Abstract:Abstract: Toko Zuma faces challenges in optimizing customer relationship management and transaction recording due to conventional manual systems, which hinder real-time loyalty monitoring and sales analysis. This research…
h aims to design a digital Electronic Customer Relationship Management (E-CRM) system as an integrative solution for systematic and centralized management. The design method employs Unified Modeling Language (UML) for requirements analysis, user interface design, and Black-box Testing for validation. Results demonstrate a 100% success rate across all primary modules. The platform features Point Reward, automated transaction management, and live chat for direct interaction. Implementation enables personalized promotional strategies based on accurate data to increase customer retention. In conclusion, the Digital E-CRM system effectively automates business processes, serving as a strategic instrument for transparent and measurable customer relationship management.
Keywords: digital e-crm; relationship management; toko zuma; transaction activities.
Abstrak: Toko Zuma menghadapi kendala dalam optimalisasi manajemen hubungan pelanggan dan pencatatan transaksi karena masih menggunakan sistem manual konvensional. Penelitian ini bertujuan merancang sistem Electronic Customer Relationship Management (E-CRM) digital sebagai solusi integratif untuk pengelolaan basis data dan transaksi secara terpusat. Metode perancangan meliputi analisis kebutuhan menggunakan Unified Modeling Language (UML), desain antarmuka, dan validasi fungsional melalui Black-box Testing. Hasil pengujian menunjukkan tingkat keberhasilan 100% pada seluruh modul utama. Platform ini dilengkapi fitur Point Reward, manajemen transaksi otomatis, dan media interaksi live chat. Implementasi sistem ini memungkinkan strategi promosi personal berdasarkan data akurat untuk meningkatkan retensi pelanggan. Simpulannya, sistem E-CRM digital berhasil mengotomatisasi proses bisnis dan menjadi instrumen strategis dalam manajemen hubungan pelanggan yang transparan dan terukur.
Kata kunci: aktivitas transaksi; digital e-crm; pengelolaan relasi; toko zuma.
Abstract:Abstract: The election of the Student Council President is an important process in building a democratic, responsible, and integrity-based leadership culture in the school environment. In addition, through the main discussion…
ssion in this study aims to optimize the selection process for candidates for Student Council President at SMP Negeri 11 Tanjung Balai through the implementation of a Decision Support System (DSS) based on the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method. The MOORA method is used to normalize values, weight criteria, and calculate optimization values to produce the best alternative ranking. Data were obtained through observation, interviews with school officials, and literature studies. The results of the study indicate that the MOORA method is able to provide objective and transparent ranking results, where M. Asril Sitorus Pane obtained the highest score of 0.347 (Rank 1), followed by M. Rian with a score of 0.333 (Rank 2). The implementation of this system is expected to be able to provide recommendations for the best candidates regularly and accurately, so that it can support fairer and more accountable decision-making in the next Student Council President election.
Keywords: decision support system; osis chairman election; MOORA; SMP negeri 11 tanjung balai.
Abstrak: Pemilihan Ketua OSIS merupakan proses penting dalam membangun budaya kepemimpinan yang demokratis, bertanggung jawab dan berintegritas di lingkungan sekolah. Selain itu, melalui pokok pembahasan pada penelitian ini bertujuan untuk dapat mengoptimalkan proses seleksi calon Ketua OSIS di SMP Negeri 11 Tanjung Balai melalui penerapan Sistem Pendukung Keputusan berbasis metode MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis). Metode MOORA digunakan agar dapat melakukan normalisasi nilai, pembobotan kriteria serta perhitungan nilai optimasi guna menghasilkan peringkat alternatif terbaik. Data diperoleh melalui observasi, wawancara dengan pihak sekolah serta dan studi kepustakaan. Hasil penelitian menunjukkan bahwa metode MOORA mampu memberikan hasil peringkat yang objektif dan transparan, yang dimana M. Asril Sitorus Pane memperoleh nilai tertinggi sebesar 0,347 (Peringkat 1), diikuti oleh M. Rian dengan nilai 0,333 (Peringkat 2). Penerapan sistem ini diharapkan mampu memberikan rekomendasi kandidat terbaik secara sistematis dan akurat, sehingga dapat mendukung pengambilan keputusan yang lebih adil dan akuntabel dalam pemilihan Ketua OSIS selanjutnya.
Kata kunci: MOORA; pemilihan ketua osis; sistem pendukung keputusan; SMP negeri 11 tanjung balai.
Abstract:This study aims to apply the Analytic Network Process (ANP) method as a decision support tool in determining the eligibility of education grant recipients in North Sumatra Province. The background of this research arises…
from the large number of grant applicants compared to the available budget, as well as the absence of clear and objective evaluation standards. The ANP method was chosen because it allows the interdependence between assessment criteria such as institutional feasibility, performance and achievement, social and educational impact, and accountability and transparency to be analyzed comprehensively. Data were obtained through interviews, documentation, and observation at the North Sumatra Provincial Education Office. The results of the ANP model show that the criterion with the highest weight is accountability and transparency (0.44), followed by social and educational impact (0.31). Among the three alternatives, community-based education foundations (A2) obtained the highest total weight (0.30), indicating that they are the most eligible recipients of education grants. The implementation of the ANP-based decision support system produces valid and consistent ranking results (CR < 0.1), enabling faster, fairer, and more transparent decision-making. Therefore, the ANP method contributes significantly to improving governance, objectivity, and accountability in the distribution of education grants in North Sumatra Province.
Abstract:Abstract: SMP Muhammadiyah 5 Samarinda still relies on manual evaluation with limited data analysis tools in predicting student academic achievement. This study aims develop a system for predicting the learning achievement…
nt of students at SMP Muhammadiyah 5 Samarinda using the Naive Bayes classification method. The dataset used consists of 192 student exam scores covering academic scores, attendance, parents’ education and income, and living conditions as independent variables, while the dependent variable is the achievement label (achieved or not achieved). The preprocessing stage includes label normalization, feature selection, and median imputation to handle missing data. The dataset was divided into 75% training data and 25%. The model was implemented as a pipeline consisting of a median imputer and a Gaussian Naive Bayes classifier. The evaluation results showed that the model achieved an accuracy of 79.2%, with a perfect recall value (1.00) in the high-achieving class and (0.64) in the low-achieving class. This shows that the model is quite effective in identifying high-achieving students. The trained model was then integrated into a Flask-based web application, which enables online predictions through a simple form interface, facilitating contextual interpretation. This system is expected to assist in educational decision-making by helping teachers identify students’ achievement levels early on and design more targeted learning interventions.
Keywords: academic performance; educational data mining; naive bayes; prediction system; student achievement
Abstrak: SMP Muhammadiyah 5 Samarinda masih bergantung pada evaluasi manual dengan alat analisis data terbatas dalam melakukan prediksi prestasi akademik siswa. Penelitian ini bertujuan mengembangkan sistem prediksi prestasi belajar siswa SMP Muhammadiyah 5 Samarinda menggunakan metode klasifikasi Naive Bayes. Dataset yang digunakan terdiri atas 192 data nilai ujian siswa yang mencakup skor akademik, kehadiran, pendidikan dan pendapatan orang tua, serta kondisi tempat tinggal sebagai variabel independen, sedangkan variabel dependen berupa label prestasi (berprestasi atau tidak berprestasi). Tahap preprocessing meliputi normalisasi label, seleksi fitur, serta imputasi median untuk menangani data yang hilang. Dataset dibagi menjadi 75% data latih dan 25%. Model diimplementasikan dalam bentuk pipeline yang terdiri atas median imputer dan Gaussian Naive Bayes classifier. Hasil evaluasi menunjukkan bahwa model mencapai akurasi sebesar 79,2%, dengan nilai recall sempurna (1,00) pada kelas berprestasi dan lebih rendah (0,64) pada kelas tidak berprestasi. Hal ini menunjukkan bahwa model cukup efektif dalam mengidentifikasi siswa berprestasi. Model yang telah dilatih kemudian diintegrasikan ke dalam aplikasi web berbasis Flask, yang memungkinkan prediksi secara daring melalui antarmuka formulir sederhana untuk mendukung interpretasi kontekstual. Sistem ini diharapkan dapat membantu untuk pengambilan keputusan dalam pendidikan dengan membantu guru mengidentifikasi tingkat prestasi siswa sejak dini dan merancang intervensi pembelajaran yang lebih terarah.
Kata kunci: prestasi akademik; penambangan data Pendidikan; naive bayes; sistem prediksi; prestasi siswa
Abstract:Abstract: Higher education plays an essential role in improving human resource quality, one of which is through the institution’s ability to monitor and predict student graduation outcomes. This study does not focus on a…
a specific university but utilizes the publicly available Students Performance in Exams dataset from Kaggle, consisting of 1,000 student records containing mathematics, reading, and writing scores, along with demographic attributes such as gender, parental education level, lunch type, and test preparation participation. The data were processed through a feature engineering stage by adding an average score variable as an early indicator of graduation status. A predictive model was developed using the Random Forest Classifier, achieving an accuracy of 94.5%. The final model was integrated into a Streamlit-based web application to provide an accessible tool for academic stakeholders. The results indicate that the proposed model can serve as an effective decision-support tool for early evaluation of students’ likelihood of graduation.
Keywords: prediction; random forest classifier, streamlit, student graduation.
Abstrak: Pendidikan tinggi memegang peran penting dalam peningkatan kualitas sumber daya manusia, salah satunya melalui kemampuan institusi dalam memantau dan memprediksi tingkat kelulusan mahasiswa. Penelitian ini tidak berfokus pada perguruan tinggi tertentu, melainkan menggunakan dataset publik Students Performance in Exams dari Kaggle yang berisi 1.000 data mahasiswa, terdiri atas nilai matematika, membaca, menulis, serta atribut demografis seperti gender, tingkat pendidikan orang tua, jenis makan siang, dan partisipasi kursus persiapan. Data diolah melalui tahap feature engineering dengan menambahkan variabel average score sebagai indikator awal kelulusan. Model prediksi dibangun menggunakan algoritma Random Forest Classifier, yang menghasilkan tingkat akurasi sebesar 94,5%. Model ini kemudian diimplementasikan ke dalam aplikasi web berbasis Streamlit untuk memberikan layanan prediksi yang mudah diakses oleh pihak akademik. Hasil penelitian menunjukkan bahwa model mampu digunakan sebagai alat pendukung keputusan untuk melakukan evaluasi dini terhadap potensi kelulusan mahasiswa.
Kata kunci: kelulusan mahasiswa; prediksi; random forest classifier; streamlit.
Abstract:Giving awards is essential to motivate students; however, selecting outstanding students at the junior high school level is often conducted manually and subjectively, which can lead to unfairness and prolonged processing…
time. This study develops a Decision Support System (DSS) that integrates the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support objective and transparent student selection. A quantitative descriptive approach was employed, with data collected through questionnaires, interviews, and documentation at two state junior high schools in Banjarmasin City. Seven assessment criteria were applied: attendance, behavior, uniform neatness, extracurricular participation, academic grades, competition achievements, and disciplinary records. AHP was used to determine the weight of each criterion, while TOPSIS ranked students based on these weights. The web-based system was developed using PHP and MySQL and evaluated using the Technology Acceptance Model (TAM). Results show that academic grades had the highest weight (28.5%), followed by attendance (22.3%) and competition performance (15.2%). The TAM evaluation yielded average scores of 4.32 for Perceived Ease of Use, 4.40 for Perceived Usefulness, 4.15 for Attitudes Towards Use, and 4.28 for Behavioral Intention to Use. The DSS produces accurate rankings, is well-received by users, and offers an efficient, fair, and replicable solution for data-driven educational governance in the digital era.
Abstract:Abstract: Teacher performance appraisal is a very important aspect in improving the quality of education today, but often occurs during the assessment process of subjectivity constraints and lack of a structured system,…
in this study aims to build a data structure modeling and facilitate the school MAS Islamiyah Hessa Air Genting in the assessment to determine the best teacher transparently and measurably by using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The TOPSIS method was chosen because it is able to provide ranking results based on the closeness of alternatives to the ideal solution. In this modeling, assessment criteria data such as pedagogical, professional, personality, social competencies, as well as other indicators such as teacher discipline and achievement are modeled structurally in a relational database. The results show that the designed data structure is able to support the decision-making process efficiently and objectively.
Keywords: data structure; decision support system; teacher assessment; topsis; ranking.
Abstrak: Penilaian kinerja guru merupakan aspek yang sangat penting dalam peningkatan mutu pendidikan saat ini, namun sering terjadi saat proses penilaian kendala subjektivitas dan kurangnya sistem yang terstruktur, dalam penelitian ini bertujuan untuk membangun pemodelan struktur data serta mempermudah pihak sekolah MAS Islamiyah Hessa Air Genting dalam penilaian untuk menentukan guru terbaik secara transparan dan terukur dengan menggunakan algoritma Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Metode TOPSIS dipilih karena mampu memberikan hasil perankingan berdasarkan kedekatan alternatif terhadap solusi ideal. Dalam pemodelan ini, data kriteria penilaian seperti kompetensi pedagogik, profesional, kepribadian, sosial, serta indikator lain seperti kedisiplinan dan prestasi guru dimodelkan secara terstruktur dalam basis data relasional. Hasil penelitian menunjukkan bahwa struktur data yang dirancang mampu mendukung proses pengambilan keputusan secara efisien dan objektif.
Kata kunci: struktur data; topsis; penilaian guru; sistem pendukung keputusan; perangkingan
Abstract:Abstract: On-time graduation is an important indicator in measuring the success of higher education and reflects the effectiveness of the academic process in higher education. Royal University, especially the Information…
Systems Study Program, still faces challenges in increasing the percentage of students who graduate on time. This study aims to identify factors that influence students' on-time graduation and build a prediction model using the multiple linear regression method. This method was chosen because it is able to analyze the simultaneous influence of several independent numeric variables on one dependent variable, making it suitable for studying the complex relationship between factors that influence student graduation. The independent variables analyzed in this study include GPA, parental income, and student part-time jobs with student graduation as the dependent variable. The results showed that parental income and part-time jobs had a significant positive effect on on-time graduation, while GPA had a negative effect. The model built had an R² value of 0.6153 and a standard error of 4.0653, indicating that the model was quite strong and accurate. These findings recommend Universitas Royal to strengthen the academic monitoring system and support working students, as well as design policies based on students' socio-economic conditions to increase the on-time graduation rate.
Keywords: multiple linear regression; on-time graduation; students.
Abstrak: Kelulusan tepat waktu merupakan indikator penting dalam mengukur keberhasilan pendidikan tinggi serta mencerminkan efektivitas proses akademik di perguruan tinggi. Universitas Royal, khususnya Program Studi Sistem Informasi, masih menghadapi tantangan dalam meningkatkan persentase mahasiswa yang lulus tepat waktu. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang memengaruhi kelulusan tepat waktu mahasiswa serta membangun model prediksi menggunakan metode regresi linear berganda. Metode ini dipilih karena mampu menganalisis pengaruh simultan beberapa variabel independen numerik terhadap satu variabel dependen, sehingga sesuai untuk mengkaji hubungan kompleks antar faktor yang memengaruhi kelulusan mahasiswa. Variabel independen yang dianalisis dalam penelitian ini meliputi IPK, penghasilan orangtua, dan pekerjaan sambilan mahasiswa dengan kelulusan mahasiswa sebagai variabel dependen. Hasil penelitian menunjukkan bahwa penghasilan orangtua dan pekerjaan sambilan berpengaruh positif signifikan terhadap kelulusan tepat waktu, sedangkan IPK justru memiliki pengaruh negatif. Model yang dibangun memiliki nilai R² sebesar 0,6153 dan standar error 4,0653, menandakan model cukup kuat dan akurat. Temuan ini merekomendasikan Universitas Royal untuk memperkuat sistem monitoring akademik dan mendukung mahasiswa yang bekerja, serta merancang kebijakan berbasis kondisi sosial-ekonomi mahasiswa guna meningkatkan angka kelulusan tepat waktu.
Kata kunci: kelulusan tepat waktu; mahasiswa; regresi linear berganda.
Abstract:Abstract: Secondary education plays an important role in shaping students' academic, social, and emotional skills and preparing them for further education or entering the workforce. One important aspect of education is the…
he application of discipline through sanctions for violations of school rules. SMA Negeri 1 Kisaran currently still uses a manual system in recording and imposing sanctions, which is prone to errors, data loss, and is less efficient in decision making. This study aims to propose the implementation of a decision support system based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to determine more objective and transparent sanctions. The results of the application of the TOPSIS method in the process of determining objective sanctions for students at SMA Negeri 1 Kisaran are based on factors such as attendance, neatness, diligence, and student behavior, resulting in more accurate and systematic decisions. This study shows that the application of the TOPSIS method increases efficiency in determining sanctions for students and supports a fairer and data-based coaching process in schools.
Keywords: decision support system; discipline; sanctions; TOPSIS.
Abstrak: Pendidikan menengah memiliki peran penting dalam membentuk keterampilan akademik, sosial, dan emosional peserta didik serta mempersiapkan mereka untuk pendidikan lebih lanjut atau masuk ke dunia kerja. Salah satu aspek penting dalam pendidikan adalah penerapan disiplin melalui sanksi terhadap pelanggaran aturan sekolah. SMA Negeri 1 Kisaran saat ini masih menggunakan sistem manual dalam pencatatan dan pemberian sanksi, yang rentan terhadap kesalahan, kehilangan data, serta kurang efisien dalam pengambilan keputusan. Penelitian ini bertujuan mengusulkan penerapan sistem pendukung keputusan berbasis metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk menentukan sanksi yang lebih objektif dan transparan. Hasil dari penerapan metode TOPSIS dalam proses penentuan sanksi objektif pada peserta didik di SMA Negeri 1 Kisaran didasarkan pada faktor-faktor seperti kehadiran, kerapian, kerajinan, serta kelakuan siswa, sehingga menghasilkan keputusan yang lebih akurat dan sistematis. Studi ini menunjukkan bahwa penerapan metode TOPSIS meningkatkan efisiensi dalam menentukan sanksi bagi siswa serta mendukung proses pembinaan yang lebih adil dan berbasis data di sekolah.
Kata kunci: kedisiplinan; sanksi; sistem pendukung keputusan; TOPSIS.
Abstract:Abstract: School building construction is an important part of educational facilities and infrastructure. Many elementary school buildings in Asahan Regency are damaged, unfit for use or lack facilities including classrooms…
oms and other supporting infrastructure. The results of the selection that are not transparent in deciding the feasibility of rehabilitation and construction of elementary school buildings are often subjective and time-consuming. This causes decisions to be taken that cannot be made as quickly as possible and inequality, where schools that actually need rehabilitation more do not get priority for rehabilitation. The purpose of this study is to implement data mining in the selection of school building construction projects with the K-Means clustering algorithm in clustering the feasibility of rehabilitation of elementary school building construction. The results of this study found 31 elementary schools that are eligible for school building construction rehabilitation and 4 are not eligible for school building construction rehabilitation. This study is expected to provide a significant contribution in increasing the efficiency of school building construction selection and more transparency towards elementary school buildings to be rehabilitated.
Keywords: education authorities; k-means; rehabilitation and construction of school buildings.
Abstrak: Pembangunan gedung sekolah ialah bagian penting dalam sarana dan prasarana pendidikan. Banyak gedung Sekolah Dasar di Kabupaten Asahan menderita kerusakan, tidak layak pakai atau kekurangan fasilitas meliputi ruang kelas dan infrastruktur pendukung lainnya. Hasil penyeleksian yang bersifat tidak transparan dalam memutuskan kelayakan rehabilitasi dan pembangunan gedung Sekolah Dasar sering kali bersifat subjektif dan memakan waktu lama.Hal tersebut menyebabkan keputusan yang diambil tidak dapat dilakukan secepat mungkin serta ketimpangan, dimana sekolah yang sebenarnya lebih membutuhkan rehabilitasi justru tidak mendapatkan prioritas untuk direhabilitasi. Tujuan penelitian ini ialah mengimplementasi data mining pada pemilihan proyek pembangunan gedung sekolah dengan algoritma K-Means clustering dalam mengcluster kelayakan rehabilitasi pembangunan gedung sekolah dasar. Hasil Penelitian ini terdapat 31 sekolah dasar layak untuk direhabilitasi pembangunan gedung sekolah dan 4 tidak layak untuk direhabalitasi pembangunan gedung sekolah. Penelitian ini diharapkan dapat memberikan kontribusi signifikan dalam menaikkan efisiensi penyeleksian pembangunan gedung sekolah dan lebih transparansi terhadap gedung sekolah dasar yang akan direhabilitasi.
Kata kunci: dinas pendidikan; k-means; rehabilitasi dan pembangunan gedung sekolah.