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PEMILIHAN DOSEN TELADAN BERPRESTASI DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) Pujiastuti, Lise; Amin, Ruhul; Hariyanto, Hariyanto; Supriyatna, Adi; Christian, Ade; Sumanto, Sumanto
Journal of Innovation And Future Technology (IFTECH) Vol 6 No 2 (2024): Vol 6 No 2 (August 2024): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v6i2.3398

This study aims to evaluate the performance of lecturers in higher education using the Multi Attribute Utility Theory (MAUT) method. The main problem faced is the complexity of assessing lecturers based on the Tri Dharma of Higher Education-education, research, and community service-as well as the challenges of subjectivity and inefficiency in manual assessment. MAUT was chosen due to its ability to consider various assessment criteria in a structured and objective manner and follows the standardization of outstanding lecturer assessment including: Education, Research, Community Service, Discipline, Commitment, Cooperation Ability and Ability to innovate. The results showed that Adi Fajar Insani had the best performance with a total final score of 1.01, while Dian Eka Fitriani had the lowest score of 0.00. The MAUT method proved effective in providing a comprehensive and fair assessment, overcoming the limitations of traditional methods that are not thorough. The conclusion of this study is that the application of MAUT can improve the objectivity, efficiency, and accuracy of the lecturer evaluation process, thus encouraging the improvement of lecturer quality and productivity in various fields. Further research is recommended to develop more relevant assessment criteria, involve larger samples, and explore the use of more sophisticated technology to support the assessment process.

ANALISIS PENJUALAN PRODUK UMKM DI SHOPEE PADA TOKO AGUNG0NA9 MENGGUNAKAN MODEL ALGORITMA REGRESI LINEAR Supriyatna, Adi; Irma Purnamasari, Ade; Ali, Irfan
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 2 (2024): JATI Vol. 8 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i2.8372

Shopee merupakan platform e-commerce yang beroperasi secara online dan hadir di berbagai negara di Asia Tenggara, Shopee telah berkembang pesat dalam beberapa tahun terakhir memungkinkan konsumen membeli produk secara online, Toko umkm Agung0na9 Menjual produk kategori musik dan juga kerajinan. Tujuan dari penelitian ini adalah menerapkan algoritma regresi linier untuk memprediksi produk dengan Kategori musik dan kerajinan yang akan terjual dalam waktu 3 bulan berikutnya. Regresi linear digunakan sebagai metode prediksi dengan jumlah produk yang terjual sebagai variabel Y dan periode sebagai variabel X. relative Error digunakan untuk mengevaluasi hasil prediksi. Hasil prediksi kategori Musik pada bulan pertama terjual 68 pcs, pada bulan kedua 69 pcs dan bulan ketiga 70 pcs dan kategori Kerajinan pada bulan pertama terjual 1078 pcs, pada bulan kedua 1029 pcs dan bulan ketiga 1066 pcs. Hasil evaluasi nilai Nilai Relative Error pada kategori Musik 13.64%, sedangkan, Nilai Relative Error kategori Kerajinan 22.65%. Prediksi penjualan handphone menggunakan metode regresi linear ini dapat dikatakan tergolong dalam kategori cukup atau bisa digunakan.

Analisis Bibliometrik Shannon Entropy: Tren Penelitian dan Relevansi Multidimensional Supriyatna, Adi
Jurnal Infortech Vol 6, No 2 (2024): Desember 2024
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v6i2.24445

Dengan meningkatnya adopsi Shannon Entropy di berbagai bidang, penting untuk melakukan analisis komprehensif mengenai perkembangan penelitiannya, termasuk tren utama, kolaborasi antarpeneliti, dan arah inovasi di masa depan. Penelitian ini bertujuan untuk menelaah perkembangan riset tentang Shannon Entropy dan Information Theory melalui pendekatan bibliometrik. Shannon Entropy adalah konsep dasar dalam Information Theory yang diterapkan secara luas dalam bidang kecerdasan buatan, statistik, dan ilmu informasi. Seiring bertambahnya publikasi terkait topik ini, diperlukan analisis mendalam untuk memahami tren penelitian, kolaborasi antar peneliti, dan sumber referensi yang berpengaruh. Penelitian ini menggunakan analisis bibliometrik terhadap publikasi dari basis data ilmiah internasional, meliputi jumlah publikasi per tahun, kolaborasi internasional, topik penelitian dominan, dan sumber jurnal utama. Hasil penelitian menunjukkan bahwa publikasi tentang Shannon Entropy mencapai puncaknya pada tahun 2020, dengan kontribusi signifikan dari Amerika Serikat, Pakistan, dan China. Topik utama meliputi Information Theory dan Shannon Entropy, dengan minat yang meningkat pada kecerdasan buatan dan statistik. Jurnal Entropy serta publikasi IEEE seperti IEEE International Symposium on Information Theory dan IEEE Transactions on Information Theory terbukti sebagai referensi paling relevan. Kesimpulannya, studi ini memberikan wawasan komprehensif tentang perkembangan, kolaborasi, dan signifikansi sumber penelitian terkait Shannon Entropy, yang berperan penting dalam Information Theory dan berdampak luas pada berbagai disiplin terkait.

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

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

Clustering Koridor Transjakarta Berdasarkan Jumlah Penumpang Dengan Algoritma K-Means Supriyatna, Adi; Carolina, Irmawati; Janti, Suhar; Haidir, Ali
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.259

Transportation is one of the facilities that make it easy for humans to carry out activities to move places using vehicles that are driven by humans or machines. Based on data obtained from data.jakarta.go.id, the number of Transjakarta bus passengers in corridors 1 to 13 of 2017 amounted to 114,239,960, and in 2018 there were 121,918,964 passengers. The algorithm used in this research is K-Means Cluster, which is implemented using Microsoft Excel and Rapidminer Studio. The purpose of this study is to cluster Transjakarta corridors based on the number of passengers divided into 3 clusters: high, medium, and low. The results of data processing show that the Transjakarta corridor data cluster is based on the number of passengers using the K-Means cluster algorithm using Microsoft Excel and Rapidminer Studio to produce 3 clusters, namely cluster 1 with the highest number of passengers, one corridor, cluster 2 with the number of passengers being nine corridors and cluster 3 or 0 with a low number of passengers there are three corridors. The highest number of passengers is corridor one which serves the Blok M - Kota route, indicating that the Blok M - Kota route is the most used by Transjakarta passengers.

Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil Supriyatna, Adi; Mustika, Wida Prima
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 2, No 2 (2018): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Warts is a skin health problem that is generally characterized by the appearance of small, rough-textured lumps on the skin surface caused by a virus that is human papilloma virus (HPV). One technique of treatment of wart disease is immunotherapy, this method is a treatment by boosting the immune system to overcome the disease of warts. Naive bayes and Support Vector Machine (SVM) is a method of data mining algorithm used to classify. The aim of this study was to compare the Naive bayes algorithm with Support Vector Machine (SVM) in predicting the success of immunotherapy treatment method in the treatment of wart disease. Tests conducted using the method of Naive bayes and Support Vector Machine (SVM) using the R programming language, then the results are used to do the comparison. The results of this study revealed that the Naive bayes method has superior prediction capability compared to Support Vector Machine (SVM) because Naive bayes can predict all class instances correctly with the accuracy level of 1.

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

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

Clustering Koridor Transjakarta Berdasarkan Jumlah Penumpang Dengan Algoritma K-Means Supriyatna, Adi; Carolina, Irmawati; Janti, Suhar; Haidir, Ali
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Transportation is one of the facilities that make it easy for humans to carry out activities to move places using vehicles that are driven by humans or machines. Based on data obtained from data.jakarta.go.id, the number of Transjakarta bus passengers in corridors 1 to 13 of 2017 amounted to 114,239,960, and in 2018 there were 121,918,964 passengers. The algorithm used in this research is K-Means Cluster, which is implemented using Microsoft Excel and Rapidminer Studio. The purpose of this study is to cluster Transjakarta corridors based on the number of passengers divided into 3 clusters: high, medium, and low. The results of data processing show that the Transjakarta corridor data cluster is based on the number of passengers using the K-Means cluster algorithm using Microsoft Excel and Rapidminer Studio to produce 3 clusters, namely cluster 1 with the highest number of passengers, one corridor, cluster 2 with the number of passengers being nine corridors and cluster 3 or 0 with a low number of passengers there are three corridors. The highest number of passengers is corridor one which serves the Blok M - Kota route, indicating that the Blok M - Kota route is the most used by Transjakarta passengers.

Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil Supriyatna, Adi; Mustika, Wida Prima
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 2, No 2 (2018): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v2i2.78

Warts is a skin health problem that is generally characterized by the appearance of small, rough-textured lumps on the skin surface caused by a virus that is human papilloma virus (HPV). One technique of treatment of wart disease is immunotherapy, this method is a treatment by boosting the immune system to overcome the disease of warts. Naive bayes and Support Vector Machine (SVM) is a method of data mining algorithm used to classify. The aim of this study was to compare the Naive bayes algorithm with Support Vector Machine (SVM) in predicting the success of immunotherapy treatment method in the treatment of wart disease. Tests conducted using the method of Naive bayes and Support Vector Machine (SVM) using the R programming language, then the results are used to do the comparison. The results of this study revealed that the Naive bayes method has superior prediction capability compared to Support Vector Machine (SVM) because Naive bayes can predict all class instances correctly with the accuracy level of 1.

Reinforcement learning for bitcoin trading: A comparative study of PPO and DQN Prasetyo, Romadhan Edy; Sumanto, Sumanto; Chaidir, Indra; Supriyatna, Adi
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.455

Bitcoin’s high volatility demands automated strategies that adapt to changing market regimes while managing risk. This study compares Proximal Policy Optimization (PPO) and Deep Q-Network (DQN) for Bitcoin trading using hourly BTC/USDT data from 2019 to early 2025. The models are trained to generate buy and sell signals from technical indicators including the Relative Strength Index (RSI), MA20, volatility, Moving Average Convergence Divergence (MACD), volume trend, SMA200, and a weekly trend filter. All features are computed on hourly bars. The evaluation shows that PPO tends to trade more aggressively and delivers higher performance during bullish phases, though with greater risk in unstable markets. By contrast, DQN trades more selectively and maintains better stability in sideways or choppy conditions. These findings support the effectiveness of reinforcement learning for adaptive cryptocurrency trading and highlight complementary strengths between PPO and DQN across market regimes.

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