9 research outputs found
STUDI KOMPARASI METODE PROFILE MATCHING DAN SIMPLE ADDITIVE WEIGHTING DALAM REKOMENDASI PEMINATAN PESERTA DIDIK BARU (STUDI KASUS: MA NU ASSALAFIE CIREBON)
No full textIn the 2013 curriculum, the specialization process is implemented since the
commencement of the students will start learning in class X, expecting that students can
learn according to their interests and talents. Therefore the specialization process is one of
the fundamental methods in the 2013 curriculum, and accuracy is needed in determining it.
MA NU Assalafie is a private Madrasah Aliyah in Cirebon and has three specialization
groups: MIA, IIS, and IIK. In the process of interested in new students MA NU Assalafie has
implemented the policies set out in the 2013 Curriculum. However, the method applied is
still conventional by only seeing the results of the entrance selection exam scores. This
system is examined to be less than optimal because it cannot elaborate on all aspects of
determining specialization maximally.
In this study, a Decision Support System (DSS) is proposed to address these
problems. A comparison was made between the Profile Matching, Simple Additive Weighing
methods and a combination of the two methods. The comparison process is realized with the
same alternatives and criteria, and only the types and weights of measures are adjusted to
befit the specialization group. From each method, three experiments will be carried out by
specialization groups in MA NU Assalafie to be later known as one of the most dominant
methods.
The results confirmed that the DSS could be one of the solutions in the process of
interested in new students, with 121 of 157 participants conducting the selection of choosing
specialization based on the DSS recommendations. In this research, the SAW method became
the most dominant method, with 106 of 121 new students who take guidance based on the
recommendation of the SAW method. The application of DSS in the specialization process
provides specialization recommendations more not only objectively but also directly impacts
student learning outcomes. There are only six of 121 students who take a suggestion from the
results of the DSS application, which has a grade below the KKM
PENERAPAN METODE PROFILE MATCHING UNTUK MENENTUKAN PENULIS KARYA TULIS ILMIAH TERBAIK
No full textWriting scientific papers is an annual agenda carried out by MA NU Assalafie for twelfth-grade students at the beginning of the odd semester. This activity is an effort by MA NU Assalafie to improve the competence of students, especially in terms of communication. Every student will be reporting the results of a book review they have read in the form of a paper, which throughout the process, every student will be accompanied by a teacher as a mentor who will guide them from the beginning of writing until the end when the student takes the scientific paper exam. Along the way, this activity will always produce the best scientific paper author, which is determined through the scientific paper writing exam. The problem that often arises from the decision-making process is the feeling of dissatisfaction from each examiner, as each examiner has a subjective view of the student being tested. To address this issue, in the 2022/2023 academic year, the decision-making process will be carried out by a subsection of the information system, namely the decision support system (DSS), using profile matching as the method used in the decision-making process. The implementation of DSS using profile matching produces the best alternative from a total of 139 students. Through usability testing using the system usability scale (SUS) method, the implementation of profile matching in determining the best student obtained a final score of 75, which means the system is acceptable to all parties involved. This is based on the fact that the implementation of profile matching can reduce the subjectivity of examiners in the process of determining the best student. In addition, the information generated by the DSS will be faster, more accurate, and accountable
Travel Package Recommendation System Using Collaborative Filtering Method at Loka Travel
No full textThe rapid development of information technology drives the need for a system that can help tourists in determining the choice of tourist destinations that suit their preferences. The Loka Travel application was developed as a web-based platform that provides various tour packages and is equipped with a recommendation system to suggest relevant destinations for users. This study aims to design and implement a tour package recommendation system using the Collaborative Filtering method with a memory-based approach. This method works by calculating the similarity between users based on their rating or booking history for tour packages, allowing the system to suggest packages that are preferred by other users who have similar preferences. The cosine similarity algorithm is used in the process of calculating the similarity between users, with interaction data obtained from booking and payment activities in the application. The implementation of this system is carried out using the Laravel framework and MySQL database. The results of the system test show that the system is able to provide recommendations with an accuracy level of 80.63%, based on the calculation of Mean Absolute Error (MAE). Thus, this system can help users find suitable tourist destinations and improve their experience in using the Loka Travel application
Sistem rekomendasi peminatan peserta didik baru pada kurikulum K-13 menggunakan metode profile matching, simple additive weighting, dan kombinasi keduanya
No full textThe selection of students' interests based on the 2013 curriculum (K-13) is carried out before students start learning in class X. Accuracy in its determination is required to ensure that students learn according to their interests and talents. This study applies three DSS methods, namely profile matching, SAW, and a combination of both, to provide accurate recommendations for determining these students' interests. The three methods are compared using the same alternatives and criteria to find the most dominant method. The results of this study indicate that the application of SPK can assist PPDB activities with an accuracy of 79.2 %. In determining interest for students, the combination method is the most dominant, with an accuracy of 78 %. The application of DSS not only helps the specialization process to be faster but also accurate. This is indicated by only 6 out of 122 students who chose specialization based on the DSS recommendation getting a score below the KKM.Peminatan peserta didik dalam kurikulum 2013 dilakukan sebelum peserta didik memulai belajar di kelas X. Ketepatan dalam penentuannya diperlukan untuk memastikan peserta didik belajar sesuai dengan minat dan bakat yang dimiliki. Penelitian ini menerapkan tiga metode SPK, yaitu profile matching, SAW dan kombinasi keduanya, untuk memberikan rekomendasi peminatan siswa didik ini. Ketiga metode tersebut dikomparasikan menggunakan alternatif dan kriteria yang sama untuk mengetahui metode yang paling dominan. Hasil penelitian ini menunjukkan bahwa penerapan SPK dapat membantu kegiatan PPDB dengan akurasi 79,2 %. Dalam proses penentuan minat bagi peserta didik, metode kombinasi menjadi yang paling dominan dengan persentase sebesar 78 %. Penerapan SPK tidak hanya membantu proses peminatan menjadi lebih cepat, tetapi juga akurat. Hal ini dibuktikan dengan hanya terdapat 6 dari total 122 peserta didik yang memilih peminatan berdasarkan rekomendasi SPK mendapatkan nilai di bawah KKM
Carbon Footprint of Semi-Mechanical Sago Starch Production
No full textIndonesia is the country with the greatest potential for sago in the world. This research is intended to determine the
carbon footprint of sago starch produced from a semi-mechanical process. The calculation was carried out using
the LCA approach with the system boundary of cradle to gate. The process steps were carried out in a combination of manual work and diesel-driven engines. The inventory data on material, energy input flows and emissions
were obtained from 3 samples of typical medium-scale semi-mechanical sago mills. It was found that the carbon
footprint of the sago produced from semi-mechanical processes was 37.9±0.6 kgCO2
eq per 1 ton of dried sago
starch. Further analysis shows that 62% of the carbon footprint comes from the extraction stage and 38% from the
transportation. It can be estimated that the amount of greenhouse gas emissions from the semi-mechanical sago
starch production in Indonesia for 2018 reached around 2,617,639 kg CO2
eq
Application of Content-Based Filtering for Moisturizer Recommendation System Based on Skin Type Suitability
No full textMany users face significant challenges when trying to select the most suitable moisturizer for their skin. This difficulty often arises due to the overwhelming variety of available products on the market, combined with a lack of personalized information that could guide users toward the best choice. To address this issue, the present study aims to develop a recommendation system based on the Content-Based Filtering approach, which is specifically designed to align the benefits of moisturizer products with the unique needs of users' skin types. The data for this study were collected manually from 17 moisturizer products featured on the Sociolla e-commerce platform. Each product was carefully analyzed according to the descriptive information provided, including the benefits claimed and the skin types for which the product is recommended. The methodology involved several important steps: preprocessing the text from product descriptions, applying TF-IDF to assign term weights, and calculating cosine similarity scores between the user’s skin profile and product attributes. The analysis revealed that products such as D10 and D6, which yielded the highest similarity values, are strongly aligned with particular skin types. The resulting system demonstrates its ability to generate relevant and personalized product suggestions without the need for prior user preference data. This study concludes that using descriptive content as the foundation for recommendation logic can significantly enhance accuracy and targeting. Future enhancements may involve expanding the product database, integrating user-generated reviews, and leveraging machine learning techniques to produce even more adaptive and intelligent recommendations
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No full textIndonesia is an archipelagic country with abundant marine wealth that makes it the world's second largest producer of fish after China. While most of Indonesia's capture marine fisheries (80%) are consumed domestically, around 90% of blue swimming crab (BSC) products are exported, mainly in cans. This makes up almost half of all BSC products on the global market, with the United States and the European Union being the main importers. We carried out a life cycle assessment (LCA) of canned BSC products from Indonesia. Our LCA evaluated the production of “one tonne of canned BSC” at market as a functional unit (FU), with a cradle-to-market system boundary, encompassing wild capture, preprocessing, processing, and distribution to the port of destination at home and abroad. The processing stage was found to be the highest contributor (hotspot) for most of the impact categories considered, mainly due to the use of tin cans for packaging. Despite producing less by-catch, BSC caught with traps resulted in around threefold greater global warming impact per FU than those caught using nets. We also concluded that BSC meat produced in Java is environmentally preferable to that from Sumatra, as most of the shells were sold as coproducts. In addition to recycling and substitution of packaging materials, environmental improvements can also be obtained by increasing the number of shell-processing facilities outside Java. The results of this study can be used by the Indonesian government to develop more sustainable practices to avoid overexploitation of BSC and limit its environmental impacts.</p
Life cycle assessment research and application in Indonesia
No full textThe International Journal of Life Cycle Assessment ( https://link.springer.com/article/10.1007/s11367-018-1459-3 )Purpose This paper presents a review of the research and application of life cycle assessment (LCA) in Indonesia over the last
20 years and analyzes challenges and opportunities for future development.
Methods The study assessed 107 peer-reviewed scientific publications on LCA about Indonesia or written by authors affiliated
with institutions in Indonesia. Relevant programs and recommendations to advance LCA adoption were elaborated.
Results and discussion The first paper on the subject of LCA appeared as early as in 1996, while the number of publication
significantly increased since 2010. The majority of these articles came from universities, research institutions, and international
organizations. Drivers were mainly related to product competitiveness aiming to fulfill sustainability requirements of the global
commodities market. Government policies also played an essential role in many aspects, including a reduction in greenhouse gas
emissions, sustainable consumption and production, green public procurement, eco-labeling, and green industry. Simultaneously,
life cycle thinking has been embraced by governments and industries, especially with an immediate increase in the number of
organizations implementing the recent version of ISO 14001. Increased participation in voluntary sustainability reporting also
provides evidence of the prevalence of the sustainability concept. We believe that this development can serve as an essential step
toward the spread of LCA studies in the future. Furthermore, the recent adoption of ISO 14040/44 as national standards in
2016/2017 also marked the commitment of Indonesian governments in LCA and is expected to stimulate the adoption of LCAbased
environmental labels, such as carbon footprint, environmental product declaration, and product environmental footprint.
Conclusions The research and application of LCA in Indonesia are still in its infancy, as partly proved by a relatively small
number of publications as compared to some other Southeast Asian countries. However, there was a notable increase in
publication over the last 5 years, indicating a growing interest in LCA, mainly from academics and to less extent from private
sectors. Although LCA has not been explicitly formulated in the national strategies and legislation, Indonesian governments do
require life cycle thinking to inform policy-making. Nevertheless, the lack of incentives for green products, LCA programs, LCA
expertise, and localized inventory data hampers its implementation. In the future, improvement should focus on LCA capacit
