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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.
Arjuna Subject : -
Articles 3,645 Documents
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ANALISIS HUKUM TERHADAP UPAYA PENCEGAHAN DAN DETEKSI PENCUCIAN UANG DALAM BISNIS ASURANSI BNI LIFE (Studi Putusan Nomor 740/Pid.Sus/2014/PT MDN) Nurul Qoedatul Khoiriyah Siregar; Mahmud Mulyadi; Abdul Aziz Alsa
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.v9i3.6683

Abstract

Abstract: Money laundering is a crime that can exploit various financial service sectors—including the insurance industry—as a means to disguise the origins of assets derived from criminal activity. The increasing complexity of insurance products and services heightens the risk of the sector being used as a vehicle for money laundering. This study aims to analyze efforts to prevent and detect money laundering within the insurance business, specifically focusing on Court Decision Number 740/Pid.Sus/2014/PT MDN, which involved a former agent of PT BNI Life Insurance Medan. The study employs a normative legal research method utilizing a statutory approach, supplemented by empirical data obtained through interviews. A descriptive-qualitative analysis was conducted on the relevant legislation, legal literature, and the court decision serving as the study's subject. The findings indicate that criminal acts in the insurance sector can take the form of insurance fraud, fraudulent claims, premium embezzlement, policy document forgery, and money laundering. In the case under review, the defendant was proven to have forged documents and misappropriated client investment funds, subsequently using those funds in a manner that disguised their origins. PT BNI Life Insurance’s efforts to prevent and combat money laundering are implemented through the application of "Know Your Customer" (KYC) principles, Customer Due Diligence (CDD), continuous transaction monitoring, the reporting of suspicious financial transactions to the Financial Transaction Reports and Analysis Center (PPATK), and the enhancement of human resource competence. Based on crime prevention theory, these measures are effective in narrowing the opportunities for money laundering and increasing the likelihood of criminal activity being detected. An analysis of the judicial decision reveals that the ruling upholds the principles of justice, legal certainty, and legal utility; however, from a restorative justice perspective, there remain shortcomings, as the restitution of the victim's losses has not been fully realized.  Keywords: Money Laundering, Insurance, Prevention and Detection, BNI Life Insurance, Judgment Number 740/Pid.Sus/2014/PT MDN. Abstrak: Tindak pidana pencucian uang (TPPU) merupakan kejahatan yang dapat memanfaatkan berbagai sektor jasa keuangan, termasuk industri perasuransian, sebagai sarana untuk menyamarkan asal-usul harta kekayaan yang diperoleh dari tindak pidana. Perkembangan produk dan layanan asuransi yang semakin kompleks meningkatkan potensi sektor ini menjadi media pencucian uang. Penelitian ini bertujuan untuk menganalisis upaya pencegahan dan deteksi tindak pidana pencucian uang dalam bisnis asuransi, khususnya berdasarkan Putusan Nomor 740/Pid.Sus/2014/PT MDN yang melibatkan mantan agen PT BNI Life Insurance Medan. Penelitian ini menggunakan metode penelitian hukum normatif dengan pendekatan perundang-undangan (statute approach) yang didukung data empiris melalui wawancara. Analisis dilakukan secara deskriptif kualitatif terhadap peraturan perundang-undangan, literatur hukum, serta putusan pengadilan yang menjadi objek penelitian.Hasil penelitian menunjukkan bahwa tindak pidana dalam sektor asuransi dapat berupa penipuan asuransi, penipuan klaim asuransi, penggelapan premi, pemalsuan dokumen polis, dan pencucian uang. Dalam perkara yang diteliti, terdakwa terbukti melakukan pemalsuan dokumen dan penyalahgunaan dana investasi nasabah yang kemudian digunakan untuk menyamarkan asal-usul dana tersebut. Upaya pencegahan dan pemberantasan TPPU yang dilakukan oleh PT BNI Life Insurance diwujudkan melalui penerapan prinsip mengenali nasabah (Know Your Customer), Customer Due Diligence (CDD), pemantauan transaksi secara berkelanjutan, pelaporan transaksi keuangan mencurigakan kepada PPATK, serta peningkatan kompetensi sumber daya manusia. Berdasarkan teori pencegahan kejahatan, langkah-langkah tersebut efektif dalam mempersempit peluang terjadinya pencucian uang dan meningkatkan risiko terdeteksinya tindak pidana. Analisis terhadap putusan hakim menunjukkan bahwa putusan telah memenuhi prinsip keadilan, kepastian hukum, dan kemanfaatan hukum, meskipun dari perspektif keadilan restoratif masih terdapat kelemahan karena pemulihan kerugian korban belum sepenuhnya terpenuhi. Kata Kunci: Tindak Pidana Pencucian Uang, Asuransi, Pencegahan dan Deteksi, BNI Life Insurance, Putusan Nomor 740/Pid.Sus/2014/PT MDN.
UJI EFEKTIVITAS ANTIINFLAMASI GEL EKSTRAK ETANOL DAUN CIPLUKAN (Physalis angulata) PADA TIKUS PUTIH JANTAN (Rattus norvegicus) Yulia Kusumanti; Indriati Aulia; Nur ‘aini; Indah Almaidah; Wahidah
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.v9i3.6685

Abstract

Abstract: Ciplukan leaves (Physalis angulate) are a plant that has many benefits to society, one of which is anti-inflammatory. Inflammation is a process in the body to respond to infection or tissue damage. This research aims to test the anti-inflammatory effectiveness of ciplukan leaf extract. Ciplukan leaves contain flavonoids and tannins which are effective in inhibiting the cyclooxygenase pathway which can inhibit inflammation. The results showed that the percentage inhibition results of the sodium diclofenac gel group had a percentage of 93.11%, the 20% ciplukan leaf ethanol extract gel group had a percentage of 79.85%, the 25% ciplukan leaf ethanol extract gel group had a percentage of 81.36%, and the 30% ciplukan leaf ethanol extract gel group had a percentage of 89.95%. These results indicate that the method applied provides accurate and precise results. The results of the study can be concluded that from the three formulations of ciplukan leaf ethanol extract gels that have the highest percentage results are in the 30% ciplukan leaf ethanol extract formulation. Keywords: anti-inflammatory, gel, ground cherry leaves   Abstrak: Daun ciplukan (Physalis angulate) merupakan tanamannyang memiliki banyaknmanfaat pada masyarakat, salah satunya sebagai antiinflamasi. Inflamasi merupakan proses dalam tubuh untuk merespon infeksi atau kerusakan jaringan. Penelitian ini bertujuan untuk menguji efektivitas antiinflamasi ekstrak daun ciplukan. Daun ciplukan mengandung flavonoid dan tannin yang berkhasiat untuk menghambat jalur sikloogsigenase yang dapat menghambat inflamasi. Hasil penelitian menunjukkan bahwa pada hasil persentase inhibsi kelompok gel natrium diklofenak memiliki persentase 93,11%, kelompok gel ekstrak etanol daun ciplukan 20% memiliki persentase 79,85%, kelompok gel ekstrak etanol daun ciplukan 25% memiliki persentase 81,36%, dan pada kelompok gel ekstrak etanol daun ciplukan 30% memiliki persentase 89,95%. Hasil ini menunjukkan bahwa metode yang dilakukkan memberikkan hasil yang akurat dan teliti. Hasil penelitian dapat disimpulkan bahwa dari ketiga formulasi gel ekstrak etanol daun ciplukan yang memiliki hasil persentase paling tertinggi terdapat pada formulasi ekstrak etanol daun ciplukan 30%. Kata Kunci: antiinflamasi, gel, daun ciplukan
UJI EFEKTIVITAS GEL EKSTRAK ETANOL DAUN RAMBUSA (Passiflora foetida L.) TERHADAP PENYEMBUHAN LUKA BAKAR DERAJAT II PADA TIKUS PUTIH JANTAN (Rattus norvegicus) Desi Alviolina; Eldesi Medisa lmawati; Ichmi Ikhtiari Nanjar; Ilham Syahputra
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.v9i3.6686

Abstract

Abstract: Burn wounds are tissue damage caused by exposure to high heat, chemicals, electricity, or radiation, requiring appropriate treatment to prevent nfection and accelerate tissue regeneration. Passiflora foetida L. leaves contain bioactive compounds such as alkaloids, flavonoids, saponins, tannins, and steroids, which possess anti-inflammatory, antimicrobial, and antioxidant properties, making them a potential agent for burn wound healing. This study aimed to evaluate the effectiveness of ethanol extract gel of P. foetida leaves n burn wound healing n male white rats (Rattus norvegicus) and to determine the most optimal concentration. A true experimental method with a completely randomized design (CRD) was applied, nvolving five treatment groups: negative control, positive control, and P. foetida leaf extract gel at various concentrations, n 5%,10% and 15% concentration. Observed parameters ncluded wound diameter reduction and the percentage wound reduction. The results showed that the ethanol extract gel of P. foetida leaves significantly promoted burn wound healing (p < 0.05) compared to the negative control. A 15% concentration demonstrated the highest effectiveness n accelerating wound closure and mproving tissue condition. n conclusion, P. foetida leaves can be formulated nto effective gel preparation for burn wound treatment. Keywords: Passiflora foetida L., gel, burn wound, diameter reduction and percentage wound healing and reduction, male white rats Abstrak: Luka bakar merupakan kerusakan jaringan kulit akibat paparan panas tinggi, bahan kimia, listrik, atau radiasi, yang memerlukan penanganan tepat untuk mencegah nfeksi dan mempercepat regenerasi jaringan. Daun rambusa (Passiflora foetida L.) diketahui mengandung senyawa bioaktif seperti alkaloid, flavonoid, saponin, dan tanin yang berkhasiat sebagai antiinflamasi, antimikroba, dan antioksidan sehingga berpotensi digunakan sebagai bahan penyembuhan luka bakar. Penelitian ni bertujuan untuk mengetahui efektivitas gel ekstrak etanol daun rambusa terhadap penyembuhan luka bakar pada tikus putih jantan (Rattus novergicus) serta menentukan konsentrasi yang paling optimal. Metode yang digunakan adalah eksperimental murni dengan rancangan acak lengkap (RAL) menggunakan lima kelompok perlakuan, yaitu kontrol negatif, kontrol positif, serta gel ekstrak daun rambusa dengan beberapa konsentrasi yaitu pada konsentrasi 5%,10% dan 15%. Parameter yang diamati meliputi diameter penurunan luka bakar dan persentase penyembuhan luka bakar. Hasil penelitian menunjukkan bahwa gel ekstrak etanol daun rambusa memberikan aktivitas penyembuhan luka bakar yang signifikan (p < 0,05) dibandingkan kontrol negatif. Konsentrasi 15% diketahui menunjukkan efektivitas tertinggi dalam mempercepat penutupan luka dan memperbaiki kondisi jaringan. Kesimpulannya, daun rambusa dapat diformulasikan menjadi sediaan gel yang efektif sebagai agen penyembuh luka bakar. Kata kunci: Passiflora foetida L., gel, luka bakar, diameter dan persentase penyembuhan luka, tikus putih jantan
URGENSI REFORMASI HUKUM PERLINDUNGAN SAKSI DAN KORBAN UNTUK MEWUJUDKAN SISTEM PERADILAN PIDANA YANG BERKEADILAN DAN BERORIENTASI PADA HAK KORBAN Asri Vivi Yanti Sinurat; Junaidi Sholat; Ahmad Ray Fadillah 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.v9i3.6687

Abstract

Abstract: The protection of witnesses and victims had constituted a fundamental element in the administration of a fair criminal justice system. Nevertheless, its implementation in Indonesia had encountered various normative and institutional shortcomings that impeded the effective fulfillment of victims' rights. This study aimed to examine the urgency of legal reform in witness and victim protection in order to promote a criminal justice system grounded in substantive justice and victim-oriented principles. The study employed a normative legal research method with statutory and conceptual approaches through the analysis of legislation, legal doctrines, and relevant scholarly literature. The findings indicate that strengthening legal substance, enhancing institutional effectiveness, and developing comprehensive mechanisms for protection and recovery are essential to ensure effective access to justice and the restoration of victims' rights. Therefore, legal reform in witness and victim protection constitutes a strategic prerequisite for establishing a more responsive, equitable, and victim-oriented criminal justice system. Keywords: Legal Reform; Witness and Victim Protection; Substantive Justice; Criminal Justice System; Victims' Rights.   Abstrak: Perlindungan saksi dan korban merupakan elemen fundamental dalam penyelenggaraan sistem peradilan pidana yang berkeadilan, namun implementasinya di Indonesia masih menghadapi berbagai kelemahan normatif dan kelembagaan yang berdampak pada belum optimalnya pemenuhan hak-hak korban. Penelitian ini bertujuan menganalisis urgensi reformasi hukum perlindungan saksi dan korban dalam mewujudkan sistem peradilan pidana yang berorientasi pada keadilan substantif dan pemulihan hak korban. Penelitian menggunakan metode hukum normatif dengan pendekatan perundang-undangan dan pendekatan konseptual melalui kajian terhadap peraturan perundang-undangan, doktrin, dan literatur yang relevan. Hasil penelitian menunjukkan bahwa reformasi hukum diperlukan melalui penguatan substansi hukum, optimalisasi peran kelembagaan, serta pengembangan mekanisme perlindungan dan pemulihan yang komprehensif. Dengan demikian, reformasi hukum perlindungan saksi dan korban merupakan prasyarat strategis dalam membangun sistem peradilan pidana yang lebih responsif, berkeadilan, dan berorientasi pada pemenuhan hak-hak korban. Kata kunci: Reformasi Hukum; Perlindungan Saksi dan Korban; Keadilan Substantif; Sistem Peradilan Pidana; Hak Korban
TREN, TANTANGAN, DAN ARAH PENELITIAN PEMANFAATAN MACHINE LEARNING PADA BERBAGAI SEKTOR DI ERA ARTIFICIAL INTELLIGENCE: SEBUAH SYSTEMATIC LITERATURE REVIEW TAHUN 2020–2026 Sudy; Dita Mitha Sucitra; Aulianza Alfirzy Saragih; Novaldo Andrian Syahputra; Dicky Apdillah
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.v9i3.6688

Abstract

Abstract: The advancement of Artificial Intelligence (AI) has driven the widespread adoption of Machine Learning (ML) across various sectors. This study aims to analyze the development trends, implementation sectors, dominant algorithms, key challenges, and future research directions of ML during the 2020–2026 period. Utilizing a Systematic Literature Review (SLR) based on PRISMA 2020 and Kitchenham Guidelines, 120 peer-reviewed articles from six international academic databases were systematically evaluated. The findings indicate a significant increase in ML publications post-Generative AI era, with the highest adoption rates observed in the healthcare, finance, and manufacturing sectors. Algorithms such as Random Forest, XGBoost, CNN, and LSTM dominate for prediction and classification tasks. Despite its benefits, the primary challenges of ML deployment involve data quality, privacy, algorithmic bias, and model interpretability. This study highlights a shifting research paradigm toward transparent and human-centered AI, outlining future agendas in Explainable AI (XAI), Federated Learning, and Green AI. Keywords: Artificial Intelligence; Explainable AI; Federated Learning; Generative AI; Machine Learning.   Abstrak: Perkembangan Artificial Intelligence (AI) mendorong pemanfaatan Machine Learning (ML) secara luas di berbagai sektor lintas disiplin. Penelitian ini bertujuan menganalisis tren perkembangan, sektor implementasi, algoritma dominan, tantangan utama, serta arah penelitian masa depan terkait pemanfaatan ML selama periode 2020–2026. Metode yang digunakan adalah Systematic Literature Review (SLR) berbasis pedoman PRISMA 2020 dan Kitchenham Guidelines terhadap 120 artikel ilmiah terpilih dari enam database akademik internasional. Hasil tinjauan menunjukkan adanya peningkatan signifikan publikasi ML pasca-era Generative AI, dengan adopsi tertinggi pada sektor kesehatan, keuangan, dan manufaktur. Algoritma berbasis data tabular (seperti Random Forest dan XGBoost) serta data citra/deret waktu (seperti CNN dan LSTM) menjadi yang paling dominan digunakan untuk kebutuhan prediksi dan klasifikasi. Meskipun menawarkan efisiensi tinggi, tantangan utama implementasi ML berpusat pada kualitas data, privasi, bias algoritma, dan interpretabilitas model. Penelitian ini merumuskan agenda riset masa depan yang mulai bergeser ke arah pengembangan AI yang transparan dan berpusat pada manusia, seperti Explainable AI (XAI), Federated Learning, dan Green AI. Kata Kunci: Artificial Intelligence; Explainable AI; Federated Learning; Generative AI; Machine Learning.
SYSTEMATIC LITERATURE REVIEW TERHADAP SEMANTIC PARSING BERBASIS TRANSFORMER DALAM NATURAL LANGUAGE PROCESSING Dwi Suci Ramadani; Fahira Hasanah Br Harahap; Suci Lestari Br Batu Bara; Winda Sari; Dicky Apdillah
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.v9i3.6689

Abstract

Abstract: The development of transformer architecture has brought significant changes in Natural Language Processing (NLP) research, particularly in semantic parsing tasks. This study aims to analyze the development of transformer-based semantic parsing through a Systematic Literature Review (SLR) approach. The research method uses the PRISMA guidelines with a process of identification, selection, and analysis of articles from the Scopus, ScienceDirect, IEEE Xplore, Springer, and Google Scholar databases for the period 2019–2026. The results of the study show that transformer models such as BERT, T5, GPT, and transformer encoder–decoder have become the dominant approaches in modern semantic parsing because they are able to improve contextual understanding, semantic representation, and reasoning more effectively than previous methods. The most widely used datasets include Spider, WikiSQL, GeoQuery, ATIS, and Overnight, with the main evaluation being Execution Accuracy and Exact Match Accuracy. This study also identifies various challenges, such as limited labeled data, high computational costs, low model interpretability, the risk of hallucinations, and limitations in low-resource languages. This research contributes to a literature review, identifying research gaps, and recommending future research directions for transformer-based semantic parsing. Keywords: BERT, Natural Language Processing, Semantic Parsing, Systematic Literature Review, Transformer, T5, Text-to-SQL.   Abstrak: Perkembangan arsitektur transformer telah membawa perubahan signifikan dalam penelitian Natural Language Processing (NLP), khususnya pada tugas semantic parsing. Penelitian ini bertujuan untuk menganalisis perkembangan semantic parsing berbasis transformer melalui pendekatan Systematic Literature Review (SLR). Metode penelitian menggunakan pedoman PRISMA dengan proses identifikasi, seleksi, dan analisis artikel dari database Scopus, ScienceDirect, IEEE Xplore, Springer, dan Google Scholar pada periode 2019–2026. Hasil kajian menunjukkan bahwa model transformer seperti BERT, T5, GPT, dan encoder–decoder transformer menjadi pendekatan dominan dalam semantic parsing modern karena mampu meningkatkan contextual understanding, semantic representation, dan reasoning secara lebih efektif dibandingkan metode sebelumnya. Dataset yang paling banyak digunakan meliputi Spider, WikiSQL, GeoQuery, ATIS, dan Overnight, dengan metrik evaluasi utama berupa Execution Accuracy dan Exact Match Accuracy. Penelitian ini juga mengidentifikasi berbagai tantangan, seperti keterbatasan data berlabel, tingginya biaya komputasi, rendahnya interpretabilitas model, risiko hallucination, serta keterbatasan pada low-resource language. Penelitian ini berkontribusi dalam memberikan pemetaan literatur, identifikasi research gap, dan rekomendasi arah penelitian semantic parsing berbasis transformer pada masa mendatang. Kata Kunci: BERT, Natural Language Processing, Semantic Parsing, Systematic Literature Review, Transformer, T5, Text-to-SQL.
PEMANFAATAN AUGMENTED REALITY BERBASIS OBJEK 3D UNTUK PENGENALAN ORGAN TUBUH MANUSIA Subhan Hartanto; Sarwo Edi Wibowo; Almasari Aksenta
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 4 (2026): August 2026 (1)
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i4.6692

Abstract

The development of digital technology encourages innovation in learning media that is more interactive and easier for students to understand. One technology that can be used is Augmented Reality or AR, which combines three-dimensional virtual objects with the real environment in real time. This study aimed to design and implement an Augmented Reality-based learning media for introducing human body organs. The development method used was the Luther-Sutopo version of the Multimedia Development Life Cycle or MDLC, consisting of concept, design, material collecting, assembly, testing, and distribution stages. The object used in this study was a three-dimensional model of human anatomy equipped with annotations on several organs, such as the liver, heart, and gut. The implementation results showed that AR media could display human anatomy objects virtually through marker scanning using a mobile device. This media allowed users to observe the shape, position, and parts of human organs more clearly and interactively. Therefore, Augmented Reality-based learning media can be an innovative alternative to help improve students’ understanding and learning interest in human body organ materials.
PENGARUH CONTENT MARKETING DAN ELECTRONIC WORD OF MOUTH (e-WOM) TERHADAP KEPUTUSAN PEMBELIAN MELALUI TIKTOK PADA MAHASISWA STAMBUK 2023 Talenta Emma Renata Marbun; Erlianti Simanjuntak; Benyamin Nababan; Faisal Bimantaro Ompusunggu; Syerin Sihombing
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.v9i3.6693

Abstract

Abstract: This study aims to analyze the influence of content marketing and electronic word of mouth on purchase decisions through TikTok among students of the 2023 cohort of the Bachelor of Management Study Program, Faculty of Economics, Universitas Sisingamangaraja XII Tapanuli. This research employed a quantitative approach with a descriptive-causal design. The entire population of 76 students was used as the sample through a total sampling technique. Data were collected using a Likert-scale questionnaire and analyzed using multiple linear regression with SPSS version 26. The results show that content marketing has a positive and significant effect on purchase decisions, with a t-value of 4.870 and a significance level of 0.000. Electronic word of mouth also has a positive and significant effect, with a t-value of 6.186 and a significance level of 0.000. Simultaneously, both variables have a significant effect on purchase decisions, with an F-value of 47.498 and a significance level of 0.000. The coefficient of determination of 0.565 indicates that 56.5% of the variation in purchase decisions is explained by content marketing and electronic word of mouth, while the remaining 43.5% is influenced by other factors. These findings confirm the importance of relevant content strategies and credible user reviews in encouraging student purchase decisions through TikTok. Keywords: content marketing; electronic word of mouth; purchase decision; TikTok; students; digital marketing.   Abstrak: Penelitian ini bertujuan menganalisis pengaruh content marketing dan electronic word of mouth terhadap keputusan pembelian melalui TikTok pada mahasiswa Program Studi S1 Manajemen Fakultas Ekonomi Universitas Sisingamangaraja XII Tapanuli angkatan 2023. Penelitian menggunakan pendekatan kuantitatif dengan desain deskriptif-kausalitas. Seluruh populasi sebanyak 76 mahasiswa dijadikan sampel melalui teknik total sampling. Data dikumpulkan menggunakan kuesioner skala Likert dan dianalisis dengan regresi linear berganda menggunakan SPSS versi 26. Hasil penelitian menunjukkan bahwa content marketing berpengaruh positif dan signifikan terhadap keputusan pembelian dengan nilai t-hitung 4,870 dan signifikansi 0,000. Electronic word of mouth juga berpengaruh positif dan signifikan dengan nilai t-hitung 6,186 dan signifikansi 0,000. Secara simultan, kedua variabel berpengaruh signifikan terhadap keputusan pembelian dengan nilai F-hitung 47,498 dan signifikansi 0,000. Nilai koefisien determinasi sebesar 0,565 menunjukkan bahwa 56,5% variasi keputusan pembelian dijelaskan oleh content marketing dan electronic word of mouth, sedangkan 43,5% dipengaruhi faktor lain. Temuan ini menegaskan pentingnya strategi konten yang relevan dan ulasan pengguna yang kredibel dalam mendorong keputusan pembelian mahasiswa melalui TikTok. Kata Kunci: content marketing, electronic word of mouth, keputusan pembelian, TikTok, mahasiswa, pemasaran digital.
MIMBAR HIJAU KONTEMPORER: ANALISIS WACANA KRITIS TERHADAP FRAMING KRISIS EKOLOGIS DALAM KHUTBAH JUMAT MUHAMMADIYAH DAN NAHDLATUL ULAMA (2024-2026) Abdul Dzakkir
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 4 (2026): August 2026 (1)
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i4.6698

Abstract

Krisis iklim global menuntut transformasi peran institusi agama dari sekadar otoritas penjaga moral-ritual menjadi agen pelestarian bumi. Penelitian ini bertujuan untuk menganalisis pergeseran paradigma ekoteologi (Green Islam) dalam korpus khutbah Jumat dan publikasi resmi Nahdlatul Ulama (NU) serta Muhammadiyah pada periode 2024–2026. Menggunakan metode kualitatif-deskriptif dengan analisis framing Robert Entman, penelitian ini mengungkap tiga temuan fundamental. Pertama, terjadi pergeseran epistemik yang radikal dari teodise konvensional-fatalistik (membingkai bencana murni sebagai azab atas dosa ritual) menuju kritik struktural (membingkai bencana sebagai akibat kejahatan eksploitasi alam dan kelalaian kebijakan negara). Kedua, terjadinya dekonstruksi semantik teologis; NU secara progresif merekonseptualisasi istilah klasik “Maksiat” menjadi “Maksiat Eksploitasi” dan “Tobat” menjadi “Tobat Ekologis” menggunakan legitimasi kitab kuning. Ketiga, terbentuknya polarisasi strategi gerakan yang komplementer. NU mengambil peran makro-teologis melalui sentralisasi hukum publik di ruang mimbar maskulin, sementara Muhammadiyah bermanuver secara mikro-kultural melalui pendekatan ekofeminisme yang menyasar ruang domestik dan gaya hidup (Green Idul Fitri). Penelitian ini menyimpulkan bahwa Islam Indonesia tidak sekadar mengadopsi enviromentalisme sekuler Barat, melainkan berhasil merumuskan epistemologi ekologinya sendiri yang otentik dan bersinergi melalui teks suci dan tradisi lokal.
IMPLEMENTASI ALGORITMA NAIVE BAYES DALAM MENENTUKAN KATEGORI DISKON PELANGGAN BERDASARKAN PERILAKU PEMBELIAN PADA TOKO RETAIL SEBAGAI PENDUKUNG TRANSFORMASI DIGITAL BERKELANJUTAN Fikry Dian Anugerah R Siregar
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/zwty5k55

Abstract

Abstract: Digital transformation has encouraged retail companies to leverage information technology and data analytics to improve operational efficiency and the quality of decision-making. The utilization of technology and data analytics enables companies to automate business processes, enhance analytical accuracy, and manage customer data more effectively. This study aims to implement the Naive Bayes algorithm to determine customer discount categories based on purchasing behavior in retail stores as a form of data-driven decision-making that supports digital transformation. The dataset used in this research is the Marketing Campaign Dataset, which consists of the attributes Income, Recency, NumDealsPurchases, NumWebPurchases, NumStorePurchases, and Response. The research stages include data collection, preprocessing, data transformation, classification model development using the Naive Bayes algorithm, and model evaluation using the Confusion Matrix, Accuracy, Precision, Recall, and F1-Score. The results show that the Naive Bayes model achieved an accuracy of 70% in classifying customers into low, medium, and high discount categories based on their purchasing behavior patterns. The implementation of this model enables retail companies to provide discount category recommendations more quickly, accurately, and consistently. In addition to improving the effectiveness of promotional strategies, this study demonstrates that the application of machine learning-based data analytics can support digital transformation through faster, more accurate, and data-driven decision-making, thereby helping retail companies improve service quality and business process effectiveness. Keywords: Naive Bayes; Digital Transformation; Customer Discount Categories; Purchasing Behavior; Retail Store.   Abstrak: Transformasi digital telah mendorong perusahaan retail untuk memanfaatkan teknologi informasi dan analisis data dalam meningkatkan efisiensi operasional serta kualitas pengambilan keputusan. Pemanfaatan teknologi dan analitik data memungkinkan perusahaan mengotomatisasi proses bisnis, meningkatkan akurasi analisis, serta memanfaatkan data pelanggan secara lebih efektif. Penelitian ini bertujuan mengimplementasikan algoritma Naive Bayes dalam menentukan kategori diskon pelanggan berdasarkan perilaku pembelian pada toko retail sebagai salah satu bentuk pengambilan keputusan berbasis data yang mendukung transformasi digital. Dataset yang digunakan adalah Marketing Campaign Dataset yang terdiri dari atribut Income, Recency, NumDealsPurchases, NumWebPurchases, NumStorePurchases, dan Response. Tahapan penelitian meliputi pengumpulan data, preprocessing, transformasi data, pembentukan model klasifikasi menggunakan algoritma Naive Bayes, serta evaluasi menggunakan Confusion Matrix, Accuracy, Precision, Recall, dan F1-Score. Hasil penelitian menunjukkan bahwa model Naive Bayes memperoleh akurasi sebesar 70% dalam mengklasifikasikan pelanggan ke dalam kategori diskon rendah, sedang, dan tinggi berdasarkan pola perilaku pembelian. Implementasi model ini mampu membantu perusahaan retail dalam memberikan rekomendasi kategori diskon secara lebih cepat, tepat, dan konsisten. Selain meningkatkan efektivitas strategi promosi, penelitian ini menunjukkan bahwa penerapan analitik data berbasis machine learning dapat mendukung transformasi digital melalui pengambilan keputusan yang lebih cepat, akurat, dan berbasis data sehingga membantu perusahaan retail meningkatkan kualitas layanan serta efektivitas proses bisnis. Kata kunci: Naive Bayes; Transformasi Digital; Kategori Diskon Pelanggan; Perilaku Pembelian; Toko Retail.

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