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INDONESIA
JOURNAL OF SCIENCE AND SOCIAL RESEARCH
Published by Smart Education
ISSN : 26154307     EISSN : 26153262     DOI : -
Core Subject : Economy, Science, Education, Social,
Computer Science & IT Economics, Econometrics & Finance Education Social Sciences
Journal of Science and Social Research is accepts research works from academicians in their respective expertise of studies. Journal of Science and Social Research is platform to disclose the research abilities and promote quality and excellence of young researchers and experienced thoughts towards Change for Development. The journal releases on February and July.
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Articles 3,645 Documents
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Pengembangan Sistem Pendaftaran Siswa Baru Berbasis Web di SMK N 1 Painan Eggi Mahnedra; Heri Mulyono; Haris Kurniawan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6560

Abstract

Problems in the new student admission process at SMK Negeri 1 Painan are still encountered, one of which is the administrative process that is carried out manually. This causes applicant data management to be less effective, prone to errors, and time-consuming in the selection process up to the announcement stage. In addition, the limitations of the manual system make it difficult for the admission committee to verify documents and prepare reports. Therefore, a web-based information system is needed to manage the processes of registration, selection, journaling, announcement, and re-registration in a more structured, efficient, and accessible manner. The research method used was the Iterative Development method, which is carried out gradually and repeatedly. The research stages consisted of requirements analysis to identify system needs, design to create the interface and workflow, and development to implement the main features such as dashboard, account management, registration form, document verification, announcement of selection results, and reporting.   The results of this study show that system testing using the White Box method obtained an average score of 89.27% in the very valid category. Meanwhile, testing using the Black Box method obtained an average score of 94.86% in the very valid category. The practicality test based on the responses of administrators/admission committees reached 97.22% in the very practical category, while user responses (prospective students) reached 94.5% in the very practical category. The conclusion of this study is that the web-based new student admission system developed with the Laravel framework has been tested valid and practical based on white box and black box testing, as well as user evaluations. Thus, the system is feasible to be used as the main tool in the admission process at SMK Negeri 1 Painan because it improves the effectiveness and efficiency of school administration.
MODEL PREDIKSI CURAH HUJAN HARIAN KOTA PADANG MENGGUNAKAN DEEP NEURAL NETWORK (DNN) Aisyah Fadri; Satrio Junaidi; Ainil Mardiyah
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6561

Abstract

Extreme weather in coastal areas such as Kota Padang is influenced by complex topography and local atmospheric dynamics, making daily rainfall prediction a critical challenge for disaster mitigation and sectoral planning. This study aims to develop a daily rainfall prediction model using a Deep Neural Network (DNN) and evaluate its performance. The dataset consists of daily temperature, humidity, and air pressure data collected from the Automatic Weather Station (AWS) of BMKG Maritime Teluk Bayur from January 2020 to December 2024, comprising 1,823 samples after preprocessing. The research methodology follows the CRISP-DM framework, which includes six main phases. The proposed DNN architecture contains three hidden layers (128, 64, and 32 neurons) with ReLU activation and dropout regularization, enhanced by lag and rolling average features to capture temporal patterns. The model achieved an MAE of 1.79, RMSE of 17.31, and R² of 0.8972, indicating strong predictive performance. The model was deployed through a Streamlit-based interactive dashboard
REFORMULASI KEBIJAKAN HUKUM PIDANA TERHADAP TINDAK PIDANA PERDAGANGAN ORANG SEBAGAI KEJAHATAN LUAR BIASA (EXTRAORDINARY CRIME) Alfiandi Wisudawansyah Nasution; Asri Vivi Yanti Sinurat
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6562

Abstract

The Crime of Human Trafficking is a transnational crime that violates human rights through various forms of exploitation, including sexual exploitation, forced labor, and modern slavery. Although Indonesia has enacted Law Number 21 of 2007 on the Eradication of Human Trafficking, its enforcement still faces numerous challenges, including weak supervision, inadequate victim protection, and the emergence of digital-based trafficking methods. This study aims to analyze the weaknesses of the existing criminal law policy and to formulate a reformed legal policy by positioning human trafficking as an extraordinary crime. Using a normative legal research method, the findings indicate that human trafficking possesses the characteristics of an organized, transnational, and profit-driven crime, thereby requiring special legal treatment. Therefore, it is necessary to strengthen criminal sanctions, optimize asset confiscation, expand corporate criminal liability, and enhance victim protection and recovery mechanisms in order to achieve a more effective and just eradication of human trafficking.
INDUKSI TRICODERMA SP DAN PAENIBACILLUS POLYMYXA TERHADAP KETAHANAN PENYAKIT BLAS DAN KRESEK PADA PRODUKTIVITAS TANAMAN PADI (ORYZA SATIVA L.) Elfin Efendi, S.TP., MP; Zunaida Sitorus, S.Si., M.Si; Rahmadi Rajab, SP
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6563

Abstract

The reseach was conducted in Panca Arga Village, Rawang Panca Arga District, Asahan, North Sumatra, to determine the effect of Trichoderma sp. and Paenibacillus polymexa induction on rice blast and kresek disease resistance. The study used a factorial randomized block design with two factors: four levels of Trichoderma sp. concentration: T0 0 ml/liter, T1 25 ml/liter, T2 50 ml/liter, T3 70 ml/liter, and three levels of Paenibacillus polymexa bacteria: P0 0 ml/liter, P1 50 ml/liter, P2 100 ml/liter, with three replications. Observation parameters included plant height, number of tillers, flowering age, intensity of blast disease attacks, intensity of kresek disease attacks, harvest age, production per clump, and production per plot. The results showed that Trichoderma sp induction gave the best results at a plant height of 90.80 cm, the number of tillers was 30.58 plants, flowering age was 46.08 days, blast attack intensity was 0.51%, kresek attack intensity was 3.63%, harvest age was 110.72 days, production per clump was 64.78 g and production per plot was 1.61 kg. Paenibacillus polymyxa induction gave the best results at a plant height of 85.88 cm, the number of tillers was 30.15 plants, flowering age was 45.81 days, blast attack intensity was 4.20%, kresek attack intensity was 4.40%, harvest age was 110.31 days, production per clump was 61.25 g and production per plot was 1.54 kg. The interaction between Trichoderma sp and Paenibacillus polymyxa induction had no significant effect on plant height, number of tillers, flowering age, harvest age, production per clump, and production per plot. The interaction had a significant effect on the intensity of blast and kresek attacks
PENGARUH MODEL PEMBELAJARAN DISCOVERY LEARNINGTERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA BERBANTU APLIKASI PhETMTs MUHAMMADIDYAH 17 PUNGGULANKELAS VII Amanda Rizky Aulia Putri; Muthia Dewi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6564

Abstract

The study aims to determine whether Guided Discovery Learning influences students' mathematical problem-solving ability assisted by the PhET application at VIIth-grade students of MTs Muhammadiyah 17 Punggulan. This study used a quantitative method with a Quasi-Experimental method using a Two-Group Pretest-Posttest Design. In addition, this study found that the sample used was normally distributed and homogeneous. The results of data analysis indicate that the instrument used was valid and reliable. The population in this study are VIIth-grade students of MTs Muhammadiyah 17 Punggulan, with a sample consisting of two classes: VIIth- 1 grade as the experimental class and VIIth- 2 grade as the control class. The instrument used was a posttest of mathematical problem solving ability using a t-test with a significance level of 0.05. The results of the t-test obtained tcount = 2.716> ttable = 2.004 so that H0 was rejected and H1 was accepted, so it can be concluded that there is an influence of the Discovery Learning learning model assisted by the PhET application on students' mathematical problem solving abilities on the material of flat shapes at VIIth grade studentas of  MTs Muhammadiyah 17 Punggulan in 2025/2026 Academic Year.
MODEL KINERJA KARYAWAN BERBASIS PARTISIPASI KERJA, STRES KERJA, DAN KOMPENSASI: STUDI PADA PT TIDAR KERINCI AGUNG SOLOK SELATAN Rahmatullah Pratama; Dike Rama Putra
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6565

Abstract

This study aims to determine the extent of the influence of work participation, work stress, and compensation on the employee performance of PT. Tidar Kerinci Agung Solok Selatan. The study consists of three independent variables, namely work participation, work stress, and compensation, and one dependent variable, employee performance. The analytical methods employed were correlation analysis and multiple regression analysis. Data were collected through questionnaires completed by employees of PT. Tidar Kerinci Agung Solok Selatan. Furthermore, based on the simultaneous hypothesis test (F-test), the calculated F-value was 19.077, which is greater than the F-table value of 2.76 (19.077 > 2.76), with a significance level of 0.000 (< 0.050). Therefore, it can be concluded that work participation, work stress, and compensation simultaneously have a positive and significant effect on employee performance. In addition, the coefficient of determination (R²) was found to be 0.467, or 46.7%. This indicates that 46.7% of the variation in employee performance can be explained by work participation, work stress, and compensation, while the remaining 53.3% is influenced by other variables not examined in this study.
MODEL PRIORITAS PENINGKATAN KUALITAS SISTEM INFORMASI AKADEMIK MENGGUNAKAN INTEGRASI AHP DAN IMPORTANCE PERFORMANCE ANALYSIS (IPA) PADA SMA NEGERI 1 TALAMAU Afni Nia Sari; Rizalina; Elvira Sawitri
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6566

Abstract

The rapid development of information technology has encouraged schools to implement Academic Information Systems (AIS) to improve the effectiveness of academic data management. However, the quality of information system services is often not optimal, resulting in a gap between users' expectations and perceptions. This study aims to determine the priority areas for improving the quality of the Academic Information System at SMA Negeri 1 Talamau through the integration of the Analytical Hierarchy Process (AHP) and Importance Performance Analysis (IPA) methods. The AHP method is employed to determine the priority weights of each system quality criterion, while IPA is used to identify attributes that require improvement based on their importance and performance levels. The study adopts a quantitative approach involving students, teachers, and administrative staff as respondents. The results indicate that the information quality dimension has the highest priority weight, followed by system quality and service quality. The IPA analysis reveals that several attributes fall into Quadrant I (Concentrate Here), making them the main priorities for improvement, particularly regarding system access speed, academic information accuracy, and service responsiveness. This study produces a priority model that can be utilized by the school as a basis for decision-making in enhancing the quality of its Academic Information System.  
OPTIMASI ALGORITMA K-MEANS TERHADAP DATA OUTLIER MENGGUNAKAN ROBUST DALAM SEGMENTASI PELANGGAN BIZNET MEDAN Dwina Pri Indini; Solly Ariza; Zulham Sitorus
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6568

Abstract

Abstract: The massive growth of internet penetration in Indonesia has created competitive competition among internet service providers (ISPs), including Biznet Medan. However, the highly diverse and heterogeneous characteristics of customers make one-size-fits-all marketing strategies ineffective and inefficient. Processing large customer data for segmentation is often hampered by the presence of outliers, such as extreme income variations, which can disrupt the clustering accuracy of conventional algorithms. This study aims to optimize the K-Means algorithm in segmenting Biznet Medan's target market to maintain accuracy despite outliers, allowing the company to design more targeted marketing strategies. To overcome K-Means' sensitivity to outliers, this study applies the Robust Scaling technique. This solution uses the Median and Interquartile Range (IQR) values ​​instead of the mean, so that the cluster center points (centroids) remain stable and are not distorted by extreme data values. The research flow includes data collection of prospective Biznet Medan customers, data pre-processing (cleaning and scaling), feature selection (income, distance, and network requirements), and implementation of the K-Means model. Cluster quality evaluation is carried out by comparing the results of using StandardScaler and RobustScaler through the Silhouette Score and Davies Bouldin Index (DBI) metrics. The implementation successfully formed two main segments: Cluster 0 (Enterprise/Premium Customers) with high income characteristics and large bandwidth requirements (>200 Mbps), and Cluster 1 (Casual/Economical Customers) who dominate the market with lower network requirements (<50 Mbps). Optimization with Robust showed significant improvements in the evaluation metrics, where the Silhouette Score increased from 0.3133 to 0.6023, and the DBI value improved from 1.1421 to 0.8007. The implementation of Robust Scaling is effectively able to handle outlier problems in the K-Means algorithm, resulting in a more robust, efficient, and representative cluster structure. These results contribute to the processing of customer data for more objective strategic decision-making in ISP market expansion. Keywords: k-means; clustering; outlier; robust scaling; customer segmentation.   Abstrak: Pertumbuhan internet di Indonesia yang masif telah menciptakan persaingan kompetitif di antara penyedia jasa internet (ISP), termasuk Biznet Medan. Namun, karakteristik pelanggan yang sangat beragam dan bersifat heterogen membuat strategi pemasaran satu untuk semua (one-size-fits-all) menjadi tidak efektif dan tidak efisien. Data calon pelanggan yang besar sering ditemui data yang hilang, perbedaan nilai data yang ekstrim sehingga pengolahan data calon pelanggan untuk segmentasi sering kali terkendala oleh adanya data pencilan (outlier) yang dapat mengganggu akurasi pengelompokan pada algoritma konvensional. Penelitian ini bertujuan untuk mengoptimasi algoritma K-Means dalam melakukan segmentasi target pasar Biznet Medan agar tetap akurat meskipun terdapat data outlier, sehingga perusahaan dapat merancang strategi pemasaran yang lebih tepat sasaran. Untuk mengatasi sensitivitas K-Means terhadap pencilan, penelitian ini menerapkan teknik Robust Scaling. Solusi ini menggunakan nilai Median dan Interquartile Range (IQR) sebagai pengganti rata-rata, sehingga titik pusat klaster (centroid) tetap stabil dan tidak terdistorsi oleh nilai data yang ekstrem. Alur penelitian meliputi pengumpulan data calon pelanggan Biznet Medan, pra-pemrosesan data (pembersihan dan scaling), pemilihan fitur (penghasilan, jarak, dan kebutuhan jaringan), serta implementasi model K-Means. Evaluasi kualitas klaster dilakukan dengan membandingkan hasil penggunaan StandardScaler dan RobustScaler melalui metrik Silhouette Score dan Davies Bouldin Index (DBI). Implementasi berhasil membentuk dua segmen utama: Cluster 0 (Pelanggan Enterprise/Premium) dengan karakteristik penghasilan tinggi dan kebutuhan bandwidth besar (>200 Mbps), serta Cluster 1 (Pelanggan Casual/Hemat) yang mendominasi pasar dengan kebutuhan jaringan lebih rendah (<50 Mbps). Optimasi dengan Robust menunjukkan peningkatan signifikan pada metrik evaluasi, di mana Silhouette Score meningkat dari 0,3133 menjadi 0,6023, dan nilai DBI membaik dari 1,1421 menjadi 0,8007. Penerapan Robust Scaling secara efektif mampu menangani masalah outlier pada algoritma K-Means, menghasilkan struktur klaster yang lebih kuat, efisien, dan representatif. Hasil ini memberikan kontribusi pada pengolahan data pelanggan untuk pengambilan keputusan strategis yang lebih objektif dalam ekspansi pasar ISP. Kata kunci: K-Means; klasterisasi; data pencilan; Robust Scaling; Segmentasi Pelanggan.
DEVELOPMENT OF IOT-BASED MOTORCYCLE ELECTRICAL LEARNING MEDIA Ricki Ananda; Muhammad Amin; Febby Madonna Yuma; Adi Mas Afandi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/cj3tgy87

Abstract

Abstract: The development of Industry 4.0 toward Society 5.0 requires innovation in vocational learning media based on Internet of Things (IoT) for motorcycle electrical systems. This study aims to develop a learning media for real-time monitoring and fault diagnosis. The method used is Design Based Research (DBR) consisting of analysis, design, development, and testing stages. The system integrates an ADC voltage sensor (12.6 V normal; ADC ≈ 859 and 12.1 V weak; ADC ≈ 820), pull-up resistor switch detection (logic 0 = 0 V normal; logic 1 = 5 V fault), ACS712 current sensor (1.5 A lamp ON; ADC ≈ 568 and 0 A fuse fault; ADC ≈ 511), and INA219 charging sensor (14.0 V normal charging; ADCbus ≈ 3500 and 12.4 V not charging; ADCbus ≈ 3100). The results show that all sensors operate stably and accurately in detecting both normal and fault conditions. Integration into a web-based dashboard enables real-time monitoring via computers and smartphones. Therefore, the developed learning media effectively improves students’ understanding, visualization, and analytical skills in IoT-based motorcycle electrical systems. Keywords: ACS712; ADC; Design Based Research; INA219; IoT; Motorcycle Electrical System; Learning Media   Abstrak: Perkembangan Revolusi Industri 4.0 menuju Society 5.0 menuntut inovasi media pembelajaran vokasi berbasis Internet of Things (IoT) pada sistem kelistrikan sepeda motor. Penelitian ini bertujuan mengembangkan media pembelajaran untuk monitoring dan diagnosis kerusakan kelistrikan secara real-time. Metode yang digunakan adalah Design Based Research (DBR) melalui tahap analisis, perancangan, pengembangan, dan pengujian. Sistem menggunakan sensor ADC (12,6 V normal; ADC ≈ 859 dan 12,1 V lemah; ADC ≈ 820), pull-up resistor (logika 0 = 0 V normal; logika 1 = 5 V kerusakan), ACS712 (1,5 A lampu ON; ADC ≈ 568 dan 0 A saat sekring putus; ADC ≈ 511), serta INA219 (14,0 V charging normal; ADCbus ≈ 3500 dan 12,4 V tidak mengisi; ADCbus ≈ 3100). Hasil pengujian menunjukkan seluruh sensor bekerja stabil, akurat, dan sesuai fungsi dalam mendeteksi kondisi normal maupun fault pada sistem kelistrikan. Integrasi data sensor ke dashboard web memungkinkan pemantauan real-time melalui perangkat komputer dan smartphone. Dengan demikian, media pembelajaran yang dikembangkan efektif meningkatkan pemahaman, visualisasi, dan kemampuan analisis peserta didik pada sistem kelistrikan sepeda motor berbasis IoT.. Kata kunci: ACS712; ADC; Design Based Research; INA219; IoT; Kelistrikan Sepeda Motor; Media  Pembelajaran
SINERGI AI (QUILLBOT) DAN BUDAYA BATAK TOBA: UPAYA MENDUKUNG KETERAMPILAN MENULIS BAHASA PRANCIS DENGAN BUKU CERITA DIGITAL Herman Syahputra; Hadijah Handayani Sibuea; Irda Yusepa; Widya Trisna Handayani; Harun Sitompul
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6570

Abstract

Abstract: This study aims to develop a digital storybook based on Batak Toba culture integrated with QuillBot AI as an editing assistant to support students' French writing skills. The study employed a mixed-methods approach using the Educational Design Research (EDR) framework. Data were collected through interviews, observations, expert validation questionnaires, and limited trials. The resulting product was a digital storybook entitled Sahabat Danau Toba, equipped with writing tasks, a French glossary, and a QuillBot-assisted editing feature. Material and media expert validations achieved scores of 94% and 93%, respectively, indicating that the product was highly feasible. The one-to-one, small-group, and field-test evaluations obtained scores of 83.3%, 88%, and 96%, respectively. The overall user response reached 94.3% and was categorized as very good. Students reported that the Batak Toba-based story was interesting, easy to understand, and helpful in generating writing ideas. QuillBot also helped students independently revise their grammar and improve their writing. Therefore, the developed product is feasible as a supporting medium for French writing instruction based on local culture. Keywords: Artificial Intelligence, Batak Toba Culture, Digital Storybooks, Writing Skills, French Language Learning   Abstrak: Penelitian ini bertujuan mengembangkan buku cerita digital berbasis budaya Batak Toba yang terintegrasi dengan AI QuillBot sebagai asisten editor untuk mendukung keterampilan menulis bahasa Prancis mahasiswa. Penelitian menggunakan pendekatan mixed methods dengan desain Educational Design Research (EDR). Data dikumpulkan melalui wawancara, observasi, angket validasi ahli, dan uji coba terbatas. Produk yang dihasilkan berupa buku cerita digital Sahabat Danau Toba yang dilengkapi tugas menulis, glosarium bahasa Prancis, dan fitur QuillBot. Hasil validasi ahli materi dan ahli media masing-masing memperoleh skor 94% dan 93% dengan kategori sangat layak. Hasil one-to-one evaluation memperoleh skor 83,3%, small group evaluation 88%, dan field test 96%. Rata-rata respons pengguna mencapai 94,3% dengan kategori sangat baik. Mahasiswa menyatakan bahwa cerita berbasis budaya Batak Toba menarik, mudah dipahami, dan membantu mengembangkan ide menulis. Fitur QuillBot juga membantu mahasiswa memperbaiki tata bahasa dan tulisan secara mandiri. Dengan demikian, produk yang dikembangkan layak digunakan sebagai media pendukung pembelajaran menulis bahasa Prancis berbasis budaya lokal. Kata kunci: Artificial Intelligence, Budaya Batak Toba, Buku Cerita Digital, Writing Skills, French Language Learning

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