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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.
Arjuna Subject : -
Articles 3,645 Documents
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ANALISIS YURIDIS TERHADAP PERTIMBANGAN HAKIM DALAM PERKARA TINDAK PIDANA KORUPSI PENGUASAAN DAN PENGALIHFUNGSIAN KAWASAN HUTAN KONSERVASI (Studi Putusan PN Medan Nomor: 138/Pid.SUS-TPK/2024/PN Mdn) Dika Wirapratama; Wessy Trisna; Fajar Khaify Rizky
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.v9i3.6575

Abstract

Abstract: The unlawful occupation and conversion of conservation forest areas constitute acts that not only cause state financial losses but also result in environmental degradation and the loss of conservation functions. This study aims to analyze the legal regulation of corruption crimes related to the occupation and conversion of conservation forest areas and to examine judicial considerations in Medan District Court Decision Number 138/Pid.Sus-TPK/2024/PN Mdn. This research employs a normative legal research method using statutory, conceptual, and case approaches. Data were collected through library research on primary, secondary, and tertiary legal materials and analyzed qualitatively. The results indicate that the legal framework governing corruption crimes in the forestry sector is relatively comprehensive; however, challenges remain regarding unclear legal norms and regulatory disharmony. The judges’ considerations in the case were based on the legal status of the conservation forest area, the existence of unlawful acts, state losses, and the environmental damage caused by the defendant’s actions. The court concluded that the defendant had fulfilled the elements of corruption, and therefore the decision was not solely based on juridical considerations but also on environmental protection and broader public interests. This study highlights the importance of strict law enforcement against corruption in the forestry sector to ensure legal certainty, environmental protection, and sustainable natural resource management. Keywords: Corruption Crime; Conservation Forest; Judicial Consideration; State Losses; Environmental Protection   Abstrak: Penguasaan dan pengalihfungsian kawasan hutan konservasi secara melawan hukum merupakan perbuatan yang tidak hanya menimbulkan kerugian keuangan negara, tetapi juga berdampak pada kerusakan lingkungan hidup dan hilangnya fungsi konservasi. Penelitian ini bertujuan untuk menganalisis pengaturan hukum tindak pidana korupsi dalam penguasaan dan pengalihfungsian kawasan hutan konservasi serta menganalisis pertimbangan hakim dalam Putusan Pengadilan Negeri Medan Nomor 138/Pid.Sus-TPK/2024/PN Mdn. Metode penelitian yang digunakan adalah penelitian hukum normatif dengan pendekatan perundang-undangan, pendekatan konseptual, dan pendekatan kasus. Data diperoleh melalui studi kepustakaan terhadap bahan hukum primer, sekunder, dan tersier yang dianalisis secara kualitatif. Hasil penelitian menunjukkan bahwa pengaturan hukum mengenai tindak pidana korupsi di sektor kehutanan telah memiliki dasar hukum yang kuat, namun masih menghadapi kendala berupa ketidakjelasan norma dan disharmonisasi peraturan. Pertimbangan hakim dalam putusan a quo didasarkan pada pembuktian status kawasan hutan konservasi, adanya perbuatan melawan hukum, kerugian negara, serta dampak kerusakan lingkungan hidup yang ditimbulkan. Hakim menilai bahwa tindakan terdakwa terbukti memenuhi unsur tindak pidana korupsi sehingga putusan tidak hanya berorientasi pada aspek yuridis, tetapi juga memperhatikan perlindungan lingkungan hidup dan kepentingan masyarakat. Penelitian ini menegaskan pentingnya penegakan hukum yang tegas terhadap tindak pidana korupsi di sektor kehutanan guna menjamin kepastian hukum, perlindungan lingkungan, dan keberlanjutan sumber daya alam. Kata kunci: Tindak Pidana Korupsi; Hutan Konservasi; Pertimbangan Hakim; Kerugian Negara; Lingkungan Hidup
ANALISIS HUKUM NASIONAL DAN HUKUM INTERNASIONAL DALAM PENANGGULANGAN ILLEGAL, UNREPORTED, AND UNREGULATED FISHING DI PERAIRAN INDONESIA UNTUK MEWUJUDKAN KEBERLANJUTAN LINGKUNGAN LAUT (STUDI DI ZONA EKONOMI EKSKLUSIF LAUT NATUNA UTARA) Yunus Ralie Siregar; Suhaidi; Vita Cita Emia Tarigan
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.v9i3.6576

Abstract

Abstract: Illegal, Unreported, and Unregulated Fishing (IUU Fishing) is one of the fisheries-related crimes that threatens the sustainability of marine resources, causes significant economic losses to the state, and undermines Indonesia's maritime sovereignty. The North Natuna Sea Exclusive Economic Zone (EEZ) is particularly vulnerable to such practices due to its abundant fishery resources and strategic geographical location. This study aims to analyze the national legal framework governing the prevention and eradication of IUU Fishing in the North Natuna Sea EEZ, identify the challenges faced by Indonesia in combating such activities, and examine the role of national and international law in promoting marine environmental sustainability. This research employs a normative juridical method with a descriptive-analytical approach. The data used consist of secondary data obtained through library research on primary, secondary, and tertiary legal materials related to international maritime law and national fisheries law. The data were analyzed qualitatively through the examination of legislation and relevant legal literature. The results indicate that Indonesia has established a relatively comprehensive legal framework for combating IUU Fishing through various laws and regulations that incorporate principles of international law. The synergy between national legal instruments and the provisions of UNCLOS 1982 plays a crucial role in strengthening law enforcement, protecting fishery resources, safeguarding national sovereignty, and supporting the sustainability of the marine environment. Keywords: IUU Fishing, Exclusive Economic Zone, Marine Environmental Sustainability   Abstrak: Illegal, Unreported, and Unregulated Fishing (IUU Fishing) merupakan salah satu bentuk kejahatan perikanan yang mengancam keberlanjutan sumber daya laut, menimbulkan kerugian ekonomi negara, serta mengganggu kedaulatan wilayah perairan Indonesia. Zona Ekonomi Eksklusif (ZEE) Laut Natuna Utara menjadi kawasan yang rentan terhadap praktik tersebut karena memiliki potensi sumber daya perikanan yang besar dan posisi strategis. Penelitian ini bertujuan untuk menganalisis pengaturan hukum nasional terkait penanggulangan IUU Fishing di ZEE Laut Natuna Utara, mengidentifikasi kendala yang dihadapi Indonesia, serta mengkaji peran hukum nasional dan internasional dalam mewujudkan keberlanjutan lingkungan laut. Penelitian ini menggunakan metode yuridis normatif dengan pendekatan deskriptif analitis. Data yang digunakan berupa data sekunder yang diperoleh melalui studi kepustakaan terhadap bahan hukum primer, sekunder, dan tersier yang berkaitan dengan hukum laut internasional dan hukum perikanan nasional. Analisis dilakukan secara kualitatif melalui penelaahan peraturan perundang-undangan dan literatur yang relevan. Hasil penelitian menunjukkan bahwa Indonesia telah memiliki landasan hukum yang cukup komprehensif dalam penanggulangan IUU Fishing melalui berbagai peraturan perundang-undangan yang mengadopsi prinsip-prinsip hukum internasional. Sinergi antara hukum nasional dan ketentuan UNCLOS 1982 berperan penting dalam memperkuat penegakan hukum, melindungi sumber daya perikanan, menjaga kedaulatan negara, serta mendukung keberlanjutan lingkungan laut. Kata kunci: IUU Fishing, Zona Ekonomi Eksklusif, Keberlanjutan Lingkungan Laut
IMPLEMENTASI ALGORITMA K-MEANS DALAM PENGELOMPOKAN DOSIS PEMUPUKAN KELAPA SAWIT BERDASARKAN KONDISI TANAMAN Fajar Hardiansyah; Helmi Fauzi 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/jssr.v9i3.6578

Abstract

Oil palm is one of the plantation commodities that plays an important role in improving Indonesia's economy. PT Socfindo Kebun Aek Loba has a large amount of oil palm plant condition data; however, the data has not been optimally utilized to determine fertilizer dosage requirements. This study aims to classify oil palm fertilizer dosage requirements based on plant conditions using the K-Means algorithm and to design an application that supports the clustering process. The variables used in this study include plant age, tree height, number of fruit bunches, and number of fronds. The dataset consisted of 200 oil palm plant records. The clustering process was carried out by forming three clusters, namely low, medium, and high fertilizer dosage groups, using the K-Means method with Euclidean Distance calculations. The results showed that out of 200 plant data records processed, 92 data (46%) were classified into the low fertilizer dosage cluster, 54 data (27%) into the medium fertilizer dosage cluster, and 54 data (27%) into the high fertilizer dosage cluster. In addition, this study successfully developed an application using PHP and MySQL that is capable of managing data, performing clustering automatically, and presenting clustering results in the form of tables and charts. The developed application can assist PT Socfindo Kebun Aek Loba in obtaining information regarding fertilizer dosage requirements more quickly, effectively, and systematically, thereby supporting decision-making related to oil palm fertilization.
ANALISIS VISUALISASI DATA PASIEN GIGI DAN MULUT DENGAN ALGORITMA K-MEANS BERBASIS WEB Putri Salma; Eva Rianti; Liga Mayola; Retno Devita; Ondra Eka 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.v9i3.6579

Abstract

RSGM Baiturrahmah serves as a medical institution that generates a high volume of daily patient records. However, this wealth of data has not been optimally utilized by management as a primary consideration for strategic decision-making. The identified core problem is the absence of comprehensive patient characteristic mapping, which often leads to an uneven distribution of medical resources. To address this critical issue, this study applies advanced data mining techniques using the K-Means Clustering algorithm to group 1,708 dental and oral disease patient records. The clustering process was conducted by determining three main clusters based on three crucial attributes patient age, the total number of diagnoses received, and the duration of medical service provided. The results of this study successfully classify all patients into three specific service categories, namely Basic Service, Intermediate Service, and Intensive Service. This research also produced a comprehensive web-based decision support system developed using the Python programming language and MySQL database. The system is specifically designed to assist the management of RSGM Baiturrahmah in accurately visualizing the characteristics of each patient group. With the successful implementation of this system, hospital management can be more effective in formulating highly personalized and targeted service strategies for every patient group.
PEMANTAUAN KUALITAS AIR DENGAN PENERAPAN IOT (INTERNET OF THINGS) Muhammad Sabir Ramadhan; Harmayani
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 2 (2026): April 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i2.6580

Abstract

Abstract: The availability of clean water is a basic need that significantly impacts the health and quality of life of the community, especially in rural areas such as Sei Kepayang District, which still relies on well water and surface air sources with quality that does not always meet health standards, such as high turbidity levels and unsuitable air pH. The need for clean water for the Indonesian people is very important. Whether it is used for drinking water, cooking, bathing and washing. However, this need for clean water is very difficult to meet in areas far from water sources, especially private wells. Most air sources obtained from wells are often cloudy and the water pH does not match the nominal limit. One example is in Sei Kepayang District. Many residents still use rain-fed wells whose water quality is not always good. Given this problem, a solution that can be applied is to monitor air quality to determine the good or bad air quality so that it can be used by the community. The implementation of IoT (internet of things) air quality monitoring and administration systems in small-scale clean water management that displays conditions visually on the monitoring feature can be controlled efficiently with wireless media via the website. Furthermore, the addition of a sensor to detect and filter air pH levels can help communities struggling to access clean air and determine whether it is fit for consumption. The monitoring website also displays monthly PDAM usage costs, obtained from flow meter sensor data. This development falls under small-scale Smart City management, as it helps communities modernize their daily appliances. The implementation of the IoT (Internet of Things) air quality monitoring and administration system involved testing each sensor. Tests were conducted on each device. The test results showed that the pH sensor obtained a value of 7.00 for mineral water, 5.9 for lemon juice, and 10.4 for soapy water, and a litmus test for acid-base determination. Tests on the turbidity sensor for clean water yielded an average error of 0.12%, 0.02% for tea, and 0.08% for coffee.   Keywords: Internet of Things, air quality monitoring, Administration, pH meter, turbidity, flow meter, Arduino uno, Smart City, ESP8266. Abstrak: Ketersediaan air bersih merupakan kebutuhan mendasar yang sangat berpengaruh terhadap kesehatan dan kualitas hidup masyarakat, khususnya di wilayah pedesaan seperti Kecamatan Sei Kepayang yang masih bergantung pada sumber air sumur dan air permukaan dengan kualitas yang tidak selalu memenuhi standar kesehatan, seperti tingkat kekeruhan yang tinggi dan pH air yang tidak sesuai. Kebutuhan air bersih untuk masyarakat Indonesia sangatlah penting. Baik itu digunakan untuk air minum , memasak, mandi dan mencuci. Namun kebutuhan air bersih ini sangat sulit di penuhi di daerah yang jauh dari sumber mata air, terlebih lagi sumur-sumur milik pribadi. Kebanyakan sumber air yang diperoleh dari sumur sering sekali keruh dan pH airnya tidak sesuai dari batas nomal. Salah satunya di Kecamatan Sei Kepayang. Masih banyak penduduknya menggunakan sumur tadah hujan yang kualitas airnya tidak selalu baik. Dengan adanya masalah tersebut, solusi yang dapat diterapkan adalah monitoring kualitas air untuk menentukan baik buruknya kualitas air agar bisa digunakan oleh masyarakat. Dikembangkan implementasi IoT (internet of things) monitoring kualitas air dan sistem administrasi pada pengelola air bersih skala kecil yang menampilkan keadaan secara visual pada fitur monitoring dapat dikendalikan secara efisien dengan media wireless melalui website. Disamping itu dengan ditambahkannya sebuah sensor untuk mendeteksi kadar pH air dan penyaringannya dapat membantu penduduk yang sulit mendapatkan air bersih maupun menentukan bahwa air tersebut layak tidaknya untuk di konsumsi. Serta menampilkan biaya penggunaan PDAM dalam kurun waktu bulanan pada website monitoring yang didapatkan dari data sensor flow meter. Pengembangan ini termasuk dalam pengelolaan Smart City skala kecil, karena pengembangan alat ini membantu penduduk untuk lebih moderenisasi alat-alat dalam kehidupan sehari- hari . Dari Implementasi IoT (internet of things) monitoring kualitas air dan sistem administrasi dilakukan pengujian pada Setiap alat yang dilakukan pada setiap sensor yang di gunakan pada tiap alat. Diperoleh Hasil pengujian menunjukkan bahwa sensor pH didapatkan nilai 7.00 untuk air mineral, air lemon 5.9, air sabun 10.4, dan dengan indikasi lakmus dalam penentuan asam basa pada air. Pengujian diperoleh pada sensor turbidity terhadap air bersih didapatkan nilai rata-rata error 0.12%, teh 0.02%, dan air kopi 0.08%. Kata kunci : Internet of Things , monitoring kualitas air, Administrasi,pH meter, turbidity,flow meter , Arduino                       uno,Smart City,ESP8266.  
KLASIFIKASI SENTIMEN PUBLIK TERHADAP PROGRAM SDG 1 PENGENTASAN KEMISKINAN DI INDONESIA MENGGUNAKAN SVM DAN INDOBERT Nia Mardiah; M. Imam Santoso; Putri Athirah Thaibur; Ayu Andini Br Sitepu
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.v9i3.6582

Abstract

Abstract: The first goal of the Sustainable Development Goals (SDGs), namely poverty eradication, is a major priority of Indonesia’s national development agenda. Public responses to poverty alleviation initiatives provide valuable insights for assessing the effectiveness of government policies. This study examines public sentiment regarding the implementation of SDG 1 using posts collected from the X platform and compares the classification performance of Support Vector Machine (SVM) and IndoBERT models. A dataset consisting of 1,002 Indonesian-language posts was gathered through web scraping and Application Programming Interface (API) techniques. The research process included data preprocessing, sentiment labeling through a lexicon-based approach, TF-IDF feature extraction for the SVM model, and fine-tuning for the IndoBERT model. Model performance was evaluated using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The findings indicate that negative sentiment is more dominant than positive sentiment toward poverty alleviation programs. The SVM model achieved an accuracy of 80.60%, while IndoBERT reached 80.10%. These results suggest that SVM performed slightly better on the dataset used in this study. Overall, the findings demonstrate that artificial intelligence-based sentiment analysis can support monitoring public perceptions and evaluating poverty reduction policies in Indonesia more effectively and comprehensively for evidence-based decision making processes nationwide. Keywords: sentiment analysis; SDG 1; poverty; SVM; IndoBERT.   Abstrak: Tujuan pertama Sustainable Development Goals (SDGs), yaitu menghapus kemiskinan, menjadi salah satu agenda strategis pembangunan nasional Indonesia. Respons masyarakat terhadap berbagai program pengentasan kemiskinan dapat digunakan sebagai bahan evaluasi terhadap efektivitas kebijakan yang diterapkan pemerintah. Penelitian ini menganalisis sentimen publik mengenai implementasi SDG 1 dengan memanfaatkan unggahan pada platform X serta membandingkan kinerja model Support Vector Machine (SVM) dan IndoBERT dalam proses klasifikasi. Sebanyak 1.002 unggahan berbahasa Indonesia dikumpulkan melalui teknik scraping dan pemanfaatan API. Tahapan penelitian meliputi praproses data, pemberian label sentimen menggunakan pendekatan leksikon, pembentukan fitur TF-IDF pada SVM, serta fine-tuning model IndoBERT. Kinerja model dievaluasi menggunakan confusion matrix dengan indikator accuracy, precision, recall, dan F1-score. Hasil penelitian memperlihatkan bahwa opini negatif lebih dominan dibandingkan opini positif terhadap program pengentasan kemiskinan. Model SVM memperoleh tingkat akurasi sebesar 80,60%, sedangkan IndoBERT mencapai 80,10%. Temuan tersebut menunjukkan bahwa SVM memiliki performa yang sedikit lebih unggul pada dataset yang digunakan. Penelitian ini mengindikasikan bahwa analisis sentimen berbasis kecerdasan buatan berpotensi menjadi alat pendukung dalam memonitor persepsi masyarakat serta mengevaluasi kebijakan pengurangan kemiskinan di Indonesia. Kata kunci: analisis sentimen; SDG 1; kemiskinan; SVM; IndoBERT.
EVALUASI MULTIDIMENSI KEBERLANJUTAN PENGELOLAAN BENIH BENING LOBSTER (PUERULUS) DI PERAIRAN KABUPATEN TULUNGAGUNG BERBASIS RAPID APPRAISAL FOR FISHERIES (RAPFISH) Susadiana; Lis M Yapanto; Hatim Albasri
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.v9i3.6586

Abstract

Abstract: The waters of Tulungagung Regency possess potential for clear lobster seed (BBL), driving high levels of fishing activity for this commodity. BBL management—including harvesting activities—is governed by government regulations that underwent frequent changes between 2021 and 2024. This study aimed to examine BBL management issues in Tulungagung by characterizing BBL utilization, assessing the sustainability status of BBL management, and formulating management strategies. Data were collected through interviews, observation, and documentation. Analysis employed MDS RAPFISH to determine sustainability status and AHP to formulate priority management strategies. The results indicate that BBL fishing activities in Tulungagung are environmentally friendly, utilizing *pocong* nets that comply with the standards set in the Regulation of the Minister of Marine Affairs and Fisheries Number 7 of 2024. RAPFISH analysis classified the sustainability status as "sustainable," reflecting controlled utilization levels alongside relatively stable fishing volumes and activity among local fishers. Meanwhile, AHP analysis identified the implementation of a closed season—based on peak lobster spawning periods—as the primary management strategy for BBL in Tulungagung Regency. This study recommends this priority strategy as the key measure to improve and maintain the sustainability of BBL management in the region. Keywords: Sustainability, lobster spawning season, MDS RAPFISH, AHP   Abstrak: Perairan Kabupaten Tulungagung memiliki potensi benih bening lobster (BBL) yang mendorong tingginya aktivitas penangkapan komoditas tersebut. Pengelolaan BBL termasuk di dalamnya aktivitas penangkapan telah diatur dalam peraturan pemerintah yang sering mengalami perubahan pada kurun waktu 2021 hingga 2024. Penelitian ini dilakukan dengan beberapa tujuan guna mendalami persoalan pengelolaan BBL khususnya di Tulungagung diantaranya menentukan keragaan karakteristik pemanfaatan BBL, menetapkan status keberlanjutan pengelolaan BBL, serta menentukan strategi pengelolaan BBL. Teknik pengumpulan data berupa wawancara, observasi dan dokumentasi. Analisis data yang digunakan MDS RAPFISH untuk penetapan status keberlanjutan dan AHP perumusan strategi prioritas pengelolaan BBL. Hasil penelitian menunjukkan bahwa kegiatan penangkapan BBL yang di Tulungagung tergolong ramah lingkungan menggunakan alat berupa jaring pocong yang masih sesuai dengan kaidah yang ditetapkan dalam Permen KP Nomor 7 Tahun 2024. Hasil analisis RAPFISH menunjukkan status keberlanjutan pada kategori berkelanjutan yang menunjukkan tingkat pemanfaatan yang masih terkontrol dengan relatif stabilnya jumlah dan aktivitas penangkapan oleh nelayan setempat. Sedangkan pada hasil analisis prioritas rekomendasi kebijakan (AHP) diperoleh strategi penerapan musim tertutup berdasarkan puncak pemijahan lobster sebagai pilihan strategi pengelolaan BBL paling utama di Kabupaten Tulungagung. Studi ini merekomendasikan strategi prioritas tersebut sebagai upaya utama untuk memperbaiki dan mempertahankan status keberlanjutan pengelolaan BBL di Tulungagung. Kata kunci: Keberlanjutan, BBL, MDS RAPFISH, AHP
RANCANG BANGUN SISTEM INFORMASI INVENTARIS BARANG BERBASIS WEB PADA DIVISI PERENCANAAN STRATEGIS DAN PELAYANAN TERMINAL PETIKEMAS PT. PELABUHAN INDONESIA Mohamad Hilal Monoarfa; Rouli Doharma
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.v9i3.6588

Abstract

Abstract: This research aims to design and build a web-based Inventory Information System for the Strategic Planning and Container Terminal Services Division of PT. Pelabuhan Indonesia (Persero). This system was developed to address the problem of manual inventory recording using Microsoft Excel, which is prone to recording errors, data loss, and difficulties in preparing reports and monitoring goods in real time. The system development method used is the System Development Life Cycle (SDLC) with a Prototype model. The result of this research is a web application that allows for structured recording of incoming and outgoing goods, as well as requests for borrowing goods. Key features include master data management (goods, suppliers, shelves, officers, admins), automated stock updates, an information dashboard, and report generation. System testing using the Black Box Testing method showed that all system functions were running well and in accordance with user needs. The implementation of this system is expected to improve operational efficiency, data accuracy, and support faster and more accurate decision-making processes within the company. Keywords: Information System, Inventory, Website, SDLC Prototype, Black Box Testing, PT. Pelabuhan Indonesia.   Abstrak: Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Inventaris Barang berbasis web pada Divisi Perencanaan Strategis dan Pelayanan Terminal Petikemas PT. Pelabuhan Indonesia. Sistem ini dikembangkan untuk mengatasi permasalahan pencatatan inventaris yang masih dilakukan secara manual menggunakan Microsoft Excel, yang rentan terhadap kesalahan pencatatan, kehilangan data, serta kesulitan dalam penyusunan laporan dan pemantauan barang secara real-time. Metode pengembangan sistem yang digunakan adalah System Development Life Cycle (SDLC) dengan model Prototype. Hasil dari penelitian ini berupa aplikasi web yang memungkinkan pencatatan barang masuk, keluar, dan pengajuan peminjaman barang secara terstruktur. Fitur-fitur utama mencakup manajemen data master (barang, supplier, rak, petugas, admin), otomatisasi pembaruan stok, dashboard informasi, serta pembuatan laporan. Pengujian sistem menggunakan metode Black Box Testing menunjukkan bahwa seluruh fungsi sistem telah berjalan dengan baik dan sesuai dengan kebutuhan pengguna. Implementasi sistem ini diharapkan dapat meningkatkan efisiensi operasional, akurasi data, serta mendukung proses pengambilan keputusan yang lebih cepat dan tepat di lingkungan perusahaan. Kata Kunci: Sistem Informasi, Inventaris Barang, Website, SDLC Prototype, Black Box Testing, PT. Pelabuhan Indonesia.
KOMPARASI ALGORITMA K-NEAREST NEIGHBOR DAN NAIVE BAYES UNTUK KLASIFIKASI KELAYAKAN EKSPOR KOPI ARABIKA DENGAN CORRELATION-BASED FEATURE SELECTION Diva Agustin Purba; Nazma Aulia; Pujawati; Dicky Apdillah; Bambang Irwansyah; Harmayani
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.v9i3.6589

Abstract

Abstract: Arabica coffee is a high-value export commodity for the Indonesian economy. To maintain global competitiveness, coffee beans must meet export feasibility quality standards based on the cupping score from the Coffee Quality Institute (CQI). This study aims to compare the performance of the K-Nearest Neighbor (KNN) and Gaussian Naive Bayes algorithms in classifying the export feasibility of Arabica coffee beans. In sensory quality testing, high-dimensional attributes (10 parameters) can cause accuracy instability and increase computational load. Therefore, Correlation-based Feature Selection (CFS) was applied to reduce redundant features. The CFS process filtered the initial 10 features into 4 selected features (Flavor, Acidity, Cupper Points, and Aroma). The Dataset was obtained from the Kaggle Coffee Quality Database and had undergone Excel format adjustments before being loaded into the system. Modeling was conducted using 1,303 data records with a 30% split for testing data. The evaluation results showed that the Naive Bayes algorithm provided the best performance, achieving an accuracy rate of 97.95%. The use of CFS proved successful in reducing feature dimensions by 60% without significantly decreasing classification accuracy. Keywords: Arabica Coffee; Export Classification; K-Nearest Neighbor; Naive Bayes; Correlation-based Feature Selection.   Abstrak: Kopi Arabika merupakan komoditas ekspor bernilai tinggi bagi perekonomian Indonesia. Untuk menjaga daya saing di tingkat global, biji kopi harus memenuhi standar kualitas kelayakan ekspor berdasarkan cupping score dari Coffee Quality Institute (CQI). Penelitian ini bertujuan membandingkan kinerja algoritma K-Nearest Neighbor (KNN) dan Gaussian Naive Bayes dalam klasifikasi kelayakan ekspor biji kopi Arabika. Dalam pengujian sensoris mutu, dimensionalitas atribut yang tinggi (10 parameter) dapat menyebabkan ketidakstabilan akurasi dan meningkatkan beban komputasi. Oleh karena itu, Correlation-based Feature Selection (CFS) diterapkan untuk mereduksi fitur redundan. Proses CFS menyaring 10 fitur awal menjadi 4 fitur terpilih (Flavor, Acidity, Cupper Points, Aroma). Dataset diambil dari Kaggle Coffee Quality Database dan telah melalui tahapan penyesuaian format Excel sebelum dimuat ke sistem. Pemodelan dilakukan menggunakan 1303 rekam data dengan pembagian data uji sebesar 30%. Hasil evaluasi menunjukkan bahwa algoritma Naive Bayes memberikan performa terbaik dengan tingkat akurasi mencapai 97,95%. Penggunaan CFS terbukti berhasil memangkas dimensi fitur sebesar 60% tanpa menurunkan akurasi klasifikasi secara signifikan. Kata Kunci: Kopi Arabika; Klasifikasi Ekspor; K-Nearest Neighbor; Naive Bayes; Correlation-based Feature Selection.
IMPLEMENTASI TEXT MINING DALAM ANALISA SENTIMEN MASYARAKAT TERHADAP KETTANGGAPAN PEMERINTAH DALAM PENANGGULANGAN BENCANA BANJIR Apri Affandi; Muhammad Sabir Ramadhan
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.v9i3.6590

Abstract

Abstract : The development of information technology and social media has made it easier for people to express their opinions on various issues, including the government’s responsiveness in handling flood disasters. The large number of comments generated on social media makes manual opinion analysis ineffective because it requires a long time and involves a large volume of data. Therefore, an automated method is needed to process and classify public sentiment. This study aims to implement text mining to analyze public sentiment toward the government’s responsiveness in flood disaster management using the K-Nearest Neighbour (KNN) algorithm. The research data were collected from social media platforms such as Instagram, TikTok, and X, consisting of public comments related to flood disasters in Aceh and North Sumatra. The research stages include data collection, text preprocessing, feature extraction, data splitting into training and testing sets, sentiment classification using the KNN method, and evaluation of classification results. The system was developed as a web-based application using PHP programming language and MySQL database. The results of this study are expected to provide an overview of public opinion tendencies in the form of positive, negative, and neutral sentiments and serve as evaluation material for the government to improve its response in flood disaster management. Keywords: Text Mining, Sentiment Analysis, K-Nearest Neighbour (KNN), Social Media, Flood Disaster, Government Responsiveness.   Abstrak : Perkembangan teknologi informasi dan media sosial menyebabkan masyarakat semakin mudah menyampaikan pendapat terhadap berbagai isu, termasuk ketanggapan pemerintah dalam penanggulangan bencana banjir. Banyaknya komentar yang muncul di media sosial menjadikan analisis opini secara manual tidak efektif karena membutuhkan waktu yang lama dan jumlah data yang besar. Oleh karena itu, diperlukan metode otomatis untuk mengolah dan mengklasifikasikan sentimen masyarakat. Penelitian ini bertujuan untuk mengimplementasikan text mining dalam menganalisis sentimen masyarakat terhadap ketanggapan pemerintah dalam penanggulangan bencana banjir menggunakan algoritma K-Nearest Neighbour (KNN). Data penelitian diperoleh dari platform media sosial Instagram, TikTok, dan X yang berisi komentar masyarakat terkait bencana banjir di wilayah Aceh dan Sumatera Utara. Tahapan penelitian meliputi pengumpulan data, preprocessing teks, ekstraksi fitur, pembagian data training dan testing, proses klasifikasi menggunakan metode KNN, serta evaluasi hasil klasifikasi. Sistem dibangun berbasis web menggunakan bahasa pemrograman PHP dan database MySQL. Hasil penelitian diharapkan dapat memberikan gambaran kecenderungan opini masyarakat dalam bentuk sentimen positif, negatif, dan netral serta membantu sebagai bahan evaluasi bagi pemerintah dalam meningkatkan kualitas respon terhadap bencana banjir. Kata kunci: : Text Mining, Analisis Sentimen, K-Nearest Neighbour (KNN), Media Sosial, Bencana Banjir, Ketanggapan Pemerintah.

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