kecepatan download maksimal. Hasil pengujian Network Checker dengan aplikasi resmi LibreSpeed memiliki perbedaan di bawah 15% untuk ping dan download speed; perbedaan 21,9% dan 39,5% untuk jitter dan upload speed. Pengujian persentase throughput menunjukkan perbedaan hanya sebesar 0,29%. Pembandingan Network Checker dengan Speedtest memperlihatkan perbedaan ping dan download speed tidak lebih dari 8%; jitter dan upload speed sebesar 25,68% dan 58,16%. Aplikasi Network Checker unggul dalam segi fitur dibandingkan dengan Speedtest, namun dengan server yang terbatas.

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The global COVID-19 pandemic was driving digitalization around the world. Digitization in various activities triggered the rapid increase in internet users. In addition to users increases, the need for internet service performance checking applications also grew. Currently, there are several applications to measure internet performance, such as the Speedtest application. This application tests internet connectivity parameters, such as ping, jitter, and download and upload speeds. However, the application does not provide explanations related to technical terms that can be understood by ordinary users. The Java-based Network Checker application that the author developed uses the internet performance measurement feature of LibreSpeed. The author also provides explanations of these technical terms in the help page. Furthermore, this application has a feature to detect the throughput percentage. These additional features are implemented on the basis of the TCPDUMP packet sniffer. The size of the TCPDUMP captured data per second is converted into a percentage of the maximum download speed. The test results of Network Checker with the official LibreSpeed application have a difference of under 15% for ping and download speeds; difference of 21.9% and 39.5% for jitter and upload speed. Throughput percentage testing shows a difference of only 0.29%. Comparison of Network Checker with Speedtest shows the difference in ping and download speed is not more than 8%; jitter and upload speed of 25.68% and 58.16%. The Network Checker application excels in features compared to Speedtest, but with limited servers."

"The implementation of good governance principles particularly in the accountability principles in administrating a state constitutes a solution / an answer over the demand of a clean and good government. This effort has a very important meaning upon the life of nation state, as with the implementation of the accountability principles, it means that public organization must not only be responsible for its obligation to its superior position according to its hierarchy line but must also be able to be responsible for the mandate given by the people.

In order to be well recognized upon the implementation pattern of Inpres No 711999 on the Accountability of Government Institution Performance (AKIP) in the Area of Cabinet Secretariat Office, in this study, it is used an approach as what stated by Peters and Waterman, i.e. by analyzing 7-dimension basis of managerial activities. The seven dimensions abovementioned are: strategy, structure, system, style, (style of leadership), staff, skill, and shared value. Meanwhile the methodology of study which is applied in this academic work /research is descriptive quantitative. In this academic work it applies study case with a sample of population, where the populations here are the staff who work in the core area of Cabinet Secretariat. In this case the sample or respondents having been collected are as many as 61 persons. The primary data collection through observation and close and open questionnaires. The collection of secondary data through literature study. The supporting equipment used in analyzing data questionnaire is the Percentage of Categorical Data Frequency Tables.

From the result of study it can be identified that, the implementation of Inpres on AKIP is relatively not optimal or not improved. The main obstacle of this implementations is the weakness of organizational culture or climate. Even though the result of study/analysis shows that the scope of strategy of Cabinet Secretariat Office which is specified in the mission and vision is relative comprehensive. The formulation system of its strategy has just been applied into a level of conceptual (not yet operational). Assessment result data and performance-based evaluation is not used as a peed-back of improvement, and there still find the any difficulties, even there is no agreement yet in deciding and establishing performance indicator. However, the arrangement of the Report of Accountability of Government Institution Performance (LAKIP) is running well. The obstacles factor in the arrangement of LAKIP is the content of LAKIP which is relatively not perfect yet, and not comprehensive, and its performance information system is still below standard. The lack of effectiveness of supporting organization and the lack of authority delegation in the decision making activities indicates that the organization structure of Cabinet Secretariat Office is not effective yet. But study result suggests that, the coordination and delegation of work and obligation system is significantly running well. Leadership is the main factor of the obstacle in the implementation of Inpres on AKIP. Human Resources constitute a supporting factor in the success of the implementation of Inpres AKIP. However the result of study draws that, the participation rate or the involvement of Human Resources and Level of awareness/understanding upon the mission and vision of Cabinet Secretariat Office is very low standard. The result of study also indicates that the accountability policy of the performance itself is still poor, so that it will make many weaknesses and will become an obstacle factor for the success of its implementation.

Based on the result of study, there have been some advices/inputs that must strictly be notified and performed, namely: To perform the socialization of the realization of the System of Accountability of Government Institution Performance (SAKIP); to create the culture of conducive organizational climate; to create the deliberation for establishing performance indicator and it is needed to improve the Performance Information System. Organizational structure needs to get any improvement. In the dimension of this organizational structure, it is necessary to change the point of decision making policy. The leader is needed to enlarge his role by becoming the leader in formulating organizational vision, to have strong commitment in implementing organization vision, be able to become a model through its attitudes as well as to give the opportunity to any staff to be more active and initiative; To improve the trust of mutual benefit between the leader and the subordinate, to improve discretion of staff in making decision, as well to create a performance-and- achievement based reward system. In the national scope, it is needed to improve the performance accountability Implementation.

In order to identify the success or the fail of policy implementation, the organization can use Mc. Kinsey'7-S' framework. With this management equipment, the draw of problems in its policy implementation can be viewed as an interconnected unification system, where its problem solving must be viewed comprehensively."