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All Journal Elkom: Jurnal Elektronika dan Komputer CESS (Journal of Computer Engineering, System and Science) NUR EL-ISLAM : Jurnal Pendidikan dan Sosial Keagamaan JSiI (Jurnal Sistem Informasi) JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurnal Riset Informatika Jurnal Informatika dan Rekayasa Elektronik Jurnal Sistem Komputer dan Informatika (JSON) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer International Journal Software Engineering and Computer Science (IJSECS) el-Madib: Jurnal Pendidikan Dasar Islam Jurnal Komtekinfo Indonesian Health Issue Data Sciences Indonesia (DSI) PIJAR: Jurnal Pendidikan dan Pengajaran VISA: Journal of Vision and Ideas Da'watuna: Journal of Communication and Islamic Broadcasting The Indonesian Journal of Computer Science Jurnal Ilmu Sosial dan Humaniora SAMBARA: Jurnal Pengabdian Kepada Masyarakat INOVTEK Polbeng - Seri Informatika Sriwijaya Foodtech Journal MUTAADDIB: Islamic Education Journal
Sriani
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Penerapan Metode Vikor dalam Pemilihan Bibit Unggul Pohon Karet Rizki Ananda Putra Fajar; Rakhmat Kurniawan; Sriani
Da'watuna: Journal of Communication and Islamic Broadcasting Vol. 4 No. 4 (2024): Da'watuna: Journal of Communication and Islamic Broadcasting (In Press)
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/dawatuna.v4i4.1842

Abstract

Rubber plant is one of the plantation commodities that has an important role in economic activities in Indonesia. The need for rubber seeds continues to increase in line with the increase in the area of ​​smallholder rubber plantations and the government. Quality seeds are a community need in developing rubber plantations in Indonesia from year to year. The first step to get good rubber seeds is that rubber farmers need to use quality rubber seed planting material and are able to produce high latex. Given the very importance of seeds in determining quality rubber repair. With a Decision Support System with the vikor method to build a system that has the ability to be able to assist farmers in choosing superior rubber tree seeds with a system that is able to provide problem solving skills and communication skills for problems with semi-structured and unstructured conditions. This study uses the vikor method because this method is suitable for use in most real-time problems such as making decisions to find quality rubber tree seeds so that this research can be useful for rubber tree farmers in improving the quality of superior seeds.
Subject Selection Decision Support System Using the Weighted Aggregated Sum Product Assessment Method Setiawan, Mhd. Liandra; Sriani
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/s2d8vn67

Abstract

High school subject selection is crucial for aligning with students' interests and goals, but manual processes are often time-consuming and prone to errors. This study developed a decision support system using the WASPAS method, which combines WSM and WPM to produce a more stable and consistent evaluation of alternatives. A total of 35 10th-grade students of SMAN 16 Medan were recruited through total sampling using a Likert-scale questionnaire as the basis for the calculation. The system evaluation was verified on the entire data set, not just three samples like the previous version, to ensure the algorithm's suitability. The results show that the system generates interest recommendations based on the highest Qi score and is consistent with manual calculations, although its accuracy cannot yet be fully concluded. The distribution of student preferences is also presented, along with explanations of potential instrument bias and response bias as limitations of the study. Overall, this WASPAS-based system is considered capable of helping provide more objective and efficient subject selection recommendations.
Analisis Sentimen Publik Terhadap Kenaikan Pajak Pertambahan Nilai (PPN) Sebesar 12% Menggunakan Naïve Bayes Classifier Lu'luil Jannah; Sriani
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9151

Abstract

Perkembangan teknologi digital membuka peluang yang semakin luas bagi masyarakat untuk menyampaikan pendapat secara bebas melalui berbagai platform media sosial. Salah satu isu yang banyak menarik perhatian publik adalah kebijakan pemerintah terkait kenaikan Pajak Pertambahan Nilai (PPN) menjadi 12%. Ragam opini yang muncul dari masyarakat dapat dimanfaatkan sebagai bahan pertimbangan dalam proses evaluasi maupun pengambilan keputusan. Penelitian ini bertujuan untuk mengidentifikasi sentimen publik terhadap kebijakan kenaikan PPN dengan memanfaatkan algoritma Naïve Bayes Classifier. Tahapan penelitian meliputi pengumpulan data dari media sosial, pra-pemrosesan teks seperti case folding, tokenisasi, stopword removal, dan stemming serta pengubahan data teks ke bentuk numerik menggunakan metode TF-IDF. Dari total 600 data yang berhasil dihimpun dari media social X, dengan 80% digunakan sebagai data pelatihan dan 20% data sebagai data pengujian. Hasil penelitian menunjukkan adanya 51 tweet yang bernada positif, 352 bernada netral, dan 197 bernada negatif. Model Naïve Bayes menghasilkan performa klasifikasi yang cukup baik dengan akurasi 81,36%, presisi rata-rata 88%, recall 79%, dan F1-Score 82%. Temuan ini membuktikan bahwa Naïve Bayes merupakan algoritma yang efektif dan layak diandalkan untuk mengklasifikasikan opini publik secara cepat dan sistematis. Dengan demikian, model ini berpotensi menjadi alat pendukung dalam menganalisis persepsi masyarakat terhadap kebijakan pemerintah secara berbasis data.
Penerapan Logika Fuzzy Tsukamoto Sebagai Sistem Pendukung Keputusan Penentuan Mata Kuliah Pilihan Mahasiswa Ilmu Komputer XYZ Muhammad Reza Alhafiz; Sriani
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9453

Abstract

The selection of elective courses poses a challenge for Computer Science students at XYZ University because it influences competency development, while objective decision-making guidance remains limited. This study aims to develop a web-based decision support system to recommend specialization elective courses using the Fuzzy Tsukamoto method. Data were collected through questionnaires from students in semesters five to seven and processed into four input variables: Robotics, Mathematics, Programming, and Analysis. Each variable was modeled into three fuzzy sets (Weak, Moderate, Strong) using trapezoidal membership functions and processed through IF–THEN rule-based inference with a total of 162 rules. Output values were obtained through weighted average defuzzification to generate course recommendations. System testing was conducted by comparing system outputs with manual calculations and evaluated using the Mean Absolute Percentage Error (MAPE). The results showed a MAPE value of approximately ±0.1096%, indicating that the implementation of the Tsukamoto method in the system is consistent with manual calculations. This study contributes to providing a structured and objective decision support system to assist students in determining elective courses based on their competencies.
Segmentation of Toddlers Based on Nutritional Status Using Agglomerative Hierarchical Clustering with Average Linkage Malid, Abdul; Sriani
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 3 (2026): Maret 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i3.9598

Abstract

Nutritional status among children under five remains an important public health concern, particularly in developing regions where early detection of growth problems is essential for effective intervention. Conventional nutritional assessments often rely on categorical classifications that may not fully capture variations in anthropometric characteristics among toddlers. This study aims to segment children under five based on nutritional status using the Agglomerative Hierarchical Clustering (AHC) algorithm with the Average Linkage method in the NA-IX-X District, North Labuhanbatu Regency. The study used secondary anthropometric data from 1,452 children obtained from the Aek Kota Batu Public Health Center. Quantitative variables, including body weight, height, and age, were standardized using z-score transformation prior to clustering analysis. The results show that a three-cluster configuration provides the optimal segmentation, with a Silhouette Coefficient value of 0.5154, indicating a moderate clustering structure. Cluster 1 (n = 180) shows relatively lower anthropometric measurements with an average body weight of 7.3 kg and height of 68.3 cm. Cluster 2 (n = 511) represents intermediate measurements with an average body weight of 11.5 kg and height of 87.8 cm, while Cluster 3 (n = 761) reflects higher measurements with an average body weight of 15.0 kg and height of 101.7 cm. Dendrogram analysis indicates that a cutting point at height = 1.5 produces the most interpretable cluster separation. These findings demonstrate that hierarchical clustering can support more targeted nutritional intervention strategies at the community health center level. 
Sistem Prediksi Kelulusan Santri Tahfidz Qur’an Menggunakan Algoritma C4.5 Sriani; Juraidah, Juraidah
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3325

Abstract

Yayasan Tahfidz Qur’an Umul Mukminin Aisyah merupakan lembaga pendidikan penghafal Al-Qur’an yang setiap tahun kuota santri semakin bertambah. Namun, tidaklsemua santri dapat lulus tepat waktu sesuai masaabelajar yang ditempuhhsehingga mengakibatkannpenumpukkan santri yang tidakllulus sesuai masapperiodelkelulusanya. Penentuan kelulusan santri berdasarkan beberapa kriteria yang harus dilalui oleh santri selama menempuh pembelajaran dilYayasan Tahfidz Qur’an. Oleh karena itu, perlu dilakukan penelitian menggunakannteknik klasifikasi yanggdapat mengolahhdata dalam jumlahhbesar untuk menemukanppola yang terjadilpada dataasantri. Pengolahanndata tersebut digunakan untuk memprediksikkelas yang belumddiketahui yaitu prediksikkelulusan santri. Teknikkklasifikasi yanggdigunakan adalah decisionttreeedengan penerapanaalgoritmaaC4.5. Inputannyang digunakannberupa data santri yanggmeliputi dari prestasi, kedisiplinan, hapalan dan lafadz. Data santri yang digunakan adalah data sampelttraining yang sudah lulus pada tahun 2019 dengan jumlah data 170. Dimana berdasarkan hasil pengolahan, didapati 114 data santri lulus dan 56 tidak lulus.
Prediction of Burnout Syndrome Risk in University Students Using the C5.0 Algorithm Rahmadani, Noni Fauzia; Sriani
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 2 (2026): April 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i2.9550

Abstract

Burnout among university students is a serious issue that can reduce learning motivation, academic performance, and mental health. Approximately 25–30% of students experience burnout symptoms, which negatively affect concentration and academic productivity. Early detection is still limited due to the lack of accurate data analysis. This study aims to predict the risk level of student burnout using the C5.0 algorithm as a classification method capable of handling both categorical and numerical data. The research data were obtained from 306 students at Universitas Islam Negeri Sumatera Utara through an online questionnaire based on the Maslach Burnout Inventory–Student Survey (MBI-SS). The data were processed through cleaning, encoding, and splitting into training and testing sets using Python. The results show that the model achieves excellent classification performance, with an accuracy of 99.25% on the training set (precision 99.72%, recall 99.45%) and 97% on the testing set (precision 100%, recall 96%). The model also identifies the most influential attributes contributing to burnout, such as stress level and emotional exhaustion. The main contribution of this study is the development of an accurate and interpretable machine learning-based model for predicting student burnout risk. These findings provide practical implications for educational institutions in supporting early detection and designing data-driven preventive interventions, such as counseling services and stress management programs.
Digital Media in Islamic Religious Education: A Systematic Literature Review of Its Influence on Student Learning Motivation Saidah; Sriani; Baili; Hidayatullah, M. Predi; Medianto, Gufron; Muttaqin
Jurnal Ilmu Sosial dan Humaniora Vol. 2 No. 4 (2024): Oktober
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/isihumor.v2i4.1604

Abstract

The proliferation of digital technologies has reshaped contemporary classrooms, yet Islamic Religious Education (IRE) in Indonesian schools largely retains lecture-based instruction that frequently fails to sustain learner engagement. Prior studies have examined educational technology broadly, but syntheses focused on how digital media shape motivation within IRE remain limited, particularly regarding the typologies of media most effective for spiritual and moral content. This study aimed to map the influence of digital media on IRE learning motivation, identify the most effective media typologies, and document the principal barriers to adoption. A systematic literature review (SLR) was conducted following the PRISMA 2020 protocol. Peer-reviewed publications issued between January 2019 and December 2024 were retrieved from Scopus, ERIC, DOAJ, and SINTA-indexed databases using Boolean strings combining "digital media," "interactive media," "augmented reality," "virtual reality," "learning motivation," and "Islamic education." Of 318 records identified, 46 articles met the inclusion criteria, with inter-rater agreement of κ = 0.84 (substantial agreement). Thematic content analysis revealed that audiovisual media particularly animated videos were associated with motivational gains in 39.1% of the corpus; interactive applications and gamified platforms increased classroom engagement; and immersive AR/VR, although appearing in only 13.0% of studies, produced the largest reported gains for spiritual and historical narratives. Recurring obstacles included infrastructural limitations (60.9%) and insufficient teacher digital-pedagogical competence (54.3%). Digital media exert a positive influence on IRE motivation when integrated through pedagogically grounded designs that embed Islamic ethical values, addressing cognitive, affective, and spiritual dimensions concurrently.
Implementing the Wafa Five-Stage (5P) Right-Brain Method in Qur’an Memorization at an Indonesian Primary School: A Qualitative Case Study of Pedagogical Adaptation Azimin, Choirul; Sriani; Narti, Wiwin; Andryadi
PIJAR: Jurnal Pendidikan dan Pengajaran Vol. 3 No. 2 (2025): April
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/pijar.v3i2.1606

Abstract

Conventional Qur’an memorization (tahfidz) in Indonesian elementary schools often relies on uniform repetition that disregards the concrete-operational cognition of children aged 7–12, yielding fatigue, motivational decline, and uneven progress. The Wafa method, structured around a five-stage protocol (Opening, Experiencing, Teaching, Assessing, Closing abbreviated 5P) and grounded in right-brain multisensory learning, has been promoted as a pedagogical response, yet most existing studies report aggregate effectiveness without examining how classroom teachers operationalize and adapt it when contextual constraints emerge. This study therefore investigates the planning, enactment, encountered constraints, and adaptive strategies of the Wafa 5P method at SD Lab School Integrated SKB, Bungo Regency, Indonesia. A qualitative case-study design was employed; data were generated over a ten-week period (March–May 2024) through participant observation of 24 lessons, semi-structured interviews with eight purposively sampled informants (principal, four tahfidz teachers, three homeroom teachers), and document analysis. Analysis followed the Miles, Huberman, and Saldaña interactive model, with credibility secured through source and method triangulation and prolonged engagement. Findings show that the 5P protocol was implemented in full sequence but encountered three recurrent constraints: difficulty internalizing the Hijaz tonal pattern, irregular attendance linked to home distance, and heterogeneous memorization pace within a 35-minute slot shared with Dhuha prayer. Teachers responded with three contextual adaptations: routine playback of child-oriented murottal audio, autonomy-supportive responses to tardiness coupled with catch-up tasks, and a 14:30–17:00 supplementary tahfidz class. Findings reframe Wafa as a teacher-mediated, context-responsive system, contributing evidence for differentiated Qur’an instruction in primary education.
Co-Authors Abdul Halim Hasugian Agustin Mardiana, Nur Agustina, Chaterine Aidil Halim Lubis Aidil Halim Lubis Andriyadi, Andriyadi Andryadi Anggraini, Chintya Armansyah Azimin, Choirul Baili Berutu, Nurhalimah Desmarini, Mutia Dwitia Ayu Lestari Fachry Abda El Rahman Fawi, Hafiz Frianda Gultom, Irsan Gusrianti, Rita Harahap, Lailan Sofinah Harahap, Ulil Amri Harahap, Yunus Fadillah Hidayatullah, M. Predi Ibnu Rusydi Ibsan, Muhammad Hanafi juraidah, juraidah Khairani, Fuji Khairunnisa Lu'luil Jannah Mahmudah, Nur Aini Malid, Abdul Mawaddah Mawaddah, Mawaddah Maya Nurmalasari Medianto, Gufron Mona Novita Muhammad Alwi Baihaqi Muhammad Reza Alhafiz Muttaqin Nasution, Yurika Nur Aisyiyah, Siti R Panjaitan, Nurhalimah Pasaribu, Nur Adha Pohan, Rifani Khairani Rahmadani, Noni Fauzia Rahman Sari, Arfani Rakhmat Kurniawan R Rizki Ananda Putra Fajar Saidah Setiawan, Mhd. Liandra Shania perida Br tarigan Simanulang, Ester Sinaga, Siti Nurmawan Siti Zubaidah Sofiah Sri Wahyuni Suhardi Tarigan, Eka Falentina Wiwin Narti Zoyasri Ananta