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All Journal JMM (Jurnal Masyarakat Mandiri) INTECOMS: Journal of Information Technology and Computer Science JURIKOM (Jurnal Riset Komputer) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH INFOKUM Jurnal UNITEK Jurnal Pengabdian Masyarakat Indonesia Jurnal Ekonomi Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Bulletin of Information Technology (BIT) Jurnal Minfo Polgan (JMP) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal UMKM, Manajemen dan Akuntansi (JUMA) Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan The Journal of Information Technology, Computer Science, and Electrical Engineering
Sri Wahyuni
Faculty Of Science And Technology, Program Study Computer System, Universitas Pembangunan Panca Budi, Medan, Nortth Sumatera, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Public Health Social Sciences Other

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Data Mining Prediksi Minat Customer Penjualan Handphone Dengan Algoritma Apriori Sri Wahyuni; Indri Sulistianingsih; hermansyah; Eko Hariyanto; Oki Cindi Veronika Lumbanbatu
JURNAL UNITEK Vol. 14 No. 2 (2021): Juli - Desember
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/unitek.v14i2.243

Abstract

Mengetahui minat customer pada suatu jenis produk merupakan kunci suskses dari sebuah bisnis. dari data yang tersimpan pada data penjualan dapat diolah dan diimplementasi untuk mengetahui pola minat item customer, hal ini dapat meminimalisir penumpukan stok barang yang kurang diminati dan tidak kehabisan barang pada produk yang diminati. Data Mining dapat menjadi solusi. Penelitian ini menganalisis data informasi penjualan handphone yang bersumber dari database sistem informasi transaksi penjulanan handphone menggunakan data mining algoritma apriori. Uji data menggunakan aplikasi data mining weka dalam menemukan hubungan pola penjualan handphone antar item. Proses pengolahan data dimulai praprocesing dengan memilih variable data kemudian menemukan nilai spot dari tiap item set handphone dan kombinasi antara jenis handphone dari hasil pencarian nilai spot dan kombinasi antara jenis handphone kemudian ditemukan nilai confidence dalam tiap kombinasi. Kombinasi yang memenuhi nilai minimum spot dan minimum confidence akan menjadi sebuah aturan asosiasi. Aturan asosiasi yang dihasilkan menjadi informasi jenis handphone yang paling banyak terjual selama 1 bulan sampai 2 tahun. Hasilnya di peroleh knowlwge jenis handphone yang paling diminati dan hubungan antara jenis atau tipe hanphone tersebut. Knowledge tersebut dapat dijadikan dasar menentukan stok jenis handphone
THE INFLUENCE OF WORK DISCIPLINE, MOTIVATION AND COMPETENCE ON EMPLOYEE PERFORMANCE WITH JOB SATISFACTION AS AN INTERVENING VARIABLE AT THE NATIONAL NARCOTICS AGENCY (BNN) LANGKAT REGENCY Sri Wahyuni; Yohny Anwar
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 3 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i3.4050

Abstract

This study aims to analyze the influence of work discipline, motivation, and competence on employee performance with job satisfaction as an intervening variable at the National Narcotics Agency (BNN) of Langkat Regency. The independent variables in this study are work discipline, motivation, and competence; the dependent variable is employee performance; while the intervening variable is job satisfaction. This study uses a quantitative method with the Partial Least Squares – Structural Equation Modeling (PLS-SEM) approach through the SmartPLS application. The research sample was 39 respondents selected using a purposive sampling technique. The research instrument was a questionnaire with a Likert scale. Data analysis was carried out through evaluation of the outer model (validity and reliability) and the inner model (direct and indirect hypothesis testing). The results showed that: Work Discipline (X1) has a positive effect on Job Satisfaction (Z), with a path coefficient value (Original Sample column) of 0.173, and is significant, with a P-Value = 0.012 (Hypothesis Accepted). Work Discipline (X1) has a positive effect on Employee Performance (Y), with a path coefficient value (Original Sample column) of 0.235, with P-Value = 0.002 (Hypothesis Accepted). Job Satisfaction (Z) has a positive effect on Employee Performance (Y), with a path coefficient value (Original Sample column) of 0.942, with P-Value = 0.000 (Hypothesis Accepted). Competence (X3) has a positive effect on Job Satisfaction (Z), with a path coefficient value (Original Sample column) of 0.466, with P-Value = 0.000 (Hypothesis Accepted). Competence (X3) has a positive effect on Employee Performance (Y), with a path coefficient value (Original Sample column) of 0.472 with P-Value = 0.000 (Hypothesis Accepted). Motivation (X2) has a positive effect on Job Satisfaction (Z), with a path coefficient value (Original Sample column) of 0.502, with a P-Value = 0.000 (Hypothesis Accepted). Motivation (X2) has a positive effect on Employee Performance (Y), with a path coefficient value (Original Sample column) of 0.458, with a P-Value = 0.000 (Hypothesis Accepted). Employee Performance (Y) significantly mediates the relationship between Work Discipline (X1) and Job Satisfaction (Z), with a P-Value = 0.017 < 0.05 (Mediation Hypothesis Accepted). Employee Performance (Y) significantly mediates the relationship between Competence (X3) and Job Satisfaction (Z), with a P-Value = 0.000 < 0.05 (Mediation Hypothesis Accepted). Employee Performance (Y) significantly mediates the relationship between Motivation (X2) and Job Satisfaction (Z), with P-Value = 0.000 < 0.05 (Mediation Hypothesis Accepted). The implication of this study is the need for the management of the Langkat Regency BNN to continue to improve work discipline, work motivation, and employee competence, as well as create a work environment that supports job satisfaction, so that employee performance can be improved sustainably.
Pengaruh Debt Default dan Financial Distress Terhadap Opini Audit Going Concern Pada Perusahaan Subsektor Makanan dan Minuman Di BEI Wan Fachruddin; Sri Wahyuni; Handriyani Dwilita
Jurnal UMKM, Manajemen dan Akuntansi Vol. 2 No. 1: Agustus 2025
Publisher : Universitas Battuta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh debt default dan financial distress secara parsial terhadap opini audit going concern pada perusahaan yang tergolong dalam subsektor makanan dan minuman yang terdaftar di Bursa Efek Indonesia. Penelitian ini termasuk dalam kategori penelitian asosiatif dengan pendekatan kuantitatif. Data yang digunakan merupakan data sekunder yang diperoleh dari laporan keuangan tahunan yang telah dipublikasikan melalui situs resmi Bursa Efek Indonesia. Populasi dalam penelitian ini terdiri atas 75 perusahaan dari subsektor makanan dan minuman yang terdaftar di Bursa Efek Indonesia. Pemilihan sampel dilakukan dengan menggunakan teknik purposive sampling, sehingga diperoleh 26 perusahaan sebagai sampel penelitian. Dengan demikian, total data observasi yang dianalisis sebanyak 104. Hasil penelitian menunjukkan bahwa secara parsial debt default dan financial distress tidak memiliki pengaruh yang signifikan terhadap opini audit going concern.
Analysis of Accounting Information Systems and E-Marketing for MSMEs in Pari Village Serdang Bedagai Noviani; Hernawaty Hernawaty; Sri Wahyuni; Miftahurrahman Sinaga
Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan Vol. 5 No. 4 (2024): Oktober
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/emak.v5i4.2131

Abstract

Micro, Small and Medium Enterprises (MSMEs) are business sectors that consistently develop in the national economy. This research was conducted on MSME actors in the village of Kota Pari Serdang Bedagai, especially palm sugar business actors. This study aims to analyse accounting information systems and e-marketing for MSMEs in Kota Pari Village, Serdang Bedagai. This type of research is descriptive using a qualitative approach. Data analysis techniques used in this study include observation, interviews, and documentation. The results of this study are that MSMEs in Kota Pari Serdang Bedagai village have not carried out Accounting Information Systems and e-marketing properly. Bookkeeping records still use notebooks whose contents are only receipts and expenses. Marketing of brown sugar in MSMEs in Kota Pari village Serdang Bedagai has also not used an e-marketing system. Marketing of brown sugar products generally still runs traditionally, namely by word of mouth, the marketing channels carried out are only from producers to collector traders. Their obstacle is the lack of knowledge about e-marketing due to the level of education and lack of socialisation about the e-marketing system. From the results of research and discussion, it is known that the level of education affects the use of accounting information systems and e-marketing.
Analisis Sentimen Analisis Sentimen Publik Terhadap Pariwisata Aceh di Media Sosial X Menggunakan Algoritma Naive Bayes Classifier Susilawati Yahya; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1700

Abstract

Aceh has been synonymous with negative perceptions among people outside the province. This is due to the prolonged armed conflict and the devastating tsunami in 2004. Despite these challenges, Aceh possesses abundant potential for tourism, including natural attractions, historical sites, cultural arts, and religious tourism. However, negative perceptions continue to influence tourists' decisions to visit Aceh. Therefore, this study aims to analyze public sentiment or public opinion towards Aceh's tourism using the Naive Bayes algorithm on the X (Twitter) social media platform. Data for this study was collected from tweets on X (Twitter) using the keyword "Aceh tourism" and then underwent several data pre-processing stages to improve data quality, including text cleaning, case folding, word normalization, tokenization, stop word removal, and stemming. Afterward, the Naive Bayes algorithm was applied to classify tweet sentiment into positive and negative categories. Model evaluation was conducted using a confusion matrix, accuracy, and classification report. The results showed that Naive Bayes performed well in classifying public sentiment with an accuracy of 81%. This analysis indicates that public perception towards Aceh's tourism has begun to shift positively, presenting a promising opportunity for the future development of Aceh's tourism sector.
Analisis Data Mining Dalam Pemilihan Smartphone dan Klasifikasi di Berbagai Perangkat Menggunakan Random Forest Ananda Aulia; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1703

Abstract

Abstract− Smartphone technology continues to develop rapidly, driving the need for effective analysis methods to assist users in selecting devices that suit their needs. This research aims to implement data mining using the Random Forest method in the process of selecting smartphones and classifying devices based on their technical specifications. The Random Forest method was chosen because of its reliable ability to handle data with a large number of attributes, produce an accurate classification model, and minimize the risk of overfitting. The dataset used includes technical specifications of various smartphones, such as camera resolution, chipset, RAM capacity, screen resolution, and support for 4K video recording. The research process involved data collection, pre-processing to handle missing values ​​and data transformation, as well as model training using the Random Forest algorithm.  The research results show that the Random Forest method is able to classify devices with high accuracy, helping users determine smartphones that meet their criteria, such as support for 4K video recording and overall performance. Additionally, this research provides insight into the importance of certain attributes in smartphone selection. Thus, implementing data mining using Random Forest can be an effective solution in supporting data-based decision making in the field of consumer technology. Keywords: Data Mining, Random Forest, Smartphone, Classification, Technical Specifications
Optimasi Strategi Penjualan Am2000 Tirtamart Dengan Algoritma Apriori Untuk Mengidentifikasi Produk Favorit Pelanggan Bambang Sugito; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1707

Abstract

The retail industry faces increasing competition, and to survive, companies need to understand customer purchasing behavior and optimize their sales strategies. One effective approach is the use of data mining to analyze sales data and identify purchasing patterns. This study aims to optimize the sales strategy of Toko AM2000 by applying the Apriori algorithm to identify the most popular products among customers. The data used includes sales transactions from January to September 2024, with a total of 1,000 transactions and 10 attributes. The results of the analysis using the Apriori algorithm show a significant association between the products "Water Softener" and "Filter Tank," although the support value obtained, which is 20.4%, does not meet the minimum support threshold of 30%. However, the confidence value of 80.6% indicates a high likelihood that customers who purchase "Water Softener" also buy "Filter Tank." This suggests that Toko AM2000 should focus its marketing strategies on promoting these two products. To improve the effectiveness of the analysis, it is recommended to lower the minimum support value, increase the number of transactions, and consider using other algorithms, such as K-means. This study provides valuable insights for business decision-making and the enhancement of Toko AM2000's marketing strategy.
Analysis Of Public Sentiment Towards The Corruption Eradication Commission On Twitter Siti Nurhaliza Sofyan; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1711

Abstract

The Corruption Eradication Commission (KPK) is a state institution in Indonesia which was formed to eradicate corruption. The Corruption Eradication Committee (KPK) [1]has the main task of carrying out investigations, inquiries and prosecutions of criminal acts of corruption. This institution is independent and free from the influence of any power in carrying out its duties and authority [2]. This research explores the analysis of Indonesian people's sentiment towards the KPK in the current situation such as arrests for corruption and the policies and actions carried out by the KPK. Sentiment analysis used in the journal with data obtained from Twitter data and using Orange Data Mining, with multilingual sentiment analysis techniques to analyze Indonesian people's sentiment towards the KPK agency. The results of sentiment analysis are visualized through box plots and scatter plots, which aim to classify Twitter users based on their emotional responses. The findings of this research provide valuable insight into the landscape of sentiment surrounding the Corruption Eradication Commission's bicycles, as well as providing sustainable benefits and are expected to be used as material for evaluating the government's role. Data totaling 300 tweets were processed using text mining techniques in the Orange Data Mining application [3][4]. This technique consists of several stages of text processing, namely transformation, filtering, and tokenization. The text processing results are extracted via wordcloud to find out the features of words that are often discussed by the public. After that, sentiment analysis was carried out to determine public opinion regarding the KPK institution based on positive, negative and neutral categories [5], [6]
Penerapan Algoritma Apriori untuk Optimasi Strategi Penjualan Berdasarkan Analisis Pola Pembelian di Torsa Cafe Anzas Ibezato Zalukhu; Dewi Sartika; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1715

Abstract

This study aims to analyze consumer purchasing patterns at Torsa Café using data mining methods with the Apriori algorithm to discover association rules between products that are frequently purchased together. In facing the increasingly competitive business environment in the food and beverage industry, understanding consumer purchasing behavior becomes key to enhancing marketing and operational strategies. This research uses sales transaction data from October 2024, consisting of 31 transactions with a total of 129 items. The analysis process begins with data collection and normalization of transaction data, followed by the application of the Apriori algorithm to calculate the support and confidence values of items in the transactions. The analysis results show several items with high support levels, such as "Sanger Espresso", "Avocado Cappuccino Torsa", and "Kopi Susu Torsa", with support values above 30%. Additionally, product combinations frequently purchased together, such as Kopi Tancap with Redvelvet, Macchiato, Frappucino, and Kopi Susu Torsa, can serve as the basis for promotions or more efficient stock management. These findings provide valuable insights for Torsa Café management to determine product placement strategies, raw material stock management, and design more targeted promotions based on the identified purchasing patterns. Therefore, the results of this study are expected to improve operational efficiency and enhance Torsa Café’s competitiveness in the increasingly competitive market.
Analisa data Untuk Menentukan Kelulusan Proposal Penelitian Dosen internal STMIK Triguna Dharma Menggunakan Metode Analytical Hierarchy Proses (AHP) Ayu Ofta Sari Ayu; Sri Wahyuni
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1726

Abstract

he selection process for lecturer research proposals at STMIK Triguna Dharma is often faced with challenges in objective and transparent assessment. This is due to the high number of proposals submitted and the variety of criteria that need to be considered, such as scientific contribution, innovation, relevance and implementation potential. This research aims to develop a more objective selection model by applying the Analytical Hierarchy Process (AHP) method in determining the feasibility of lecturer research proposals. The AHP method is used because of its ability to break down complex problems into a hierarchical structure and calculate the priority weights of each assessment criterion. This research process begins with identifying the main criteria and sub-criteria, followed by collecting data from research proposals, expert interviews, and literature studies. Each criterion is evaluated through a pairwise comparison matrix to obtain objective priority weights. Next, all research proposals are assessed based on the weight of the criteria and ranked to determine the most feasible proposal. The research results show that the criteria for scientific contribution and relevance to institutional goals have the highest weight in the assessment, making them the main aspects in the proposal selection process at STMIK Triguna Dharma. With the AHP method, this research concludes that the proposal selection process can be carried out more systematically, transparently and fairly. The implementation of this model is expected to be able to help institutions fund research that is most relevant and has a significant impact in accordance with the campus' vision and mission. Keywords: Lecturer research; Analytical Hierarchy Process; Data analysis; Matrix; Ranking
Co-Authors Abdul Khaliq Abiyyu Ardani Ade Rizka Aditya Rizky Titin Ramadhana Ahmad Akbar Akhyar Lubis Alfira Mutiah A. Siregar Ananda Aulia Anzas Ibezato Zalukhu Aulia Akbar Ayu Ofta Sari Ayu Bambang Sugito Cendra Wadisman Darmeli Nasutioan Darmeli Nasution Dery Antoro Dewi Nurmasari Pane Dewi Sartika Dinda Rizki Putri Dini Julia Sari Eko Hariyanto Erna Budhiarti Nababan Fajar Chrisman Ziliwu Febry Nurandika Fikri Yolanda Handriyani Dwilita Hanifah Mutia Zaida Ningrum Amrul Heni Wulandari Heni Wulandari Hermansyah Hernawaty Hernawaty Irwan Syahputra Leni Marlina M.Praja Kelana Maya Macia Sari Mesra B Mhd Imam Maulana Miftahurrahman Sinaga Muhammad Iqbal Muhammad Rifai Sipayung Muhammad Zen Nabila Octabia Cahyandi Nadya Septiani Nadya Nelviony Parhusip Nida Syaida Tamba Noviani Nur Afifah Oki Cindi Veronika Lumbanbatu Prayoga Ramadhan Putra, Randi Rian Putri Ayu Aisyah Rahayu Mayang Sari Ricky Ramadhan Harahap Ruly Dwi Arista Satria Wira Yudha Siti Dewi Murni Siti Nurhaliza Sofyan Sugeng Pranoto Suherman Suherman Sulistianingsih, Indri Supina Batubara Susilawati Yahya Virdyra Tasril Wan Fachruddin Yohny Anwar