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All Journal Syntax Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Paradigma JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Inovasi Informatika Jurnal Sistem Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknologi Sistem Informasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Bianglala Informatika Jurnal Infortech
Hadi Sukmana, Sulaeman
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Environmental Science Social Sciences

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Penerapan Algoritma C.45 Untuk Menentukan Tingkat Kepuasan Pelanggan Kartu Telkomsel Prabayar Sikumbang, Erma Delima; Ariani, Fattya; Handayani, Tiwi; Ramanda, Kresna; Sukmana, Sulaeman Hadi; Supriyatna, Adi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.492

Abstract

Telkomsel is an operator mobile phone company that provides services for mobile phone users. The mobile phone Operator creates a small SIM card for the customer by means of having to be inserted into each phone to get access to the service. One of the most used mobile operators and belongs to the largest category in Indonesia is Telkomsel. In This study implemented algorithm method C. 45 in deciding customer satisfaction against the use of prepaid Telkomsel cards. This type of research is to implement data mining concept by involving as many as 100 user data of prepaid Telkomsel card through the dissemination of questionnaires. There is an attribute in each variable that affects customer satisfaction including: price, promotion, product quality and service quality. Based on manual calculation results and with the help of the RapidMiner studio 9.7 software is known to be the root is a variable quality service with the highest gain value of 0.266396957 and results classification accuracy value of 0.9655 so that belongs to the classification category is very good
Metode Simple Additive Weighting (SAW) dalam Pemilihan Media Pembelajaran Bahasa Korea Ramanda, Kresna; Sundari, Wiwin; Rusman, Arief; Sikumbang, Erma Delima; Sukmana, Sulaeman Hadi; Azizah, Qudsiah Nur
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.660

Abstract

Almost all Asian countries experience the Korean Wave phenomenon. Asian countries such as Japan, China, Taiwan, Hong Kong, Thailand, Philippines, Singapore, Malaysia, Indonesia and others. With such a phenomenon, it can be observed that if someone likes something from abroad, most people are interested in learning the language. However, it is still difficult for them to find Korean language learning solutions. And one solution is to use appropriate learning media to support learning. The simple additive weight (SAW) method, also known as the weight sum method, will be applied in this study. The SAW method can select the best alternative from several available alternatives because it is ranked after determining the weight of each feature. The results showed that alternative or mobile learning at A2 is the best learning media for Korean and the simple additive weight (SAW) method can determine the best choice of Korean language learning environment. Keywords: Simple Additive Weighting, learning media, Korean language
Metode Analytic Hierarchy Process Dalam Menentukan Promosi Jabatan Pujiati, Tri Wahyuni; Sikumbang, Erma Delima; Ariani, Fattya; Ramanda, Kresna; Sukmana, Sulaeman Hadi; Azizah, Qudsiah Nur
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.605

Abstract

Promotion plays an important role for every employee in the workplace, because promotion can offer changes in social status, authority, responsibility and increase in income to every employee who is given the opportunity. In the process of promotion to the position of the DKI Jakarta Province Population and Civil Registry Service, criteria are needed in making a decision. Promotion decisions require different considerations of many different factors and suggestions must be made objectively, if the wrong decision is taken during the promotion process, it will have a negative impact on employees and the Agency. The Analytic Hierarchy Process (AHP) method is applied to examine the effect of each criterion in determining promotions to obtain accurate results in determining the best and most appropriate criteria. The results showed that the "Employee educational background" criterion was the most important criterion for promotion. The results of processing survey data using the AHP method and the Expert Choice survey are not much different from one another. The AHP (Analytical Hierarchy Process) method can determine promotion selection.
Metode Pieces untuk Evaluasi Kinerja Sistem Aplikasi Newspaper Delivery Shafa, Muadzi; Ramanda, Kresna; Sukmana, Sulaeman Hadi; Azizah, Qudsiah Nur; Rusman, Arief
Jurnal Teknologi Sistem Informasi Vol 6 No 1 (2025): Jurnal Teknologi Sistem Informasi
Publisher : Program Studi Sistem Informasi, Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jtsi.v6i1.9307

Abstract

Industri media telah mengalami perkembangan pesat dalam teknologi informasi, khususnya dalam hal penyebaran konten berita. PT Jasatama Polamedia fokus pada layanan pengiriman surat kabar, tetapi masih menghadapi beberapa masalah. Surat kabar yang tidak terkirim dan keterlambatan pengantaran yang tinggi menunjukkan bahwa kinerja kurir masih belum optimal. PT Jasatama Polamedia telah mengembangkan sistem aplikasi Newspaper Delivery untuk membantu mengelola distribusi surat kabar. Sistem ini memungkinkan perusahaan melacak lokasi dan kinerja kurir, serta mengoptimalkan rute distribusi. Meskipun aplikasi ini telah diimplementasikan, evaluasi kinerjanya masih diperlukan untuk pengembangan masa depan aplikasi Newspaper Delivery. Metode PIECES (Performance, Information, Economic, Control, Efficiency, Service) digunakan untuk evaluasi kinerja aplikasi Newspaper Delivery. Hasil penelitian dengan metode PIECES menunjukan bahwa variabel performance mendapatkan skor 3,93, variabel Information mendapat skor 3,85, variabel Economic mendapat skor 3,75, variabel control mendapat skor 4,19, variabel Efficiency mendapat skor 4,24, dan variabel Service mendapatkan skor 3,93, serta rata - rata skor dari semua variabel adalah 3,98 yang dimana loper atau pengguna merasa puas terhadap kinerja Aplikasi Newspaper Delivery.
Pendekatan Algoritma Naive Bayes Dalam Memprediksi Penyakit Diabetes Qudsiah Azizah; Diah Puspitasari; Sulaeman Hadi Sukmana; Erma Delima Sikumbang; Kresna Ramanda
Jurnal Infortech Vol. 7 No. 2 (2025): Desember 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v7i2.11397

Abstract

Diabetes melitus merupakan penyakit metabolik yang bersifat kronis dan multifaktorial. Penyakit ini menunjukkan gejala peningkatan kadar gula darah (hiperglikemia) akibat proses metabolisme karbohidrat yang tidak normal, lemak, dan protein yang tidak normal. Hingga saat ini, terdapat lebih dari 150 juta orang yang tercatat di seluruh dunia mengidap penyakit ini dan perkembangan penyakit yang terus meningkat dapat menyebabkan komplikasi yang fatal. Faktanya, sebagian besar masyarakat mengabaikan tanda-tanda awal ini: rasa lapar yang berlebihan, rasa lelah yang tidak wajar, dan luka yang lambat sembuh. Penelitian ini dilakukan untuk analisis algoritma Naïve Bayes pada klasifikasi penyakit diabetes untuk mendapatkan hasil optimal dengan akurasi yang ditawarkan dengan cara ini. Dataset diambil dari website Kaggle yang berjumlah 10.000 data dengan jumlah 2 kelas yaitu Diabetes dan Non Diabetes, kelas Diabetes mencakup sebanyak 8.500 data, sementara kelas Non-Diabetes mencakup 91.500 data. Metode yang digunakan yaitu Algoritma Naïve Bayes. Hasil pengujian menunjukkan bahwa Naïve Bayes mencapai tingkat akurasi sebesar 90,66% yang artinya Algoritma Naive Bayes adalah metode yang baik dan tepat untuk mengklasifikasikan penyakit diabetes.
Penerapan Algoritma K-Nearest Neighbors (KNN) Dalam Analisis Sentimen Ulasan Pengguna Aplikasi JMO (Jamsostek Mobile) Ghifari Fatihah Rabbani; Kresna Ramanda; Sulaeman Hadi Sukmana; Qudsiah Nur Azizah; Erma Delima Sikumbang
Bianglala Informatika Vol. 14 No. 1 (2026): Maret 2026
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/bianglala.v14i1.11335

Abstract

JMO (Jamsostek Mobile) is an official application launched by BPJS Ketenagakerjaan, designed to support workers in facilitating access to social protection. However, several obstacles are experienced by application users, such as errors in the application, difficulties logging in, and JHT balances not being displayed. To obtain a general overview of JMO application user sentiment, an evaluation is needed to capture user concerns. Therefore, this study will explore the precision of the KNN algorithm in analyzing sentiment from JMO application user reviews. The objectives of this research are to identify and analyze user feedback, classify overall sentiments, implement sentiment analysis, and test the accuracy of the KNN algorithm. This study adopts a quantitative approach, applying numerical data analysis through text mining techniques. From a dataset of 10,000 reviews collected via web scraping and refined Preprocessing, 7,185 reviews were obtained, revealing that 51.38% expressed positive sentiment. The KNN algorithm achieved its highest accuracy 76.2%, precision 76.2%, recall 78.0%, and F1-score 77.1% at K = 21 under 90%-10% data split. Furthermore, the model’s AUC score of 0.7617 indicated fair and reasonably good performance. These findings suggest that the KNN classification model is capable of providing balanced classification results across classes, leading to a fairer and less biased evaluation.
Co-Authors Adi Supriyatna Agustina, Bella Aldo Priamnistiko Andi Saryoko Anggi Budiyono Arief Rusman Arifin Nugroho Azizah, Qudsiah Nur Deri Saputra, Deri Diah Puspitasari Erma Delima Sikumbang Fattya Ariani Fernando B Siahaan Ghifari Fatihah Rabbani Handayani, Tiwi Hendri Hendri Hendri Hendri Ikhwanul Hakim Irawan Satriadi Kresna Ramanda Miftahul Janah, Miftahul Miwan Kurniawan Hidayat Phindika, Phindika Prima, Harry Pujiati, Tri Wahyuni Qudsiah Azizah Qudsiah Nur Azizah Rahmat Hidayat Rizqi Agung Permana Satriadi, Irawan Shafa, Muadzi Sucitra Sahara Sundari, Wiwin Syara Chintya Dewi Syifa Fauziah Windu Gata Yopi Handrianto, Yopi