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All Journal Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer SENSITEK Jurnal Sains Komputer dan Teknologi Informasi Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Indonesia : Manajemen Informatika dan Komunikasi International Journal Software Engineering and Computer Science (IJSECS) Innovative: Journal Of Social Science Research Mutiara: Multidiciplinary Scientifict Journal Tamilis Synex: Multidimensional Collaboration Jurnal Administrasi Negara Jurnal Salome (Multidisipliner Keilmuan)
Sutejo, Heru
Universitas Sepuluh Nopember Papua
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Analisa Kepuasan Pengguna E-Learning Universitas Sepuluh Nopember Papua Menggunakan Metode Servqual Bahar, Dimas Adhitya; Sutejo, Heru; Tatuhey, Emy L.
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i2.1942

Abstract

Sepuluh Nopember University Papua implements an e-learning system to support learning. The quality of e-learning services is measured using the SERVQUAL method to identify gaps between user perceptions and expectations. This research aims to measure the quality of USN Papua's current e-learning services and become an important reference for USN Papua in making improvements and improving the quality of e-learning services in the future. The SERVQUAL method used in this research has five measurement dimensions, namely Tangible, Reliability, Responsiveness, Assurance, and Empathy. This research focuses on the Gap 5 dimension, namely identifying the gap between user perceptions and expectations of USN Papua e-learning services. The results of this research found that USN Papua e-learning users were still "dissatisfied" with the quality of service offered with attribute values with the largest gaps in attributes T4 (-0.12), REL6 (-0.21), RES1 (-0, 16), A1 (-0.20) and E4 (-0.12).Keywords: E-learning; Servqual; Quality; Service; Gaps AbstrakUniversitas Sepuluh Nopember Papua menerapkan sistem e-learning untuk mendukung pembelajaran. Kualitas layanan e-learning diukur dengan metode SERVQUAL untuk mengidentifikasi kesenjangan antara persepsi dan ekspektasi pengguna. Penelitian ini bertujuan untuk mengukur kualitas layanan e-learning USN Papua saat ini dan menjadi acuan penting bagi USN Papua dalam melakukan perbaikan dan peningkatan kualitas layanan e-learning di masa depan. Metode SERVQUAL yang digunakan dalam penelitian ini memiliki lima dimensi pengukuran, yaitu Tangible, Reliability, Responsiveness, Assurance, dan Empathy. Penelitian ini berfokus pada dimensi Gap 5, yaitu mengidentifikasi kesenjangan antara persepsi dan ekspektasi pengguna terhadap layanan e-learning USN Papua. Hasil penelitian ini mendapatkan bahwa pengguna e-learning USN Papua masih ”tidak puas” dengan kualitas pelayanan yang ditawarkan dengan nilai atribut dengan gap terbesar pada atribut T4 (-0,12), REL6 (-0,21), RES1 (-0,16), A1 (-0,20) dan E4 (-0,12). 
Sistem Pendukung Keputusan Penilaian Kinerja Guru Menggunakan Metode EDAS Robaha, Paskalino Melgibson; Sutejo, Heru; Irjanto, Nourman Satya
Progresif: Jurnal Ilmiah Komputer Vol 20, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v20i2.1994

Abstract

Teacher performance appraisal at SD YPK I Sion Dok III Jayapura is still based on attendance and number of subjects, so the results are less optimal and accurate. All criteria are given equal weight, making the assessment less precise. This research aims to develop a Decision Support System with the EDAS method to objectively assess teacher performance. This method involves collecting and processing data from 4 criteria consisting of Pedagogic, Professional, Personality, and Social. The results showed that Johanna Nahumay had the highest score of 0.938, making her the best performing teacher. System accuracy testing reached 80%, demonstrating the effectiveness of the EDAS method in assessing teacher performance objectively and consistently.Keywords: Teacher Performance Appraisal; Decision Support System; EDAS Method. AbstrakPenilaian kinerja guru di SD YPK I Sion Dok III Jayapura masih berdasarkan kehadiran dan jumlah mata pelajaran, sehingga hasilnya kurang optimal dan akurat. Semua kriteria diberi bobot sama, membuat penilaian kurang tepat. Penelitian ini bertujuan mengembangkan Sistem Pendukung Keputusan (SPK) dengan metode EDAS untuk menilai kinerja guru secara objektif. Metode ini melibatkan pengumpulan dan pengolahan data dari 4 Kriteria yang terdiri dari Pedagogik, Profesionalitas, Kepribadian, dan Sosial. Hasil penelitian menunjukkan bahwa Johanna Nahumay memiliki nilai tertinggi 0.938, menjadikannya guru dengan kinerja terbaik. Pengujian akurasi sistem mencapai 80%, menunjukkan efektivitas metode EDAS dalam menilai kinerja guru secara objektif dan konsisten.Kata kunci: Penilaian Kinerja Guru; Sistem Pendukung Keputusan; Metode EDAS.
Optimalisasi Keuntungan Penjualan Tahu Dengan Metode Grafik Program Linier Berbasis QM For Windows Utari, Yanik; Sutejo, Heru; Irjanto, Nourman S
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i1.17968

Abstract

Tofu is typically produced in small to medium-scale industries, with the production technology still being very basic, heavily reliant on manual labor, and lacking optimization. Efforts to optimize tofu sales profits require strategies that focus on maximizing sales revenues. This study aims to optimize the profits from tofu production conducted in the morning and evening by employing linear programming through the graphical method. Data collection on operational costs, raw materials, and production quantities, developed into a mathematical model, can be utilized to achieve efficient and accurate decision-making. The Linear Programming Graphical Method can be used to identify the optimal point for maximizing profits. The research successfully demonstrated that by applying the Linear Programming Graphical Method, Mas Aziz Tofu Factory could significantly increase its sales profits from tofu production in the morning and evening. This study supports the business owner of Mas Aziz Tofu Factory in optimizing production and formulating strategies to maximize profits in the future.
Perancangan Sistem Kendali Gate Valve Dengan Logika Fuzzy Tsukamoto Berbasis Arduino (Studi Kasus Pada Perusahaan Daerah Air Minum Jayapura) Husaini, Muammar; Sutejo, Heru; Kiswanto, Rahmat H.
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 1: April 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i1.1901

Abstract

In distributing clean water, Local water company (PDAM) Jayapura has to deal with problems related to water pressure. One of them is the problem of excess water pressure that causes damage and leakage. A sudden increase in water pressure occurs due to an imbalance between the flow of water from the reservoir and the amount of water consumed by customers. At certain times when many customers no longer use PDAM water, the Gate Valve should also adjust the water flow to avoid excessive pressure. The proposed solution is a control system that automatically controls the Gate Valve using the Tsukamoto type Fuzzy logic method. In this research, a prototype was made to simulate the PDAM water distribution process. After collecting data by interview, observation, and searching for related documents, a prototype was designed using an automatic control system. The system uses water pressure and water flow sensors. The sensor measurement results are used to detect an increase in pressure due to the difference in flow entering and leaving the pipe. Then the system responds by moving the servo to adjust the opening of the main faucet as needed to prevent water pressure from rising. The results of the research show that the tool built can work well and the Fuzzy Tsukamoto method succeeds in preventing water pressure from rising significantly. Keywords: Local water company; Water Pressure; Controll System; Tsukamoto Fuzzy AbstrakDalam mendistribusikan air bersih, Perusahaan Daerah Air Minum (PDAM) Jayapura harus menghadapi masalah terkait tekanan air. Salah satunya adalah masalah kelebihan tekanan air yang menyebabkan kerusakan dan kebocoran. Tekanan air yang tiba-tiba naik terjadi karena tidak seimbang antara aliran air dari reservoir dan jumlah air yang dikonsumsi pelanggan. Pada saat-saat tertentu ketika bayak pelanggan tidak lagi menggunakan air PDAM, sebaiknya Gate Valve juga menyesuaikan aliran air nya agar menghindari tekanan yang berlebihan. Solusi yang diusulkan adalah dengan sistem kendali yang otomatis mengendalikan Gate Valve dengan menggunakan metode logika Fuzzy tipe Tsukamoto. Pada penelitian ini dibuat prototipe untuk mensimulasikan proses distribusi air PDAM. Setelah dilakukan pengumpulan data dengan wawancara, observasi, dan pencarian dokumen terkait, kemudian dirancang sebuah prototipe dengan menggunakan sistem kendali otomatis. Sistem menggunakan sensor tekanan air dan aliran air. Hasil pengukuran sensor digunakan untuk mendeteksi adanya kenaikan tekanan akibat perbedaan aliran yang masuk dan yang keluar pipa. Kemudian sistem merespon dengan menggerakan servo untuk mengatur buka kran utama sesuai kebutuhan untuk mencegah tekanan air naik. Hasil dari penelitian menunjukan alat yang dibangun dapat bekerja dengan baik dan metode Fuzzy Tsukamoto berhasil mencegah tekanan air naik signfikan. 
Analisis Optimalisasi Meminimumkan Biaya Operasional Menggunakan Program Linier Melalui Metode Simpleks (Studi Kasus pada Pabrik Tahu Dan Tempe) Meylisa Kurdita; Heru Sutejo; Emy Lenora Tatuhey
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2618

Abstract

This study discusses the optimization of operational costs at Apo Gudang Tofu and Tempe Factory using linear programming with the Simplex Method. The primary issue faced was the rising costs of raw materials and labor, affecting production efficiency. This study aimed to determine the optimal combination of resource allocation to minimize operational costs without reducing production capacity. The Simplex Method was applied in a mathematical model solved using QM for Windows software. The results indicated that balanced tofu and tempeh production achieved a minimum operational cost of Rp1,766,999,000. Sensitivity analysis showed that the obtained solution was stable, with a shadow price of zero, meaning minor constraint changes did not affect the optimization results. These findings support the application of linear programming in the soybean-based food industry and can serve as a reference for similar industries in managing production costs more efficiently.Keywords: Cost optimization; Linear programming; Simplex Method. AbstrakPenelitian ini membahas optimasi biaya operasional pada Pabrik Tahu dan Tempe Apo Gudang menggunakan pemrograman linier dengan metode Simpleks. Permasalahan utama yang dihadapi adalah meningkatnya biaya bahan baku dan tenaga kerja, yang mempengaruhi efisiensi produksi. Penelitian ini bertujuan untuk menentukan kombinasi optimal dalam alokasi sumber daya guna menekan biaya operasional tanpa mengurangi kapasitas produksi. Metode Simpleks diterapkan dalam model matematis yang diselesaikan menggunakan perangkat lunak QM for Windows. Hasil penelitian menunjukkan bahwa produksi tahu dan tempe yang seimbang menghasilkan biaya operasional minimum sebesar Rp1.766.999.000. Analisis sensitivitas menunjukkan bahwa solusi yang diperoleh stabil, dengan shadow price nol, sehingga perubahan kecil dalam kendala tidak berpengaruh terhadap hasil optimasi. Hasil ini mendukung penerapan pemrograman linier dalam industri makanan berbasis kedelai dan dapat menjadi referensi bagi industri serupa dalam mengelola biaya produksi secara lebih efisien.Kata kunci: Optimasi biaya; Pemrograman linier; Metode Simpleks.
Penerapan Metode Support Vector Machine Untuk Memprediksi Kelulusan Tepat Waktu Avif Setyawan; Rahmat Haryadi Kiswanto; Heru Sutejo
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2619

Abstract

Timely graduation is a key indicator of student academic success in higher education. This study develops a predictive model for on-time student graduation at Universitas Sepuluh Nopember Papua using the Support Vector Machine (SVM) method with a linear kernel. The model examines the influence of academic performance and student status as Indigenous Papuans (OAP) or non-OAP in predicting graduation probability. Model evaluation was conducted using Confusion Matrix, ROC Curve, and Cross-Validation, demonstrating that the model achieved high accuracy of 92% in the initial testing phase, increasing to 97% after cross-validation. The evaluation also showed a Precision of 90%, Recall of 100%, and F1-Score of 95%, confirming the model’s effectiveness in distinguishing students at risk of delayed graduation. With its high predictive accuracy, this model can serve as a data-driven academic decision-making tool to identify at-risk students and implement more targeted academic interventions to improve timely graduation rates.Keywords: graduation prediction; model evaluation; machine learning; Support Vector Machine.AbstrakKelulusan tepat waktu menjadi indikator utama keberhasilan akademik mahasiswa di perguruan tinggi. Penelitian ini mengembangkan model prediksi kelulusan tepat waktu mahasiswa Universitas Sepuluh Nopember Papua menggunakan metode Support Vector Machine (SVM) dengan kernel linier. Model ini menganalisis pengaruh kinerja akademik dan status mahasiswa sebagai Orang Asli Papua (OAP) atau non-OAP dalam menentukan probabilitas kelulusan tepat waktu. Evaluasi model dilakukan menggunakan Confusion Matrix, ROC Curve, dan Cross-Validation, yang menunjukkan bahwa model memiliki akurasi tinggi sebesar 92% pada tahap pengujian awal dan meningkat menjadi 97% setelah validasi silang. Hasil pengujian juga menunjukkan nilai Precision 90%, Recall 100%, dan F1-Score 95%, yang menegaskan efektivitas model dalam membedakan mahasiswa yang berisiko mengalami keterlambatan kelulusan. Dengan tingkat akurasi yang tinggi, model ini dapat digunakan sebagai alat bantu akademik berbasis data untuk mengidentifikasi mahasiswa berisiko dan menerapkan intervensi akademik yang lebih tepat sasaran guna meningkatkan tingkat kelulusan tepat waktu.Kata kunci: Prediksi kelulusan; Evaluasi model; Machine learning; Support Vector Machine
PREDICTION OF DIPLOMA LEGALIZATION STATUS USING DECISION TREE ON DATA FROM THE PAPUA PROVINCIAL EDUCATION OFFICE Mona Angelika Ngaderman; Gladis Dominika Ngaderman; Marcella Putri Pentury; Tirza Meira Pontoh; Heru Sutejo
ADMIN: Jurnal Administrasi Negara Vol. 3 No. 6 (2026): Jurnal Administrasi Negara
Publisher : CV. Adiba Aisha Amira

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

Abstract

The diploma legalization service of the Papua Provincial Education Office serves over 5,000 applicants per year, with 65% coming from outside Jayapura for purposes such as civil servant (CPNS), police (Polri), and military (TNI) applications, which require the original diploma. This study develops a C4.5 Decision Tree model to predict the status of 'Completed'/'Not Completed' using a dataset of 50 legalization entries from January to May 2025. Predictor variables include Year of Graduation, School Type, Document Status, and Number of Documents, with the target being Process Category. The model achieved an accuracy of 86.67%, class precision of 85.71% for Completed and 100% for Not Completed, recall of 100% for Completed and 33.33% for Not Completed. Key decision rule: diploma >15 years AND private school → Not Completed (risk 82%). Implementing the model has the potential to save 45% verification time through automatic pre-screening for out-of-town applicants.
PERANCANGAN SISTEM INFORMASI AKADEMIK SEKOLAH MENENGAH PERTAMA BERBASIS WEB David Oni Apaseray; Noberti Chandra Putra Tambay; Jayando Haloho; Heru Sutejo
Jurnal Salome : Multidisipliner Keilmuan Vol. 3 No. 6 (2025): JULI
Publisher : CV. ADIBA AISHA AMIRA

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

Abstract

This study focuses on the design of a comprehensive web-based academic information system for Junior High Schools. Observations reveal that the current academic data management system largely relies on manual and fragmented processes, leading to inefficiencies, susceptibility to input errors, data duplication, and limited real-time information access for students, teachers, and parents. To address these challenges, the Object-Oriented Analysis and Design (OOAD) approach was applied in the system's design phase. This methodology enables the visualization of system functionalities through Use Case Diagrams, core entity structures via Class Diagrams, object interaction flows using Sequence Diagrams, and key business processes like report card generation with Activity Diagrams. The resulting design is expected to provide an automated solution for academic data management, significantly enhance accuracy and operational efficiency, and establish an integrated platform that ensures quick and easy information access for all stakeholders within the school environment.
Expert System for Identifying Hardware Damage Using Naïve Bayes Method (Case Study: Computer Laboratory of Sepuluh Nopember University Papua) Isaac Samon Sabra; Heru Sutejo; Ajenkris Yanto Kungkung
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.5400

Abstract

This research aims to design and implement an expert system based on the Naïve Bayes method to identify computer hardware failures in the Computer Laboratory of Universitas Sepuluh Nopember Papua. The laboratory operates approximately 40 computer units used daily by students across multiple study programs, yet is supported by only three technicians — a gap that frequently delays repairs and disrupts practical sessions. The system draws on a knowledge base covering 15 hardware failure categories and 11 observable symptoms, including failures in processors, memory/RAM, storage devices (HDD/SSD), and peripheral components such as keyboards, mice, and monitors. Development followed the Waterfall model, system design was documented using UML, the application was built with CodeIgniter, and evaluation was conducted through accuracy testing against expert diagnoses. Testing on 20 cases yielded a 75% accuracy rate, demonstrating that the system is capable of supporting technicians in accelerating the troubleshooting process, reducing dependence on manual inspection, and sustaining the quality of laboratory practice sessions for students
Analisis Rasio Siswa dan Guru dalam Penentuan Kinerja Sekolah di Berbagai Wilayah Indonesia Melalui Metode Naive bayes Semuel Krimadi; Alan Fonataba; Charles Sesera Isawa; Heru Sutejo
Tamilis Synex: Multidimensional Collaboration Vol. 2 No. 02 (2024): Tamilis Synex: Multidimensional Collaboration
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/tls.v2i02.615

Abstract

School performance assessment is a crucial aspect of improving the quality of education in Indonesia. This study aims to classify school performance using the Naive Bayes method, based on the student-to-teacher ratio and other supporting variables. The dataset used includes 400 schools in various locations with attributes such as school name, location, education level, number of students, number of teachers, and student-to-teacher ratio. School performance labels are categorized into three categories: Good, Adequate, and Poor. The Naive Bayes method is applied to predict performance categories based on the relationship patterns between variables in the dataset. Experimental results show that the Naive Bayes method achieves a classification accuracy of [insert accuracy value if available], with the student-to-teacher ratio being the most significant factor in predicting performance. This study demonstrates the potential of using probabilistic-based methods to support decision-making in school evaluation and management, and provides recommendations for education policy to maintain an ideal student-to-teacher ratio.
Co-Authors Abidondifu, Yonas Abraham Victor Patrick Ohoiwutun Aderiani Wahyuti Ajenkris Yanto Kungkung Alan Fonataba Avif Setyawan Bahar, Dimas Adhitya Charles Sesera Isawa David Oni Apaseray Desy Akwita de Queljoe Gladis Dominika Ngaderman Husaini, Muammar Isaac Samon Sabra Jayando Haloho Kiswanto, Rahmat Haryadi Marcella Putri Pentury Meylisa Kurdita Mona Angelika Ngaderman Muh Rajab S Yaslin Noberti Chandra Putra Tambay Nourman Satya Irjanto Robaha, Paskalino Melgibson Semuel Krimadi Sherly Jayanti Susi Hendartie Susi Hendartie Tatuhey, Emy Lenora Thamrin, Rosiyati M.H Tirza Meira Pontoh Utari, Yanik