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Design Of A Debit And Credit Financial Information System Prototype Method Ami Abdul Jabar; Zulham Sitorus; Sipra Barutu; Nelviony Parhusip
Jurnal Info Sains : Informatika dan Sains Vol. 13 No. 03 (2023): Informatika dan Sains , Edition December 2023
Publisher : SEAN Institute

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

Abstract

The absence of an available financial information system makes it difficult to record financial records and prepare financial reports, making it difficult for company leaders to understand their company's financial condition and make decisions. The legal entity company which was founded in 2018 has not yet utilized technology in carrying out financial records and preparing financial reports, especially debits and credits. This research aims to design a debit and credit Financial Information System using the Prototype Method at PT Bangkit Mulya Prakoso Teknik.The results include relational database design, activity diagrams, use case diagrams, and interface displays. It is hoped that this system design can improve corporate financial governance, make a significant contribution, and become a role model for other companies facing similar challenges.
Analysis Of Item-Based Collaborative Filtering For Sales Of Processed Oil Palm Products Sitorus, Zulham; Sri Wahyuni, Meri; Rika Uli Samosir, Siska
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2195

Abstract

Abstract- The sales system for processed palm oil necessitates a recommendation system that offers product suggestions to users, facilitating their selection of sales items for processed palm oil products. This study used the Item-Based Collaborative Filtering approach, which identifies the similarity between items. The system will assess the rating of each item and compute the similarity value utilising the Pearson correlation-based similarity formula. Companies will exhibit greater interest in product sales that possess identical similarity values. This article presents recommendations for system development concerning processed products intended for the sale of technology-based items that employ item-based collaborative filtering methods. It specifies a recommended selling value for processed palm oil products, with a Mean Absolute Error (MAE) of 10.463126965591, derived from the equation 5/1, yielding a final result of -5. The execution of the sales suggestions for processed palm oil products indicates that the items with the highest similarity value calculations are i4 and i5. PT. Sugih Riesta Jaya employs the Item-Based collaborative filtering method to enhance sales of refined palm oil products, thereby facilitating sales assistance and providing the public with sales information and recommendations for essential refined palm oil products..
Sistem Pakar untuk Menentukan Konsentrasi Mahasiswa Prodi Sistem Komputer Menggunakan Metode Forward Chaining Boy Rizki Akbar; Muhammad Fahriza; , Fery Anugerah; Chelfina Utami; Laila Maghfirah; Rian Farta Wijaya; Zulham Sitorus
Jurnal Nasional Teknologi Komputer Vol 5 No 4 (2025): Oktober 2025
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v5i4.319

Abstract

Determining a concentration is one of the obligations for computer systems students because it has a direct impact on their careers and individual potential development. However, most students determine their concentration based on general perceptions without understanding their personal interests and talents, job trends, or even following their friends' choices. Therefore, this study aims to help students recognize their potential, interests, and abilities in choosing the right concentration. This study uses the Forward Chaining method, which is an expert system-based approach oriented towards factual data to draw conclusions and provide relevant recommendations. In its implementation, the system will process inputs in the form of interests, talents, and ability assessment results, then trace logical rules to determine the most suitable concentration. The final result of the research is expected to produce visual recommendations in the form of percentages, which show the level of compatibility between students' interests and talents with various concentration options. The system is expected to support a more objective, systematic, and data-driven academic decision-making process so that students can optimize their potential to the maximum.
Analisis Deteksi Kecurangan Ujian Online Dengan Sistem Pakar Berbasis Event Browser Tanpa Kamera : Studi Kasus Penyelenggara Olimpiade Sains Digniti Ade Surya Bakti Pane; Harmiati Bungsu Bangun; Astri Mutia Rahma; Erbin Sitorus; Rian Farta Wijaya; Zulham Sitorus
Jurnal Nasional Teknologi Komputer Vol 6 No 1 (2026): Januari 2026
Publisher : CV. Hawari

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Abstract

The implementation of online exams differs significantly from exams supervised directly by proctors. Participants' body movements and interactions can be easily read. Even with camera monitoring, participants can still easily switch browser tabs or open applications on their devices. On the other hand, camera-based proctoring solutions can also raise invasive privacy concerns. Furthermore, device limitations can hinder someone from taking the exam due to the lack of a camera, and bandwidth limitations can result in unstable connections during the exam. Sample log activity data from test participants for log_id ranges from 44790 to 46883, while the actions consist of fullscreen_exit, context_switch, standby_log, focus_return, fullscreen_enter, and devtools_open. The results and rules of this test have scores, with each result having an average value of 1, and the rules having an average value of 1-10. In this process, experts assess each detection result using a binary scheme: a score of 1 is given if the expert system's conclusion matches the expert's decision, and a score of 0 is given if the expert system's decision does not match the expert's decision. This study proposes an expert system framework with a cameraless forward chaining method running on the Google Chrome browser (desktop and Android) as decision support. The system utilizes browser event telemetry (visibility changes, fullscreen, standby) that aligns with existing policies, such as mandatory fullscreen mode, copy/paste blocking, and question blurring when exiting fullscreen or a visibility change occurs. This can generate an audit trail that can be audited by decision makers.
MEDAN SMART TOURISM INFORMATION SYSTEM BASED ON IOT AND ACO FOR ROUTE RECOMMENDATIONS AND VISITOR MANAGEMENT Septia Harliansyah; Muhammad Irfan Sarif; Zulham Sitorus; Eko Wahyudi
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 12 (2025): NOVEMBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v4i12.1553

Abstract

The abstract serves as a concise summary of your research paper, highlighting the essential components that provide readers with an overview of your work. It should effectively capture the key issues addressed, the primary objectives of the study, the methods utilized, and the significant results achieved. This summary must be written in a single cohesive paragraph, limited to a maximum of 200 words. Ensure to follow the formatting specifications: use Times New Roman font, size 11, with single spacing, and present it in italics. The goal is to engage the reader while successfully conveying the importance and impact of your findings.
Sistem Pendukung Keputusan Penentuan Calon Ketua OSIS pada SMK Swasta Dwitunggal 2 Menggunakan Metode Simple Additive Weighting Zai, Yulianus; Syahputra, Irwan; Azhari, M. Idrus; Audry, Beby; Tumangger, Oktavia; Wijaya, Rian Farta; Sitorus, Zulham
Jurnal Media Informatika Vol. 7 No. 1 (2026): Edisi Januari - Februari IN PROGRESS
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v7i1.7940

Abstract

Pemilihan ketua OSIS merupakan kegiatan penting dalam lingkup sekolah karena menentukan arah kepemimpinan organisasi siswa. Pada SMK Swasta Dwitunggal 2, proses pemilihan selama ini masih dilakukan secara manual dan subjektif sehingga hasil yang diperoleh kurang akurat serta rentan terhadap bias. Penelitian ini bertujuan mengembangkan sebuah Sistem Pendukung Keputusan (SPK) menggunakan metode Simple Additive Weighting (SAW) untuk menentukan calon ketua OSIS secara objektif berdasarkan beberapa kriteria, yaitu nilai raport, kedisiplinan, kepemimpinan, keaktifan organisasi, komunikasi, prestasi akademik, dan tanggung jawab. Metode SAW digunakan karena mampu memberikan perangkingan alternatif berdasarkan bobot dan nilai kriteria secara sistematis. Metode penelitian dilakukan dengan observasi, studi literatur, dan wawancara yang dilakukan kepada kepala sekolah. Penelitian dilakukan melalui tahapan pengumpulan data, analisis kebutuhan, perancangan metode SAW, normalisasi, pembobotan, dan perhitungan nilai preferensi. Hasil penelitian menunjukkan bahwa kandidat terbaik berdasarkan nilai preferensi tertinggi adalah Nurul Alya Azizah dengan nilai 0.960, disusul oleh Syahfira Amellia Dachi dengan nilai 0.900. Temuan ini menunjukkan bahwa metode SAW mampu memberikan hasil yang objektif dan konsisten sesuai bobot kriteria yang telah ditentukan. Sistem yang dibangun dapat membantu pihak sekolah dalam mengambil keputusan secara lebih adil, transparan, dan terukur.
Analisis Sentimen Publik Berbasis KNN Terhadap Kinerja Purbaya dan Sri Mulyani Selama Sebulan anshari, ari; Diva, Krisna; Azwan, M; Nainggolan, Irfan; Wijaya, Rian Farta; Sitorus, Zulham
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 3 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i3.1461

Abstract

Masyarakat selalu khawatir tentang perubahan staf Menteri Keuangan karena mereka memainkan peran penting dalam menjaga stabilitas ekonomi negara. Purbaya Yudhi Sadewa menggantikan Sri Mulyani sebagai Menteri Keuangan dalam Kabinet Merah Putih. Karena mungkin mengungkapkan tingkat penerimaan publik dan kepercayaan terhadap kebijakan yang akan diterapkan, persepsi publik selama bulan pertama menjabat sangat penting. Studi ini menggunakan algoritma K-Nearest Neighbor (KNN) untuk menguji sentimen publik terhadap pemikiran di platform media sosial X selama bulan pertama masa jabatan kedua kedua tokoh tersebut. Dataset ini mencakup 2.071 cuitan dari Sri Mulyani (21 Oktober–20 November 2024) dan 2.960 cuitan dari Purbaya Yudhi Sadewa (8 September–7 Oktober 2025). Setelah praproses dan pelabelan data dengan IndoBERT, distribusi sentimen untuk Purbaya adalah 57,80% positif dan 42,20% negatif, sedangkan untuk Sri Mulyani adalah 46,74% positif dan 53,26% negatif. TF-IDF kemudian akan digunakan untuk ekstraksi fitur, sementara KNN dengan K=5 dan metrik jarak kesamaan kosinus akan digunakan untuk klasifikasi. Menurut hasil evaluasi, model KNN Sri Mulyani memiliki akurasi 77% dengan presisi 78%, recall 77%, dan skor F1 77%, sedangkan model KNN Purbaya memiliki akurasi 80% dengan presisi 80%, recall 78%, dan skor F1 79%.
ANALISIS SENTIMEN TERHADAP ULASAN PENGGUNA APLIKASI RUMAH PENDIDIKAN DI PLAYSTORE MENGGUNAKAN ALGORITMA NAIVE BAYES Razaq, Abdul; Hidayat, Rahmat; Pasaribu, Ryan Fahreza; Sitorus, Zulham
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4935

Abstract

Abstract: The development of digital technology has led to the emergence of various educational applications that play an important role in supporting the teaching and learning process. One of the most widely used applications is Rumah Pendidikan, which provides a variety of online learning features. However, user perceptions and experiences of this application vary greatly, requiring a systematic analysis to determine public sentiment towards the application. This study aims to apply the Naive Bayes Classifier algorithm in analyzing user sentiment reviews of the Rumah Pendidikan application on the Google Playstore platform. The data, consisting of 284 reviews, was classified into three sentiment categories, namely positive, negative, and neutral. The analysis process included data cleaning, tokenization, stopword removal, and TF-IDF vectorization before classification. The results show that the Naive Bayes algorithm is capable of classifying sentiment with an accuracy of 78.95%, a precision value of 72%, a recall of 67%, and an F1-score of 70%. These findings indicate that the Naive Bayes approach is effective in identifying user sentiment towards the Rumah Pendidikan application. The findings of this analysis can be used by developers as a basis for consideration in improving the quality of the application and user satisfactioninthefuture.Keyword: Sentiment Analysis, Naive Bayes, Rumah Pendidikan Application, Google Play StoreAbstrak: Perkembangan teknologi digital telah mendorong munculnya berbagai aplikasi pendidikan yang berperan penting dalam mendukung proses belajar-mengajar. Salah satu aplikasi yang banyak digunakan adalah Rumah Pendidikan, yang menyediakan beragam fitur pembelajaran daring. Meskipun demikian, persepsi dan pengalaman pengguna terhadap aplikasi ini sangat beragam, sehingga diperlukan analisis yang sistematis untuk mengetahui sentimen masyarakat terhadap aplikasi tersebut. Penelitian ini bertujuan untuk menerapkan algoritma Naive Bayes Classifier dalam menganalisis sentimen ulasan pengguna terhadap aplikasi Rumah Pendidikan pada platform Google Playstore. Data yang terdiri atas 284 ulasan diklasifikasikan ke dalam tiga kategori sentimen, yaitu positif, negatif, dan netral. Proses analisis meliputi tahap data cleaning, tokenization, stopword removal, serta TF-IDF vectorization sebelum dilakukan klasifikasi. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes mampu mengklasifikasikan sentimen dengan akurasi sebesar 78.95%, nilai precision sebesar 72%, recall sebesar 67%, dan F1-score sebesar 70%. Temuan ini menunjukkan bahwa pendekatan Naive Bayes mampu bekerja secara efektif dalam mengidentifikasi sentimen pengguna terhadap aplikasi Rumah Pendidikan. Temuan analisis tersebut dapat dimanfaatkan oleh pengembang sebagai dasar pertimbangan dalam meningkatkan kualitas aplikasi dan tingkat kepuasan pengguna dimasamendatang.Kata kunci: Analisis Sentimen, Naive Bayes, Rumah Pendidikan, Playstore
Perancangan Antarmuka Website Labusel Creative sebagai Media Informasi Daerah Menggunakan Metode UCD Rafandi, Rangga; Sitorus, Zulham; Fachri, Barany
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 3 (2026): Februari 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i3.828

Abstract

Bobabox, sebuah usaha minuman di Medan, menghadapi tantangan operasional akibat proses transaksi dan manajemen inventaris yang masih dilakukan secara manual. Proses ini rentan terhadap kesalahan pencatatan, ketidakakuratan data stok, dan menghambat analisis data penjualan untuk pengambilan keputusan strategis. Penelitian ini bertujuan untuk merancang dan membangun sebuah aplikasi Point of Sale (POS) berbasis website sebagai solusi. Metode perancangan yang digunakan adalah model Waterfall, yang meliputi tahapan analisis, perancangan dengan pemodelan UML, implementasi, dan pengujian. Aplikasi dikembangkan menggunakan framework Laravel dan diuji menggunakan metode Black Box Testing. Hasil dari penelitian ini adalah sebuah sistem Web-POS yang fungsional, mencakup modul manajemen data, modul transaksi interaktif, dan modul pelaporan dinamis. Berdasarkan pengujian, seluruh fungsionalitas sistem dinyatakan Valid. Kesimpulannya, aplikasi Web-POS yang dibangun mampu menjadi solusi efektif untuk meningkatkan efisiensi operasional, akurasi data, dan mendukung pengambilan keputusan berbasis data guna mengoptimalkan penjualan di Bobabox
A Optimization of Sales Strategies and Inventory Forecasting for Processed Banana Products Utilizing the Conceptual Framework of Economic Efficiency and Accounting Precision Based on Simple Moving Average Zulham Sitorus; Lia Nazliana Nasution; Rahima Br Purba; Amnisuhaila Abarahan; Rowiyah Asengbaramae; Feby Wulandari Sembirinng; Mhd Ihsan Abidi
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9505

Abstract

Fluctuations in demand for processed banana products often lead to inaccurate inventory planning at the MSME scale, resulting in decreased operational efficiency and potential accounting inaccuracies in inventory valuation and the calculation of Cost of Goods Sold (COGS). The calculation of raw material stock forecasting for 2024-2025 produces the following predicted values: 124 bunches of bananas, 80 pieces of chocolate, 81 kg of cooking oil, and 42 kg of granulated sugar. This simple, fast, and accurate forecasting process enables producers to more accurately predict product demand, ultimately reducing the risk of overstocking or shortages. This study aims to optimize sales strategies and inventory forecasting for processed banana products through a conceptual framework that integrates economic efficiency. The method used is the Simple Moving Average (SMA) to forecast inventory needs based on historical sales data at the BananaChips MSME, by testing several variations of the forecasting period to obtain the most stable and representative results. Overall, the recapitulation results show that the Cooking Oil raw material has the highest forecasting accuracy, with the lowest MAPE of 1.81% (MAD 1.50, MSE 5.20). Meanwhile, Granulated Sugar raw material recorded the highest MAPE value of 5.08% (MAD 2.25, MSE 9.73), followed by Chocolate (MAPE 2.43%) and Banana (MAPE 2.18%). The implementation results show an increase in stock management efficiency of up to 20% and a 15% decrease in excess raw materials. These findings indicate that integrating SMA forecasting with an economic efficiency framework and accounting accuracy can improve the quality of inventory and sales decision-making, thereby strengthening the profitability and sustainability of the banana-processed product business at the Bananachips MSME
Co-Authors , Arpan , Fery Anugerah , Rahima Br Purba A.A. Ketut Agung Cahyawan W Abda Abda Ade Surya Bakti Pane Afrizal, Sandi Akbar Maulana, Taufik Aldi Kesuma Alvian Alvian Ami Abdul Jabar Amnisuhaila Abarahan Andi Ernawati Andysah Putera Utama Siahaan Angkat, Chairul Indra Anshari, Ari Antoni, Robin Ardya, Dwika Arief, Muhammad Arif Rahman Astri Mutia Rahma Audry, Beby Aulia, Ananda Ayu Ofta Azhari, M. Idrus azwan, m Baehaqi Bambang Sugito Batubara, Supina Boy Rizki Akbar Br Tarigan, Sella Monika Chelfina Utami Daniel Happy Putra Danu Wardhana Azhari Darmeli Nasution DEWI SARTIKA diansyah, Suhar Diva, Krisna Eko Hariyanto Eko Hariyanto Eko Hariyanto Eko Wahyudi Erbin Sitorus Fachri, Barany Fahmi Iskandar Fahmi Kurniawan Farta wijaya, Rian Faza Wardanu Damanik, Dwi Feby Wulandari Sembirinng Gilang Ramadhan Gultom, Ananda Christianto Hafiz Rodhiy Haliza, Siti Nur Hamzah, Iswadi Harmiati Bungsu Bangun Hartono Sinambela, Sugi Helmy, Ahmad Hendra Harnanda Heni Wulandari Hrp, Abdul Chaidir Ibezato Zalukhu, Anzas Ika Devi Perwitasari Indra Angkat, Chairul IQBAL , MUHAMMAD Irwan Syahputra Irwan Syahputra, Irwan Izhari, Fahmi Khairul Khairul Khairul, Khairul Kiki Artika Kurniawan, Fahmi Laila Maghfirah Larius Ambasador Parlindungan Leni Marlina Leni Marlina Lia Nazliana Nasution Limbong, Yohannes France M Imam Santoso M. Rasyid M.Rizki Khadafi Mardiah, Nia Marzuki Sianturi, Ismail Maulian Saputra Melva Sari Panjaitan Meri Sri Wahyuni Mhd Arie Akbar Mhd Ihsan Abidi Mohammad Yusuf, Mohammad Muhammad Fahriza Muhammad Iqbal Muhammad Irfan Sarif Muhammad Wahyudi Nahampun, Natalia Nainggolan, Andreas Ghanneson Nainggolan, Irfan Nazar Saputra, Risfan Nelviony Parhusip Nurwijayanti Ofta Sari, Ayu Parhusip, Nelviony Pasaribu, Ryan Fahreza Pranoto, Sugeng Putra, Khairil Rafandi, Rangga Ragil Satya Adi W Rahmat Hidayat Ramadani, Pebri Ramadhan, Aditya Ramadhan, Deni Ramadhani, Aditya Razaq, Abdul Retno Mutiara Rian Farta Wijaya Rian Putra, Randi Rika Uli Samosir, Siska Risky, Raihan Rowiyah Asengbaramae Rusydi Tanjung , Miftah Sahputra, Fajar Said Oktaviandi Sari Penjaitan, Melva Septia Harliansyah Septiani, Nadya Sianturi, Ismail Sibarani, Dina Marsauli Simamora, Siska Simbolon, Fikri Zuhaili Simorangkir, Elsya Sabrina Asmita Sinambela, Sugi Hartono Sinyo Andika Nasution, Ahmad Sipra Barutu Siregar, Andree Risky Yuliansyah Sitepu, Fernando Siti Nurhaliza Sofyan Sitinur, Siti Nurhaliza Sofyan Sitompul, Jelly Rolley Sofyan, Siti Nurhaliza Solly Ariza Lubis Sri Wahyuni, Meri Suhardiansyah Suhardiansyah Suhardiansyah Suherman Suherman Sukrianto, Sukrianto Sutiono, Sulis Syahputri, Maulisa Syamsiar, Syamsiar T, Siti Isna Syahri Tanjung, Miftah Rusydi Tiara Aninditha Tumangger, Oktavia Utama, Hendra Vina Arnita Vivin Yulfia Sarah Wahyu Agung Pratama Wahyuni, Meri Sri Wijaya, Rian Farta Wirda Fitriani Yahya, Susilawati Zai, Yulianus Zalukhu, Anzas Ibezato Zulfahmi Syahputera Zulfahmi Zulfahmi Zulfahmi Zulfahmi