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All Journal Jurnal Matematika EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis Communicatus: Jurnal Ilmu Komunikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Andragogi: Jurnal Diklat Teknis Pendidikan dan Keagamaan EDUKATIF : JURNAL ILMU PENDIDIKAN Indonesian Journal of Electrical Engineering and Computer Science G-Tech : Jurnal Teknologi Terapan Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Jurnal Pendidikan Annals of Mathematical Modeling Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Wawasan: Jurnal Kediklatan Balai Diklat Keagamaan Jakarta Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Kepada Masyarakat Patikala As-Sidanah : Jurnal Pengabdian Masyarakat Indonesian Community Journal AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis Jurnal Natural
Selly Anastassia Amellia Kharis
Mathematics Department, Faculty Of Science And Technology, Universitas Terbuka, Indonesia
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Predicting life expectancy of lung cancer patients after thoracic surgery using SMOTE and machine learning approaches SELLY ANASTASSIA AMELLIA KHARIS; ARMAN HAQQI ANNA ZILI
Jurnal Natural Volume 23 Number 3, October 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i3.29144

Abstract

. Lung cancer is a life-threatening condition characterized by the uncontrolled growth and spread of abnormal cells in the lungs. Thoracic surgery is a commonly employed diagnostic and treatment procedure for lung cancer. The objective of this study is to utilize machine learning techniques to predict the life expectancy of lung cancer patients one year after thoraric surgery. The study utilizes the Thoraric  Surgery Data Set, consisting of 454 data, with 385 data representing surviving patients and 69 data representing patients who passed away. Due to an imbalance in the data, the Synthetic Minority Oversampling Technique (SMOTE) process is applied to balance the dataset. Multiple machine learning algorithms, including Random Forest (RF), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM), are employed for prediction. Validation is performed using 5-fold cross validation, repeated three times. The results indicate that the KNN model achieves the highest mean accuracy of 84.80% before the SMOTE process, although all models exhibit a low mean F1-score. Following the SMOTE process, the RF model attains  the highest mean accuracy of 79.52%, while the KNN model demonstrates  the highest mean F1-score of 26.54%. This research contributes valuable insights to clinicians in making informed decisions and improving patient outcomes.
EVALUASI PASCA PELATIHAN KEPEMIMPINAN ADMINISTRATOR (PKA) Kharis, Selly Anastassia Amellia; Qonitah, Laity; Zubir, Edward; Arisanty, Melisa; Robiansyah, Anton
Wawasan: Jurnal Kediklatan Balai Diklat Keagamaan Jakarta Vol. 5 No. 1 (2024): WAWASAN: Jurnal Kediklatan Balai Diklat Keagamaan Jakarta
Publisher : Balai Diklat Keagamaan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53800/wawasan.v5i1.275

Abstract

Abstract Assessing performance emerges as a vital component within the management continuum, serving as a means to improve the future quality and efficacy of training initiatives. This study seeks to appraise the leadership training. The evaluation approach includes assessments from various perspectives, encompassing participant evaluation, trainer evaluation, implementation evaluation, encompassing participant evaluation, trainer evaluation, implementation evaluation, and post-training evaluation. The research method used is a mixed method that combines quantitative and qualitative approaches. The evaluation process is conducted on alumni and mentors (direct supervisors of alumni) of the Leadership Training for Administrators (PKA) held 12 months after the PKA concludes. The evaluation involves the distribution of online questionnaires and conducting direct interviews with alumni and mentors, utilizing simple random sampling, resulting in a total of 34 alumni and 14 PKA mentors. The average score of alumni for the progress of change actions is 4.46, which falls into the very good category. The average score of mentors for the progress of change actions is 4.57, which also falls into the very good category. Through this evaluation, it is expected that the direction of policies embedded in various programs and activities can be implemented accurately and correctly to support the achievement of organizational goals in realizing a world-class bureaucracy in government agencies. Abstrak Evaluasi adalah salah satu elemen yang memiliki signifikansi tinggi dalam rangkaian proses manajemen sebagai upaya dalam peningkatan kualitas dan efektivitas pelatihan di masa mendatang. Penelitian ini bertujuan untuk mengevaluasi pelaksanaan program pelatihan kepemimpinan administrator. Pendekatan evaluasi mencakup penilaian dari berbagai sudut pandang, termasuk evaluasi peserta, evaluasi tenaga pelatihan, evaluasi penyelenggaraan, dan evaluasi pasca pelatihan. Metode penelitian yang digunakan adalah mixed method yang menggabungkan metode kuantitatif dan kualitatif. Proses evaluasi dilakukan kepada alumni dan mentor (atasan langsung alumni) Pelatihan Kepemimpinan Administrastor (PKA) yang dilaksanakan setelah 12 bulan sejak PKA berakhir. Evaluasi dilakukan dengan membagikan kuesioner secara online dan melakukan wawancara secara langsung kepada alumni dan mentor. Pemilihan sampel dilakukan secara acak menggunakan simple random sampling. Jumlah sampel yang diperoleh adalah 34 alumni dan 14 mentor PKA. Rata-rata dari skor alumni dari perkembangan aksi perubahan adalah 4,46 yang termasuk kategori sangat baik. Rata-rata dari skor mentor dari perkembangan aksi perubahan adalah 4,57 yang termasuk kategori sangat baik.  Melalui evaluasi ini diharapkan arah kebijakan yang telah dituangkan ke dalam berbagai program dan kegiatan dapat dilaksanakan dengan tepat dan benar untuk mendukung pencapaian tujuan organisasi guna mewujudkan world class bureaucracy pada instansi-instansi pemerintah.
Pengukuran Terhadap Pelatihan Klasikal dan Jarak Jauh di Perguruan Tinggi Keagamaan Islam Negeri (PTKIN) Kharis, Selly Anastassia Amellia; Qonitah, Laity; Kusriyah, Siti
Andragogi: Jurnal Diklat Teknis Pendidikan dan Keagamaan Vol 11 No 2 (2023): Andragogi: Jurnal Diklat Teknis Pendidikan dan Keagamaan
Publisher : Pusdiklat Tenaga Teknis Pendidikan dan Keagamaan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36052/andragogi.v11i2.315

Abstract

Distance and classical training are two different types of training based on the space and media used. Both have become popular choices in education and training in this digital era. Administrative Technical Training utilizes distance and classical training to enhance participants’ administration skills. This research aims to evaluate distance and classical training in Administrative Technical Training from the participants’ perspective. The evaluation method employed includes data collection through questionnaires and interviews. The evaluation is categorized into two types: distance training evaluation and classical training evaluation. The review of classical training is further divided into academic and administrative indicators. The evaluation results indicate that distance and classical training in the Administrative Technical Training program fall into the “Good” category in terms of participants rated as “Good” with a satisfaction level of 83.51. Meanwhile, classical training, as assessed in the academic and administrative fields, places in the “Good” category with a satisfaction level of 85.98. The average satisfaction level of distance and classical training participants is 84.75, which also falls within the “Good” category.(Pelatihan jarak jauh dan klasikal adalah dua jenis pelatihan yang berbeda berdasarkan ruang dan media yang digunakan. Keduanya telah menjadi pilihan yang popular dalam pendidikan dan pelatihan di era digital ini. Pelatihan Teknis Administrasi menggunakan pelatihan jarak jauh dan klasikal untuk memberikan peningkatan keterampilan administrasi kepada peserta. Tujuan penelitian ini adalah mengevaluasi pelatihan jarak jauh dan klasikal dalam Pelatihan Teknis Administrasi dari perspektif peserta. Metode evaluasi yang digunakan mencakup pengumpulan data melalui kuesioner dan wawancara. Evaluasi yang dilakukan terbagi menjadi dua jenis yaitu evaluasi pelatihan jarak jauh dan evaluasi pelatihan klasikal. Evaluasi pelatihan klasikal terbagi menjadi dua indikator, yaitu bidang akademik dan administrasi. Hasil evaluasi menunjukkan bahwa pelatihan jarak jauh dan klasikal dalam Pelatihan Teknis Administrasi masuk ke dalam kategori Baik dari segi kepuasan peserta. Tingkat kepuasan peserta pelatihan jarak jauh berada pada Kategori “Baik” dengan tingkat kepuasan 83,51. Sedangkan pelatihan klasikal dilihat dari bidang akademik dan administrasi mendapat nilai persepsi sebesar 85,98 yang termasuk kategori Baik. Rata-rata tingkat kepuasan peserta pelatihan jarak jauh dan klasikal adalah 84,75 yang termasuk pada Kategori “Baik”.)
Optimizing banana production in aroma Lumajang business using goal programming method and sensitivity analysis Bramastary, Aurelly Meidy; Kharis, Selly Anastassia Amellia
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 2 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i2.46732

Abstract

Lumajang regency, located in the East Java Province, Indonesia, is renowned for its extensive banana cultivation. Aroma Business, situated in Kalibendo Village, Pasirian District, Lumajang Regency, specializes in banana processing. The company faces challenges including suboptimal production levels, underutilization of resources, raw material shortages, and escalating production costs. These issues contribute to financial instability and unmet market demand. This study aims to establish optimal production planning strategies to address these critical challenges. The research employs the Goal Programming method, which is selected for its suitability in addressing multi-objective problems. Optimization of production is essential for achieving desirable outcomes, ensuring both quantity and quality of products. Research conducted with the aid of LINDO software reveals that production costs can be reduced from IDR 6,647,400 to IDR 6,417,000. Additionally, raw material availability can be increased by 1,512 pieces and the production of banana stem chips can be increased from 240 pieces to 372 pieces, resulting in an increase in company profits from IDR 10,506,000 to IDR 11,727,000. Sensitivity analysis indicates that variations in the right-hand side ranges value do not impact the obtained optimal results. Keywords: Banana production, goal programming, optimization, sensitivity analysis, LINDO software. MSC2020: 90B30.
Analisis Sistem Antrean Pelayanan Administrasi Pasien di Klinik dr. Asih Krustiyani, Probolinggo, Jawa Timur Kharis, Selly Anastassia Amellia
Jurnal Matematika Vol 13 No 1 (2023)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2023.v13.i01.p156

Abstract

The discussion taken in this research is "How is the queue system for patient administration services at the Dr. Asih Krustiyani clinic in Probolinggo City". The purpose of this research is to determine the patient queue administration service system at dr. Asih Krustiyani Probolinggo. From the results of the calculation of the performance analysis of the queuing system using the Single Change Single Phase (M/M/1) method. On Mondays, the most patients who come, the highest average is at 19.00 - 20.00 WIB, where the average time required for patients to wait the longest in the queue is 0.09 minutes and the shortest time is 20.00 - 21.00 WIB for 0, 04 minutes. The longest time required by the patient on the system is 0.14 minutes, namely at 19.00 – 20.00 WIB and the shortest time is 0.1 minutes, which is at 18.00 – 19.00 WIB. And 0.061 minutes per patient for the longest waiting time in line with a single server.fluctuated with greater amplitude.
Learning Analytics dan Educational Data Mining pada Data Pendidikan Kharis, Selly Anastassia Amellia; Zili, Arman Haqqi Anna
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 6 No. 1 (2022): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.061.02

Abstract

Salah satu kelebihan dari pemanfaatan teknologi pada masa pandemi di dunia pendidikan adalah meningkatnya digital footprint. Digital footprint dapat berupa data mengenai diskusi antara pendidik dan peserta didik, nilai diskusi, nilai tugas, nilai ujian, kehadiran, frekuensi mengakses materi, dan sebagainya. Dengan bertambahnya digital footprint, semakin banyak hal yang dapat diketahui dan digali. Penggalian data pendidikan (educational data mining) telah dilakukan beberapa negara untuk menganalisis dan menyelesaikan isu-isu dalam bidang pendidikan. Educational Data Mining telah secara luas dipergunakan untuk berbagai keperluan seperti analisa gaya belajar siswa, kajian efektivitas bahan ajar, prediksi tren kinerja peserta didik, simulasi pengambilan keputusan, dan lain-lain. Penelitian ini bertujuan untuk menjelaskan pengertian, penggunaan, dan dampak Learning Analytics dan Educational Data Mining pada data pendidikan. Penelitian ini menggunakan metode studi literatur dengan pendekatan kualitatif. Sumber-sumber pada penulisan artikel ini berasal dari jurnal dan buku. Teknik analisis yang digunakan pada penelitian ini adalah teknik analis isi. Learning Analytics dan Educational Data Mining menggabungkan beberapa ilmu seperti statistika, data mining, machine learning. Learning Analytics dan Educational Data Mining memiliki potensi untuk dikembangkan pada data pendidikan di Indonesia. Learning Analytics dan Educational Data Mining dapat memberikan informasi kepada institusi, pendidik, dan peserta didik sehingga mendukung analisis prediksi dan pada akhirnya dapat meningkatkan motivasi, kinerja dan hasil dari suatu proses pembelajaran. Dengan melacak, menggabungkan, dan menganalisis digital footprint peserta didik, jalur baru untuk kebijakan pendidikan hadir secara lebih terbuka sesuai dengan pertumbuhan database peserta didik
Prediksi Kelulusan Siswa pada Mata Pelajaran Matematika menggunakan Educational Data Mining Kharis, Selly Anastassia Amellia
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 7 No. 1 (2023): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.071.03

Abstract

Pesatnya perkembangan teknologi menyebabkan keterlimpahan data di berbagai bidang termasuk pendidikan. Dengan fenomena tersebut akan sangat berguna jika data-data tersebut dapat dihubungkan dan dicari pola sehingga mudah dipahami dan dapat digunakan untuk pengambilan keputusan dalam sistem managemen instansi pendidikan. Di dunia pendidikan tentu banyak data yang dapat digali, mulai dari data kinerja pengajar, data nilai mahasiswa, tracer study, dan data proses pembelajaran. Di sisi lain, evaluasi pembelajaran yang dilakukan biasanya terlaksana setelah nilai ujian keluar dan tidak ada peringatan dini untuk siswa terkait dengan kemajuan pembelajarannya. Akibatnya, tindakan pencegahan yang dilakukan oleh guru atau pihak sekolah menjadi terlambat dan dapat berdampak hingga ketidaklulusan siswa. Salah satu inovasi evaluasi pembelajaran yang dapat dilakukan di sekolah adalah dengan menggunakan educational data mining untuk memprediksi kelulusan siswa. Educational data mining diawali dengan pengumpulan, transformasi hingga analisis data. Pada penelitian ini, dilakukan perbandingan berbagai metode machine learning untuk memprediksi kelulusan siswa. Dalam penggalian data, penelitian ini menggunakan data akademik siswa menengah pada mata pelajaran di Portugal dengan 395 sampel dan 33 variabel bebas. Hasil dari educational data mining diharapkan dapat menjadi rujukan untuk menentukan strategi yang tepat untuk menurunkan ketidaklulusan siswa dan menjadi peringatan dini untuk ketidaklulusan siswa.
Comparison of Mathematical Learning Capabilities Among Students Using the Reciprocal Teaching and Problem Posing Model Kharis, Selly Anastassia Amellia; Tri Murdiyanto; Wijayanti, Dwi Antari; Zubir, Edward
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 6 No. 2 (2022): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.062.01

Abstract

The purpose of this study is to ascertain whether students who learn to utilize the reciprocal teaching model have a greater understanding of mathematical topics than students who learn to use the problem posing approach. This research was carried out at SMP Negeri 97 Jakarta for seventh grade students on the subject of Persamaan Linear Satu Variabel (PLSV). This study was conducted using a quasi-experimental design. A two-stage random sampling method was employed for the sampling process.The first stage is purposive sampling, in this case three classes are selected which are taught by the same teacher. Then the second stage is cluster random sampling, from three classes that are normally distributed, homogeneous and have the same average, two classes are randomly selected as experimental class I (reciprocal teaching model) and experimental class II (problem posing model). The research instrument used was the final test of the ability to understand mathematical concepts on the subject of PLSV as many as 6 questions. Validity testing uses content, construct, and empirical validity. Calculation of the reliability of the instrument using the Cronbach Alpha correlation formula and obtained a reliability coefficient of 0.714 which is classified as high. The research hypothesis was tested using t-test statistics.The result show that the ability to understand mathematical concepts of students who learn to use the reciprocal teaching model is higher than problem posing model.
Penguatan Digital Culture Siswa dalam Meningkatkan Literasi Digital: Pendekatan Teoritis dan Praktis Selly Anastassia Amellia Kharis; Melisa Arisanty; Gunawan Wiradharma; Anton Robiansyah; Edward Zubir; Sri Sukatmi; Sri Maulidia Permatasari
I-Com: Indonesian Community Journal Vol 4 No 3 (2024): I-Com: Indonesian Community Journal (September 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i3.5227

Abstract

Good digital literacy skills are essential in the digital era. One crucial element of digital literacy is digital culture. Digital culture needs to be instilled from en early age to prevent the negative impacts of digital transformation. This activity aimed to enhance digital literacy, particularly digital culture, among students at SMP PGRI 1 Ciputat. The activity involved 40 student representatives who are members of the Organisasi Siswa Intra Sekolah (OSIS). The program was in the form of a training session that covered both theoretical and practical applications, including material on digital literacy, social media communication ethics, and data security. The results showed an improvement in students’ understanding of the concept of digital culture. Through this activity, students are expected to become more conscious and responsible technology users and participate positively in the digital society.
Analyzing Social and Psychological Impacts: Shifting Student Interaction from Teachers to ChatGPT in the Learning Process Kharis, Selly Anastassia Amellia; Indriyani, Annisa
EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 6, No 5 (2024)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/edukatif.v6i5.7109

Abstract

The integration of artificial intelligence (AI), specifically ChatGPT, into education it may reduce social engagement among students and teachers also can diminish critical thinking skills, as students might prefer easy answers over deep, analytical thinking. This study investigates the social and psychological impacts of shifting student interactions from teachers to AI. The research method used is a literature study by reviewing seceral relevant and current literature. The result of this study is the reduction in face-to-face interaction can hinder the development of essential communication and collaborative skills between students and teachers as an impact of the intensity of AI use. Moreover, the dependency on AI could lead to a superficial understanding of subjects, with students accepting information at face value without thorough evaluation, thereby affecting their overall academic development and comprehension. Additionally, the study underscores the necessity of developing emotional intelligence, which AI cannot effectively nurture. The findings underscore the irreplaceable role of educators in nurturing cognitive and socio-emotional development, advocating for a balanced approach to integrating AI in education
Co-Authors AA Sudharmawan, AA Abdulmana, Sahidan Agustiani Putri Ajmal, Muhammad Anna Zili, Arman Haqqi Anuraga Jayanegara ARMAN HAQQI ANNA ZILI Arman Haqqi Anna Zili Arman Haqqi Anna Zili Asmara Iriani Tarigan Asmara Iriani Tarigan Asmara Iriani Tarigan Bramastary, Aurelly Meidy Bustamam, Alhadi Danial, T Ahmad Darsih Idayani Darsih Idayani Darwin Hartono Derick Hendri Devvi Sarwinda Dian Lestari Dwi Antari Wijayanti Edward Zubir Edward Zubir Eka Wirajuang Daurrohmah Elin Herlinawati Elin Herlinawati Endang Wahyuningrum Endy Grade Tampubolon Fajar, Fauzan Ihza Fatia Fatimah Fauzan Ihza Fajar Febri Maulana Hasoloan Siregar Hasoloan Siregar Heny Kurniawati Heny Kurniawati Hertono, Gatot Fatwanto Hirawati Lubis Indriyani, Annisa Irawan, Sam Rizky Kusriyah, Siti Martinasari, Made Diyah Putri Maulana Malik, Maulana Maulidia Permatasari, Sri Melisa Arisanty Melisa Arisanty NadyaAsanul Husna Nur Izani Maulani Nur Mahin Nuryaningrum, Wahyu Nyoman A. Wibawa Pesi Suryani Putri, Agustiani Qonitah, Laity Riady, Yasir Robiansyah, Anton Robiansyah, Anton Saputra, Dimas Septian Siti Umamah Naili Muna Sri Maulidia Permatasari Sri Maulidia Permatasari Sukatmi, Sri Sumartono Sumartono Sumartono Tarigan, Asmara Iriani Tri Murdiyanto Tri Wijayanti Septiarini Wahyu Hidayat Wiradharma, Gunawan Yasir Riady Yumiati Zubir, Edwar Zubir, Edward