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Pengembangan Media Pembelajaran Informatika Menggunakan Canva Pada Kelas X di SMK Teknologi Muhammadiyah Bukittinggi Hasannah, Nonny Nuriswatun; Musril, Hari Antoni; Ilmi, Darul; Derta, Sarwo
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1460

This study aims to develop and test the feasibility of Canva-based informatics learning media through validity, practicality, and effectiveness tests to increase the engagement and understanding of class X students at SMK Teknologi Muhammadiyah Bukittinggi. Based on observations and interviews at SMK Teknologi Muhammadiyah Bukittinggi, the informatics learning process in class X is still dominated by lecture methods and conventional media, thus not maximizing active student participation and making learning feel monotonous. This study uses a Research and Development (R&D) model with the Hannafin and Peck approach consisting of three stages: needs analysis, design, and development. The results of the validity test show that the media is in the valid category with an average score of 0.88. The practicality test by the teacher showed very high results with a value of 0.94, while the effectiveness test showed a value of 0.90, with a high effectiveness category. Based on these results, it can be concluded that the informatics learning media for class X developed using Canva is proven to be valid, practical, and effective, and has the potential to help increase student engagement and understanding in the learning process. Thus, this media is worthy of being used as a supporting alternative in informatics learning activities in schools. Abstrak

Pengembangan dan Evaluasi Bahan Ajar Elektronik Berbasis iSpring Suite untuk Pembelajaran Informatika Hawani, Siti; Darmawati, Gusnita; Annas, Firdaus; Yuspita, Yulifda Elin
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1473

Informatics learning at MTsN 6 Agam still faces challenges related to the limited availability of innovative, technology-based instructional materials and the dominance of conventional teaching methods, which negatively affect students’ learning interest and conceptual understanding. These conditions indicate the need for the development of interactive electronic teaching materials that are aligned with students’ characteristics. This study aims to develop electronic teaching materials based on iSpring Suite that are valid, practical, and effective for Grade VIII Informatics learning at MTsN 6 Agam. The study employed a Research and Development (R&D) approach using the 4D development model, consisting of the Define, Design, Develop, and Disseminate stages. The research subjects included media experts, subject-matter experts, Informatics teachers, and Grade VIII students. Data were collected through validity, practicality, and effectiveness questionnaires. The results indicate that the developed electronic teaching materials are valid, with an average validity score of 0.84, highly practical with an average practicality score of 0.94, and effective for learning implementation with an effectiveness score of 0.91. These findings demonstrate that electronic teaching materials based on iSpring Suite are suitable for use in Informatics learning and are capable of enhancing students’ motivation and learning engagement. The contribution of this study lies in providing empirical evidence on the development of application-based electronic teaching materials integrated with interactive multimedia at the madrasah tsanawiyah level, thereby enriching research on Informatics learning media development in the context of digital education. Abstrak Pembelajaran Informatika di MTsN 6 Agam masih menghadapi kendala berupa keterbatasan bahan ajar inovatif berbasis teknologi serta dominasi metode pembelajaran konvensional yang berdampak pada rendahnya minat dan pemahaman siswa. Kondisi tersebut menunjukkan perlunya pengembangan bahan ajar elektronik yang interaktif dan sesuai dengan karakteristik peserta didik. Penelitian ini bertujuan untuk mengembangkan bahan ajar elektronik berbasis iSpring Suite yang valid, praktis, dan efektif pada mata pelajaran Informatika kelas VIII MTsN 6 Agam. Penelitian ini menggunakan metode Research and Development (R&D) dengan model pengembangan 4D yang meliputi tahap Define, Design, Develop, dan Disseminate. Subjek penelitian melibatkan ahli media, ahli materi, guru Informatika, serta siswa kelas VIII. Data dikumpulkan melalui angket validitas, praktikalitas, dan efektivitas. Hasil penelitian menunjukkan bahwa bahan ajar elektronik yang dikembangkan dinyatakan valid dengan nilai rata-rata 0,84, memiliki tingkat praktikalitas sangat tinggi dengan nilai rata-rata 0,94, serta efektif digunakan dalam pembelajaran dengan nilai efektivitas sebesar 0,91. Temuan ini menunjukkan bahwa bahan ajar elektronik berbasis iSpring Suite layak digunakan sebagai media pembelajaran Informatika dan mampu meningkatkan motivasi serta keterlibatan belajar siswa. Kontribusi penelitian ini terletak pada penyediaan bukti empiris pengembangan bahan ajar elektronik berbasis aplikasi yang terintegrasi dengan multimedia interaktif pada jenjang madrasah tsanawiyah, serta memperkaya kajian penelitian pengembangan media pembelajaran Informatika di era pembelajaran digital.

Evaluasi Interaktif dalam Pembelajaran Informatika: Studi Penggunaan Zep Quiz untuk Evaluasi Berbasis Game Fitri, Rahma Dina; Supriadi, Supriadi; Ilmi, Darul; Zakir, Supratman
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1509

The aim of this research is to design educational game-based learning evaluation media using the Zep Quiz platform which is expected to be a solution for evaluating Informatics learning that is more interactive, effective and efficient compared to conventional evaluation using physical answer sheets, as well as increasing student involvement in the evaluation process. This research is based on the results of interviews with class VII Informatics subject teachers at SMPN 6 Bukittinggi as well as direct observations in class, which show that the learning evaluation process still uses conventional media in the form of physical answer sheets. This condition makes students feel bored and less motivated, while teachers face obstacles in checking and recording evaluation results because they are still done manually. To overcome these problems, this research applies the Research and Development (R&D) method with the ADDIE model which includes analysis, design, development, implementation and evaluation stages. Validity testing was carried out using Aiken's V, practicality testing using Cohen's Kappa, and effectiveness testing using Hake's G-Score. The research results showed that the Zep Quiz-based evaluation media was declared valid with an average score of 0.86, practical with an average score of 0.93, and effective with an average score of 0.83. The contribution of this research is to present educational game-based learning evaluation media using Zep Quiz which is valid, practical and effective, so that it can be an alternative solution for teachers in carrying out learning evaluations that are more interactive, efficient and able to increase student motivation. Abstrak Tujuan dari penelitian ini adalah merancang media evaluasi pembelajaran berbasis game edukasi menggunakan platform Zep Quiz yang diharapkan dapat menjadi solusi evaluasi pembelajaran Informatika yang lebih interaktif, efektif, dan efisien dibandingkan evaluasi konvensional menggunakan lembar jawaban fisik, serta meningkatkan keterlibatan siswa dalam proses evaluasi. Penelitian ini didasari oleh hasil wawancara dengan guru mata pelajaran Informatika kelas VII SMPN 6 Bukittinggi serta observasi langsung di kelas, yang menunjukkan bahwa proses evaluasi pembelajaran masih menggunakan media konvensional berupa lembar jawaban fisik. Kondisi tersebut membuat siswa merasa jenuh dan kurang termotivasi, sementara guru menghadapi kendala dalam pemeriksaan dan perekapan hasil evaluasi karena masih dilakukan secara manual. Untuk mengatasi permasalahan tersebut, penelitian ini menerapkan metode Research and Development (R&D) dengan model ADDIE yang mencakup tahap analisis, desain, pengembangan, implementasi, dan evaluasi. Uji validitas dilakukan dengan menggunakan Aiken’s V, uji praktikalitas dengan Cohen’s Kappa, dan uji efektivitas dengan G-Score Hake. Hasil penelitian menunjukkan bahwa media evaluasi berbasis Zep Quiz dinyatakan valid dengan skor rata-rata 0,86, praktis dengan skor rata-rata 0,93, dan efektif dengan skor rata-rata 0,83. Kontribusi penelitian ini adalah menghadirkan media evaluasi pembelajaran berbasis game edukasi menggunakan Zep Quiz yang valid, praktis, dan efektif, sehingga dapat menjadi solusi alternatif bagi guru dalam melaksanakan evaluasi pembelajaran yang lebih interaktif, efisien, dan mampu meningkatkan motivasi siswa.

Perancangan Aplikasi Pembelajaran Tata Cara Sholat Berbasis Android Untuk Meningkatkan Keterampilan Praktik Ibadah Siswa Maiyana, Efmi; Hidayat, Wahyu; Martua Haholongan Sir, Sadar
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1634

Technological advances in education provide opportunities to improve Islamic teaching, particularly in learning to read and practice prayer. MTsN 1 Bukittinggi experienced a problem, namely boredom among students due to the continued use of presentation slides and lecture-based teaching methods. Therefore, the researcher wanted to design a learning media application for prayer procedures. This study aims to design an Android-based application for learning prayer procedures as a medium to improve students' worship skills. The application was developed using the Research and Development (R&D) method with the ADDIE model, which includes needs analysis, design, development, implementation, and evaluation. The application design consisted of two stages, namely logical design using UML, which included use case diagrams, sequence diagrams, and activity diagrams, followed by physical design, where the application was developed using Android Studio and equipped with features such as prayer material, movement guides, audio recitations, and evaluations. The results of the black box media test showed that the application functioned properly. The designed learning media application provides features and supporting menus that offer practicality in using the learning media application for prayer procedures, such as the prayer menu, the Qur'an, and the determination of the qibla direction. Abstrak Pertumbuhan teknologi dalam bidang Pendidikan memberikan peluang untuk meningkatkan pembelajaran ajaran islam, khususnya dalam pembelajaran bacaan dan praktik sholat. Pada MTsN 1 Bukittinggi mengalami permasalahan yaitu rasa bosan yang timbul bagi siswa karena masih menggunakan media pembelajaran slide presentasi dengan metode ceramah sehingga peneliti ingin merancang sebuh aplikasi media pembelajaran tata cara sholat. Penelitian ini bertujuan merancang aplikasi pembelajaran tata cara salat berbasis Android sebagai media untuk meningkatkan keterampilan praktik ibadah siswa. Pengembangan aplikasi dilakukan dengan metode Research and Development (R&D) menggunakan model ADDIE yang meliputi analisis kebutuhan, perancangan, pengembangan, implementasi, dan evaluasi. Perancangan aplikasi terdiri dari dua tahapan yaitu perancangan secara logika menggunakan UML yang meliputi use case diagram, sequence diagram dan activity diagram, kemudian perancangan secara fisik dimana aplikasi dikembangkan menggunakan Android Studio dan dilengkapi fitur materi salat, panduan gerakan, audio bacaan, serta evaluasi. Hasil uji black box media menunjukkan bahwa aplikasi berfungsi dengan baik. Aplikasi media pembelajaran yang telah dirancang menghadirkan fitur dan menu – menu pendukung yang dapat memberikan kepraktisan dalam menggunakan aplikasi media pembelajaran tata cara sholat seperti menu do’a, Al – Qur’an dan penentuan arah kiblat.

Pemodelan dan Prediksi Curah Hujan Menggunakan SARIMA untuk Mendukung Perencanaan Irigasi Presisi di Kabupaten Temanggung Wardhani, Olivia; Wibowo, Rheza Ari; Fathony, Ikhwan Alfath Nurul Fathony; Adiana, Beta Estri; Natawijaya, Yasabuana Athallahaufa; Akbar, Rayfal Mayvandra Aurora
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1642

Changes in rainfall patterns in tropical regions increase uncertainty in agricultural water management, particularly in rainfed areas such as Temanggung Regency, Indonesia. This condition highlights the need for data-driven rainfall prediction models to support precision irrigation planning and drought risk mitigation. This study aims to develop rainfall and rainday prediction models using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method based on monthly climatological data for the period 2014–2024. The analysis follows the Box–Jenkins procedure, including seasonal pattern exploration, stationarity testing, parameter identification using ACF and PACF, parameter estimation, and diagnostic and accuracy evaluation. The results indicate that the SARIMA(0,0,1)(1,0,1,12) model provides the best performance for rainfall prediction, achieving an RMSE of 99.92 mm and an MAE of 57.84 mm, while rainday prediction exhibits relatively higher errors. The model successfully captures consistent annual seasonal patterns and generates projections for 2025, indicating higher rainfall at the beginning of the year and a significant decrease during the dry season. These findings provide a quantitative basis for developing water availability risk calendars and adjusting precision irrigation strategies at the regional level, supporting sustainable water resource management and regional food security. Abstrak Perubahan pola curah hujan di wilayah tropis meningkatkan ketidakpastian dalam pengelolaan air pertanian, terutama pada wilayah tadah hujan seperti Kabupaten Temanggung. Kondisi ini menuntut pemanfaatan model prediksi berbasis data sebagai landasan perencanaan irigasi presisi dan mitigasi risiko kekeringan. Penelitian ini bertujuan untuk membangun model prediksi curah hujan dan hari hujan menggunakan metode Seasonal Autoregressive Integrated Moving Average (SARIMA) berbasis data klimatologis bulanan periode 2014–2024. Analisis dilakukan menggunakan prosedur Box–Jenkins yang mencakup eksplorasi pola musiman dan pengujian stasioneritas. Tahapan selanjutnya meliputi identifikasi parameter melalui ACF dan PACF, estimasi parameter, serta evaluasi diagnostik residual dan akurasi model. Hasil pemodelan menunjukkan bahwa model SARIMA(0,0,1)(1,0,1,12) memberikan kinerja terbaik untuk prediksi curah hujan dengan nilai RMSE sebesar 99,92 mm dan MAE sebesar 57,84 mm, sedangkan prediksi hari hujan menghasilkan tingkat kesalahan yang relatif lebih tinggi. Model mampu merepresentasikan pola musiman tahunan secara konsisten dan menghasilkan proyeksi tahun 2025 yang menunjukkan curah hujan tertinggi pada awal tahun serta penurunan signifikan pada periode kemarau. Temuan ini memberikan landasan kuantitatif untuk penyusunan kalender risiko ketersediaan air dan penyesuaian strategi irigasi presisi pada skala regional, sehingga mendukung pengelolaan sumber daya air dan ketahanan pangan daerah.

AI-Driven Learning Analytics for Self-Regulated and Metacognitive Learning: A Systematic Review Romdhoni, Rhezwan Dhaifullah; Arrasyid, Rafli; Widodo, Suprih; Elviani, Ulva
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1657

Artificial intelligence (AI) and learning analytics are increasingly integrated into educational systems, yet their impact on self‑regulated learning (SRL) and metacognition remains not fully understood. This systematic review synthesizes findings from 34 empirical and review studies on AI‑driven learning analytics in formal education, focusing on their effects on SRL, metacognition, motivation, and academic performance. Following PRISMA guidelines, studies were identified through searches in Scopus, Web of Science, ERIC, and Google Scholar for articles published between 2020 and 2025, using keywords related to AI, learning analytics, SRL, and metacognition. Studies were included if they used AI‑based analytical or adaptive systems, standardized SRL or metacognitive measures, and pre–post or comparison data. Results show that AI‑based tools such as predictive models, intelligent tutoring systems, adaptive platforms, learning dashboards, and generative or conversational AI support goal setting, monitoring, strategy adjustment, and reflective evaluation through feedback, progress visualization, and personalized recommendations. Most studies report improvements in SRL strategies, metacognitive awareness, motivation, engagement, and learning outcomes, though effects vary across research design quality, educational levels, and subject areas. However, several challenges persist, including infrastructural limitations, limited teacher readiness, data privacy and ethical issues, algorithmic bias, and potential overreliance on AI that may weaken learners’ independent strategic thinking. Overall, AI‑driven learning analytics hold substantial potential to enhance SRL and metacognition when integrated within coherent pedagogical frameworks and supported by institutional policies promoting transparency, equity, and human agency. Abstrak Kecerdasan buatan (AI) dan learning analytics semakin meluas dalam sistem pendidikan, namun dampaknya terhadap self‑regulated learning (SRL) dan metakognisi masih belum sepenuhnya dipahami. Tinjauan sistematis ini mensintesis temuan dari 34 studi empiris dan tinjauan pustaka mengenai penerapan AI‑driven learning analytics di pendidikan formal, berfokus pada pengaruhnya terhadap SRL, metakognisi, motivasi, dan kinerja akademik. Dengan mengikuti pedoman PRISMA, artikel dipilih melalui pencarian di Scopus, Web of Science, ERIC, dan Google Scholar untuk periode 2020–2025 menggunakan kata kunci terkait AI, learning analytics, SRL, dan metakognisi. Studi disertakan jika menggunakan sistem analitik atau adaptif berbasis AI dengan instrumen terstandar dan data perbandingan pre–post. Hasil menunjukkan bahwa alat berbasis AI seperti model prediktif, sistem tutor cerdas, platform adaptif, dashboard pembelajaran, serta AI generatif atau konversasional mendukung penetapan tujuan, pemantauan, adaptasi strategi, dan refleksi melalui umpan balik, visualisasi kemajuan, dan rekomendasi otomatis. Sebagian besar studi melaporkan peningkatan strategi SRL, kesadaran metakognitif, motivasi, keterlibatan, dan hasil belajar, meski efek berbeda bergantung pada desain penelitian, jenjang pendidikan, dan bidang studi. Namun, tantangan tetap muncul, termasuk keterbatasan infrastruktur, kesiapan guru, privasi data, bias algoritmik, serta potensi ketergantungan berlebih pada AI yang dapat melemahkan kemandirian berpikir strategis. Secara keseluruhan, AI‑driven learning analytics berpotensi memperkuat SRL dan metakognisi bila diintegrasikan dalam kerangka pedagogis yang jelas dan didukung kebijakan institusional yang menegakkan transparansi, keadilan, dan agensi manusia.

Analysis of Lifestyle Classification Using a Decision Tree Approach Syawitri, Afriosa; Hidayatullah, Siti Rahmi; Nuraini, Miranda
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1661

Lifestyle related health issues continue to increase, highlighting the need for data-driven approaches that not only classify lifestyle patterns but also provide interpretable insights to support health-related decision making. This study aims to develop an interpretable lifestyle classification model using the Decision Tree algorithm, with a specific analytical focus on identifying dominant behavioral factors and their hierarchical relationships in distinguishing healthy and unhealthy lifestyles. The dataset was collected through a questionnaire survey involving 130 respondents representing diverse lifestyle behaviors. Initially, 23 attributes measured using Likert scales were used to capture multiple aspects of lifestyle. To improve analytical clarity and reduce data complexity, the attributes were transformed by grouping conceptually related items into four main behavioral domains: diet, physical activity, sleep patterns, and mental health. Personal demographic attributes were excluded from the modeling process due to their limited relevance to lifestyle behavior and their potential to introduce classification bias. Within each domain, sub-attributes were aggregated using mean values to generate stable composite scores, a methodologically appropriate approach given the non-parametric and threshold-based characteristics of the Decision Tree algorithm. The applied to reduce overfitting. The results indicate that the proposed model achieved an accuracy of 84.62% and a weighted average F1-score of 0.84, demonstrating balanced classification performance. The model showed strong recall in identifying healthy lifestyles, while limitations related to generalizability remain. Transformed dataset was divided into training and testing sets using a 70:30 hold-out validation strategy. Model construction employed the entropy criterion and information gain for attribute selection, with complexity control. Abstrak Masalah kesehatan terkait gaya hidup terus meningkat, menyoroti perlunya pendekatan berbasis data yang tidak hanya mengklasifikasikan pola gaya hidup tetapi juga memberikan wawasan yang dapat ditafsirkan untuk mendukung pengambilan keputusan terkait kesehatan. Penelitian ini bertujuan untuk mengembangkan model klasifikasi gaya hidup yang dapat diinterpretasikan menggunakan algoritma Decision Tree, dengan fokus analitis khusus untuk mengidentifikasi faktor perilaku dominan dan hubungan hierarkisnya dalam membedakan gaya hidup sehat dan tidak sehat. Kumpulan data dikumpulkan melalui survei kuesioner yang melibatkan 130 responden yang mewakili beragam perilaku gaya hidup. Awalnya, 23 atribut yang diukur menggunakan skala Likert digunakan untuk menangkap berbagai aspek gaya hidup. Untuk meningkatkan kejelasan analitis dan mengurangi kompleksitas data, atribut diubah dengan mengelompokkan item yang terkait secara konseptual menjadi empat domain perilaku utama: diet, aktivitas fisik, pola tidur, dan kesehatan mental. Atribut demografis pribadi dikecualikan dari proses pemodelan karena relevansinya yang terbatas dengan perilaku gaya hidup dan potensinya untuk memperkenalkan bias klasifikasi. Dalam setiap domain, sub-atribut dikumpulkan menggunakan nilai rata-rata untuk menghasilkan skor komposit yang stabil, pendekatan yang sesuai secara metodologis mengingat karakteristik non-parametrik dan berbasis ambang batas dari algoritma Pohon Keputusan. Himpunan data yang diubah dibagi menjadi set pelatihan dan pengujian menggunakan strategi validasi penahanan 70:30. Konstruksi model menggunakan kriteria entropi dan perolehan informasi untuk pemilihan atribut, dengan kontrol kompleksitas diterapkan untuk mengurangi overfitting. Hasil menunjukkan bahwa model yang diusulkan mencapai akurasi 84,62% dan skor F1 rata-rata tertimbang 0,84, menunjukkan kinerja klasifikasi yang seimbang. Model ini menunjukkan ingatan yang kuat dalam mengidentifikasi gaya hidup sehat, sementara keterbatasan yang terkait dengan generalisasi tetap ada.

Analisis Tren Produksi dan Preferensi Penonton Netflix: Pendekatan Big Data untuk Menyusun Strategi Konten Global Azmi, Muhamad Thoriq; Azima, Enpri Rifa; Fergiana, Egie; Utomo, Hadi Prasetyo
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1387

The objective of this study is to support strategic decision-making in content investment and diversification on the Netflix platform using a big Data analytics approach. This research utilizes a Dataset obtained from Kaggle, covering the period from 2010 to 2025. The Dataset consists of 21,845 titles and includes attributes such as title name, content type, genre, release year, content ID, rating, vote count, and country of availability. Kaggle is a widely used platform for sharing Datasets and hosting Data analysis competitions in both academic research and industry. The analyzed Data encompass various attributes, including release year, country of origin, genre, duration, and audience response metrics such as ratings, vote counts, and popularity. Exploratory Data analysis (EDA) was employed to identify content production patterns based on genre and to evaluate audience responses through the distribution of ratings and popularity levels. Data analysis was conducted using Python and executed through Google Colab. The results indicate that content with high popularity—reflected by higher vote counts and popularity scores—tends to have relatively higher ratings compared to content with lower exposure. These findings suggest that popularity can serve as a proxy for global audience preferences. However, the relationship between popularity and rating is not entirely linear, as it is influenced by external factors such as promotional strategies and genre-specific characteristics. The study identifies genres and content types that achieve not only high ratings but also high popularity, thereby more accurately reflecting global audience preferences. Based on these findings, a practical recommendation for Netflix is to invest in producing more content within genres that consistently demonstrate high popularity and ratings, such as drama and action, as these genres most strongly represent global viewer preferences. From a social perspective, this strategy may carry the risk of reducing content diversity and cultural narratives if the platform overly prioritizes the most popular genres. Abstrak Tujuan penelitian ini adalah untuk pengambilan keputusan strategis dalam investasi dan diversifikasi konten pada aplikasi Netflix menggunakan pendekatan big Data analitik. Studi ini menggunakan Dataset Website Kaggle sejak tahun 2010 hingga 2025 yang diperoleh website Kaggle, Data yang didapat sebanyak 21.845 tayangan dengan atribut Judul Tayangan, Jenis Tayangan, Genre Tayangan, Tahun Rilis, ID Tayangan, Rating, Jumlah Vote dan Daftar Negara, sebuah platform berbagi Dataset dan kompetisi analisis Data yang banyak digunakan dalam penelitian dan industri. Data yang dianalisis mencakup berbagai atribut seperti tahun rilis, negara asal, genre, durasi, hingga metrik respons penonton seperti rating, vote count, dan popularitas. Metode analisis eksploratif digunakan untuk mengidentifikasi pola produksi konten berdasarkan genre serta mengevaluasi tanggapan audiens melalui distribusi rating dan tingkat popularitas. Analisis Data dilakukan menggunakan Phyton yang dijalankan menggunakan Google Collabs. Hasil penelitian menunjukkan konten dengan popularitas tinggi, yang ditunjukkan oleh nilai vote dan popularity, cenderung memiliki rating yang relatif lebih tinggi dibandingkan konten dengan eksposur rendah. Temuan ini mengindikasikan bahwa popularitas dapat merefleksikan preferensi penonton global, meskipun hubungan antara kedua variabel bersifat tidak sepenuhnya linier karena dipengaruhi oleh faktor eksternal seperti strategi promosi dan karakteristik genre. Temuan ini mengidentifikasi genre dan tipe konten yang tidak hanya memiliki rating tinggi, tetapi juga popularitas tinggi, sehingga lebih mencerminkan preferensi penonton global. Berdasarkan temuan tersebut, Rekomendasi praktis yang bisa dilakukan adalah dengan memproduksi lebih banyak konten dari genre yang konsisten memiliki popularitas dan rating tinggi (seperti drama dan action), karena genre ini paling mencerminkan preferensi penonton global. Secara implikasi sosial, ini dapat berpotensi menurunkan keragaman konten dan narasi budaya jika platform terlalu fokus pada genre yang paling populer.

Implementasi Metode SAW dalam Sistem Pendukung Keputusan Pemilihan Mata Pelajaran Kurikulum Merdeka Rahmadani, Nessa; Yuspita, Yulifda Elin; Darmawati, Gusnita; Annas, Firdaus
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1459

This study aims to implement the Simple Additive Weighting (SAW) method as a decision support system for determining elective subjects under the Merdeka Curriculum at SMAN 1 Harau. The study is motivated by the high level of uncertainty experienced by Grade X students in selecting elective subjects. Although the school provides nine elective options and has conducted socialization programs for students and parents, questionnaire results indicate that 83.7% of students remain uncertain in making their choices. This uncertainty is primarily influenced by peer pressure, recommendations from senior students, and students’ lack of confidence in identifying their own interests and academic abilities. The research employs the Simple Additive Weighting (SAW) method, which involves determining criteria and alternatives, assigning weights to each criterion, constructing and normalizing the decision matrix, calculating preference values (Vi), and ranking the alternatives, where the alternative with the highest Vi is selected as the primary recommendation. The results show that the SAW method achieves a sensitivity value of 0.0011 and an accuracy rate of 98.85%, indicating a high level of stability and reliability. Based on the sensitivity and accuracy tests, it can be concluded that the SAW method is effective and feasible for determining elective subjects. This study contributes by providing an objective, measurable, and transparent decision-making approach, with practical implications for improving academic guidance and decision support services in secondary education. Abstrak Penelitian ini bertujuan untuk mengimplementasikan metode Simple Additive Weighting (SAW) sebagai sistem pendukung keputusan dalam menentukan mata pelajaran pilihan Kurikulum Merdeka di SMAN 1 Harau. Latar belakang penelitian ini didasarkan pada tingginya tingkat keraguan siswa kelas X dalam memilih mata pelajaran pilihan. Meskipun sekolah telah menyediakan sembilan mata pelajaran pilihan serta melakukan sosialisasi kepada siswa dan orang tua, hasil angket menunjukkan bahwa 83,7% siswa masih mengalami kebingungan dalam pengambilan keputusan. Faktor utama yang memengaruhi kondisi tersebut meliputi pengaruh teman sebaya, rekomendasi senior, serta ketidakpastian siswa terhadap minat dan kemampuan diri. Metode penelitian yang digunakan adalah Simple Additive Weighting (SAW), yang meliputi penentuan kriteria dan alternatif, pemberian bobot kriteria, penyusunan dan normalisasi matriks keputusan, perhitungan nilai preferensi (Vi), serta proses perangkingan alternatif. Alternatif dengan nilai Vi tertinggi ditetapkan sebagai rekomendasi utama. Hasil penelitian menunjukkan bahwa metode SAW memiliki tingkat sensitivitas sebesar 0,0011 dan tingkat akurasi sebesar 98,85%, yang mengindikasikan stabilitas dan keandalan metode dalam menghasilkan rekomendasi. Berdasarkan hasil uji sensitivitas dan akurasi, dapat disimpulkan bahwa metode SAW layak dan efektif digunakan dalam menentukan mata pelajaran pilihan. Kontribusi penelitian ini terletak pada penyediaan pendekatan pengambilan keputusan yang objektif, terukur, dan transparan, serta berimplikasi pada peningkatan kualitas layanan bimbingan akademik di sekolah.

Klasifikasi Aksesori Fashion Berdasarkan Fitur Citra Menggunakan K-Means Clustering Tomi, Zebbil Billian; Ramadhanu, Agung
Intellect : Indonesian Journal of Learning and Technological Innovation Vol. 4 No. 02 (2025): Intellect : Indonesian Journal of Learning and Technological Innovation
Publisher : Yayasan Lembaga Studi Makwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57255/intellect.v4i02.1476

The rapid development of computer vision and machine learning has enabled new applications in the fashion industry, particularly in image-based product classification and recommendation systems. This study aims to classify fashion accessories, namely wallets, bags, and belts, based on image features using the K-Means clustering algorithm. The dataset consists of 30 images acquired under controlled conditions with uniform lighting, resolution, and background. Although the dataset size is relatively limited, this study is designed as an initial baseline to evaluate the effectiveness of K-Means clustering on small and homogeneous datasets, which are commonly encountered in early-stage image classification research. The research workflow includes image preprocessing (resizing, color space conversion, and noise reduction), object segmentation, and feature extraction focusing on color, texture, and shape characteristics. The extracted features include Local Binary Pattern (LBP), entropy, edge density, eccentricity, extent, and area ratio. The results demonstrate that K-Means clustering is capable of grouping fashion accessories into distinct categories according to their visual characteristics. From a practical perspective, the proposed approach can be applied to automated fashion product cataloging to support inventory management, image-based product search, and recommendation systems in e-commerce platforms. This study provides a simple and interpretable baseline for fashion accessory classification and serves as a foundation for future work involving larger datasets, advanced feature descriptors, or deep learning-based methods. Abstrak Perkembangan computer vision dan machine learning memungkinkan penerapan baru dalam industri fesyen, khususnya pada sistem klasifikasi dan rekomendasi produk berbasis citra. Penelitian ini bertujuan mengklasifikasikan aksesori fesyen berupa dompet, tas, dan ikat pinggang berdasarkan fitur citra menggunakan algoritme K-Means clustering. Dataset yang digunakan terdiri dari 30 citra yang dikumpulkan dalam kondisi terkontrol dengan pencahayaan, resolusi, dan latar belakang seragam. Meskipun jumlah dataset relatif terbatas, pendekatan ini dirancang sebagai studi awal (baseline) untuk mengevaluasi efektivitas K-Means pada dataset kecil dan homogen yang umum dijumpai pada tahap awal pengembangan sistem klasifikasi berbasis citra. Tahapan penelitian meliputi preprocessing (penyeragaman ukuran, konversi warna, dan reduksi noise), segmentasi objek, serta ekstraksi fitur warna, tekstur, dan bentuk. Fitur yang digunakan meliputi Local Binary Pattern (LBP), entropi, kerapatan tepi, eksentrisitas, extent, dan rasio area. Hasil penelitian menunjukkan bahwa algoritme K-Means mampu mengelompokkan aksesori fesyen ke dalam kategori yang berbeda berdasarkan karakteristik visualnya. Secara praktis, hasil penelitian ini berpotensi diterapkan sebagai sistem klasifikasi otomatis pada katalog produk fesyen digital untuk mendukung manajemen inventori, pencarian produk berbasis citra, serta sistem rekomendasi pada platform e-commerce. Penelitian ini diharapkan dapat menjadi baseline sederhana dan interpretatif dalam klasifikasi aksesori fesyen, serta menjadi pijakan untuk pengembangan lanjutan menggunakan dataset yang lebih besar, deskriptor fitur modern, maupun metode berbasis deep learning.

Home Page

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Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Firdaus Annas

Contact Email
info@makwadfoundation.org

Phone
+6285278566869

Journal Mail Official
intellect.makwafoundation@gmail.com

Editorial Address
Jl. Dusun Pandam Jorong Aro Kandikir Nagari Gadut Kecamatan Tilatang Kamang Kabupaten Agam Sumatera Barat

Location
Kab. agam,

Sumatera barat

INDONESIA

Abstract

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Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Firdaus Annas

Contact Email info@makwadfoundation.org

Phone +6285278566869

Journal Mail Official intellect.makwafoundation@gmail.com

Editorial Address Jl. Dusun Pandam Jorong Aro Kandikir Nagari Gadut Kecamatan Tilatang Kamang Kabupaten Agam Sumatera Barat

Location Kab. agam, Sumatera barat INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Firdaus Annas

Contact Email
info@makwadfoundation.org

Phone
+6285278566869

Journal Mail Official
intellect.makwafoundation@gmail.com

Editorial Address
Jl. Dusun Pandam Jorong Aro Kandikir Nagari Gadut Kecamatan Tilatang Kamang Kabupaten Agam Sumatera Barat

Location
Kab. agam,

Sumatera barat

INDONESIA