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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Media Infotama MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Syntax Jurnal Informatika Indonesian Journal of Artificial Intelligence and Data Mining JMM (Jurnal Masyarakat Mandiri) SINTECH (Science and Information Technology) Journal Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Sistem Informasi Kaputama (JSIK) Majalah Ilmiah Kaputama Journal of Information Systems and Informatics Jurnal Sistem informasi dan informatika (SIMIKA) International Journal of Advances in Data and Information Systems Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Pengabdian Masyarakat Nusantara Journal of Artificial Intelligence and Engineering Applications (JAIEA) IT For Society : Journal of Information Technology Journal of Comprehensive Science Eduvest - Journal of Universal Studies Jurnal Hasil Penelitian dan Pengembangan (JHPP) Journal of Data Science, Technology, and Artificial Intelligence
Fahmi, Hasanul
Unknown Affiliation
Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

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PENERAPAN METODE SAW DALAM SISTEM PENDUKUNG KEPUTUSAN PERPANJANGAN KONTRAK THL (TENAGA HARIAN LEPAS) DI DINAS KEPENDUDUKAN DAN PENCATATAN SIPIL KOTA SIBOLGA Natanael, Anju Mastaurat; Fahmi, Hasanul
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i1.180

Abstract

The Population and Civil Registration Office of the City of Sibolga provides an extension of the freelance daily labor contract (THL) which is carried out once a year. However, with the many proposals and the many criteria used in the assessment, this makes it difficult for the Dinas to make a decision about who is entitled to apply for an extension of the work contract. The solution to the problem of extending the contract for casual daily workers at the Department of Population and Civil Registration of Sibolga City is by making a decision support system for extending the contract for casual daily workers using the SAW method. The SAW (Simple Additive Weighting) method was chosen because this method determines the weight value for each attribute, then continues with ranking which will select the best alternative from a number of alternatives.
IMPLEMENTASI METODE K-MEANS CLUSTERING DALAM MENGKLASTERKAN BUKU PERPUSTAKAAN DI SMK NEGERI 1 PANTAI LABU Harianja, Turiami; Fahmi, Hasanul
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i1.181

Abstract

The development of the era of globalization in the field of technology at this time, or what is often referred to as the development of the technological industrial revolution, makes technology grow rapidly from time to time. One technology that shows development is a computerized system, which does not rule out the possibility that it will always be used in human activities. (Fahmi & Sianturi, 2019). The use of computers has penetrated almost all areas of human life today, such as in the field of education. Computer technology also plays an important role in helping humans to take important decisions such as making decisions in processing large data or what is now called Data Mining.The existence of books is very important, especially for students in schools at SMK Negeri 1 Pantai Labu. This research was conducted at SMK Negeri 1 Pantai Labu. However, to read and search for books in the Library of SMK Negeri 1 Pantai Labu, it is necessary to have a way to do clustering to make it easier to group books according to reading interests.
Penerapan Data Mining Pada Penjualan Kartu Paket Internet Yang Banyak Diminati Konsumen Dengan Metode K-Means Turnip, Hendra Nicodemus; Fahmi, Hasanul
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v5i2.704

Abstract

Royal Ponsel saat ini memiliki permasalahan dimana untuk menentukan kartu paket internet mana yang paling banyak diminati konsumen dari penjualan kartu internet Telkomsel, XL, Axis, Im3, 3 (Tri), dan Smartfren. Banyak informasi yang dimiliki namum tidak cukup jika informasi tersebut tidak dimanfaatkan dengan sebaik mungkin, sehingga diperlukan pengelompokan data penjualan untuk mengetahui daya saing produk kartu internet mana saja yang memiliki tingkat penjualan yang paling tinggi berdasarkan penjualan yang ada di usaha Royal Ponsel. Permasalahan ini tentunya dibutuhkan suatu teknologi yang dapat melakukan analisa terhadap data transaksi penjualan kartu paket internet. Salah satunya yaitu dengan menerapkan data mining terhadap penjualan kartu paket internet yang banyak diminati dengan menggunakan perhitungan metode K-Means Clustering. Dengan adanya pengelompokkan jenis kartu internet yang digunakan untuk meningkatkan performance dari penjualan sehingga dapat menentukan langkah peningkatan stock pada kartu paket internet secara tepat.
Analisa Akurasi Algoritma Naive Bayes Dalam Penentuan Klasifikasi Pada Data Jenis Pohon Di Medan Pratama, Jaka Yudhi; Fahmi, Hasanul
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v5i2.705

Abstract

Adanya teknologi informasi yang sudah berkembang ini membawa dampak positif bagi kehidupan manusia. Teknologi informasi sangat berharga, karena memberikan manfaat baik secara langsung maupun tidak. Sehingga manusia menjadi lebih produktif dalam membuat perubahan dan mempertinggi ilmu pengetahuan. Medan menjadi salah satu Kota pendukung aktivitas nasional. Hal tersebut diperkuat dengan tingkat kemacetan lalu lintas yang terjadi hampir setiap hari sepanjang jalan arteri primer dan arteri sekunder di Kota Medan. Kepadatan transportasi tersebut tentunya menimbulkan dampak negatif terhadap lingkungan seperti pencemaran udara dan kebisingan yang menyebabkan rendahnya tingkat kenyamanan hidup terutama di lingkungan yang berdekatan dengan jalan raya. Penerapan metode naïve bayes diharapkan mampu untuk memprediksi jenis pohon yang banyak menghasilkan oksigen pada Taman Kota Medan agar lebih efisien mengetahui pohon mana yang layak untuk ditanam di Taman Kota Medan berdasarkan dari survey yang telah dijalani. Maka dapat diambil kesimpulan bahwa pengolahan data secara komputerisasi tersebut bermanfaat bagi Dinas Pertamanan Kota Medan, karena Proses penyusunan data pada data jenis pohon dapat lebih cepat, Hasil laporan lebih teliti dan penyimpanan datanya lebih praktis karena tidak memerlukan banyak tempat dan Secara keseluruhan sistem yang berjalan pada Dinas Pertamanan Kota Medan yang berjalan belum efektif dan efisien.
Rancang Bangun Sistem Penanganan Kredit Macet Pada BRI Unit Medan Sunggal Dengan Metode K–Nearest Neighbour Murdani, Toynbe; Fahmi, Hasanul
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v5i2.708

Abstract

Bank Rakyat Indonesia (BRI) dalam pengelolaan usaha pelayanan kredit selalu memperhitungkan sifat kehati-hatian. Syarat pemberian pinjaman/kredit kepada calon debitur antara lain yaitu fotokopi KTP, fotokopi kartu keluarga, fotokopi surat tanah asli PBB, pas foto 4x6, dan surat ijin usaha/SIUP. Tingkat keberhasilan pihak debitur dalam mengelola usaha yang dibiayai oleh fasilitas kredit usaha yang diberikan oleh BRI. Hal tersebut dilakukan dengan tujuan untuk menekan tingkat kegagalan dalam membayar angsuran/cicilan kredit. K-Nearest Neighbour berguna dalam klasifikasi yang dilakukan kepada objek yang didasari terhadap data pembelajaran yang memiliki jarak yang dekat dengan objek yang telah diuji. Pendekatan yang dilakukan pada pencarian kasus perhitungan pendekatan antara masalah baru dengan masalah sebelumnya dengan melakukan penyetaraan bobot dari penjumlahan fitur yangada, dalam Penanganan Kredit Macet pada BRI Unit Medan Sunggal tersebut dalam melakukan penerapan dari metode yang digunakan sangat dibutuhkan untuk proses pengolahan data yang baik untuk menganalisa kinerja algoritma melalui penerapan dari algoritma K-Nearest Neighbour dalam penentuan klasifikasi pada data Nasabah kredit BRI Unit Medan Sunggal.
IMPLEMENTASI KONSEP INFORMATION RETRIEVAL DENGAN METODE CASE INSENTIVE SEARCH PADA MESIN PENCARI DOKUMEN QUALITY BROTOKUNCORO, AGUNG; FAHMI, HASANUL; UTOMO, WIRANTO HERRY
Jurnal Hasil Penelitian dan Pengembangan (JHPP) Vol. 2 No. 1 (2024): Januari
Publisher : Perkumpulan Cendekia Muda Kreatif Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61116/jhpp.v2i1.286

Abstract

Information Retrieval adalah bidang yang berkaitan dengan struktur, analisis, organisasi, penyimpanan, pencarian, dan pengambilan informasi. Mesin pencari dokumen yang menerapkan konsep information retrieval ini telah tersedia di PT Chemco Harapan Nusantara namun belum menunjukkan performa yang optimal. Mesin pencari dokumen yang tersedia belum dapat menentukan informasi mana yang terbaik relevansinya sesuai dengan permintaan pengguna dikarenakan masih terikat pada nama dokumen dengan penempatan huruf kapital dan huruf kecil yang sama persis dengan dokumen yang tersedia, sehingga saat pengguna berbeda menempatkan huruf capital dan huruf kecil saat memasukkan query, maka mesin pencari dokumen tidak menunjukkan hasil pencarian. Mesin pencari dokumen tersebut belum dapat memprediksi apa yang sebenarnya diinginkan pengguna sehingga memerlukan waktu yang lama untuk menemukan dokumen. Konsep Information Retrieval memiliki banyak teknik diantaranya adalah metode case insensitive search yaitu teknik memperlakukan huruf besar dan kecil sebagai identik saat melakukan pencarian teks. Tujuan penelitian ini adalah menerapkan metode case insensitive search pada mesin pencarian dokumen untuk mencapai efficient search dengan meningkatkan relevansi dan akurasihasil pencarian melalui penelitian eksperimen kuantitatif. Hasil penelitian menujukkan dengan penerapan metode case insensitive search tercapai efficient search yang meliputi nilai Recall 0.85, nilai Presisi 1.00, dan nilai F1-Score 0.91. Pada hasil tertera bahwa nilai F1-Score mendekati 1.0 maka model memiliki kinerja yang baik dalam mencapai keseimbangan antara Presisi dan Recall.
PREDICTING REVENUE OF SHARIA BANKING TRANSACTIONS USING RNN, LSTM, GRU, DECISION TREE, AND QSPM (CASE STUDY: PT BANK TBV SYARIAH) Arianto, Septian Fakhrudin; Fahmi, Hasanul
Jurnal Sistem Informasi dan Informatika (Simika) Vol 7 No 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3467

Abstract

The banking business will continue to grow significantly along with the increase in the number of transactions carried out by customers through the channels provided by the bank. The variety of products and features offered by PT Bank TBV Syariah to customers means that resources are not optimal. Hence, the bank's revenue growth target still needs to be achieved. This research aims to predict transactions that can affect bank revenues by using transaction data sources for the period January 2022 to February 2024 and which products and features need to be optimized so that it is hoped that banks can run their business appropriately and according to targets. The methods in this research are the RNN, LSTM, GRU, and Decision Tree methods. To enrich information, this research adds QSPM-based strategy analysis using SWOT that the company previously defined. The expected results are to prove the effectiveness of the model used in predicting PT Bank TBV Syariah transaction data to produce MAE, MSE, and RMSE with the lowest values​​, as well as recommendations that PT Bank TBV Syariah must carry out to increase revenue. This research is expected to provide accurate and effective predictions for projecting PT Bank TBV Syariah transaction data, support strategic decision-making, and produce recommendations for significantly increasing bank income.
Analysis of Customer Satisfaction with Marketing Services Using Fuzzy Logic Alifah, Nurli; Fahmi, Hasanul
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.752

Abstract

In sales companies, the acquisition of turnover every month is very influential on the assessment of sales quality. The problem faced by the company is a decrease in turnover, this may be caused by the performance of marketing services, therefore the purpose of this study is to evaluate the service performance of the marketing team at Jayaindo Abadi Makmur. To improve customer satisfaction, the team should consider components such as reliability, responsiveness, assurance, and empathy. To get the results, mamdani fuzzy logic is used with the stages of fuzzy set, implication function, rule composition, and affirmation (deffuzzy). The results showed that customer satisfaction with manual calculations amounted to 84.12, while the results with mamdani fuzzy logic using matlab software amounted to 81.3. The company's customer satisfaction is classified as very satisfied. Sales quality shows a decrease in turnover several times, but this is not caused by the marketing team. Recommendations for improvements that can be made include improving product management, pricing policies, and overcoming market competition. The data presented shows that the company's ability to manage products, pricing policies, and the competitive market atmosphere can contribute to higher levels of customer satisfaction.
Meningkatkan Pemahaman Siswa SMA Don Bosco 3 Cikarang Mengenai Internet Sehat, Gamifikasi Dan Pergaulan Lawan Jenis di Era Digital Rosalina, Rosalina; Sahuri, Genta; Mandala, Rila; Fahmi, Hasanul
Jurnal Pengabdian Masyarakat Nusantara (JPMN) Vol. 3 No. 2 (2023): Agustus 2023 - Januari 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpmn.v3i2.1679

Abstract

In today's digital age, high school students have to survive a dynamic and interconnected online environment. Promoting responsible digital citizenship and cultivating pleasant contacts, particularly those with the opposite sex, is critical as kids develop both intellectually and socially. The goal of this activity is to: (1) educate high school students about the responsible and ethical use of the internet, emphasizing the importance of online safety, privacy, and respect for others; (2) encourage students to develop healthy internet usage habits by providing them with the knowledge and tools to navigate the digital world responsibly; and (3) use gamification principles to engage and motivate high school students to adopt responsible online behavior. The activity was held at SMA Don Bosco 3 Cikarang and was attended by students as well as teachers.
Machine Learning Algorithms for Prediction of Boiler Steam Production Lianzhai, Duan; Roestam, Rusdianto; Sen, Tjong Wan; Fahmi, Hasanul; ChungKiat, Ong; Hariyanto, Dian Tri
International Journal of Advances in Data and Information Systems Vol. 5 No. 2 (2024): October 2024 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v5i2.1339

Abstract

The continuous increase in global electricity demand has resulted in boiler power plants becoming a significant energy source. The production of steam is a principal indicator of boiler efficiency, and the accurate prediction of steam production is paramount importance for the enhancement of boiler efficiency and the reduction of operational costs. In this study employs a boiler dataset with a steam production capacity of 420 tons per hour. A total of 25 independent variables were extracted from the original 39 variables through data processing and feature engineering for the purpose of prediction analysis. Subsequently, 8 machine learning models were used for modeling predictions. Grid search cross-validation was employed in order to optimise the performance of the model. The models were analysed and assessed using the Mean Squared Error (MSE) metrics. The results show that random forest achieves the highest accuracy among the 8 single models. Based on 8 models, New Bagging ensemble model is proposed, which combined predictions from 8 single models, demonstrated the optimal overall fit and the lowest MSE, achieved the purpose of the research. The present study demonstrates the ability to analyse and predict complex industrial systems with machine learning algorithms, and provides insights into the use of machine learning algorithms for industrial big data analytics and Industry 4.0. Further work could explore using larger datasets and deep learning to make predictions more accurate.
Co-Authors Ahmad Zaki Fadilla Rangkuti Alifah, Nurli Arianto, Septian Fakhrudin Arifiandy, Rony Aulia, Afina Nisa Ayu, Desita Puspita BROTOKUNCORO, AGUNG Cexarian, Hafizh ChungKiat, Ong Daniel Happy Putra FUYU, FUYU Gerhard T, Jonathan Girsang, Rame R GUFANG, GUFANG harianja, turiami Hariyanto, Dian Tri Hastuti, Rani Puji Herry Utomo, Wiranto Lianzhai, Duan Linli, Peng murdani, toynbe Naswir, Ahmad Fadhil natanael, anju mastaurat niar, iinvera Nurul Putri Utami Prabu Wardono Pratama, Andreyanto Pratama, Jaka Yudhi Rahman, Fajri Fathur rendiarno, rendiarno Ricky Setiawan Rila Mandala Rimanti, Dewinda Rosalina Rosalina Rusdianto Roestam Rustam, Michiavelly Sahuri, Genta Sahuri Saptona, Albert Siahaan, R. Fanry Sihombing, Darvin Markus Simangunsong, Agustina Simanjorang, R. Mahdalena Sinaga, Anita Sindar RM Sitohang, Rirido Apriyanto sofyan, mhd heri Sulindawaty Tengfei, Li Tjong Wan Sen turnip, hendra nicodemus Wahyuni, Elda Wika Wahyuni Williem Williem, Williem Wiranto Herry Utomo Yunita, Yustina Zhang Jie