Abstract:Pemilihan Ketua Badan Eksekutif Mahasiswa (BEM) merupakan proses penting dalam menentukan mahasiswa yang memiliki kompetensi terbaik untuk memimpin organisasi kemahasiswaan. Namun, proses seleksi yang masih bergantung pada…
da popularitas dan penilaian subjektif berpotensi menghasilkan keputusan yang kurang optimal. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan (SPK) menggunakan metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) untuk membantu proses pemilihan Ketua BEM secara objektif. Data penelitian diperoleh melalui wawancara dengan pembina BEM untuk menentukan kriteria dan bobot penilaian. Lima kriteria yang digunakan meliputi kepemimpinan, kemampuan komunikasi, pengalaman organisasi, integritas, dan indeks prestasi kumulatif (IPK). Tahapan metode MOORA terdiri atas penyusunan matriks keputusan, normalisasi, perhitungan nilai optimasi, dan proses perangkingan. Hasil penelitian menunjukkan bahwa alternatif K1 memperoleh nilai optimasi tertinggi sebesar 0,473 sehingga direkomendasikan sebagai Ketua BEM terpilih. Penerapan metode MOORA mampu menghasilkan proses pengambilan keputusan yang lebih objektif, sistematis, transparan, dan akurat sehingga dapat dijadikan sebagai alat bantu dalam menentukan Ketua BEM berdasarkan kriteria yang telah ditetapkan.
The selection of the Student Executive Board (BEM) President is an important process in determining the most qualified student to lead the student organization. However, conventional selection processes often rely on popularity and subjective judgments, which may lead to less optimal decisions. This study aims to develop a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support a more objective selection process. Research data were collected through interviews with BEM advisors to determine the assessment criteria and their corresponding weights. Five criteria were used, namely leadership, communication skills, organizational experience, integrity, and grade point average (GPA). The MOORA method consists of decision matrix construction, normalization, optimization value calculation, and ranking. The results indicate that candidate K1 achieved the highest optimization value of 0.473 and was therefore recommended as the selected BEM President. The implementation of the MOORA method provides a more objective, systematic, transparent, and accurate decision-making process, making it an effective tool for supporting the selection of the most suitable BEM President based on predetermined criteria.
Abstract:This study aims to formulate the right business strategy for CV XYZ, an MSME in the frozen food industry, in facing operational challenges such as high employee turnover, dependence on out-of-town suppliers, and logistics…
s inefficiencies due to limited cold chain technology. This study uses a qualitative method with a case study approach. Data were collected through semi-structured interviews, internal company reports, literature reviews, and industry publications. The analysis was conducted through an external approach using PESTEL and Porter's Five Forces, as well as internal analysis through VRIO and Value Chain Analysis. The results of the analysis are summarized in a SWOT Analysis and continued with the formulation of a business strategy using Porter's Generic Strategies and TOWS Matrix. The proposed strategy is Cost Leadership with a focus on operational efficiency, investment in cold chain technology, and employee training to increase productivity. This strategy is expected to help CV XYZ increase competitiveness, expand the market, and support sustainable business growth in the frozen food industry.
Abstract:Penggunaan dompet digital yang terus meningkat menghasilkan banyak ulasan pengguna yang dapat dimanfaatkan untuk mengevaluasi kualitas layanan. Penelitian ini bertujuan meningkatkan akurasi klasifikasi sentimen pengguna…
dompet digital menggunakan metode Stacking Ensemble Machine Learning yang mengombinasikan Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), dan AdaBoost dengan Logistic Regression sebagai meta-learner. Data ulasan diproses melalui tahapan text preprocessing meliputi case folding, cleaning, tokenizing, stopword removal, stemming, dan pembobotan fitur menggunakan TF-IDF. Penyeimbangan data dilakukan dengan SMOTE, sedangkan evaluasi model menggunakan 5-Fold Cross-Validation. Hasil penelitian menunjukkan bahwa model Stacking Ensemble memperoleh akurasi rata-rata 80,55%, lebih tinggi dibandingkan algoritma dasar. Evaluasi menggunakan Confusion Matrix, Classification Report, dan ROC Curve juga menunjukkan peningkatan nilai precision, recall, F1-score, dan kemampuan diskriminasi model. Hasil ini menunjukkan bahwa pendekatan Stacking Ensemble Machine Learning efektif untuk meningkatkan akurasi klasifikasi sentimen pengguna dompet digital serta mendukung evaluasi kualitas layanan berbasis opini pengguna.
The rapid growth of digital wallet usage has generated a large volume of user reviews that can be utilized to evaluate service quality. This study aims to improve the accuracy of digital wallet user sentiment classification using a Stacking Ensemble Machine Learning approach that combines Support Vector Machine (SVM), Multinomial Naïve Bayes (MNB), and AdaBoost with Logistic Regression as the meta-learner. User reviews were processed through text preprocessing stages, including case folding, text cleaning, tokenization, stopword removal, stemming, and TF-IDF feature weighting. Synthetic Minority Over-sampling Technique (SMOTE) was employed to address class imbalance, while model performance was evaluated using 5-Fold Cross-Validation. The experimental results show that the proposed Stacking Ensemble model achieved an average accuracy of 80.55%, outperforming the individual base learners. Furthermore, evaluations based on the Confusion Matrix, Classification Report, and Receiver Operating Characteristic (ROC) Curve demonstrated improvements in precision, recall, F1-score, and the model's discriminative capability. These findings indicate that the proposed Stacking Ensemble Machine Learning approach is effective in improving the accuracy of digital wallet user sentiment classification and can serve as a reliable tool for supporting service quality evaluation based on user opinions.
Abstract:The rapid advancement of digital technology has fundamentally reshaped consumer behavior globally, with social media becoming the primary channel for product information seeking. Approximately 51% of Indonesians rely on…
user reviews before purchasing, and 62% have bought products under the direct influence of Social Media Influencers (SMIs). Despite this, the psychological mechanisms linking influencer characteristics to purchase intention remain fragmented across sectors and platforms. This systematic literature review synthesizes nineteen empirical studies published between 2020 and 2025, spanning beauty, fashion, gadget, and sustainable product sectors across multiple countries, to examine how Source Credibility (attractiveness, trustworthiness, expertise) and Parasocial Interaction (PSI) jointly shape consumer purchase intentions. Three core findings emerge: (1) trustworthiness is the sole credibility dimension that is universally and consistently significant across all contexts, fundamentally challenging assumptions about the equal contribution of the three credibility dimensions; (2) PSI operates not as a single mediator but as a multi-pathway psychological bridge through hedonic value, brand attitude, vicarious experience, and social-personal value whose specific active pathway is contingent on platform, product type, and cultural context; and (3) generational and cultural moderators systematically shape which credibility dimension most powerfully drives PSI. A Proposed Integrative Conceptual Framework and a synthetic cross-study comparison matrix (Table 2) consolidate these findings. Results offer strategic implications for influencer marketing practice and identify priority directions for future research.
Abstract:Listrik merupakan salah satu kebutuhan dasar masyarakat dan merupakan salah satu kebutuhan hajat hidup orang banyak, sehingga perlu diatur dan disediakan oleh negara sesuai amanah undang-undang 1945 pasal 33. Subsidi diberikan…
erikan dengan tujuan agar ketersediaan listrik dapat terpenuhi, serta membantu pelanggan yang kurang mampu dan masyarakat yang belum terjangkau pelayanan PT. Berdasarkan hasil evaluasi BKF dengan German International Cooperation (GIZ) terhadap subsidi listrik yang diberikan kepada kelompok pelanggan R1-450 VA dan R1-900 VA yang berlaku saat ini menunjukkan subsidi listrik tidak tepat sasaran, karena 5,9 juta pelanggan R1-450 VA dan 14,4 juta pelanggan R1-900 VA adalah kelompok rumah tangga yang telah mampu karena termasuk dalam pengeluaran per kapita lebih dari Rp.1 juta per bulan. Guna mengurangi risiko salah sasaran tersebut, perlu dilakukan klasifikasi dalam pemberian subsidi listrik berdasarkan kriteria-kriteria tertentu yang telah menjadi standar di PT. PLN menggunakan data mining dengan metode decision tree. Berdasarkan evaluasi dan hasil pengujian bab sebelumnya dengan dataset 50 data, 70 data dan 100 data produksi yang telah dilakukan, maka hasil pengukuran Confusion Matrix dalam penerapan data mining untuk memprediksi target Desa Tebara dengan metode Decision Tree (Algoritma C4.5) pada pengujian 50 data menghasilkan akurasi 74%, precision 60% dan recall 83,33%. Pada pengujian 70 data menghasilkan akurasi 81,43%, precision 76,92% dan recall 74,07%. Pada pengujian 100 data menghasilkan akurasi 82%, precision 76,67% dan recall 67,65%. Jadi untuk data uji lebih banyak akan menghasilkan akurasi yang lebih tinggi.
Abstract:Covid-19 is a serious health problem that occurs globally, including in Indonesia. Mathematical modeling is one way to see how the spread of the Covid-19 pandemic is developing. The model used in this study is SVEI1I2R and…
nd its stability will be seen. The article discusses the stability of fixed points using the Jacobian matrix and the Routh-Hurwitz criterion as well as the Castilo-Chaves and Song Theorems, reproduction numbers, and their numerical analysis. The results of the analysis show that the stability of fixed points is related to the basic reproduction number determined by the next-generation matrix, stability analysis in accordance with the theorem and the distribution of the population is shown in a numerical graph.
Abstract:This study aims to analyze the feasibility of business development for CV. Subur Indah Pertama, located in Pemecutan Kaja Village, North Denpasar, Bali, based on five main aspects of business feasibility studies: market…
and marketing, legal, human resources, environmental, and financial. This research employs a qualitative approach using descriptive methods, with data collection techniques including direct observation, in-depth interviews, and document review. The analysis results show that from the market and marketing aspect, the company has demonstrated positive performance through the optimization of digital platforms such as Tokopedia, Shopee, and TikTok, as well as strategic partnerships with contractors and property developers. Legally, the company is deemed feasible as it has fulfilled all business documents and licenses, including SIUP, NPWP, PKP, and tax compliance. In terms of human resources, a systematic organizational structure and professionally-based HR management indicate the company’s readiness to support business expansion. The environmental aspect also meets feasibility criteria, with evidence of standardized waste management systems and compliance with environmental regulations. From the financial perspective, the project is considered highly feasible based on financial indicators, namely a Net Present Value (NPV) of IDR 13.7 billion, an Internal Rate of Return (IRR) of 32%, and a Payback Period of 5 years, which is below the project’s economic life of 8 years. The IFAS and EFAS analyses show significant internal strengths, while the SWOT matrix places the company in Quadrant I with an aggressive strategy (Strength–Opportunity). Based on the overall findings, the business development of CV. Subur Indah Pertama is declared feasible and has strong prospects for long-term growth.
Abstract:Kegiatan pengabdian kepada masyarakat ini dilaksanakan pada UMKM Kedai Tahu Bakso Batununggal (Kedai TBB) di Kota Bandung yang menghadapi beberapa permasalahan, antara lain pelayanan yang belum optimal, branding yang masih…
asih fokus pada produk tahu bakso, serta perlunya strategi pengembangan usaha untuk meningkatkan daya saing.
Kegiatan ini bertujuan membantu mitra dalam mengidentifikasi kondisi internal dan eksternal usaha serta merumuskan
strategi pengembangan yang sesuai. Metode yang digunakan adalah pendampingan partisipatif melalui observasi,
wawancara, dokumentasi, serta analisis SWOT (Strengths, Weaknesses, Opportunities, Threats) dan Quantitative
Strategic Planning Matrix (QSPM). Hasil analisis menunjukkan bahwa Kedai TBB memiliki skor Internal Factor
Evaluation (IFE) sebesar 2,93 dan External Factor Evaluation (EFE) sebesar 2,90 sehingga berada pada posisi Growth
Stability dalam Matriks Internal-External. Berdasarkan hasil QSPM, strategi penetrasi pasar memperoleh nilai Total
Attractiveness Score (TAS) tertinggi sebesar 6,99 dibandingkan strategi pengembangan pasar (5,32) dan
pengembangan produk (4,91). Oleh karena itu, strategi penetrasi pasar direkomendasikan melalui penguatan pemasaran
digital, optimalisasi platform online, serta peningkatan kualitas pelayanan guna mendukung pertumbuhan usaha yang
berkelanjutan.
Abstract:Data mining merupakan salah satu metode yang paling efektif dalam menghasilkan klasifikasi yang akurat, efisien, dan relevan. Pengelompokan jenis kendaraan berdasarkan sistem transmisi dilakukan dengan menggunakan algoritma…
tma Decision Tree dan dievaluasi melalui confusion matrix. Dataset yang digunakan mencakup empat jenis kendaraan: Bebek, Skuter, Sport, dan Trail, dengan tiga jenis transmisi: Manual, Automatic, dan Kopling. Algoritma Decision Tree dipilih karena kemampuannya dalam membagi dataset secara rekursif untuk menghasilkan aturan klasifikasi yang jelas dan mudah dipahami. Model dilatih dan diuji untuk memprediksi jenis transmisi berdasarkan fitur kendaraan, dengan hasil akurasi mencapai 95%. Evaluasi menggunakan confusion matrix mengungkap distribusi prediksi benar dan salah pada setiap kategori. Hasilnya menunjukkan bahwa transmisi Automatic dan Kopling diklasifikasikan dengan akurasi tinggi, meskipun terdapat beberapa kesalahan pada prediksi transmisi Manual. Nilai Cohen’s Kappa sebesar 0,913 mengindikasikan kesesuaian yang sangat baik antara prediksi dan data aktual. Algoritma Decision Tree terbukti efektif dalam klasifikasi jenis kendaraan, meskipun diperlukan perbaikan untuk meningkatkan akurasi pada kategori tertentu.
Abstract:Abstract : The Central Bureau of Statistics (BPS) is a non-departmental government agency established as a provider of data or information based on Law No. 6/1960 on Census and Law No. 7/1997 on Statistics. The Central Statistics…
tatistics Agency (BPS) recorded the number of motorized vehicles such as cars, buses, trucks, and motorcycles in the provinces of North Sumatra and West Sumatra in 2020-2021 reaching 3,043,892 million units. The purpose of this study is to classify the number of motorized vehicles in the form of cars, motorcycles, buses and trucks. This research uses quantitative research with Naive Bayes Algorithm analysis model. The data used in this study is data from several regions in North Sumatra Province and West Sumatra Province in 2020-2021. Evaluation of model performance is based on accuracy parameters, precision and total recall of the confusion-matrix. The results of testing the dataset and calculating the model performance parameters have obtained an accuracy value of 100%. With the percentage value of the description of each dataset class, namely a little 70.6%, moderate 21.6%, and a lot 7.8%.
Keywords :classification;confusion-matrix; data; motor vehicles; naive bayes
Abstrak : Badan Pusat Statistik (BPS) adalah lembaga pemerintahan non-departemen yang dibentuk sebagai penyedia data atau informasi berdasarkan UU Nomor 6 Tahun 1960 tentang Sensus dan UU Nomor 7 Tahun 1997 tentang Statistik. Badan Pusat Statistik (BPS) mencatat jumlah kendaraan bermotor seperti mobil, bus, truk, dan sepeda motor di Provinsi Sumatera Utara dan Sumatera Barat pada tahun 2020-2021 mencapai 3.043.892 juta unit. Tujuan dari penelitian ini yaitu untuk mengklasifikasikan jumlah kendaraan bermotor berupa mobil, sepeda motor, bus dan, truk. Adapun penelitian ini menggunakan jenis penelitian kuantitatif dengan model analisis Algoritma Naive Bayes. Data yang digunakan pada penelitian ini adalah data dari beberapa daerah di Provinsi Sumatera Utara dan Provinsi Sumatera Barat tahun 2020-2021. Evaluasi kinerja model didasarkan pada parameter akurasi, presisi dan recall total dari Confusion-Matrix. Hasil pengujian dataset dan perhitungan parameter performa model telah didapat nilai akurasi 100%. Dengan presentase nilai keterangan setiap kelas dataset yaitu Sedikit 70,6%, Sedang 21,6%, dan Banyak 7,8%.
Kata kunci :confusion-matrix; data; kendaraan bermotorklasifikasi; naive bayes