Journal of Information System, Applied, Management, Accounting and Research
JISAMAR (Journal of Information System, Applied, Management, Accounting and Research) E-ISSN: 2598-8719 (Online) P-ISSN: 2598-8700(Printed) published by Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta . DECREE OF THE MINISTER OF RESEARCH AND TECHNOLOGY / HEAD OF THE NATIONAL RESEARCH AND INNOVATION AGENCY OF THE REPUBLIC OF INDONESIA, NUMBER 85 / M / KPT / 2020 ON THE ACCREDITATION RATING OF SCIENTIFIC JOURNALS PERIOD I OF 2020. JOURNAL OF INFORMATION SYSTEM, APPLIED, MANAGEMENT, ACCOUNTING AND RESEARCH, RANKED 5 (SINTA 5), CALCULATED VOLUME 2 NUMBER 1 (2018). JISAMAR is published four times a year in February, May, August and November, containing a manuscript of thought and research results in the fields: Information Systems, Computer Science, Information Technology, Informatics, Artificial Intelligence, Applied Sciences, Management, Accounting and Research Results according to the Scope and Focus of the Journal. Focus and Scope (Call for Papers)
Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta
Implementasi Metode Naïve Bayes Dalam Deteksi Akses Tidak Sah Menggunakan Dataset UNSW-NB15
The rapid growth of information technology and digital activities has led to an increasing number of attacks on computer networks. Various types of cyberattacks, such as unauthorized access and malicious activities, pose serious threats to data security and confidentiality. Therefore, an effective security mechanism is required to detect such attacks, one of which is through the implementation of an Intrusion Detection System (IDS). This study aims to apply the Naïve Bayes algorithm to detect unauthorized access in computer networks. The dataset used in this research is the UNSW-NB15 dataset, which was preprocessed to obtain 82,332 records suitable for classification. The evaluation was conducted using the 10-Fold Cross Validation method with the assistance of RapidMiner software. The experimental results indicate that the Naïve Bayes algorithm achieves excellent performance in classifying network traffic. The proposed model attained an accuracy of 95.96%, a precision of 94.11%, a recall of 98.85%, and an Area Under the Curve (AUC) value of 0.964. The high AUC value demonstrates that the model is highly effective in distinguishing between normal traffic and attack traffic. Based on these findings, it can be concluded that the Naïve Bayes algorithm is a reliable and effective method for intrusion detection systems to enhance network security.
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Environmental Accountability or Symbolic Reporting? and Evidence from ESG Disclosures in Indonesia’s Telecommunications Industry
This study examines the credibility of Environmental, Social, and Governance (ESG) environmental disclosures by evaluating whether reported sustainability information reflects actual environmental performance in Indonesian telecommunications companies. Using qualitative content analysis of sustainability reports from major telecom firms between 2022 and 2024, the study assesses disclosure transparency, availability of quantitative indicators, and alignment between narrative reporting and measurable outcomes. The findings reveal substantial discrepancies between disclosed commitments and verifiable performance evidence. Although all companies report environmental initiatives, the majority of disclosures are narrative-driven and lack quantitative indicators that enable objective performance assessment. Paper reduction initiatives associated with digitalization provide the most consistent measurable outcomes, while programs addressing electronic waste, recycling, and environmental awareness are typically reported without clear metrics. These patterns suggest that ESG reporting may function not only as an accountability mechanism but also as a legitimacy tool aimed at maintaining stakeholder confidence. From a sustainability accounting perspective, the results highlight a gap between disclosure volume and information reliability. The absence of standardized metrics limits comparability across firms and reduces the decision usefulness of ESG information for investors and regulators. The study also indicates that initiatives integrated into core business operations are more likely to produce measurable outcomes and credible disclosures. This research contributes to sustainability accounting literature by shifting the focus from the existence of environmental programs to the quality and credibility of ESG disclosures. The findings provide implications for regulators, standard-setting bodies, and corporate managers seeking to enhance transparency, accountability, and the effectiveness of sustainability reporting in infrastructure-intensive industries.
Analisis Manajemen Risiko Proyek Infrastruktur CCTV Lalu Lintas dengan PMBOK dan ISO 31000 Dishub Surabaya
Penelitian ini menganalisis manajemen risiko proyek pemeliharaan Closed-Circuit Television (CCTV) pada Surabaya Intelligent Transport System (SITS) menggunakan integrasi Project Management Body of Knowledge (PMBOK) dan ISO 31000:2018. Data observasi lapangan dan studi literatur dievaluasi melalui matriks risiko serta Failure Mode and Effects Analysis (FMEA). Hasilnya memetakan empat kategori risiko: infrastruktur eksternal, perangkat keras, penjadwalan, dan Keselamatan dan Kesehatan Kerja (K3). Risiko K3 akibat kelalaian penggunaan Alat Pelindung Diri (APD) mencatat Risk Priority Number (RPN) tertinggi (75), diikuti dominasi gangguan jaringan eksternal penyebab downtime. Strategi mitigasi yang dirumuskan meliputi pengetatan SOP keselamatan, standardisasi penundaan kerja saat cuaca ekstrem, dan penguatan Service Level Agreement (SLA) lintas instansi untuk meminimalisir deviasi jadwal serta menjamin keselamatan pekerja. This study analyzes risk management in the Closed-Circuit Television (CCTV) maintenance project at the Surabaya Intelligent Transport System (SITS) using an integrated Project Management Body of Knowledge (PMBOK) and ISO 31000:2018 framework. Field observation and literature data were evaluated using a risk matrix and Failure Mode and Effects Analysis (FMEA). The results mapped four risk categories: external infrastructure, hardware, scheduling, and Occupational Health and Safety (OHS). OHS risks due to negligence in using Personal Protective Equipment (PPE) recorded the highest Risk Priority Number (RPN) of 75, followed by external network disruptions causing downtime. Formulated mitigations include tightening safety SOPs, standardizing work postponement during extreme weather, and improving cross-agency Service Level Agreement (SLA) to minimize schedule deviation and ensure worker safety.
Analisis Strategi Bisnis Berbasis SWOT pada PT Sauna Rahaf Utama
This study aims to formulate an appropriate business development strategy for PT Sauna Rahaf Utama to navigate the competitive landscape of the engineering services industry. Utilizing the SWOT analysis framework (Strengths, Weaknesses, Opportunities, Threats), the research evaluates the firm’s competitive standing across internal and external dimensions. A qualitative descriptive methodology was employed, utilizing secondary observations and corporate document analysis. The findings, derived from IFAS and EFAS matrix calculations, yielded a total score of 2.95, positioning the company in Quadrant I (Aggressive Strategy). The primary strengths identified include operational experience since 2016 and a robust portfolio of state-owned enterprise (SOE) clients. Conversely, critical weaknesses lie in limited digital brand presence and a lack of international certifications. Consequently, the study recommends a growth-oriented strategy focusing on strengthening digital identity, obtaining ISO certifications to bolster competitiveness, and innovating technology-based services to capitalize on emerging opportunities within the mining and infrastructure sectors.
PROGRAM PENENTUAN PROPORSI SAHAM PORTFOLIO MENGGUNAKAN QUADRATIC PROGRAMMING WOLFE
Investors generally desire substantial returns from their investments with minimal risk of loss, and they invest their capital in several types of stocks (stock diversification). The problem that then arises is how they determine the proportion of stocks in their portfolio that will provide a large return (profit) with minimal risk. To solve this problem, the author will implement Quadratic Programming using the Wolfe method to determine the optimal portfolio proportion for investment. Several examples of Quadratic Programming calculations using the Wolfe method performed with the help of a computer program are presented in this paper. The results obtained show no significant difference from the results of manual calculations.
Perceived Usefulness, Trust, and the Effectiveness of Accounting Learning Using ChatGPT
Artificial Intelligence (AI), particularly ChatGPT, has increasingly been integrated into higher education to support teaching and learning activities. However, the effectiveness of AI-assisted learning depends not only on the availability of the technology but also on students' perceptions of its usefulness and their trust in the technology. This study examines the effects of perceived usefulness and trust on the effectiveness of AI-assisted accounting learning among undergraduate accounting students in Indonesia. A quantitative research design was employed using a survey of 100 undergraduate accounting students who had experience using ChatGPT for learning purposes. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that both perceived usefulness and trust have positive and significant effects on accounting learning effectiveness, with the proposed model explaining 61.4% of the variance (R² = 0.614). The novelty of this study lies in the development of a measurement of AI-assisted accounting learning effectiveness by integrating the Technology Acceptance Model (TAM) and Trust Theory within the context of generative AI. The findings provide practical implications for higher education institutions and AI developers in designing AI-assisted learning environments that enhance students' perceived usefulness, trust, and accounting learning effectiveness.
ANALISIS KOMPARATIF KINERJA LOGISTIC REGRESSION DAN RANDOM FOREST BERBASIS TF-IDF UNTUK KLASIFIKASI SENTIMEN KOMENTAR TIKTOK TERHADAP PROGRAM MAKAN BERGIZI GRATIS
Sentiment analysis of public policy on social media has become increasingly important as public participation in digital spaces continues to grow. This study compares the performance of Logistic Regression and Random Forest algorithms based on TF-IDF for classifying the sentiment of TikTok comments regarding the Free Nutritious Meal Program into three classes: positive, neutral, and negative. The dataset consists of 4,811 public comments collected from six TikTok videos between January and June 2026. After preprocessing and manual labeling, 3,884 valid comments were obtained with a sentiment distribution of 39.73% negative, 37.97% positive, and 22.30% neutral. Class imbalance was addressed using SMOTE on the training data, and the dataset was split using an 80:20 stratified split. Evaluation results show that Logistic Regression outperformed Random Forest across all metrics, achieving an accuracy of 0.76 and a macro F1-score of 0.74 compared to Random Forest's accuracy of 0.73 and macro F1-score of 0.71. In both models, the neutral class consistently showed the lowest performance, indicating semantic ambiguity that cannot be optimally captured by frequency-based feature representations. This study provides empirical evidence that Logistic Regression is more suitable for Indonesian social media text sentiment classification with TF-IDF representation, and recommends exploring context-based models such as IndoBERT for future research.
ANALISIS PENGENDALIAN PERSEDIAAN BAHAN BAKU MENGGUNAKAN METODE ECONOMIC ORDER QUANTITY (EOQ) DAN JUST IN TIME (JIT) PADA UMKM JENANG DODOL BU HARTINI
Penelitian ini dilatarbelakangi oleh belum optimalnya sistem pengendalian persediaan bahan baku tepung ketan pada Usaha Mikro, Kecil, dan Menengah (UMKM) Jenang Dodol Bu Hartini yang disebabkan oleh kebijakan persediaan yang diterapkan perusahaan sehingga mengakibatkan terjadinya peningkatan pada biaya pemesanan dan penyimpanan. Penelitian ini betujuan untuk mengevaluasi tingkat efisiensi daripada kebijakan persediaan yang dilakukan perusahaan serta membandingkan kebijakan tersebut dengan metode Economic Order Quantity (EOQ) dan Just In Time (JIT) sebagai alternatif pengendalian persediaan. Penerapan kedua metode tersebut diharapkan mampu mengoptimalkan efisiensi biaya persediaan dan menunjang keberlangsungan operasional perusahaan. Penelitian ini menerapkan pendekatan deskriptif kuantitatif dengan menggabungkan sumber data primer dan sekunder, yang diperoleh melalui wawancara, observasi, dan dokumentasi. Hasil analisis membuktikan bahwa kebijakan sistem persediaan yang diterapkan oleh perusahaan menghasilkan total biaya persediaan yang lebih tinggi jika dibandingkan dengan metode Economic Order Quantity (EOQ) maupun Just In Time (JIT). Total biaya persediaan yang diperoleh melalui metode Economic Order Quantity (EOQ) sebesar Rp 472.441, sedangkan metode Just In Time (JIT) menghasilkan biaya sebesar Rp332.039. Nilai tersebut lebih rendah dibandingkan biaya persediaan yang berdasar pada kebijakan perusahaan yang mencapai Rp 2.100.000. Dengan demikian, penerapan metode Economic Order Quantity (EOQ) dan Just In Time (JIT) mampu meningkatkan efisiensi biaya persediaan bahan baku pada UMKM Jenang Dodol Bu hartini, dengan metode Just In Time (JIT) terbukti sebagai pendekatan yang paling efisien.
PENERAPAN ALGORITMA FISHER-YATES PADA GAME EDUKASI MATEMATIKA UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS SD
Perkembangan teknologi digital memicu transformasi metode instruksional matematika di sekolah dasar. Namun, mayoritas siswa kelas 1-3 SD Negeri Wanasari 12 Cibitung menganggap matematika sebagai materi yang rumit dan menjemukan, sehingga memicu penurunan minat belajar. Siswa kerap kesulitan menguasai operasi dasar seperti penjumlahan bersusun, perkalian, dan pembagian. Studi ini bertujuan merancang game edukasi matematika interaktif guna mendongkrak ketertarikan, motivasi, dan pemahaman konsep siswa. Aplikasi dikembangkan menggunakan Unity Engine untuk platform Windows melalui kerangka Multimedia Development Life Cycle (MDLC). Metode Algoritma Fisher-Yates diimplementasikan guna mengacak urutan soal secara dinamis agar tidak mudah ditebak. Hasil riset menyajikan produk game fungsional yang valid berdasarkan kuesioner yang disebar ke para siswa setelah mereka menggunakan game math ini adalah 87%. Siswa terbantu memahami dalam mengerjakan soal matematika.
PERBANDINGAN KINERJA METODE STACKING ENSEMBLE DAN NAÏVE BAYES DALAM KLASIFIKASI PENYAKIT ALZHEIMER BERBASIS DATA KLINIS
Alzheimer's disease is the main reason people develop dementia around the world. However, diagnostic methods that use medical imaging, like MRI scans, are usually costly and not easily available, especially in hospitals and basic healthcare centers. This study is focused on creating and evaluating different classification models using clinical data, and it compares how well the Stacking Ensemble method and the Naïve Bayes method perform. The Stacking Ensemble model uses Random Forest, XGBoost, and Support Vector Machine as the base models, and Logistic Regression acts as the meta-learner.Gaussian Naïve Bayes is also used as the baseline model. The dataset came from Kaggle and includes 2,149 patient records with 32 predictor features after some cleaning and preparation. The data were split into 80% for training and 20% for testing using a stratified method. The model's performance was checked on the testing data and confirmed using 5-fold stratified cross-validation. The experimental results show that the Stacking Ensemble method got an accuracy of 94.65%, precision of 93.88%, recall of 90.79%, and an F1-score of 92.31%. These results do much better than the Naïve Bayes method, which only reached an accuracy of 77.21%. Moreover, cross-validation showed that the proposed model is reliable, achieving an average accuracy of 95.11% for the Stacking Ensemble. These results show that the Stacking Ensemble approach works better and more reliably than the Naïve Bayes model when classifying Alzheimer's disease based on clinical data.
Penerimaan Siswa Sekolah Berbasis Jarak Menggunakan Algoritma Haversine
New student admission is a critical process in the education system that requires fairness, objectivity, and transparency, particularly in domicile-based selection mechanisms. This study aims to design and implement a distance-based student admission system using the Haversine algorithm at SMK Metland Cibitung. The research method applies an applied quantitative approach with a system development framework utilizing geographic coordinate data (latitude and longitude) to calculate the distance between applicants’ residences and the school location. The Haversine algorithm is used to compute distances based on the great-circle distance concept, providing higher accuracy compared to conventional estimation-based approaches. The results show that the system is able to automatically calculate distances and rank applicants based on proximity with consistent outcomes. The implementation improves selection efficiency and supports the principles of objectivity and transparency in the Student Admission System (SPMB). Therefore, the Haversine algorithm is an effective solution for developing a distance-based student admission system.
Factor Influencing University Students’ Investment Interests: A Correlational Study
The trend toward digital technology modernization has increased students’ investment interests. However, this has not been accompanied by adequate financial literacy, which could potentially lead to poor decision making. This quantitative study using a correlation analysis method, aims to analyze the influence of lifestyle, social environment, allowance, and self control on the motivation to invest among students at the faculty of economics and business Bumigora University. The population for this study consisted of 1.119 students and the sample size was determined using the Slovin formula to be 291 participants. Primary data obtained through a digital questionnaire was analyzed using multiple linear regression. The data analysis indicates that lifestyle, social environment, allowance, and self control have a positive significant on students investment interests. Collectively, these factors also act as strong determinants of students motivation in investing. The results of this study have practical implications for educational institutions in developing more targeted financial curricula, as well as for policymakers in developing more prudent and responsible investment initiatives.
The Influence of Financial Literacy, Financial Attitude, and Self-Control on Financial Management Behavior among Students of Slamet Riyadi University
Students' financial independence is rarely tested through major decisions; it is more often revealed in how they handle their everyday small change. This research uses three elements that shape this independence—financial literacy, financial attitude, and self-control—as test variables, then explores the extent to which they shape the financial management behavior of students at the Faculty of Economics and Business, Slamet Riyadi University. A quantitative survey design was applied to 53 selected participants through purposive sampling, using a five-level Likert instrument (score 1 for Strongly Disagree to score 5 for Strongly Agree), and then processed using multiple linear regression on the IBM SPSS Statistics platform. Three main findings emerged from this test. First, financial literacy was shown to contribute a significant unidirectional effect, reflected by a coefficient of 0.384 at a significance level of 0.008. Second, financial attitude showed a similar pattern with a coefficient of 0.365 and a significance level of 0.013. Third, self-control also confirmed its contribution through a coefficient of 0.271 at a significance level of 0.002. When tested together, these three predictors formed a model that explained 61.3 percent of the variation in respondents' financial management behavior (Adjusted R Square = 0.613), a proportion large enough to leave little room for other factors outside the model. The practical implication is clear: financial knowledge needs to be nurtured alongside a healthy attitude and strong self-control, as the three only have their full impact when operating as a package, not as stand-alone elements.
Pengaruh Hedonic Value Dan Utilitarian Value Terhadap Minat Beli Konsumen Uniqlo dengan sikap Konsumen sebagai Mediasi
This study aims to analyze the influence of hedonic value and utilitarian value on purchase intention toward Uniqlo products in Indonesia, with consumer attitude as a mediating variable. Utilizing a causal quantitative approach, data were collected via questionnaires from 161 Uniqlo consumers through both offline and online channels. The data analysis methods include instrument validity and reliability tests, normality tests, multiple linear regression analysis, and the Sobel Test to evaluate the mediation effect. The results indicate that hedonic value, utilitarian value, and consumer attitude have a positive and significant influence on purchase intention. Consumer attitude was found to be the most dominant factor influencing purchase intention, with a regression coefficient value of 0.451. Simultaneously, this research model is able to explain 57.3% of the variation in consumer purchase intention. Furthermore, the Sobel Test results confirm that consumer attitude significantly functions as a partial mediator that optimizes the influence of hedonic value (Z = 2.357) and utilitarian value (Z = 3.518) on purchase intention. Practically, Uniqlo focus on building positive consumer attitudes to enhance purchase intention.
TINJAUAN PUSTAKA SISTEMATIS PERBANDINGAN ALGORITMA K-MEANS DAN DBSCAN PADA KLASTERISASI DATA LAYANAN PUBLIK
This study presents a systematic literature review comparing K-Means and DBSCAN in clustering public service data. The article adopts the PRISMA approach to make the review process systematic, transparent, and reproducible. Searches were conducted in Google Scholar, ScienceDirect, and IEEE Xplore using keywords related to K-Means, DBSCAN, clustering, and public service data. A total of 11,700 records were identified, 140 studies were retained as candidates after initial screening, and 30 studies were included in the final synthesis. The review shows that K-Means is often used because it is simple, fast, and efficient for structured data, while DBSCAN performs better for datasets containing noise, density variation, and irregular cluster shapes. In public service data, algorithm selection depends on data characteristics, analytical objectives, and parameter sensitivity.
PENGARUH MOTIVASI KERJA, DISIPLIN KERJA DAN KOMPETENSI KERJA TERHADAP PRODUKTIVITAS KERJA KARYAWAN
The retail sector in Indonesia is growing rapidly and is highly competitive; one example is Miniso, which operates 88 stores. To survive and more develope, businesses must improve their performance and productivity. Employees, as the company’s most valuable asset, are the driving force behind achieving high productivity, thereby ensuring the company’s goals are met. Factors that influence work productivity include work motivation, work discipline, and work competence. These three factors are fundamental elements that require serious attention from management. Work motivation is an internal or external drive that makes individuals more enthusiastic and innovative in their work, thereby increasing work productivity. Work discipline reflects an individual’s commitment and sense of responsibility in performing their duties. With strong discipline, employee performance improves, work quality increases, and productivity rises as a result. Job competencies refer to the abilities possessed by employees in the form of knowledge, skills, and work attitudes. Competencies are a key determinant of the quality of an employee’s work; strong competencies lead to strong performance, which in turn results in high productivity. This study aims to determine the influence of work motivation, work discipline, and work competence on employee performance. This study is a case study of Miniso employees at Central Park Mall in West Jakarta, with a sample size of 30 employees. The results show that, individually, work motivation, work discipline, and work competence significantly influence the work productivity of Miniso Central Park employees. Simultaneously, work motivation, work discipline, and work competence also influence the work productivity of Miniso Central Park employees.
ANALISIS DAMPAK CYBERCRIME DATA FORGERY DAN UU HUKUM PERLINDUNGAN KONSUMEN PADA METODE PEMBAYARAN BERBASIS DIGITAL QRIS
Era teknologi yang semakin canggih penggunaan metode pembayaran berbasis digital terutama Quick Response Code Indonesian Standard (QRIS) mengalami peningkatan yang sangat signifikan. Bank Indonesia dalam laporannya menyatakan tahun 2026 pengguna QRIS mencapai 63 Juta. QRIS sebagai standart pembayaran digital nasional menjadi tren pembayaran digital terutama dikalangan UMKM karena QRIS memberikan kemudahan dalam melakukan transaksi namun disisilain aplikasi QRIS memunculkan tantangan baru dalam dunia siber yakni cybercrime data forgery, sebuah tindakan kejahatan cyber yang melakukan penipuan data melalui aplikasi QRIS. Tingginya tingkat kejahatan yang terjadi dalam sistem pembayaran QRIS membutuhkan perlindungan hukum bagi penguna aplikasi. Penelitian ini bertujuan untuk mengeksplorasi berbagai indikasi cybercrime (kejahatan siber) data forgery pada sistem pembayaran berbasis QRIS serta menganalisis implementasi perlindungan hukum pada konsumen dalam pembayaran digital berbasis QRIS. Penelitian ini menggunakan Metode penelitian deskriptip dan yuridis normatif. Hasil penelitian menunjukkan Data forgery sebagai kejahatan siber melakukan berbagai metode penipuan melalui penggunaan stiker QR Code palsu, phishing melalui QR Code, hingga penipuan data transaksi. Kejahatan siber melalui QRIS Code terjadi dengan memanfaatkan ketidaktahuan dan ketidak hati-hatian pengguna. Kejahatan siber pada transaksi QRIS tidak hanya menimbulkan kerugian finansial tetapi juga berdampak terhadap penurunan kepercayaan masyarakat terhadap sistem pembayaran digital. Kejahatan siber data forgery menjadi tantang baru bagi regulator dan pemerintah dalam menjamin keamanan serta kepastian hukum dalam melindungi konsumen pengguna keuangan digital QRIS. Hingga saat ini undang-undang yang berlaku belum mengatur secara spesifik terkait tindakan penipuan berbasis QRIS. Keberadaan Undang-undang sejatinya harus mampu memberikan perlindungan dan kepastian hukum bagi para pengguna Aplikasi QRIS untuk bebas dari kejahatan siber data forgery. Hukum harus mampu mengimbangi perkembangan keuangan digital yang semakin inovatif.
SISTEM PENDUKUNG KEPUTUSAN PEMROSESAN ORDER CHEMICAL BERBASIS ANALISIS RISIKO MENGGUNAKAN METODE FUZZY LOGIC MAMDANI
Proses penetuan keputusan pemrosesan order chemical di PT. Sinarmas Indah Lestari masih dilakukan secara manual berdasarkan pertimbangkan pihak terkait sehingga berpotensi menghasilkan keputusan yang kurang konsisten. Kondisi tersebut menjadi tantangan karena perusahaan beroperasi tanpa safety stock dan memiliki keterbatasan cashflow, sehingga setiap keputusan pemrosesan order harus mempertimbangkan berbagai aspek risiko untuk meminimalkan kerugian operasional maupun finansial. Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan berbasis web menggunakan metode fuzzy logic mamdani untuk menghasilkan rekomendasi keputusan pemrosesan order secara lebih objektif, terstruktur, dan terukur. Pengembangan sistem menggunakan model waterfall yang meliputi analisis kebutuhan, perancangan, implementasi menggunakan PHP dan MySQL, pengujian serta implementasi sistem. Metode fuzzy mamdani mengolah empat variabel input, yaitu jenis chemical, nilai order, risiko pembayaran, dan urgensi pelanggan, melalui enam belas basis aturan. Proses inferensi dilakukan melalui tahapan fuzzifikasi, evaluasi aturan, agregasi, dan defuzzifikasi menggunakan metode weighted average untuk menghasilkan rekomendasi berupa kategori proses normal dan langsung proses. Hasil pengujian menunjukkan bahwa keluaran sistem sesuai dengan perhitungan manual, sedangkan fungsional menggunakan metode blackbox testing menunjukkan seluruh fungsi sistem berjalan sesuai dengan yang diharapkan. Dengan demikian, sistem yang dikembangkan mampu mendukung pengambilan keputusan secara lebih objektif, konsisten, dan terdokumentasi serta membantu meminimalkan risiko operasional dan finansial perusahaan.
PERANCANGAN SISTEM INFORMASI KEPEGAWAIAN BERBASIS WEB MENGGUNAKAN ALGORITMA ADVANCED ENCRYPTION STANDARD (AES)-256 DI PT BERSIH SUKSES SEJAHTERA
The employee data management at PT Bersih Sukses Sejahtera is still carried out using Microsoft Excel in spreadsheet form, which has the potential to cause recording errors, data duplication, delays in information retrieval, and increase the risk of employee data leakage and loss. This study aims to design an integrated web-based employee information system by implementing the Advanced Encryption Standard (AES)-256 security algorithm to improve data management security. The method used is Waterfall which includes the stages of planning, requirement analysis, design, implementation, testing, deployment, and maintenance. Data collection techniques are carried out through observation, interviews, and literature studies, while the research data includes employee data, positions, departments, training, and educational history. The system was developed using the PHP programming language and MySQL database. The results of the study show that the system is able to integrate employee data management in one platform, while the implementation of the AES-256 algorithm successfully secures URL parameters in the employee data module through encryption and decryption processes. Testing using the Black Box Testing method on 15 features obtained a 100% success rate, so that all system functions run according to user needs. Thus, the developed system is able to support structured personnel data management while increasing information security and confidentiality through the application of the AES-256 algorithm.
PERANCANGAN SISTEM PRESENSI BERBASIS WEB MENGGUNAKAN ALGORITMA HAVERSINE PADA PT MITRA PERKASA EKATAMA
The development of information technology encourages companies to implement digital systems to support administrative management, including employee attendance processes. PT Mitra Perkasa Ekatama still uses fingerprint machines that have limitations in monitoring the attendance of employees who work outside the office or project locations and do not yet support attendance location validation. This study aims to design a web-based employee attendance system by implementing the Haversine Algorithm as a method for calculating the distance between the user's location and the company's location to validate attendance. The system development method used is Waterfall which includes the stages of planning, needs analysis, design, implementation, testing, implementation, and system maintenance. The system was built using PHP, HTML, CSS, JavaScript, MySQL, and utilizes Global Positioning System (GPS) technology. The Haversine Algorithm is used to calculate the distance based on latitude and longitude coordinates so that the system can determine whether the user is within the permitted attendance radius. The results of the study show that the system successfully integrates login features, employee data management, positions, departments, attendance entry, attendance departure, permit applications, leave applications, and attendance recapitulation in one web-based application. Testing using the Black Box Testing method shows that all system functions run well with a success rate of 100%. The resulting system is able to help companies in automatically validating attendance locations and improving the management of employee attendance data in an integrated manner
ANALISIS DIVIDEND PAYOUT RATIO DAN DEBT TO EQUITY RATIO TERHADAP KINERJA KEUANGAN PERUSAHAAN FARMASI YANG TERDAFTAR DI BURSA EFEK INDONESIA (BEI) TAHUN 2021 – 2023
This study analyzes the effect of the Dividend Payout Ratio (DPR) and Debt to Equity Ratio (DER) on the financial performance of pharmaceutical companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2023 period. The population consists of 13 companies, with a sample of 11 companies meeting the criteria. This research employs a quantitative approach with a documentation technique, collecting secondary data from annual financial reports published on www.idx.co.id. Data analysis was conducted using classical assumption tests, multiple linear regression, correlation analysis, t-test, and F-test with the assistance of SPSS version 20. The results indicate that DPR does not significantly affect Return on Equity (ROE), with a t-value of -1.083 < t-table 2.04227 and a significance level of 0.287 > 0.050. An increase in DPR tends to decrease ROE, as dividends reduce reinvested earnings. Meanwhile, DER has a negative effect on ROE, with a t-value of -18.039 > t-table 2.04227 and a significance level of 0.000 < 0.050. High reliance on debt can lower profitability and increase financial risk. Simultaneously, DPR and DER significantly affect ROE, with an F-value of 168.456 > F-table 3.32 and a significance level of 0.000 < 0.05. DPR reflects profit distribution policies, while DER influences capital structure, providing insights into corporate financial management strategies to maximize profitability.
Sistem Informasi Persediaan Barang Elektronik Menggunakan Framework Laravel pada The Habibie Center Jakarta
Di era transformasi digital global, sistem informasi menjadi faktor penting dalam menunjang efektivitas pengelolaan data pada suatu instansi. The Habibie Center Jakarta menghadapi permasalahan pengelolaan persediaan barang elektronik yang masih dilakukan secara manual menggunakan Microsoft Excel, mengakibatkan keterlambatan pencatatan, kesalahan data, sulitnya monitoring stok secara real-time, dan lemahnya sistem monitoring sehingga beberapa barang elektronik dilaporkan hilang pada saat pelaksanaan kegiatan. Penelitian ini bertujuan membangun sistem informasi persediaan barang elektronik berbasis web menggunakan framework Laravel dengan metode pengembangan Waterfall (SDLC). Sistem mencakup tujuh modul utama: pengelolaan data barang, peminjaman dan pengembalian multi-barang dengan notifikasi email otomatis (WelcomeMail dan ReturnConfirmationMail via SMTP), pencatatan kerusakan terintegrasi dengan DB::transaction, penjadwalan maintenance dengan soft delete Laravel, import data massal dari PDF menggunakan Smalot PdfParser, ekspor laporan PDF (DomPDF) dan Excel (Maatwebsite), serta role-based access control (RBAC) tiga tingkat. Evaluasi menggunakan Black Box Testing pada 24 test case menunjukkan hasil Pass 100%. Sistem terbukti mampu menghilangkan keterlambatan pencatatan manual, menyediakan monitoring stok real-time, dan menghasilkan laporan terstruktur yang mendukung pengambilan keputusan pengelola The Habibie Center.
ANALISIS USABILITY APLIKASI E-RAPOR MENGGUNAKAN METODE SYSTEM USABILITY SCALE (SUS) PADA SEKOLAH DASAR NEGERI PINANG RANTI 05 PAGI
The e-Rapor application is used at SDN Pinang Ranti 05 Pagi to support the recording and management of student learning outcomes. However, its usability has not been formally evaluated. This study evaluates the usability of the application using the System Usability Scale (SUS). A quantitative approach was applied by distributing a SUS questionnaire through Google Forms to 20 respondents, including teachers, the principal, and the school operator. The responses were analyzed using the SUS scoring method and descriptive statistics. The evaluation produced an average SUS score of 73.12, which is classified as Acceptable with a Grade C rating. The results suggest that users generally find the application easy to use and helpful in carrying out student assessment activities. Most respondents gave positive responses to the application's functionality and interface consistency. Nevertheless, several aspects, including navigation, workflow, and user guidance, still require improvement to make the application easier to operate and to provide a better user experience.
ANALISIS PENGALAMAN PELANGGAN DALAM RESERVASI SALON KECANTIKAN MELALUI WHATSAPP BUSINESS PADA LIA SALON JAKARTA PUSAT
Penelitian ini bertujuan mendeskripsikan pengalaman pelanggan dalam menggunakan WhatsApp Business sebagai media reservasi di Lia Salon Jakarta Pusat, menganalisis komunikasi dan respons pelayanan, serta mengidentifikasi kendala selama reservasi. Penelitian menggunakan metode kualitatif dengan paradigma interpretatif. Data diperoleh melalui wawancara, observasi, dan dokumentasi terhadap enam pelanggan dan satu pemilik Lia Salon yang dipilih secara purposive. Analisis data menggunakan model Miles, Huberman, dan Saldaña serta triangulasi sumber dan teknik. Hasil penelitian menunjukkan bahwa WhatsApp Business memudahkan reservasi, akses informasi layanan, dan komunikasi pelanggan. Kendala utama adalah keterlambatan respons ketika salon sedang ramai karena komunikasi masih dikelola langsung oleh pemilik. Penelitian menyimpulkan bahwa WhatsApp Business memberikan pengalaman reservasi yang lebih mudah, fleksibel, dan efektif
Manajemen Proyek Peluncuran Aplikasi e-Lhu BPOM Berdasarkan Praktik ITIL 4
This study analyzes project management governance during the deployment phase of the e-Lhu application at the National Agency of Drug and Food Control (BPOM) in East Java. Although the application has successfully digitized laboratory data, the transition of new features into the operational environment still faces technical and procedural challenges. Using the ITIL 4 framework, this research evaluates five key practices: Deployment Management, and Release Management. The method employed is descriptive qualitative through participant observation and in-depth interviews. The results indicate that while BPOM demonstrates excellent bureaucratic agility in Change Enablement, a critical gap exists in Knowledge Management, creating a single point of failure risk. Furthermore, the absence of a structured rollback mechanism in Deployment Management increases the risk of system fatality during errors. This study recommends standardizing documentation as a release requirement (Definition of Done) and institutionalizing system recovery plans to ensure the continuity of laboratory testing services.
HETEROGENITAS SPASIAL PADA PREDIKSI HARGA RUMAH MULTI-KOTA
Prediksi harga rumah menggunakan model stacking ensemble umumnya dievaluasi secara agregat pada keseluruhan data uji, sehingga berpotensi menyembunyikan variasi performa yang sesungguhnya terjadi antar wilayah geografis. Penelitian ini menganalisis performa model Stacking Ensemble yang menggabungkan XGBoost, Random Forest, dan CatBoost dengan meta learner Ridge Regression pada dataset 100.000 rumah di tujuh kota Indonesia, dengan penekanan pada evaluasi yang terdekomposisi per kota dan analisis faktor penyebab disparitasnya. Hasil evaluasi agregat menunjukkan Stacking Ensemble mencapai performa terbaik dengan MAE sebesar Rp 1.106.456.898 dan R2 sebesar 0,8458, namun uji Wilcoxon signed rank menunjukkan keunggulan tersebut hanya signifikan secara statistik dibandingkan Random Forest, tidak terhadap CatBoost maupun XGBoost. Ketika performa didekomposisi per kota, ditemukan disparitas MAE lebih dari 2,5 kali lipat antara kota dengan performa terbaik dan terburuk, disertai variasi signifikansi statistik yang tidak seragam antar wilayah. Analisis lebih lanjut menunjukkan disparitas ini lebih berkaitan dengan variasi harga yang lebih besar pada kota tertentu dibandingkan keterbatasan jumlah data pelatihan. Analisis SHAP turut mengindikasikan kontribusi fitur lokasi yang cenderung lebih besar pada kota dengan performa lebih rendah, meskipun pola ini tidak berlaku seragam di seluruh kota yang diuji. Temuan ini menegaskan pentingnya evaluasi granular per wilayah dalam penelitian prediksi harga rumah multi kota.
IMPLEMENTASI METODE WEIGHTED RANKING PADA KELAYAKAN PENERIMA BANTUAN PKH DI KANTOR CAMAT KUTALIMBARU
Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan berbasis website guna menentukan kelayakan penerima bantuan Program Keluarga Harapan (PKH) di Kantor Camat Kutalimbaru dengan menerapkan metode Weighted Ranking Technique (WRT). Hambatan utama pada sistem berjalan meliputi data calon penerima yang kurang akurat, kriteria penilaian yang belum terstandarisasi, serta proses seleksi manual yang bersifat subjektif sehingga rentan salah sasaran. Sebagai solusi, sistem informasi ini dibangun memanfaatkan framework Laravel 10 dan basis data MySQL. Sistem mengolah data penilaian berdasarkan enam kriteria utama: pendapatan keluarga, jumlah tanggungan, kondisi tempat tinggal, status pekerjaan kepala keluarga, usia kepala keluarga, dan keberadaan anak yang bekerja. Hasil penelitian menunjukkan bahwa metode WRT berhasil melakukan pemeringkatan data alternatif secara objektif. Dari total 54 data keluarga yang diuji, alternatif A1 memperoleh skor tertinggi sebesar 0,1780 dan menjadi prioritas utama penerima bantuan. Implementasi sistem ini memberikan proses verifikasi data yang transparan, akurat, dan akuntabel bagi pihak kecamatan.
SISTEM INFORMASI MANAJEMEN RISIKO UNTUK OPTIMALISASI PENGELOLAAN PROYEK KONSTRUKSI DI DINAS PUPR PROVINSI SUMATERA UTARA
Pengelolaan risiko proyek konstruksi di Dinas Pekerjaan Umum dan Penataan Ruang (PUPR) Provinsi Sumatera Utara selama ini masih bertumpu pada proses manual berbasis dokumen fisik seperti Rencana Keselamatan Konstruksi (RKK), yang hanya menyoroti aspek Keselamatan dan Kesehatan Kerja (K3) tanpa mendokumentasikan kategori risiko lain secara sistematis. Untuk mengatasi keterbatasan tersebut, penelitian ini merancang dan membangun Sistem Informasi Manajemen Risiko (SIMR) berbasis web dengan mengadopsi kerangka ISO 31000:2018, dikembangkan menggunakan metode Waterfall serta teknologi PHP, framework Laravel, dan MySQL. Sistem melibatkan tiga peran pengguna (Admin, Unit Pemilik Risiko, dan Auditor) yang mencakup keseluruhan siklus manajemen risiko, mulai dari identifikasi, analisis, dan evaluasi, hingga mitigasi, pemantauan, dan pelaporan. Implementasinya berhasil menyatukan 50 data risiko nyata dari proyek konstruksi jalan dan jembatan di UPTD PUPR Medan ke dalam satu platform digital terpusat, meningkatkan efisiensi pengelolaan risiko sebesar 60%, menstandarisasi proses sesuai ISO 31000:2018, serta memperkuat akurasi penilaian dan akuntabilitas melalui dokumentasi digital dan audit trail. Pengujian black-box pada tiga peran pengguna menunjukkan tingkat keberhasilan fungsional sebesar 100%, sehingga sistem ini terbukti mampu menjadi solusi terintegrasi bagi optimalisasi manajemen proyek konstruksi.